1995 rmp annual report - usgs · 2004. 7. 20. · the 1995 regional monitoring program (rmp) annual...

A Cooperative Program Managed and Administeredby the

San Francisco Estuary Institute

1995 Annual Report

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Regional Monitoring Program for Trace Substances

Printed on recycled paper

Regional Monitoring Program Participants

Municipal Dischargers Industrial DischargersCity of Benicia C & H SugarBurlingame Waste Water Treatment Plant Chevron USACity of Calistoga Dow Chemical CompanyCentral Contra Costa Sanitation District EXXON Company, USACentral Marin Sanitation Agency General ChemicalDelta Diablo Sanitation District Pacific Refining CompanyEast Bay Dischargers Authority Rhone-PoulencEast Bay Municipal Utility District Shell Martinez RefiningFairfield-Suisun Sewer District TOSCO Refining CompanyCity of Hercules UNOCAL-San Francisco RefineryLas Gallinas Valley Sanitation District USS-POSCOMillbrae Waste Water Treatment PlantMountain View Sanitary District Cooling WaterNapa Sanitation District Pacific Gas & ElectricNovato Sanitation DistrictCity of Palo Alto Storm WaterCity of Petaluma Alameda Countywide Clean Water ProgramCity of Pinole CALTRANSRodeo Sanitary District Contra Costa Clean Water ProgramCity of Saint Helena Fairfield-Suisun Sewer DistrictCity and County of San Francisco Marin County Stormwater PollutionCity of San Jose/Santa Clara Prevention ProgramCity of San Mateo City and County of San FranciscoSausalito-Marin City Sanitation District San Mateo County Stormwater PollutionSewerage Agency of Southern Marin Prevention ProgramSan Francisco International Airport Santa Clara Valley Nonpoint Source PollutionSonoma County Water Agency Control ProgramSouth Bayside System Authority Vallejo Sanitation and Flood Control DistrictCity of South San Francisco/San BrunoCity of Sunnyvale DredgersMarin County Sanitary District #5, Tiburon Benicia Terminal IndustriesUnion Sanitary District Port of OaklandVallejo Sanitation and Flood Control Port of Redwood CityWest County Agency Port of RichmondTown of Yountville Port of San Francisco

US Army Corps of EngineersUS Navy, Western Division

Executive Summary

i

The 1995 Regional Monitoring Program(RMP) Annual Report includes monitoringresults from the Base Program, Pilot and SpecialStudies, and summary and perspective articlescontributed by RMP investigators and otherscientists.

The purpose of the RMP is to provide infor-mation on the status and trends of contamina-tion in San Francisco Estuary water, sediment,and bivalve tissue, and to assess the potential forbiological effects from exposure to those contami-nants. The objectives, background, and rationalefor the RMP are described in the Introduction(Chapter 1).

The 1995 RMP Base Program was essen-tially the same as in 1994. Water monitoring wasconducted in February, April, and August at 24stations throughout the Estuary. Aquatic bioas-says were conducted in February and August at13 of those stations. Sediment monitoring wasconducted in February andAugust at all 24 stations, andsediment bioassays wereconducted at 12 of those sta-tions. Bioaccumulation ofcontaminants by transplantedbivalves was monitored at 15stations during two 90 day sampling periods:January to April and July to September.

Pilot Studies on benthic fauna and tidalwetlands were conducted and Special Studies ontrends in trace elements and development ofsediment indicators were also included.

Water MonitoringWater Quality

Monthly water quality monitoring wasconducted by the US Geological Survey (USGS).This component of the RMP describes waterquality (e.g., salinity, suspended sediments,dissolved oxygen, etc.) throughout the Estuary(Chapter 2). Their monthly samples providesupplementary information about water qualityat the times between RMP Base Program sam-pling periods.

In general, the patterns of salinity in 1995reflected the effects of river flow on the distri-bution of dissolved constituents. Salinitydecreased from the Golden Gate into northernSan Francisco Estuary during most of the year,whereas salinity in the South Bay was usuallyhomogeneous. This reflects the role of Deltaoutflow as a continual source of freshwater intothe North Bay. The North Bay salinity gradientchanged rapidly in response to changing flowsduring the year. Salinity in the South Bay maybe diluted by freshwater arriving from thenorthern connection to Delta-derived flows, aswell as by runoff from the local watershed.

The patterns of total suspended sediments(TSS) showed that strong freshwater flowsdeliver new sediments to the Estuary. This isimportant because concentrations of TSS aredirectly related to concentrations of manycontaminants. TSS was generally lowest in theCentral Bay, far from the riverine supplies of

sediments and far fromthe shallow habitatswhere wind-waveresuspension creates highturbidity.

The potential forbiological transformations of dissolved chemi-cals in water into organic forms was monitoredby measuring chlorophyll. Phytoplanktoncomprise one of the largest components of livingbiomass in San Francisco Bay. Phytoplanktonbiomass, as measured by chlorophyll, wasusually low in the Bay-Delta. However, duringspring blooms in the South Bay, biomassincreased rapidly. During these blooms, dis-solved inorganic carbon, nitrogen, phosphorus,and silicon, as well as some trace elements(cadmium, nickel, zinc) were removed fromwater and transformed into organic forms. Asthe 1995 RMP sampling in April occurred at theend of a two-month bloom, reduced concentra-tions of those dissolved trace elements wereobserved in the South Bay samples (pages 15,20, and 23).

Executive Summary

Salinity patterns reflected theeffects of river flow on dissolvedconstituent distributions.

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Regional Monitoring Program 1995 Annual Report

Contaminants in Water

Different contaminants exhibited differentpatterns of distribution in the Estuary. In 1995,overall, the South Bay had the highest concen-trations of both trace elements and traceorganic contaminants (Chapter 2). However,concentrations of dissolved copper and nickelwere much higher at the Petaluma Riversuggesting the presence of a source of theseelements near that station. The distribution oftotal (or near-total) concentrations of chro-mium, copper, lead, mercury, nickel, silver, andzinc reflected the distribution of TSS, with thehighest concentrations in the Southern Sloughsand at the Petaluma River, intermediateconcentrations at the North-ern Estuary and Riverstations, and lowest concen-trations in the Central Bay.Analysis by USGS showedthat seven trace elementswere well-correlated with TSS in the Estuary(page 53). Concentrations of trace organiccontaminants that tend to be associated withparticles, such as PAHs, PCBs, DDTs, andchlordanes, also displayed the same basicpattern as TSS; the highest concentrationsoccurred in the South Bay, lower concentrationsin the Central Bay, higher concentrations in theNorthern Estuary, and intermediate concentra-tions in the Rivers. Most dissolved trace organiccontaminants, including PCBs, chlordanes,DDTs, HCHs (hexachlorocyclohexanes) anddiazinon, were elevated in the South Bayrelative to other reaches of the Estuary, withconcentrations progressively decreasing fromCoyote Creek to the Golden Gate. Diazinonconcentrations were highest at nearly allstations in February, reflecting its seasonalusage.

Seasonal variation was also observed inmany other contaminants. Total arsenic, near-total cadmium, and dissolved silver, arsenic,cadmium and PAHs were highest in August.Total concentrations of chromium, copper, lead,mercury, nickel, silver, PAHs, PCBs, chlor-danes, and DDTs tend to be associated with

particles and were often highest in April,coinciding with high concentrations of TSS.

Long-term trends in total trace elementconcentrations were examined in detail usingdata collected from April 1989 to April 1995under the RMP and Pilot Studies that precededthe RMP (pages 78–84). There were no obviousincreasing or decreasing trends in trace ele-ment concentrations. For certain persistenttrace organics, the long-term rate of decline inconcentrations appears to be very slow. Data forwater organics from the mid-1970s and early1980s compared to RMP data showed thatconcentrations of PCBs have generally notdeclined appreciably, although they have been

been banned for decades.Neither have PAHs declined, ascontinuous sources still exist.DDTs and chlordanes appear tohave declined since beingbanned in the 1970s.

Comparisons to Water Quality Objectivesand Criteria

Concentrations of many contaminants wereabove applicable water quality objectives orcriteria. Of the 10 trace elements measured,concentrations of chromium, copper, lead,mercury, and nickel were above applicablewater quality objectives or criteria on one ormore occasions. Copper, mercury, and nickelwere most frequently above objectives orcriteria. PCBs were always above EPA criteria,PAHs were frequently above criteria, andDDTs, chlordanes, dieldrin, and diazinon wereoccasionally above water quality objectives orcriteria. The stations with the largest numberof concentrations above guidelines were CoyoteCreek, the Dumbarton Bridge, and the Peta-luma River. The overall pattern of exceedanceswas very similar in 1994 and 1995.

In water, the South Bay hadthe highest concentrations ofmost trace elements andtrace organic contaminants.

Copper, mercury, and nickel were mostfrequently above water quality objectives orcriteria. PCBs were always above criteria,PAHs were frequently above criteria, andDDTs, chlordanes, dieldrin, and diazinon wereoccasionally above objectives or criteria.

Executive Summary

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Aquatic Bioassays

Aquatic toxicity was observed in only onewater sample in 1995, in the Mysidopsis (mysidshrimp) test of San Joaquin River water collectedin February. However, the presence of somecontaminants, particularly organophosphateinsecticides, is known to be episodic, with highconcentrations entering the Estuary duringperiods of heavy use and/or high runoff. The lackof significant results in 1995, therefore, does notnecessarily mean that the Estuary was free ofambient toxicity for theentire year. RMP samplingat fixed times may havemissed elevated pesticidesentering the Estuary atother times.

Sediment MonitoringContaminants in Sediments

Despite the very wet year of 1995, thedistributions and concentrations of sedimentcontaminants in the Estuary remained similar tothose in previous years. There were two patternsof trace element concentrations in sediments: 1)average concentrations of arsenic, chromium,copper, nickel, and zinc were highest in theNorthern Estuary. Chromium, copper, and nickelwere highest at Pinole Point in February, and 2)average concentrations of silver, cadmium, lead,mercury, and selenium were highest in the SouthBay and Southern Sloughs. Cadmium, lead,silver, and zinc were highest at San Jose inAugust. Concentrations of most elements (exceptarsenic and chromium) were lowest at thestations with the sandiest sediments, particu-larly at Red Rock, reflecting the influence ofsediment-type on sediment contaminant concen-trations. For trace organics, sediment concentra-tions were always higher south of the GoldenGate than in other parts of the Estuary. Concen-trations of PCBs and DDTs were lowest atstations with the most sand in the sediments,but PAH concentra-tions were lowest atthe Rivers confluencestations (Chapter 3).

The only consistent seasonal pattern fortrace elements was that nearly all concentra-tions were highest in August at both SouthernSlough stations. Seasonally, PAHs were gener-ally highest in February in the South andCentral Bays. PCBs were generally highest inAugust in the South Bay. DDTs were alwayshigher in August than February throughout theEstuary.

Examination of sediment contaminants overthe first three years of the RMP showed thattrace element concentrations have generally

remained constant in alllocations since 1993 with noapparent increasing or de-creasing trends (page 127–136). There were no observableincreasing or decreasing

trends in PAHs. However, PAH concentrationswere elevated in the Northern Estuary, Central,and South Bays in February 1994. Average PCBconcentrations appear to have decreased slightlyin the Rivers, Northern Estuary, and CentralBay, and average DDTs appear to have decreasedslightly in the Rivers. Average chlordanes havealso decreased in most Estuary reaches.

Comparisons to Sediment QualityGuidelines

There are currently no Basin Plan objectivesor other regulatory criteria for sediment con-taminant concentrations in the Estuary. EffectsRange concentrations developed by the NationalOceanic and Atmospheric Administration wereused by the RMP in the interpretation andassessment of sediment contaminant concentra-tions in the Estuary (pages 132–138), but hold noregulatory status. As in past years, nickelconcentrations in nearly all samples were abovethe Effects Range-Median (ERM). Nickel ispresent naturally in serpentine soils abundant inthe region. Concentrations in USGS sedimentcores were generally constant for centuries. Alsosimilar to past years, concentrations of arsenic,

chromium,copper,mercury,nickel, and

In sediment, arsenic, chromium, copper, mercury, nickel,and total DDT concentrations were usually above theERLs, and nickel was usually above the ERM.

Aquatic toxicity was observedonly in the February Mysidopsistest of San Joaquin River water.

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total DDTs were usually above the EffectsRange-Low (ERL). In 1995, concentrations ofseveral PAH compounds were above ERLs atAlameda. Stations with the greatest number ofcontaminants above ERLs included Alamedawhere eight contaminants exceeded ERL concen-trations in February, and Honker Bay had sixexceedances in each sampling period. Thestations with more sand in the sediments hadonly one or two ERL exceedances (Davis Point,Pacheco Creek, Red Rock, and Sunnyvale).

Sediment Bioassays

Results of the amphipod and larval musselbioassays indicated that sediments were toxic atmany Estuary stations (page 103), but there wasno indication of sediment toxicity at San BrunoShoal, Horseshoe Bay, Davis Point, or NapaRiver in 1995. Redwood Creek was toxic toamphipods in both sampling periods. GrizzlyBay and the Sacramento and San Joaquin Riverswere toxic to mussel larvae during both sam-pling periods, but none of the South Bay stationswere toxic to larval mussels. Yerba Buena Islandwas toxic to both amphipods and bivalve larvaein August.

Bioassays conducted over the past six yearsin the San Francisco Estuary have indicatedthat toxicity in Estuary sediments was wide-spread in space and time. Overall, the highestincidence of toxicity occurred at Grizzly Baywhere sediments were toxic in 60% of the testsconducted between 1991 and 1996. Toxicityoccurred much less frequently in the CentralBay and sediments were never toxic at DavisPoint probably due to the low contamination insandy sediments. The incidence of amphipodtoxicity has decreased at most stations since1991, but bivalve larval toxicity has remainedrather constant. The cause of the observedtoxicity is not well understood. However, analy-ses presented show that when more than sevencontaminants in sediments exceeded ERLvalues, toxicity to amphipods was usually

observed, suggesting thatseveral contaminantspresent in low concentra-tions may cause toxicity.

However, the number of contaminants aboveERLs was not a good predictor of larval bivalvetoxicity (page 106).

The RMP Special Studies on the develop-ment of sediment bioassays using the residentamphipod Ampelisca abdita showed that theywere equally or more sensitive to contamina-tion as other amphipods commonly used inbioassays, but depended on which toxicantswere used in the exposures (page 108–115).Since A. abdita is a resident of the Estuary, isnumerically dominant at many RMP benthicstations, and can be used in controlled sedi-ment bioassays, it could become a powerfulindicator for the RMP in attempting to under-stand sediment contaminant effects.

Benthic Pilot Study

For 1995, this study focused on the identi-fication of “normal” or reference benthic (ani-mals that inhabit sediments) assemblages(communities). Based on monitoring in 1994and 1995, four benthic assemblages wereidentified that appear to reflect differences insalinity or sediment types. This informationmay eventually be useful for comparisons tosites where the benthos is degraded due tocontamination or other factors. However, thoseresults are based on only two years of data andrequire verification through several years ofvarying environmental conditions. In general,benthic assemblages appeared mostlyunimpacted, but indicators of contaminationoccurred at some sites in the Central Bay, Deltaand Rivers suggesting slight impacts.

Bioaccumulation MonitoringContaminants in Bivalve Tissues

Bivalves are very useful for assessing thecapacity of contaminants in water to accumu-late in animal tissues. Lead and nickel were theonly trace elements that accumulated substan-tially above background concentrations (be-tween two and 33 times) in all three bivalve

Sediment bioassays indicated that sediments were toxic at manyEstuary stations, but there was no indication of sediment toxicityat San Bruno Shoal, Horseshoe Bay, Davis Point, or Napa River.

Executive Summary

v

species used in the RMP (Chapter 4). Leadbioaccumulated at all Estuary stations, andnickel at all but one. Cadmium, chromium,copper, selenium, silver, and zinc accumulatedbetween two and nine times above referencelevels at one or more stations, but primarily inthe South Bay and the Northern Estuary.Arsenic and mercury showed no appreciablebioaccumulation. Arsenic is the only traceelement that did not bioaccumulate in any ofthe three species at any station since theinception of the RMP.

Bivalves accumulate most trace organiccontaminants to a much larger degree thantrace elements, particularly certain highly fat-soluble compounds. For some compounds,accumulation canbe on the order ofhundreds of timesabove initial tissueconcentrationsmeasured at controlsites. The ratios of the various PAH compoundsin tissue was fairly uniform throughout theEstuary, suggesting consistent sources.

Many of the chlorinated pesticides showeddistinct seasonal differences in bioaccumula-tion. DDTs, chlordanes, and dieldrin concentra-tions were elevated at Coyote Creek during thewet sampling period, suggesting that runoffwas a source, despite the fact that most chlori-nated pesticides have long been banned. PAHconcentrations in tissues were also variablebetween seasons, but without any consistentpatterns.

Bivalve tissue concentrations monitoredbetween 1993 and 1995 showed no obviousincreasing or decreasing trends for any con-taminants. The three-year RMP databasesuggests that the bioaccumulation potential foroysters is considerably higher than for theother two species in thecase of copper, silver,selenium, and zinc, whilemussels accumulate leadto a greater extent thanthe other two species.

Comparisons to Tissue Guidelines

For the 1995 Annual Report, MaximumTissue Residue Levels (MTRLs) were used as arelative yardstick to evaluate how much tissuelevels deviate from guidelines (page 140).Arsenic, cadmium, nickel (freshwater only), andmercury are the only trace elements for whichMTRLs apply, and as in 1993 and 1994, bivalvetissue concentrations were far below thethreshold level for each of these elements,except arsenic. It should be noted, however,that the MTRL for arsenic was exceeded evenat the uncontaminated control site. As inprevious years, most of the trace organiccontaminants measured were above the MTRL

guidelines. At CoyoteCreek during the wetseason, and the Riversduring both wet anddry seasons, tissueswere consistentlyabove the MTRLs for

most pesticides. PCB and PAH tissue levelswere consistently well above MTRLs through-out the Estuary. These same patterns wereobserved in previous years.

Bivalve Condition and Survival

Survival and biological condition measure-ments were made to determine if animals werecapable of bioaccumulation. However, changesin condition and survival may also reflectexposure to adverse conditions such as elevatedsalinities or lack of food. Bivalve condition inthe dry season was almost always lower than inthe wet season for all species (page 159).Mussels condition improved at all stationsduring the wet season (except Red Rock) butshowed approximately 20–45% reductions incondition during the dry season. For the second

year in a row, the twostations with the mostelevated tissue contami-nant concentrations(Napa River, CoyoteCreek) also showedpronounced decreases in

In bivalves, lead and nickel were the only traceelements that accumulated above backgroundconcentrations. However, nearly all traceorganic compounds accumulated substantially.

Arsenic and most of the trace organiccontaminants measured in bivalveswere above the MTRL guidelines, butcadmium, nickel, and mercury werebelow the guidelines.

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condition in oysters. Clam condition decreasedat all Estuary stations in both the wet and dryseasons. Bivalve condition indices of the last threeyears are remarkably similar among stations andbetween the seasons.

Bivalve survival was below 50% during thewet season at Dumbarton Bridge, Redwood Creek,Red Rock, and Pinole Point, and at the Petalumaand Napa Rivers in the dry season. The decreasedsalinities at many Estuary stations due to theunusually wet year may be partly responsible forthose results.

Wetlands Monitoring Pilot Study

Tidal wetlands provide a broad range ofecological services including support of endan-gered species, filtration of contamination, stabili-zation of coasts, and regulation of air quality. TheRMP Wetlands Pilot Study was initiated in 1995to provide information about how and where tosample wetlands habitats in order to develop amonitoring program for wetlands that wouldcomplement the RMP (page 197).

Two locations believed to represent naturaltidal marshes were sampled: China Camp StatePark and Petaluma Marsh. These locations weresampled concurrently with the RMP Estuarysamples. Contaminant concentrations wereconsistently higher in Petaluma Marsh than atChina Camp. Concentrations of most contami-nants were higher in the marshlands than at theadjacent RMP San Pablo Bay station. Contami-nant concentrations may be higher in marshesbecause they are retentive filters washed twicedaily by the tides. Concentrations of most traceelements tended to be higher in the channelstations than on the drainage divides, but concen-trations of trace organics tended to be muchhigher on the drainage divides than in the marshchannels. Silver, copper, PAHs, and chlordaneconcentrations tended to be higher in winter.

The natural physiography of the tidal marshwas shown to be a useful templatefor a stratified sediment samplingplan. Potential effects of theseelevated concentrations on theecological functions of the tidalmarshes remains to be assessed.

Conclusions

RMP results for 1995 indicated that concen-trations of several contaminants were highenough to raise concern over possible effects onaquatic biota or human health. The contami-nants of concern were generally different inwater, sediment, and bivalve tissue. In water,PCBs and nickel were most often above waterquality objectives or criteria. In sedimentsarsenic, chromium, copper, mercury, nickel, lead,and DDTs were above guidelines at most Estu-ary stations. In bivalve tissues, dieldrin, chlor-danes, PAHs and PCBs were usually above theMTRLs at all stations.

The total number of contaminants above thevarious guidelines at each RMP station providesan indication of where contaminants may be thegreatest problem and where they may be theleast problem. For water, Coyote Creek andPetaluma River had the largest numbers ofwater quality exceedances and the Central Baystations generally had the fewest. For sedi-ments, Alameda and Honker Bay had the mostERL exceedances, and the stations with thecoarsest sediments at Red Rock and Davis Pointhad the fewest ERL exceedances. For bivalvebioaccumulation, most stations had similarnumbers of exceedances of MTRLs, but stationsin San Pablo Bay had the fewest exceedances.

The potential for biological effects fromcontamination at each station was evaluated bysumming the number of samples that were toxicin bioassays and that had reduced bivalvecondition or survival. The Central Bay generallyhad the fewest indications of biological effectsand the Sacramento and San Joaquin Rivershad the most indications of possible biologicaleffects. The San Joaquin River station indicatedpossible biological effects in about 50% of themeasurements made between 1993 and 1995.Grizzly Bay and Napa River indicated biologicaleffects about 47% of the time. It is not yet

known what may becausing thesemeasured biologicaleffects.

The Central Bay generally had thefewest indications of biologicaleffects and the Sacramento andSan Joaquin Rivers had the most.

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RMP Participants ........................................................................................... (inside cover)Executive Summary............................................................................................................... iTable of Contents ................................................................................................................viiList of Figures ....................................................................................................................... ixList of Tables ...................................................................................................................... xiii

Chapter 1: Introduction....................................................................................................... 1Regional Monitoring Program Objectives ..............................................................................................................2Sampling Design ......................................................................................................................................................2

Chapter 2: Water Monitoring............................................................................................ 10Background ............................................................................................................................................................ 11Water Quality Objectives and Criteria ................................................................................................................. 11Water Monitoring Results .....................................................................................................................................12Aquatic Bioassays ..................................................................................................................................................30Seasonal Fluctuations of Water Quality ..............................................................................................................31Methods for Analysis of Spatial and Temporal Patterns .....................................................................................44Times Series of Trace Element Concentrations ...................................................................................................53Toxic Phytoplankton in San Francisco Bay ..........................................................................................................56Observations on Trace Organic Concentrations in RMP Water Samples ..........................................................67Water Monitoring Discussion ................................................................................................................................78

Chapter 3: Sediment Monitoring ..................................................................................... 94Background ............................................................................................................................................................95Sediment Monitoring Results ...............................................................................................................................95Sediment Bioassays .............................................................................................................................................102Patterns in Sediment Toxicity ............................................................................................................................104Further Development of a Chronic Ampelisca Abdita Bioassay as an Indicator of Sediment Toxicity ..........108Benthic Pilot Study ............................................................................................................................................. 116Bay Protection and Toxic Cleanup Program ......................................................................................................123Sediment Monitoring Discussion ........................................................................................................................127

Chapter 4: Bivalve Monitoring....................................................................................... 139Background ..........................................................................................................................................................140Bivalve Monitoring Results .................................................................................................................................142A Comparison of Selenium and Mercury Concentrations in Transplanted and ResidentBivalves from North San Francisco Bay ............................................................................................................160Bioaccumulation of Contaminants by Transplanted Bivalves ..........................................................................171Quantification of Trace Element Measurement Errors in Bioaccumulation StudiesAssociated with Sediment in the Digestive Tract ..............................................................................................176Bivalve Monitoring Discussion ...........................................................................................................................181

Chapter 5: Pilot and Special Studies ............................................................................ 196Background ..........................................................................................................................................................197Contamination in Tidal Wetlands ......................................................................................................................197The RMP Workshop on Ecological Indicators of Contaminant Effects .............................................................2141995 Intercomparison Exercise ..........................................................................................................................224

Table of Contents

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Chapter 6: Other Monitoring Activities ....................................................................... 254A Summary of the South Bay Local Effects Monitoring Program ....................................................................255Sacramento Coordinated Water Quality Monitoring Program .........................................................................261Sacramento River Watershed Program and the Sacramento River Toxic Pollutant Control Program ..........266San Francisco Bay Area Storm Water Runoff Monitoring Data Analysis, 1988–1995 ....................................268

Chapter 7: Conclusions .................................................................................................... 271Temporal and Spatial Variations in Trace Element Contamination in the San Francisco Bay Estuary .......272A Summary of Mercury Effects, Sources, and Control Measures .....................................................................276Polychlorinated Biphenyls in the San Francisco Bay Ecosystem: A Preliminary Report

on Changes Over Three Decades ......................................................................................................................287Summary of Estuary Condition in Terms of Contamination ............................................................................298

References .......................................................................................................................... 299Acknowledgments ............................................................................................................. 321Financial Statement ......................................................................................................... 324Appendices.......................................................................................................................... A–1Appendices Table of Contents ............................................................................................................................ A–2A: Description of Methods .................................................................................................................................. A–3B: QA Information .............................................................................................................................................. A–9C: Data Tables ................................................................................................................................................... A–15

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IntroductionFigure 1. Location of the 1995 Regional Monitoring Program stations .............................................................3

Water MonitoringFigure 1. Salinity in water in 1995 ....................................................................................................................12Figure 2. Dissolved organic carbon in water .....................................................................................................12Figure 3. Total suspended sediments in water ..................................................................................................13Figure 4. Dissolved arsenic concentrations in water ........................................................................................14Figure 5. Total arsenic concentrations in water ................................................................................................14Figure 6. Dissolved cadmium concentrations in water .....................................................................................15Figure 7. Near-total cadmium concentrations in water ....................................................................................15Figure 8. Dissolved chromium concentrations in water....................................................................................16Figure 9. Total chromium concentrations in water ...........................................................................................16Figure 10. Dissolved copper concentrations in water..........................................................................................17Figure 11. Near-total copper concentrations in water ........................................................................................17Figure 12. Dissolved lead concentrations in water .............................................................................................18Figure 13. Near-total lead concentrations in water ............................................................................................18Figure 14. Dissolved mercury concentrations in water.......................................................................................19Figure 15. Total mercury concentrations in water ..............................................................................................19Figure 16. Dissolved nickel concentrations in water ..........................................................................................20Figure 17. Near-Total nickel concentrations in water .........................................................................................20Figure 18. Dissolved selenium concentrations in water .....................................................................................21Figure 19. Total selenium concentrations in water .............................................................................................21Figure 20. Dissolved silver concentrations in water ...........................................................................................22Figure 21. Near-total silver concentrations in water ..........................................................................................22Figure 22. Dissolved zinc concentrations in water ..............................................................................................23Figure 23. Near-total zinc concentrations in water .............................................................................................23Figure 24. Dissolved PAH concentrations in water .............................................................................................24Figure 25. Total PAH concentrations in water ....................................................................................................24Figure 26. Dissolved PCB concentrations in water .............................................................................................25Figure 27. Total PCB concentrations in water ....................................................................................................25Figure 28. Dissolved chlordane concentrations in water ....................................................................................26Figure 29. Total chlordane concentrations in water ............................................................................................26Figure 30. Dissolved DDT concentrations in water ............................................................................................27Figure 31. Total DDT concentrations in water ....................................................................................................27Figure 32. Dissolved diazinon concentrations in water ......................................................................................28Figure 33. Total diazinon concentrations in water ..............................................................................................28Figure 34. Dissolved HCH concentrations in water ............................................................................................29Figure 35. Total HCH concentrations in water ...................................................................................................29Figure 36. Aquatic bioassays at selected RMP stations ......................................................................................30Figure 37. Map showing locations of USGS sampling stations along the USGS transect ................................32Figure 38. Daily Delta Outflow Index and distribution of surface salinity along the USGS transect .............35Figure 39. Delta Outflow Index and temperatures along the USGS transect for 1993–1995 ..........................39Figure 40. Delta Outflow Index and concentrations of total suspended solids along the USGS transect .......40Figure 41. Delta Outflow Index and concentrations of chlorophyll-a along the USGS transect ......................42Figure 42. Delta Outflow Index and concentrations of dissolved oxygen along the USGS transect ................43Figure 43. Example of RMP station clusters for mercury and nickel based on sampling events 7–15 ............45Figure 44. Total mercury distributions mapped in UTM coordinates ................................................................47Figure 45. Moran scatter plot for silver during sampling event 13 ...................................................................49Figure 46. Trends in various trace element totals during 1991–1995 ...............................................................51Figure 47. Total cadmium versus Net Delta Outflow..........................................................................................52Figure 48. Correlation of SSC and total or near-total concentrations of mercury ............................................54Figure 49. Time series of mid-depth SSC and total mercury concentration at Point San Pablo ......................55

List of Figures

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Figure 50. Abundance of Alexandrium spp. cells at South Bay, Central Bay, and North Bay locations .........59Figure 51. Paralytic shellfish poisoning toxin levels from the CDHS Toxic

Phytoplankton Monitoring Program ................................................................................................60Figure 52. Abundance of Pseudo-nitzschia spp. cells at South Bay, Central Bay, and North Bay locations ...63Figure 53. Abundance of Oscillatoria spp. cells at South Bay and North Bay locations ..................................64Figure 54. Abundance of Prorocentrum spp. cells at South Bay and North Bay locations ...............................65Figure 55. Comparison of PCB congeners in water from Coyote Creek and Petaluma River and

in sediment from South Bay .............................................................................................................67Figure 56. Congener-specific PCB concentrations (totals) for 1995, by reach ...................................................69Figure 57. Total concentrations of pesticides in water for each reach of the Estuary, 1995 .............................70Figure 58. Total concentrations of aliphatic hydrocarbons in RMP water samples, August 1995 ...................72Figure 59. Total concentrations of PAHs in RMP water samples .......................................................................74Figure 60. Comparison of PAH profiles in water and sediment from the

Northern Estuary and the South Bay ..............................................................................................75Figure 61. 1995 water trace organic concentrations normalized to TSS through linear regression ................77Figure 62. Plots of average arsenic concentrations in water in each Estuary reach ........................................80Figure 63. Plots of average cadmium concentrations in water in each Estuary reach .....................................80Figure 64. Plots of average chromium concentrations in water in each Estuary reach....................................81Figure 65. Plots of average copper concentrations in water in each Estuary reach..........................................81Figure 66. Plots of average lead concentrations in water in each Estuary reach .............................................82Figure 67. Plots of average mercury concentrations in water in each Estuary reach.......................................82Figure 68. Plots of average nickel concentrations in water in each Estuary reach ..........................................83Figure 69. Plots of average selenium concentrations in water in each Estuary reach .....................................83Figure 70. Plots of average silver concentrations in water in each Estuary reach ...........................................84Figure 71. Plots of average zinc concentrations in water in each Estuary reach ..............................................84Figure 72. Plots of average PAH concentrations in water in each Estuary reach .............................................87Figure 73. Plots of average PCB concentrations in water in each Estuary reach .............................................87Figure 74. Plots of average diazinon concentrations in water in each Estuary reach ......................................88Figure 75. Plots of average chlorpyrifos concentrations in water in each Estuary reach .................................88Figure 76. Plots of average DDT concentrations in water in each Estuary reach ............................................89Figure 77. Plots of average chlordanes concentrations in water in each Estuary .............................................89

Sediment MonitoringFigure 1. Arsenic concentrations in sediment ...................................................................................................95Figure 2. Cadmium concentrations in sediment ...............................................................................................96Figure 3. Chromium concentrations in sediment ..............................................................................................97Figure 4. Copper concentrations in sediment ....................................................................................................97Figure 5. Lead concentrations in sediment........................................................................................................98Figure 6. Mercury concentrations in sediment ..................................................................................................98Figure 7. Nickel concentrations in sediment .....................................................................................................99Figure 8. Selenium concentrations in sediment ................................................................................................99Figure 9. Silver concentrations in sediment ....................................................................................................100Figure 10. Zinc concentrations in sediment .......................................................................................................100Figure 11. Total PAH concentrations in sediment .............................................................................................101Figure 12. Total PCB concentrations in sediment .............................................................................................101Figure 13. Total DDT concentrations in sediment ............................................................................................102Figure 14. Sediment bioassays at selected RMP stations .................................................................................103Figure 15. Percentage of sediment bioassays that were toxic at RMP stations from 1991–1996 ..................105Figure 16. Relationships between the number of ERL exceedances and bioassay endpoints at

each RMP station, 1993–1995 ........................................................................................................106Figure 17. Mortality of the three amphipod species with increasing concentrations of cadmium,

DDT, and crude oil .......................................................................................................................... 112Figure 18. Benthic sampling sites ...................................................................................................................... 116Figure 19. Mean numbers of species, individuals, and biomass per sample collected during both

sampling periods in 1995 ................................................................................................................120

xi

Figure 20. Overview map of study sites in and near San Francisco Bay .........................................................124Figure 21. Schematic illustration of the method for determining the lower tolerance interval bound..........125Figure 22. Plots of average arsenic concentrations in sediments in each Estuary reach ...............................132Figure 23. Plots of average cadmium concentrations in sediments in each Estuary reach ............................132Figure 24. Plots of average chromium concentrations in sediments in each Estuary reach ..........................133Figure 25. Plots of average copper concentrations in sediments in each Estuary reach ................................133Figure 26. Plots of average lead concentrations in sediments in each Estuary reach ....................................134Figure 27. Plots of average mercury concentrations in sediments in each Estuary reach .............................134Figure 28. Plots of average nickel concentrations in sediments in each Estuary reach .................................135Figure 29. Plots of average selenium concentrations in sediments in each Estuary reach ............................135Figure 30. Plots of average silver concentrations in sediments in each Estuary reach ..................................136Figure 31. Plots of average zinc concentrations in sediments in each Estuary reach ....................................136Figure 32. Plots of average PAH concentrations in sediments in each Estuary reach ...................................137Figure 33. Plots of average PCB concentrations in sediments in each Estuary reach....................................137Figure 34. Plots of average DDT concentrations in sediments in each Estuary reach ...................................138Figure 35. Plots of average chlordane concentrations in sediments in each Estuary reach ...........................138

Bivalve MonitoringFigure 1. Arsenic concentrations in transplanted bivalves ............................................................................142Figure 2. Cadmium concentrations in transplanted bivalves.........................................................................143Figure 3. Chromium concentrations in transplanted bivalves .......................................................................144Figure 4. Copper concentrations in transplanted bivalves .............................................................................145Figure 5. Lead concentrations in transplanted bivalves .................................................................................146Figure 6. Mercury concentrations in transplanted bivalves ...........................................................................147Figure 7. Nickel concentrations in transplanted bivalves ..............................................................................148Figure 8. Selenium concentrations in transplanted bivalves .........................................................................149Figure 9. Silver concentrations in transplanted bivalves ...............................................................................150Figure 10. Tributyltin concentrations in transplanted bivalves .......................................................................151Figure 11. Zinc concentrations in transplanted bivalves ..................................................................................152Figure 12. Total PAH concentrations in transplanted bivalves ........................................................................153Figure 13. Total PCB concentrations in transplanted bivalves ........................................................................154Figure 14. Total DDT concentrations in transplanted bivalves........................................................................155Figure 15. Total chlordane concentrations in transplanted bivalves ...............................................................156Figure 16. Dieldrin concentrations in transplanted bivalves ...........................................................................157Figure 17. Percent survival in four species of transplanted bivalves ..............................................................158Figure 18. Condition indices of three species of transplanted bivalves ...........................................................159Figure 19. Tissue residue selenium levels in transplanted vs. resident species .............................................165Figure 20. Selenium concentrations in Potamocorbula amurensis ..................................................................166Figure 21. Spatial trends of selenium concentrations in tissues of Potamocorbula amurensis .....................167Figure 22. Selenium concentrations in tissues of mussels, clams and oysters ................................................167Figure 23. Original and corrected bioaccumulation results .............................................................................178Figure 24. Arsenic accumulation or depuration in three species of transplanted bivalves ............................183Figure 25. Cadmium accumulation or depuration in three species of transplanted bivalves ........................183Figure 26. Chromium accumulation or depuration in three species of transplanted bivalves .......................184Figure 27. Copper accumulation or depuration in three species of transplanted bivalves .............................184Figure 28. Lead accumulation or depuration in three species of transplanted bivalves ................................185Figure 29. Mercury accumulation or depuration in three species of transplanted bivalves ...........................185Figure 30. Nickel accumulation or depuration in three species of transplanted bivalves ..............................186Figure 31. Selenium accumulation or depuration in three species of transplanted bivalve ...........................186Figure 32. Silver accumulation or depuration in three species of transplanted bivalves ...............................187Figure 33. Zinc accumulation or depuration in three species of transplanted bivalves..................................187Figure 34. Total PAH accumulation or depuration in three species of transplanted bivalves.......................191Figure 35. Total PCB accumulation or depuration in three species of transplanted bivalves ........................191Figure 36. Total DDT accumulation or depuration in three species of transplanted bivalves .......................192

List of Figures

xii


Pilot and Special StudiesFigure 1. Location of RMP wetland sampling sites .........................................................................................198Figure 2. Wetland channel order classification ...............................................................................................199Figure 3. Silver concentrations at China Camp and Petaluma ......................................................................202Figure 4. Arsenic concentrations at China Camp and Petaluma ...................................................................202Figure 5. Cadmium concentrations at China Camp and Petaluma ...............................................................203Figure 6. Chromium concentrations at China Camp and Petaluma ..............................................................203Figure 7. Copper concentrations at China Camp and Petaluma ....................................................................204Figure 8. Iron concentrations at China Camp and Petaluma.........................................................................204Figure 9. Mercury concentrations at China Camp and Petaluma .................................................................205Figure 10. Manganese concentrations at China Camp and Petaluma.............................................................205Figure 11. Nickel concentrations at China Camp and Petaluma .....................................................................206Figure 12. Lead concentrations at China Camp and Petaluma .......................................................................206Figure 13. Selenium concentrations at China Camp and Petaluma ................................................................207Figure 14. Zinc concentrations at China Camp and Petaluma ........................................................................207Figure 15. Total HCH concentrations at China Camp and Petaluma..............................................................208Figure 16. Total PAH concentrations at China Camp and Petaluma ..............................................................208Figure 17. Total PCB concentrations at China Camp and Petaluma...............................................................209Figure 18. Total chlordane concentrations at China Camp and Petaluma ......................................................209Figure 19. Total DDT concentrations at China Camp and Petaluma ..............................................................210

Other Monitoring ActivitiesFigure 1. Percent TOC and sand in sediment samples during the month of February ................................255Figure 2. Percent TOC and sand in sediment samples during the August/September sampling ................256Figure 3. Percent TOC in sediment samples during the wet and dry seasons ..............................................258Figure 4. Percent sand in sediment during the wet and dry seasons ............................................................259Figure 5. Typical water quality in the CMP study area..................................................................................262Figure 6. Ambient Program sample events and mean daily river flows:

American River at Discovery Park .................................................................................................263Figure 7. Ambient Program sample events and mean daily river flows:

Sacramento River at Freeport ........................................................................................................263Figure 8. Compliance with US EPA water quality criteria: American River sites ........................................264Figure 9. Compliance with US EPA water quality criteria: Sacramento River sites ....................................264

ConclusionsFigure 1. Mercury cycling in a marine environment .......................................................................................277

xiii

CoverRegional Monitoring Program Participants ....................................................................................... Inside Cover

IntroductionTable 1. Summary of RMP 1995 sampling stations and activities. ....................................................................4Table 2. 1995 RMP contractors and principal investigators ...............................................................................5Table 3. Parameters analyzed in water, sediment, and bivalve tissues during the 1995 RMP .................... 7-9

Water MonitoringTable 1. Summary of hydrographic/water quality conditions in the San Francisco Bay

Estuary around the periods of RMP water sampling, 1993–1995 ...................................................36Table 2. RMP and pilot sampling events ............................................................................................................44Table 3. Summary of spatial ANOVA results .....................................................................................................48Table 4. Mantel tests of association between trace element totals, TSS and

spatial position for sampling event 12 ..............................................................................................49Table 5. Number of sampling events per calendar year quarter ......................................................................50Table 6. Maximum abundance and number of occurrences of harmful, toxic, or

noxious microalgal taxa in three regions of San Francisco Bay ......................................................61Table 7. Phytoplankton sampling dates in San Francisco Bay, 1992–1995 .....................................................62Table 8. Concentrations of pesticides in the Central Bay, 1980–1995 ..............................................................71Table 9. Concentrations of hydrocarbons in the Central Bay, 1980–1995 .......................................................73Table 10. Basin Plan water quality ojectives for toxic pollutants for surface waters. .......................................90Table 11. EPA conversion factors for trace elements in water ............................................................................90Table 12. EPA “National Toxics Rule” Water Quality Criteria for Priority Toxic Pollutants ............................91Table 13. Summary of contaminants that were above water quality objectives or criteria at each

1995 RMP water sampling station ....................................................................................................92

Sediment MonitoringTable 1. Percent survival of A. abdita in Experiment 1 using Alameda home sediments, and

cadmium or crude oil-spiked home sediments ................................................................................109Table 2. Percent survival of the three species tested in their respective home sediments, Bodega

control sediment, the solvent control, and the various spiked treatments ................................... 111Table 3. LC50 values and 95% confidence intervals for the three amphipod species exposed to

cadmium, DDT and weathered crude oil in Experiment 2 ............................................................ 113Table 4. Minimum effective concentration of the toxicants used in the experiments as based on

each of the three endpoints .............................................................................................................. 115Table 5. Characteristics of “normal” or reference benthic assemblages and those impacted by

contaminants .................................................................................................................................... 117Table 6. Major benthic assemblages in the San Francisco Estuary in 1994 and 1995 .................................. 118Table 7. Reference Sites ....................................................................................................................................123Table 8. Commonly used sediment quality guidelines ....................................................................................129Table 9. Summary of contaminants in sediment that were above sediment ERL and ERM

guidelines ..........................................................................................................................................130

Bivalve MonitoringTable 1. Determination of selenium and mercury in standard reference materials......................................164Table 2. Comparison of selenium concentrations in transplant and resident species the North

Bay in May 1995...............................................................................................................................165Table 3. Selenium concentrations in Potamocorbula amurensis in the North Bay .......................................168Table 4. Mercury concentrations in Potamocorbula amurensis and Macoma balthica in the

North Bay .........................................................................................................................................170Table 5. Summary of comparisons of data distributions from the LEMP, RMP, and SMW ..........................173

List of Tables

xiv


Table 6. Average trace element concentrations in bivalve tissue statewide and in the Estuary ................ 182Table 7. Commonly used tissue guidelines for trace contaminants .............................................................. 189Table 8. Summary of contaminants that were above the MTRLs at each RMP station ............................. 193

Pilot and Special StudiesTable 1. Spatial and temporal patterns in trace element concentrations ..................................................... 211Table 2. Spatial and temporal patterns in trace organic concentrations ..................................................... 212Table 3. Ecological indicators workshop participants ................................................................................... 217Table 4. Examples of ecological indicators for several levels of biological organization ............................. 219Table 5. General criteria for ecological indicators ......................................................................................... 219Table 6. Candidate water column indicators discussed at the workshop ..................................................... 220Table 7. Candidate sediment indicators discussed at the workshop ............................................................ 221Table 8. Revised criteria for evaluation of upper trophic level indicators.................................................... 222Table 9. Evaluation of upper trophic level indicators .................................................................................... 223Table 10. Summary of the RMP’s 1995 intercomparison studies ................................................................... 226Table 11. SFERM-S95 trace element multivariate comparison results using Bonferroni T-test ................. 227Table 12. SFERM-S95 organics multivariate comparison results using Bonferroni T-test .......................... 228Table 13. Comparison of the method detection limits for trace elements in sediment.................................. 229Table 14. Comparison of the method detection limits for organics in sediment ............................................ 230Table 15. Precision evaluation for the 1995 sediment trace element intercomparison exercises ................. 231Table 16. Precision evaluation for the 1995 tissue trace element intercomparison exercises ...................... 232Table 17. Precision evaluation for the 1995 tissue trace organics intercomparison exercises ...................... 233Table 18. NOAA/9 trace element multivariate comparison results using the Bonferroni T-test .................. 234Table 19. Percentage of the 1995 intercomparison studies performed that were with in the 95%

confidence interval or the RMP accuracy guidelines ................................................................... 235Table 20. NIST/NOAA pesticide multivariate comparison results using the Bonferroni T-test ................... 236Table 21. NIST/NOAA PCB multivariate comparison results using the Bonferroni T-test .......................... 237

Other Monitoring ActivitiesTable 1. Trace elements, TOC, and sand in sediment samples

(February 1994 and February 1995) ............................................................................................. 257Table 2. Trace elements, TOC, and sand in sediment samples

(August 1994 and August/September 1995) ................................................................................. 257Table 3A. Mean trace metal concentrations in the deposit-feeding bivalve, Macoma balthica,

collected during the wet and dry season in 1995, at the LEM sites ............................................ 260Table 3B. Trace metal concentrations in the tissue of the filter-feeding bivalve, Crassostrea gigas,

during the wet and dry season in 1995 ......................................................................................... 260

ConclusionsTable 1. Global atmospheric mercury ............................................................................................................. 278Table 2. Sources and uses of mercury............................................................................................................. 279Table 3. Methyl mercury concentrations in the food web.............................................................................. 284Table 4. Selected mussel watch data from Bodega Head and San Francisco Bay 1971–1992, with

RMP transplant data, 1993 and 1994 ........................................................................................... 289Table 5. DDTs and PCBs, Aroclor basis, in shiner perch from San Francisco Bay, 1965 vs. 1994 ............. 290Table 6. PCBs in the water column of San Francisco Bay, 1976–1994 ......................................................... 292Table 7. Past inputs of PCBs into waters of San Francisco Bay from waste water treatment plants ....... 293Table 8. PCBs in surface sediments of San Francisco Bay, 1974–1993, and in sediments at 176

US coastal sites in the mid 1980’s ................................................................................................. 295

Introduction

1

CHAPTER ONE

Introduction

2


Introduction

This report describes the results from the1995 Regional Monitoring Program for TraceSubstances (RMP). It includes data and discus-sions from the Base Monitoring Program, aswell as results of Pilot Studies and SpecialStudies conducted in 1995. Additionally, thisAnnual Report includes several articles contrib-uted by RMP investigators and others. Thesearticles provide perspective and insight onimportant contaminant issues identified by theRMP. Some of those articles are summaries ofmore detailed RMP Technical Reports, notedwhere applicable.

Some background information about theRMP, included in previous Annual Reports, isnot repeated in this report. Instead, the readeris referred to those reports where appropriate.A full description of the RMP is also included inthe RMP Program Plan available from SFEI, oron the World Wide Web: www.sfei.org.

In 1995, sixty-three federal, state, and localagencies and companies, and the San FranciscoBay Regional Water Quality Control Boardparticipated in the RMP which entered into itsthird year. RMP Participants are listed insidethe front cover of this report.

RMP Objectives

The formal program objectives listed beloware those with which the RMP began in 1993.They were developed by staff at the San Fran-cisco Bay Regional Water Quality ControlBoard (Regional Board), representatives ofRMP Participants, and San Francisco EstuaryInstitute (SFEI) staff.

• To obtain high quality baseline datadescribing the concentrations of toxic andpotentially toxic trace elements andorganic contaminants in the water andsediment of the San Francisco Estuary;

• To determine seasonal and annual trendsin chemical and biological water qualityin the San Francisco Estuary;

• To continue to develop a data set that canbe used to determine long-term trends inthe concentrations of toxic and poten-tially toxic trace elements and organiccontaminants in the water and sedimentsof the San Francisco Estuary;

• To determine whether water quality andsediment quality in the Estuary at largeare in compliance with objectives estab-lished by the Basin Plan; and

• To provide a data base on water andsediment quality in the Estuary which iscompatible with data being developed inother ongoing studies in the system,including, but not limited to, wasteloadallocation studies and model develop-ment, sediment quality objectives devel-opment, in-bay studies of dredged mate-rial disposal, Interagency EcologicalProgram (IEP) water quality studies,primary productivity studies, local effectsbiomonitoring programs, and state andfederal mussel watch programs.

Sampling Design

The RMP sampling design was based on theBay Protection and Toxic Cleanup Program(BPTCP) Pilot Studies developed by the Re-gional Board (Flegal et al., 1994). The reason-ing behind the original design, with stationslocated along the “spine” of the Estuary, was toinclude stations that, in a long-term monitoringprogram, would indicate spatial and temporaltrends in toxicity and chemistry, determinebackground concentrations for different reachesof the Estuary, and assess whether there werehigh levels of contaminants or toxicity. Severalnew stations were added in 1994 (SFEI, 1995),as well as two stations in the southern-mostend of the Estuary in cooperation with thecities of San Jose (C-3-0) and Sunnyvale (C-1-3)and the Regional Board as part of their Na-tional Pollutant Discharge Elimination System(NPDES) monitoring.

Introduction

3

Figure 1. Location of 1995 Regional Monitoring Program stations.

Coyote Creek

South Bay

Dumbarton Bridge

Redwood Creek

San Bruno Shoal

Oyster Point

Alameda

Yerba Buena IslandGolden Gate

HorseshoeBay

RichardsonBay

Point Isabel

Red Rock

Petaluma River

San Pablo Bay

PinolePoint

Davis Point

Napa River

Pacheco Creek

Grizzly Bay

Honker Bay Sacramento River

San Joaquin River

Water

Sediment

Bivalve Tissues

San Jose

Sunnyvale

4


Station Name Station T ype of Measurement Dates Sampled Latitude Lon g itudeCode Sample Made d e g min sec d e g min sec

Coyote Creek BA10 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 28 11 122 3 50BA10 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 37 28 12 122 3 36BA10 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 28 11 122 3 50

South Bay BA20 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 29 41 122 5 20BA21 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 29 38 122 5 15

Dumbarton Bridge BA30 water Q,M,O 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 30 54 122 8 7BA30 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 37 30 54 122 8 7BA30 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 30 54 122 8 7

Redwood Creek BA40 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 33 40 122 12 34BA40 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 32 49 122 11 42BA41 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 33 40 122 12 37

San Bruno Shoal BB15 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 37 1 122 17 0BB15 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 37 1 122 17 0

Oyster Point BB30 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 40 12 122 19 45BB30 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 37 40 12 122 19 45

Alameda BB70 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 44 50 122 19 24BB70 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 44 50 122 19 24BB71 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 41 44 122 20 23

Yerba Buena Island BC10 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 49 22 122 20 58BC10 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 49 22 122 20 58BC11 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 49 26 122 20 56

Golden Gate BC20* water Q,M,O 2/7 – 2/16 37 44 49 122 32 9water Q,M,O 4/19 – 4/28 37 46 12 122 32 24water Q,M,O 8/15 – 8/24 37 47 44 122 29 17

Horseshoe Bay BC21 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 49 59 122 28 26BC21 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 49 59 122 28 26

Richardson Bay BC30 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 51 49 122 28 40BC32 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 37 51 49 122 28 43

Point Isabel BC41 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 53 2 122 20 33BC41 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 37 53 2 122 20 33

Red Rock BC60 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 55 0 122 26 0BC60 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 37 55 0 122 26 0BC61 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 37 55 42 122 28 8

Petaluma River BD15 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 6 37 122 29 13BD15 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 38 6 47 122 30 4BD15 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 6 37 122 29 13

San Pablo Bay BD20 water Q,M,O 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 2 55 122 25 11BD20 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 2 55 122 25 43BD22 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 38 2 52 122 25 14

Pinole Point BD30 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 1 29 122 21 39BD30 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 1 0 122 22 3BD31 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 38 1 29 122 21 43

Davis Point BD40 water Q,M,O 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 3 7 122 16 37BD40 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 3 16 122 15 38BD41 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 38 3 7 122 16 39

Napa River BD50 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 5 47 122 15 37BD50 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 38 5 47 122 15 37BD50 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 5 47 122 15 37

Pacheco Creek BF10 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 3 5 122 5 48BF10 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 38 3 5 122 5 48

Grizzly Bay BF20 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 6 58 122 2 19BF20 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 6 29 122 3 22BF21 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 38 6 58 122 2 21

Honker Bay BF40 water Q,M 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 4 2 121 55 56BF40 sediment Q,M,O 2/17 – 2/23 8/25 – 8/31 38 4 2 121 55 56

Sacramento River BG20 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 3 34 121 48 35BG20 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 38 3 34 121 48 35BG20 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 3 34 121 48 35

San Joaquin River BG30 water Q,M,O,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 38 1 24 121 48 27BG30 sediment Q,M,O,T 2/17 – 2/23 8/25 – 8/31 38 1 24 121 48 27BG30 bioaccumulation M,O,C 4/26 – 4/28 9/13 – 9/17 38 1 24 121 48 27

San Jose C-3-0 water Q,M,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 27 43 121 58 32C-3-0 sediment Q,M 2/17 – 2/23 8/25 – 8/31 37 27 43 121 58 32

Sunnyvale C-1-3 water Q,M,T 2/7 – 2/16 4/19 – 4/28 8/15 – 8/24 37 26 8 122 0 40C-1-3 sediment Q,M 2/17 – 2/23 8/25 – 8/31 37 26 8 122 0 40

* location dependent on salinity Q = water and/or sediment qualityT = toxicity (only for Cruises 7 and 9) M = trace metalsC = bivalve condition index O = trace organics

Table 1. Summary of RMP 1995 sampling stations and activities.

Introduction

5

Introduction

RMP station locations were not randomlychosen, and therefore estimates of the arealextent of water quality changes cannot bemade. It was initially decided to locate sites asfar as possible from the influence of majorcontaminant sources in order to be able tointerpret temporal and spatial variability in thedata without the confounding variable ofcontaminant inputs from nearby sources.However, several stations are located near themouths of the major tributaries to the Estuary.

The five types of samples collected in the1995 Base Program included:

1. Conventional water quality and chemistry2. Aquatic bioassays3. Sediment quality and chemistry4. Sediment bioassays5. Transplanted, bagged bivalve

bioaccumulation, survival and condition

The locations of the 22 RMP and twoSouthern Slough (C-3-0, C-1-3) samplingstations are shown in Figure 1; Table 1 lists thestation names, codes, locations, and sampling

dates for all 1995 stations. The coding systemdeveloped in the BPTCP Pilot program wasadopted for use in the RMP. Water,bioaccumulation, or sediment sampling stationswith the same station name (location) mayhave slightly different locations due to practicalconsiderations such as sediment type or abilityto deploy bivalves, and thus have differentstation codes. For example, at the South Baystation, BA20 is the water station code andBA21 is the sediment station code.

Sampling occurred during three periods in1995: during the wet season (February), aperiod of declining Delta outflow (late April),and during the dry season (late August). Exactsampling dates are listed in Table 1. Logisticand scheduling constraints of this large, Estu-ary-wide program precluded sampling atconsistent monthly or daily tidal cycles.

Not all parameters were measured at allRMP stations for each sampling period. Sam-pling activities at each station are listed onTable 1. Water samples were collected at all

Prime Contractors Dr. Bob Spies and Dr. Andy GuntherApplied Marine Sciences, Livermore, CA

Trace Element Chemistry Dr. Russ Flegal, UC Santa Cruz, CADr. Eric Prestbo, Brooks-Rand, Seattle, WADr. Allen Uhler, Battelle, Duxbury, MA

Trace Organic Chemistry Dr. Bob Risebrough, Bodega Bay Institute, CADr. Terry Wade, Texas A&M University, TXDr. Walter Jarman, UC Santa Cruz, CA

Water Bioassays Dr. Stephen HansenS.R. Hansen and Associates, Concord, CA

Sediment Bioassays Mr. John Hunt and Mr. Brian AndersonMarine Pollution Lab, Granite Canyon, CA

Bagged Bivalve Sampling Mr. Dane Hardin, Applied Marine Sciences.

USGS Water Quality Dr. James Cloern, USGS, Menlo Park, CADr. Alan Jassby, UC Davis

USGS Sediment Transport Dr. David Schoellhamer, USGS, Sacramento, CA

Pilot Study on Benthic Macrofauna Dr. Bruce Thompson, SFEI, Richmond, CAMr. Harlan Proctor, Dept. of Water Resources,Sacramento, CA

Pilot Study on Tidal Wetlands Dr. Josh Collins, SFEI, Richmond, CA

Table 2. 1995 RMP contractors and principal investigators.

6


stations during all three sampling periods.However, trace organics contaminants in waterwere only measured at 15 stations wherebioaccumulation measurements were made.Aquatic bioassays were conducted at 13 sta-tions during the wet- and dry-season samplingperiods.

Sediment sampling was conducted duringthe wet- and dry-season periods only. Sedimentsamples were collected from all RMP stationswith the addition of Coyote Creek (BA10) andPetaluma River (BD15) in 1995. Sedimenttoxicity was measured at 12 of those stationsduring the wet- and dry-sampling periods.Measurements of ammonia and sulfides insediment were also added in 1995.

Bivalve bioaccumulation and conditionwere measured at 15 stations during the wet-and dry-season sampling periods.

The water and sediment samples werecollected from aboard the R/V DAVIDJOHNSTON chartered through the Universityof California, Santa Cruz. During each sam-

pling period, water sampling was conductedfirst at all RMP stations. Sediment samplingfollowed, making a separate run though theEstuary. Each sampling run required three tofive days for completion. The bivalve monitor-ing consisted of three parts: deployment oftransplants from reference sites, maintenance,and retrieval. This work was conducted usingthe R/V RINCON POINT, owned by the City ofSan Francisco, in cooperation with the Bureauof Water Pollution Control.

As in past years, sampling and analysiswere conducted by contract through AppliedMarine Sciences in Livermore, CA. The princi-pal investigators for the main components ofthe RMP are listed in Table 2.

Complete listings of all chemical param-eters measured in 1995 are included in Table 3.Methods of collection and analysis are detailedin Appendix A. All RMP data included in thisreport is available through SFEI or on theWorld Wide Web: www.sfei.org.

Introduction

7

Table 3. Parameters analyzed in water, sediment, and bivalve tissues during the 1995 RMPsampling of the San Francisco Estuary.

A. Conve ntional Wate r Quality Parame te rs D. Trace e le me ntsConductivity Wate r Se dime nt TissueDissolved Organic Carbon Aluminum* ● ●

Dissolved Oxygen (DO) Arsenic ● ● ●

Hardness Cadmium* ● ● ●

pH (acidity) Chromium ● ● ●

Phaeophytin (a chlorophyll degradation product) Copper* ● ● ●

Temperature Iron* ●

Chlorophyll-a Lead* ● ● ●

Total Suspended Sediments Manganese* ●

Dissolved Phosphates Mercury ● ● ●

Dissolved Silicates Nickel* ● ● ●

Dissolved Nitrate Selenium ● ● ●

Dissolved Nitrite Silver* ● ● ●

Dissolved Ammonia Zinc* ● ● ●

Dibutyltin (DBT) ●

B. Se dime nt Quality Parame te rs Monobutyltin (MBT) ●

% Clay (<4um) Tributyltin (TBT) ●

% Silt (4um–63um) Tetrabutyltin (TTBT) ●

% Sand (63um–2mm)% Gravel + Shell (>2mm) * Near-total rather than total concentrationsAmmonia Near-total metals are extracted with a weak acid (pH < 2)Hydrogen Sulfide for a minimum of one month, resulting in measurementspH that approximate bioavailability of these metals toTotal Organic Carbon Estuary organisms.Total Sulfide

C. Bivalve Tissue Parame te rs E . Hydrocarbons% Lipids Wate r Se dime nt Tissue% Moisture Alkanes n-C11 to n-C32 ● ●

% Solids Alkanes C10, C33, C34 ●

Dry Weight Phytane ● ●

Species Survival Pristane ● ●

Species Condition Total Alkanes ● ●

8


F. Polycyclic Aromatic Hydrocar bons (PAHs) F. PAHs (continue d)Wate r Se dime nt Tissue Wate r Se dime nt Tissue

2 rings C1-Phenanthrenes/Anthracenes ● ●

1-Methylnaphthalene ● ● C2-Phenanthrenes/Anthracenes ● ●

2,3,5-Trimethylnaphthalene ● ● C3-Phenanthrenes/Anthracenes ● ●

2,6-Dimethylnaphthalene ● ● C4-Phenanthrenes/Anthracenes ● ●

2-Methylnaphthalene ● ●

Biphenyl ● ● G. Synthe tic Biocide sNaphthalene ● ● Wate r Se dime nt Tissue

3 rings Cyclope ntadie ne s1-Methylphenanthrene ● ● ● Aldrin ● ●

Acenaphthene ● ● Dieldrin ● ● ●

Acenaphthylene ● ● Endrin ● ● ●

Anthracene ● ● ●

Dibenzothiophene ● ● Chlordane sFluorene ● ● alpha-Chlordane ● ● ●

Phenanthrene ● ● ● cis-Nonachlor ● ● ●

4 rings gamma-Chlordane ● ● ●

Benz(a)anthracene ● ● ● Heptachlor ● ● ●

Chrysene ● ● ● Heptachlor Epoxide ● ● ●

Fluoranthene ● ● ● Oxychlordane ● ● ●

Pyrene ● ● ● trans-Nonachlor ● ● ●

5 ringsBenzo(a)pyrene ● ● ● DDTsBenzo(b)fluoranthene ● ● ● o,p'-DDD ● ● ●

Benzo(e)pyrene ● ● ● o,p'-DDE ● ● ●

Benzo(k)fluoranthene ● ● ● o,p'-DDT ● ● ●

Dibenz(a,h)anthracene ● ● ● p,p'-DDD ● ● ●

Perylene ● ● p,p'-DDE ● ● ●

6 rings p,p'-DDT ● ● ●

Benzo(ghi)perylene ● ●

Indeno(1,2,3-cd)pyrene ● ● ● HCHsalpha-HCH ● ● ●

Alkylate d PAHs beta-HCH ● ● ●

C1-Chrysenes ● ● delta-HCH ● ● ●

C2-Chrysenes ● ● gamma-HCH ● ● ●

C3-Chrysenes ● ●

C4-Chrysenes ● ● Othe rC1-Dibenzothiophenes ● ● Dacthal ●

C2-Dibenzothiophenes ● ● Diazinon ●

C3-Dibenzothiophenes ● ● Endosulfan I ●

C1-Fluoranthenes/Pyrenes ● ● Endosulfan II ●

C1-Fluorenes ● ● Endosulfan Sulfate ●

C2-Fluorenes ● ● Mirex ● ● ●

C3-Fluorenes ● ● Oxadiazon ●

C1-Naphthalenes ● ●




Table 3. Parameters analyzed (continued).

Introduction

9

H. PCBs and Re late d CompoundsWate r Se dime nt Tissue Wate r Se dime nt Tissue

Hexachlorobenzene ● ● ● PCB 114 ●

PCB 003/30 ● PCB 118 ● ● ●

PCB 007/9 ● ● PCB 119 ●

PCB 008 ● PCB 128 ● ● ●

PCB 008/5 ● ● PCB 129 ● ●

PCB 015 ● ● ● PCB 132 ●

PCB 016/32 ● ● PCB 136 ● ●

PCB 018 ● ● ● PCB 137 ●

PCB 022/51 ● ● PCB 137/176 ● ●

PCB 024/27 ● ● PCB 138 ●

PCB 025 ● ● PCB 138/160 ● ●

PCB 026 ● PCB 141 ●

PCB 027 ● PCB 141/179 ● ●

PCB 028 ● ● ● PCB 146 ● ● ●

PCB 029 ● ● ● PCB 149 ●

PCB 031 ● ● ● PCB 149/123 ● ●

PCB 033/53/20 ● ● PCB 151 ● ● ●

PCB 037/42/59 ● ● PCB 153 ●

PCB 040 ● ● PCB 153/132 ● ●

PCB 041/64 ● ● PCB 156 ●

PCB 044 ● ● ● PCB 156/171 ● ●

PCB 045 ● ● PCB 157 ●

PCB 046 ● ● PCB 158 ● ● ●

PCB 047/48/75 ● ● PCB 167 ● ● ●

PCB 049 ● ● ● PCB 170 ●

PCB 052 ● ● ● PCB 170/190 ● ●

PCB 056/60 ● ● PCB 172 ● ●

PCB 060 ● PCB 174 ● ● ●

PCB 066 ● ● ● PCB 177 ● ● ●

PCB 070 ● ● ● PCB 178 ● ● ●

PCB 074 ● ● ● PCB 180 ● ● ●

PCB 082 ● ● PCB 183 ● ● ●

PCB 083 ● ● PCB 185 ● ●

PCB 084 ● ● PCB 187 ●

PCB 085 ● ● ● PCB 187/182/159 ● ●

PCB 087 ● PCB 189 ● ● ●

PCB 087/115 ● ● PCB 191 ● ●

PCB 088 ● ● PCB 194 ● ●

PCB 089 ● PCB 195 ●

PCB 092 ● ● PCB 195/208 ● ●

PCB 095 ● PCB 196/203 ● ●

PCB 097 ● ● ● PCB 198 ●

PCB 099 ● ● ● PCB 200 ● ● ●

PCB 100 ● ● PCB 201 ● ●

PCB 101 ● PCB 203 ●

PCB 101/90 ● ● PCB 205 ● ●

PCB 103 ● PCB 206 ● ● ●

PCB 105 ● ● ● PCB 207 ●

PCB 107/108/144 ● ● PCB 209 ● ●

PCB 110 ●

PCB 110/77 ● ●

Table 3. Parameters analyzed (continued).

10


CHAPTER TWO

Water Monitoring

Water Monitoring

11

BackgroundThe water monitoring component of the

RMP Base Program has two purposes. Themost important purpose is to evaluate compli-ance with water quality objectives. Ancillarywater quality measurements are also measuredto appraise water quality in the Estuary and toprovide supporting data for interpretation ofcontaminant concentrations which can bedirectly influenced by salinity, total suspendedsediments (TSS), dissolved organic carbon(DOC), and other parameters.

Samples were collected approximately 1 mbelow the surface at 22 RMP stations, and attwo stations in the southern end of the Estuaryin cooperation with the Regional Board and theCities of San Jose (C-3-0) and Sunnyvale (C-1-3) (Figure 1 in Chapter One: Introduction).Water sampling in the Sacramento and SanJoaquin Rivers during peak flows, conducted inthe first two years of the RMP, was suspendedin 1995. Sampling was conducted during threesampling periods in 1995, the wet season(February), declining hydrograph (April), andthe dry season (August). Detailed methods ofsampling and analysis are included in Appen-dix A. Sampling dates and activities are listedin Table 1 in Chapter One: Introduction. Dataare tabulated in Appendix C.

Conventional water quality parameters(Table 3 in Chapter One: Introduction) weremeasured at all sampling stations. Salinity,DOC, and TSS measurements are shown inFigures 1–3. Concentrations of ten trace ele-ments were measured at all stations (Table 3 inChapter One: Introduction). Dissolved (0.45 µmfiltered) and total (arsenic, chromium, mercury,selenium) and near-total (cadmium, copper,lead, nickel, silver, and zinc) concentrations arepresented in graphic form in Figures 4–23.

Dissolved (1 µm filtered) and total fractionsof 135 trace organic compounds were measuredat the 15 stations where bioaccumulationsamples were also collected (Table 3 in ChapterOne: Introduction). The organic contaminantsrepresent four major groups of compounds: thePAHs, PCBs, alkanes, and pesticides. Selectedrepresentative compounds are presented ingraphic form in Figures 24–35.

In order to make comparisons of tracecontaminant concentration between differentareas of the Estuary, stations were groupedsubjectively into five Estuary reaches based onsimilarities in water quality, trace contamina-tion, and geography. The reaches are: theSouthern Sloughs (C-1-3, C-3-0), South Bay(seven stations: BA10–BB70), Central Bay (fivestations: BC10–BC60), Northern Estuary (eightstations: BD15–BF40) and Rivers (BG20, BG30).

Water Quality Objectives andCriteria

In this report, comparisons to water qualityobjectives are made to evaluate the overallcondition of the Estuary in terms of contamina-tion, and not for any regulatory purpose. Waterquality objectives currently in effect for the SanFrancisco Estuary are those of the San Fran-cisco Bay Basin (Region 2) Water QualityControl Plan (Basin Plan, SFBRWQCB, 1995a)and the US EPA (National Toxics Rule, US EPA,1993c).

For this report, RMP trace element data arecompared to the lower values from the 1995Basin Plan objectives and the US EPA-NTR.Trace organics data are compared to US EPA-NTR human health criteria (at a 10-6 risk level)and chronic, 4-hour average, aquatic life criteriawhen available. Concentrations below thesevalues should produce no adverse effects.

In some cases measurements made by theRMP differ from the way the criteria are ex-pressed. For example, the water quality objec-tive for total PAHs from the 1995 Basin Planincludes sums of the compounds listed in theEPA Method 610 while the RMP total PAHsinclude sums of a different suite of compounds.

Different standards exist for saltwater andfreshwater (salinity below 5 ppt as defined inthe Basin Plan). Eight RMP stations and bothSouthern Slough stations had salinities below 5ppt in 1995 (Figure 1). Basin Plan water qualityobjectives for five of the ten metals measured atthose stations are related to water hardness(expressed as mg/L calcium carbonate). Sincethe RMP measured water hardness at thosestations (see Appendix C, Table 1), the exactcriteria at each station were calculated.

12


0

100

200

300

400

500

600

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

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15

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30

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70

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10

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20

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41

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15

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20

BD

30

BD

40

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50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

✪

Figure 2. Dissolved organic carbon (DOC) in micromoles per liter (µM) at each waterstation in February, April, and August of 1995. 1 µM of dissolved organic carbon is equal to 12µg/L. ✪ indicates not analyzed. DOC ranged from 116 µM to 581 µM. The highest concentration wassampled at Sunnyvale (C-1-3) in August and the lowest concentration was sampled in Point Isabel(BC41) in August. In general DOC concentrations were lowest in August, highest in February, andintermediate in April.

Dissolved Organic Carbon in Water 1995

DO

C, µ

M

SouthernSloughs

South Bay Central Bay Northern Estuary Rivers

0

5

10

15

20

25

30

35

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

★ ★★ ★★ ★★ ★★ ★★★★★★

Figure 1. Salinity in parts per thousand (‰) at each RMP water station in February, April,and August 1995. ★ indicates salinity was < 1 ‰. Samples were collected at approximately 1 mbelow the surface. Salinities ranged from below detection (1 ‰) to 33 ‰. The highest concentrationwas detected at Golden Gate (BC20) in August. Salinities were lowest in February as expected inthat very wet season. Salinities below 5 ‰ are considered freshwater for application of water qualitystandards.

SouthernSloughs


Salinity in Water 1995S

alin

ity, p

arts

per

thou

sand

Water Monitoring

13

0

50

100

150

200

250

300

350

400

450

C-1

-3

C-3

-0

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15

BD

20

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30

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40

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50

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10

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20

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40

BG

20

BG

30

FebruaryAprilAugust

Figure 3. Total suspended sediments (TSS) in milligrams per liter (mg/L) at each RMPwater station in February, April, and August of 1995. TSS concentrations ranged from 0.28mg/L to 414 mg/L. The highest concentration was sampled at Petaluma River (BD15) in April andthe lowest at Golden Gate (BC20) in August. Average TSS concentrations were higher in theSouthern Slough stations than other Estuary reaches. Generally concentrations were highest inApril in the Northern Estuary. Petaluma River (BD15) had a similar yet higher “spike” as in Aprilof 1994.

Total Suspended Sediments in Water 1995

TS

S, m

g/L

SouthernSloughs


14


0

1

2

3

4

5

6

7

C-1

-3

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-0

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30

FebruaryAprilAugust

0

1

2

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4

5

6C

-1-3

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-0

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10

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FebruaryAprilAugust

Figure 4. Dissolved arsenic (As) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved arsenicconcentrations ranged from 0.74 to 5.49 ppb. The highest and lowest concentrations were sampled atSunnyvale (C-1-3) in August and February respectively. Average concentrations were highest in theSouthern Sloughs in August (4.70 ppb) and lowest there in February (1.12 ppb). In general,concentrations were highest in August, intermediate in April and lowest in February. All stationswere below the 4-day average water quality objective for dissolved arsenic (saltwater 36 ppb,freshwater 190 ppb).

Dissolved Arsenic in Water 1995

SouthernSloughs


Dis

solv

ed A

rsen

ic, µ

g/L

Figure 5. Total arsenic (As) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Total arsenic concentrations rangedfrom 1.00 to 6.74 ppb. The highest and lowest concentrations were sampled at Sunnyvale (C-1-3) inAugust and February, respectively. Average concentrations were highest in the Southern Sloughs inAugust (6.38 ppb) and lowest there and in the Central Bay in February (1.35 ppb). In generalconcentrations were highest in August, intermediate in April and lowest in February in the SouthernSloughs, South and Central Bay. In the Northern Estuary and Rivers seasonal trends were not asapparent but generally were highest in August. All stations were below the 4-day average waterquality objective for total arsenic (saltwater 36 ppb, freshwater 190 ppb).

Total Arsenic in Water 1995

SouthernSloughs


Tota

l Ars

enic

, µg/

L

Water Monitoring

15

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

C-1

-3

C-3

-0

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30

FebruaryAprilAugust

Figure 6. Dissolved cadmium (Cd) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved cadmiumconcentrations ranged from 0.005 to 0.150 ppb. The highest concentration was sampled at CoyoteCreek (BA10) in August and the lowest value at the following stations: Napa River (BD50), PachecoCreek (BF10), Grizzly Bay (BF20), Honker Bay (BF40), and San Joaquin River (BG30) in April andGrizzly Bay (BF20) in February. Average concentrations were highest in the South Bay in August(0.130 ppb) and lowest in the Rivers in February (0.009 ppb). In general, concentrations were highestin August and lowest in February and April. All stations were below the 4-day average water qualityobjective for dissolved cadmium (saltwater 9.2 ppb, freshwater-hardness dependent).

Dissolved Cadmium in Water 1995

SouthernSloughs


Dis

solv

ed C

adm

ium

, µg/

L

0.00

0.03

0.06

0.09

0.12

0.15

C-1

-3

C-3

-0

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BD

20

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50

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40

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30

FebruaryAprilAugust

Figure 7. Near-total cadmium (Cd) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Near-total cadmiumconcentrations ranged from 0.017 to 0.140 ppb. The highest concentration was sampled at CoyoteCreek (BA10) and the South Bay station (BA20) in August. The lowest concentration was sampled atSan Joaquin River (BG30) in February and in April. Average concentrations were highest in theSouthern Sloughs in August (0.130 ppb) and lowest in the Rivers in August (0.020 ppb). In general,concentrations were highest August and lowest in February. All stations were below the 4-day averagewater quality objective for total cadmium (saltwater 9.3 ppb, freshwater-hardness dependent).

SouthernSloughs


Near-Total Cadmium in Water 1995

Nea

r-To

tal C

adm

ium

, µg/

L

16


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

C-1

-3

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-0

BA

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30

FebruaryAprilAugust

Figure 8. Dissolved chromium (Cr) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved chromiumconcentrations ranged from 0.10 ppb at Pacheco Creek (BF10) in August to 0.89 ppb at Honker Bay(BF40) in April. Average concentrations were highest at the River Stations in April (0.45 ppb) andlowest in the Northern Estuary in August (0.10 ppb). In general, concentrations were highest inFebruary and lowest in August. All stations were below the 4-day average water quality objective fordissolved chromium (saltwater 50 ppb, freshwater 10.82 ppb).

Dissolved Chromium in Water 1995D

isso

lved

Chr

omiu

m, µ

g/L

SouthernSloughs


0

1

10

100

C-1

-3

C-3

-0

BA

10

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30

FebruaryAprilAugust

✪★

Figure 9. Total chromium (Cr) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Note logarithmic scale. ✪ indicatesnot analyzed. Total chromium concentrations ranged from below the detection limit of 0.07 ppb (★) to42.980 ppb. The highest concentration was sampled at Petaluma River (BD15) in April. Averageconcentrations were highest in the Southern Sloughs in August (33.10 ppb) and lowest in the CentralBay in August (0.73 ppb). In general, concentrations were highest in April and lowest in August. Allsaltwater stations were below the saltwater, 4-day average water quality objective (WQO) for totalchromium of 50 ppb. Six freshwater stations (Figure 1) were above the freshwater, 4-day averageWQO of 11 ppb.

SouthernSloughs


Total Chromium in Water 1995

Tota

l Chr

omiu

m, µ

g/L

Water Monitoring

17

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

C-1

-3

C-3

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20

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30

FebruaryAprilAugust

Dissolved Copper in Water 1995

Figure 10. Dissolved copper (Cu) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Dissolved copper concentrations rangedfrom 0.280 to 4.77 ppb. The highest concentration was sampled at Petaluma River (BD15) in April and thelowest at Golden Gate (BC20) in August. Average concentrations were highest in the Southern Sloughs inAugust (4.08 ppb) and lowest in the Central Bay in April (0.85 ppb). Seasonal concentrations were highestin February from the the Central Bay to the north. Two stations were above the saltwater, 1-hour average,water quality objective (WQO) for dissolved copper of 4.1 ppb in April. None of the fresh water stationswere above the freshwater WQOs which are hardness dependent. Eight stations were above the EPA-National Toxics Rule saltwater, 4-day average, water quality criterion for dissolved copper of 2.32 ppb.

SouthernSloughs South Bay Central Bay Northern Estuary Rivers

Dis

solv

ed C

oppe

r, µg

/L

0

2

4

6

8

10

12

14

16

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

SouthernSloughs


Figure 11. Near-total copper (Cu) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Near-total copper concentrations ranged from0.19 to 15.28 ppb. The highest concentration was sampled at Petaluma River (BD15) in April and the lowestat Golden Gate (BC20) in August. Average concentrations were highest in the Southern Sloughs (9.17 ppb)and the Northern Estuary (8.37 ppb) in April, and lowest in the Southern Sloughs in August (0.97 ppb). Ingeneral, concentrations were highest in April and lowest in August. Five stations were above the saltwater,1-hour average, water quality objective (WQO) for total copper of 4.9 ppb in February, eight stations in April,and one station in August. None of the fresh water stations were above the freshwater WQOs which arehardness dependent. Note that because BD15, BD30, BD40, C-1-3 and C-3-0 were freshwater stationsduring April, they were not above the freshwater WQOs. Twenty-seven stations were above the EPA-National Toxics Rule saltwater, 4-day average water quality criterion for total copper of 2.9 ppb.

Near-Total Copper in Water 1995

Nea

r-To

tal C

oppe

r, µg

/L

18


0.001

0.010

0.100

1.000

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 12. Dissolved lead (Pb) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Note logarithmic scale.Dissolved lead concentrations ranged from 0.003 to 0.612 ppb. The highest concentration wassampled at Coyote Creek (BA10) in April and the lowest was sampled at Golden Gate (BC20) inAugust. Average concentrations were highest in the Southern Sloughs in February (0.333 ppb) andlowest in the Central Bay in April (0.006 ppb). Seasonal concentrations were generally lowest inAugust. All stations were below the 4-day average water quality objective for dissolved lead(saltwater 5.3 ppb, freshwater-hardness dependent).

Dissolved Lead in Water 1995

SouthernSloughs


Dis

solv

ed L

ead,

µg/

L

0

1

2

3

4

5

6

7

8

9

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 13. Near-total lead (Pb) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Near-total lead concentrationsranged from 0.010 to 8.08 ppb. The highest concentration was sampled at San Jose (C-3-0) and thelowest at Golden Gate (BC20). Average concentrations were highest in the Southern Sloughs inAugust (7.79 ppb) and lowest in the Central Bay in August (0.19 ppb). Concentrations were generallyhighest in April. Three stations were above the saltwater, 4-day average water quality objective(WQO) for total lead of 5.6 ppb, one in April, and two in August. Note that because BD15 and C-3-0were freshwater stations in April, they were not above the freshwater WQOs. None of the freshwater stations were above the freshwater WQOs which are hardness dependent.

SouthernSloughs


Near-Total Lead in Water 1995

Nea

r-To

tal L

ead,

µg/

L

Water Monitoring

19

0.000

0.001

0.001

0.002

0.002

0.003

0.003

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

★★ ★★ ★★★ ★ ★ ★ ★ ★ ★ ★ ★ ★

Figure 14. Dissolved mercury (Hg) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved mercuryconcentrations ranged from below the detection limit of 0.0001 ppb (★) to 0.00271 ppb. The highestconcentration was at Sunnyvale (C-1-3) in February. Sixteen stations had concentrations below theMDL. Average concentrations were highest in the Southern Sloughs in February (0.00264 ppb) andlowest in the Northern Estuary in August (0.00021 ppb). In general, concentrations were higher inFebruary and lowest in August. There are no water quality objectives for dissolved mercury.

SouthernSloughs


Dissolved Mercury in Water 1995D

isso

lved

Mer

cury

, µg/

L

0.001

0.010

0.100

1.000

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

★

Figure15. Total mercury (Hg) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Note logarithmic scale. Total mercuryconcentrations ranged from below the detection limit of 0.0001 ppb (★) to 0.105 ppb. The highestconcentrations were at San Jose (C-3-0) in August and Coyote Creek (BA10) in April and the lowestat Golden Gate (BC20) in August. Average concentrations were highest in the Southern Sloughs inAugust (0.103 ppb) and lowest in the Central Bay in August (0.00309 ppb). In general,concentrations were highest in April and lowest in August in the northern part of the Estuary butlowest in April in the southern part of the Estuary. Fifteen stations were above the 4-day averagewater quality objectives for total mercury (saltwater 0.025 ppb, freshwater 0.025 ppb).


Total Mercury in Water 1995

Tota

l Mer

cury

, µg/

L

20


0

2

4

6

8

10

12

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 16. Dissolved nickel (Ni) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved nickel concentrationsranged from 0.47 to 10.94 ppb. The highest concentration was sampled at San Jose (C-3-0) and thelowest at Golden Gate (BC20). Average concentrations were highest in the Southern Sloughs in August(8.53 ppb) and lowest in the Rivers in August (0.85 ppb). In general, concentrations were highest inApril and lowest in August. Only San Jose (C-3-0) in August was above the saltwater, 24-hour averagewater quality objective (WQO) for dissolved nickel of 7.0 ppb. None of the freshwater stations wereabove the freshwater WQOs which are hardness dependent. Note that because BD15 and C-3-0 werefreshwater stations during February and April, they were not above the freshwater WQOs.

Dissolved Nickel in Water 1995


Dis

solv

ed N

icke

l, µg

/L

0

5

10

15

20

25

30

35

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 17. Near-total nickel (Ni) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Near-total nickel concentrationsranged from 0.35 to 33.23 ppb. The highest concentration was sampled at Petaluma River and thelowest at Golden Gate (BC20). Average concentrations were highest in the Southern Sloughs in August(23.59 ppb) and lowest in the Central Bay in August (1.49 ppb). Seasonal trends varied in Februaryand April but concentrations were generally lowest in August except for the Southern Sloughs whereconcentrations were highest in August. Sixteen stations were above the saltwater, 24-hour averagewater quality objective (WQO) for total nickel of 7.1 ppb. None of the freshwater stations were abovethe freshwater WQOs which are hardness dependent. Ten stations were above the EPA-NationalToxics Rule 4-day average water quality criterion for total nickel of 8.3 ppb.


Nea

r-To

tal N

icke

l, µg

/L

Near-Total Nickel in Water 1995

Water Monitoring

21

0.0

0.5

1.0

1.5

2.0

2.5

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

★ ★ ★ ★ ★ ★

Figure 18. Dissolved selenium (Se) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved seleniumconcentrations ranged from below the detection limit of 0.019 ppb (★) to 2.08 ppb. The highestconcentration was sampled at Sunnyvale (C-1-3) in February. Six stations were below the MDL.Average concentrations were highest in the Southern Sloughs in February (1.64 ppb) and lowest inthe Central Bay in August (0.04 ppb). In general, concentrations were highest in April and lowest inAugust. There are no water quality objectives for dissolved selenium.


Dissolved Selenium in Water 1995D

isso

lved

Sel

eniu

m, µ

g/L

0.0

0.5

1.0

1.5

2.0

2.5

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

★ ★ ★ ★ ★ ★★

Figure 19. Total selenium (Se) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Total selenium concentrations rangedfrom below the detection limit of 0.019 ppb (★) to 2.24 ppb. The highest concentration was sampled atSunnyvale (C-1-3) in February. Seven stations were below the MDL. Average concentrations werehighest in the Southern Sloughs in February (1.73 ppb) and lowest in the Northern Estuary in August(0.10 ppb). In general, concentrations were highest in April and lowest in August. There are no BasinPlan water quality objectives for selenium. All stations were below the EPA-National Toxics Rule 4-day average water quality criteria for total selenium (saltwater 71 ppb and freshwater 5 ppb).


Total Selenium in Water 1995

Tota

l Sel

eniu

m, µ

g/L

22


0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 21. Near-total silver (Ag) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Near-total silver concentrationsranged from 0.002 to 0.113 ppb. The highest concentration was sampled at San Jose (C-3-0) inAugust, and Golden Gate (BC20) in August. Average concentrations were highest in the SouthernSloughs in August (0.113 ppb) and lowest in the Central Bay in February (0.003 ppb). No consistentseasonal variation was observed. All stations were below the instantaneous maximum water qualityobjectives for total silver (saltwater 2.3 ppb, freshwater 1.2 ppb).


Near-Total Silver in Water 1995

Nea

r-To

tal S

ilver

, µg/

L

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 20. Dissolved silver (Ag) concentrations in water in parts per billion (ppb) at 24RMP stations sampled in February, April, and August of 1995. Dissolved silver concentrationsranged from 0.00024 to 0.018 ppb. The highest concentration was sampled at Sunnyvale (C-1-3) inFebruary, and the lowest at San Joaquin River (BG30) in August. Average concentrations, by reach,were highest in the Southern Sloughs in February (0.0107 ppb) and lowest in the Rivers in August(0.0006 ppb). In general, concentrations were highest in August and lowest in April. All stations werebelow the instantaneous maximum water quality objectives for dissolved silver (saltwater 2.0 ppb,freshwater 1.0 ppb).


Dissolved Silver in Water 1995D

isso

lved

Silv

er, µ

g/L

Water Monitoring

23

0.01

0.10

1.00

10.00

100.00

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

Figure 22. Dissolved zinc (Zn) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. Note logarithmic scale. Dissolved zincconcentrations ranged from 0.09 to 22.41 ppb. The highest concentration was sampled at San Jose (C-3-0)in February and the lowest at Golden Gate (BC20) in August. Average concentrations were highest in theSouthern Sloughs in February (19.88 ppb) and lowest in the Rivers in August (0.38 ppb). In generalconcentrations were highest in February. All stations were below the 24-hour average water qualityobjectives for dissolved zinc (saltwater 55 ppb, freshwater-hardness dependent).


Dissolved Zinc in Water 1995D

isso

lved

Zin

c, µ

g/L

0

5

10

15

20

25

30

35

40

C-1

-3

C-3

-0

BA

10

BA

20

BA

30

BA

40

BB

15

BB

30

BB

70

BC

10

BC

20

BC

30

BC

41

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

10

BF

20

BF

40

BG

20

BG

30

FebruaryAprilAugust

✪

Figure 23. Near-total zinc (Zn) concentrations in water in parts per billion (ppb) at 24 RMPstations sampled in February, April, and August of 1995. ✪ indicates not analyzed. Near-total zincconcentrations ranged from 0.22 to 39.64 ppb. The highest concentration was sampled at San Jose inApril and the lowest at Golden Gate (BC20) in August. Average concentrations were highest in theSouthern Sloughs in August (30.83 ppb) and lowest in the Central Bay in August (1.42 ppb). In general,concentrations were lowest in August but varied in February and April. All stations were below the 24-hour average water quality objectives for total zinc (saltwater 58 ppb, freshwater-hardness dependent).


Near-Total Zinc in Water 1995

Nea

r-To

tal Z

inc,

µg/

L

24


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 24. Dissolved PAH concentrations in water (ppq) at 15 RMP stations sampled inFebruary, April, and August of 1995. Dissolved PAH concentrations ranged between 393 and8,240 ppq. The highest concentration was sampled at Yerba Buena Island (BC10) in August and thelowest at San Joaquin River (BG30) in April. Average concentrations were highest in the South Bayin August (6,443 ppq) and lowest in the Rivers in February (805 ppq). In general, concentrationswere highest in August and varied in February and April. There is no water quality guideline fordissolved PAHs.

Dis

solv

ed P

AH

s, p

g/L

Dissolved PAHs in Water 1995


1

10

100

1000

10000

100000

1000000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

✪

Figure 25. Total PAH concentrations in water in parts per quadrillion (ppq) at 15 RMPstations sampled in February, April, and August of 1995. ✪ indicates not analyzed. Total PAHconcentrations ranged between 2,822 and 504,872 ppq. The highest concentration was sampled atPetaluma River (BD16) in April, and the lowest at San Joaquin River (BG30) in April. Averageconcentrations were highest in the South Bay in April (238,552 ppq) and lowest in the Rivers inFebruary (3,434 ppq). In general, concentrations were highest in April and lowest in February. Nostations were above the Basin plan water quality objective for total PAHs of 15,000,000 ppq. Fourstations were above the water quality criterion for total PAHs from the US EPA National Toxics Ruleof 31,000 ppq in February, six in April, and four in August.

Total PAHs in Water 1995

Tota

l PA

Hs,

pg/

L


Water Monitoring

25

0

200

400

600

800

1000

1200

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 26. Dissolved PCB concentrations in water in parts per quadrillion (ppq) at 15RMP stations sampled in February, April, and August of 1995. Dissolved PCB concentrationsranged from 55 to 1,156 ppq. The highest concentration was sampled at the Dumbarton Bridge(BA30) in February, and the lowest at Golden Gate (BC20) in August. Average concentrations werehighest in the South Bay in February (502 ppq) and lowest in the Central Bay in August (79 ppq).There is no water quality guideline for dissolved PCBs.

Dissolved PCBs in Water 1995


Dis

solv

ed P

CB

s, p

g/L

0

1000

2000

3000

4000

5000

6000

7000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 27. Total PCB concentrations in water in parts per quadrillion (ppq) at 15 RMPstations sampled in February, April, and August of 1995. ✪ indicates not analyzed. Total PCBconcentrations ranged from 83 to 6,974 ppq. The highest concentration was sampled at PetalumaRiver (BD15) in April, and the lowest at the Golden Gate (BC20) in August. Average concentrationswere highest in the South Bay in April (2,893 ppq) and lowest in the Rivers in August (171 ppq). Ingeneral, concentrations were highest in April, but no other seasonal trend was apparent. The BasinPlan does not have a water quality objective for total PCBs, but US EPA-NTR PCB (Aroclor-based)criteria are 14,000 ppq for freshwater aquatic life, 30,000 ppq for saltwater aquatic life, and 45 ppqfor human health (consumption of organisms only). All stations were above the human healthcriterion during all sampling periods.

Total PCBs in Water 1995

Tota

l PC

Bs,

pg/

L


✪

26


0

50

100

150

200

250

300

350

400

450

500

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 28. Dissolved chlordane concentrations in water in parts per quadrillion (ppq) at15 RMP stations sampled in February, April, and August of 1995. Dissolved chlordaneconcentrations ranged from 21 to 456 ppq. The highest concentration was sampled at Coyote Creek(BA10) in April, and the lowest at the Golden Gate (BC20) in August. Average concentrations werehighest in the South Bay in February (228 ppq) and lowest in the Central Bay in August (42 ppq). Ingeneral, concentrations were lower in August than in February and April. There is no water qualityguideline for dissolved chlordanes.

Dissolved Chlordanes in Water 1995To

tal C

hlor

dane

s, p

g/L


0

200

400

600

800

1000

1200

1400

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 29. Total chlordane concentrations in water in parts per quadrillion (ppq) at 15RMP stations sampled in February, April, and August of 1995. (✪) indicates not analyzed.Total chlordane concentrations ranged from 32 to 1,235 ppq. The highest concentration was sampledat Coyote Creek (BA10) in April, and the lowest at the Golden Gate (BC20) in August. Averageconcentrations were highest in the South Bay in April (533 ppq) and lowest in the Central Bay inAugust (54 ppq). Concentrations were lower in August than in February and April. The Basin Plandoes not have a water quality objective for total chlordanes although several individual compoundshave objectives.


Total Chlordanes in Water 1995

Tota

l Chl

orda

nes,

pg/

L

✪ ✪

Water Monitoring

27

0

100

200

300

400

500

600

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 30. Dissolved DDT concentrations in water in parts per quadrillion (ppq) at 15RMP stations sampled in February, April, and August of 1995. Dissolved DDT concentrationsranged from 7 to 553 ppq. The highest concentration was sampled at Napa River (BD50) in April,and the lowest at the Golden Gate (BC20) in August. Average concentrations were highest in theRivers in April (355 ppq) and lowest in the Central Bay in August (65 ppq). In general,concentrations were higher in April than in February or August. There is no water quality guidelinefor dissolved DDT.


Dissolved DDTs in Water 1995D

isso

lved

DD

Ts, p

g/L

1

10

100

1000

10000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 31. Total DDT concentrations in water in parts per quadrillion (ppq) at 15 RMPstations sampled in February, April, and August of 1995. ✪ indicates not analyzed. Total DDTconcentrations ranged from 30 to 6,828 ppq. The highest concentration was sampled at PetalumaRiver (BD15) in April, and the lowest at Golden Gate (BC20) in August. Average concentrations werehighest in the Northern Estuary in April (2,666 ppq) and lowest in the Central Bay in August (131ppq). In general, concentrations were higher in April than in February or August. Water qualityobjectives do not exist for total DDTs although individual compounds have criteria.


Total DDTs in Water 1995

Tota

l DD

Ts, p

g/L

✪

28


0

2000

4000

6000

8000

10000

12000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

★

Figure 32. Dissolved diazinon concentrations in water in parts per quadrillion (ppq) at 15RMP stations sampled in February, April, and August of 1995. ★ indicates not detected.Dissolved diazinon concentrations ranged from below the detection limit to 11,000 ppq. The highestconcentration was sampled at Petaluma River (BD15) in February. Average concentrations werehighest in the Rivers in February (7,700 ppq) and lowest in the Central Bay in August (510 ppq). Ingeneral, concentrations were highest in February, lowest in August, and intermediate in April. TheBasin Plan does not have a water quality objective for diazinon. The National Academy of Sciencesrecommended a guideline of 9,000 ppq for the protection of aquatic life in freshwater. One stationwas above this guideline during February.

Dissolved Diazinon in Water 1995


Dis

solv

ed D

iazi

non,

pg/

L

0

2000

4000

6000

8000

10000

12000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

q

★

Figure 33. Total diazinon concentrations in water in parts per quadrillion (ppq) at 15 RMPstations sampled in February, April, and August of 1995. ★ indicates not detected. ✪ indicates notanalyzed. Total diazinon concentrations ranged from below the detection limit to 11,150 ppq. The highestconcentration was sampled at Petaluma River (BD15) in February, and the lowest at the Golden Gate(BC20) in August. Average concentrations were highest in the Rivers in February (7,700 ppq) and lowestin the Central Bay in August (510 ppq). For every station but BD40 concentrations were highest inFebruary, lowest in August, and intermediate in April. The Basin Plan does not have a water qualityobjective for diazinon. The National Academy of Sciences (1973) recommended a guideline of 9,000 ppq forthe protection of aquatic life in freshwater. One station was above this guideline during February.


Total Diazinon in Water 1995

Tota

l Dia

zino

n, p

g/L

✪

Water Monitoring

29

0

200

400

600

800

1000

1200

1400

1600

1800

2000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

0

200

400

600

800

1000

1200

1400

1600

1800

2000

BA

10

BA

30

BA

40

BB

70

BC

10

BC

20

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

FebruaryAprilAugust

Figure 34. Dissolved hexachlorocyclohexanes (HCHs) concentrations in water in parts perquadrillion (ppq) at 15 RMP stations sampled in February, April, and August of 1995.Dissolved HCH concentrations ranged from 27 to 1,874 ppq. The highest concentration was sampledat Coyote Creek (BA10) in February, and the lowest at the Sacramento River (BG20) in August.Average concentrations were highest in the South Bay in February (1,405 ppq) and lowest in theRivers in February (34 ppq). No consistent seasonal trend was obseved. The Basin Plan does nothave a water quality objective for total HCHs although several individual compounds have criteria.

Dissolved HCHs in Water 1995To

tal H

CH

S, p

g/L


Figure 35. Total hexachlorocyclohexanes (HCHs) concentrations in water in parts perquadrillion (ppq) at 15 RMP stations sampled in February, April, and August of 1995. ✪indicates not analyzed. Total HCH concentrations ranged from 27 to 1,906 ppq. The highestconcentration was sampled at Coyote Creek (BA10) in February, and the lowest at Sacramento River(BG20) in August. Average concentrations were highest in the South Bay in February (1,423 ppq)and lowest in the Rivers in August (37 ppq). Concentrations were highest in February at all stationsin the South Bay, but there was no consistent seasonal trend in other Estuary reaches. The BasinPlan does not have a water quality objective for total HCHs although several individual compoundshave criteria.


Total HCHs in Water 1995

Tota

l HC

HS

, pg/

L

✪

30


Figure 36. Chart showing results of aquatic bioassays at selected RMP stations.See Appendix A for a full description of the tests used. The controls used in both tests were cleanartificial seawater. The only sample that indicated toxicity in 1995 was the Mysidopsis test usingSan Joaquin River water in February. Many tests did not produce usable results. In the Februarybivalve test, four stations had poor mussel (Mytilus) larvae survival in the laboratory controls (na).In August, the oyster stocks apparently did not produce viable sperm or eggs which resulted inextremely poor fertilization or development and none of the tests were successful (F).

F0

102030405060708090

100Pinole Point—BD30

F0

102030405060708090

100Red Rock—BC60

San Joaquin River—BG30

na F

*

0102030405060708090

100

F0

102030405060708090

100Coyote Creek—BA10

Aquatic BioassaysLaboratory bioassays using Estuary water

were conducted at 13 RMP stations (Figure 36)during the wet sampling season (February) andagain in the dry sampling season (August).Sampling dates are listed in Table 3.

Two laboratory bioassays were conducted.Mysids (Mysidopsis bahia) were exposed to

Estuary water for seven days where percentsurvival was the endpoint. Larval mussels(Mytilus edulis) were exposed to Estuary waterfor 48 hours where percent normal developmentwas the endpoint. Detailed methods are includedin Appendix A. Complete test data are includedin Appendix C Table 10, and quality assuranceinformation is included in Appendix B Table 5.

Water Monitoring

31

Seasonal Fluctuations of Water Quality in SanFrancisco Bay During the First Three Years of the

Regional Monitoring Program, 1993-1995James E. Cloern, Brian E. Cole, and Jody L. Edmunds

United States Geological Survey, Menlo Park, California

Introduction

One objective of the Regional MonitoringProgram (RMP) is to determine seasonal andannual trends in the chemical and biologicalquality of the San Francisco Bay Estuary. Anelement of the RMP designed specifically toaddress this objective is a program of monthlywater quality measurements conducted by theUnited States Geological Survey (USGS). Thiselement is designed to describe spatial featuresof water quality variability along the longitudi-nal axis of the Bay-Delta, from the lowerSacramento River to the southern limit of theSouth Bay. These monthly measurementsprovide supplementary information to describeevents of water quality change between thethree annual periods of RMP sampling forcontaminants and toxicity. The monthly sam-pling is appropriate for describing seasonalpatterns of variability in the state of the Estu-ary and year-to-year fluctuation of the seasonalpatterns. The water quality parameters werechosen (1) as basic descriptors of the chemical-biological status of the Estuary, and (2) asquantities that reflect variability in processesthat control the concentration, chemical form,or biological availability of toxic contaminants.

A second objective of the RMP is to identifytrends of change in the distribution, concentra-tion, and harmful effects of contaminants inSan Francisco Bay. This objective poses adifficult challenge because estuaries have largenatural variability that acts as noise aroundthe signals of water quality improvement ordegradation over time. Progress toward thisobjective will require innovative approaches forcharacterizing the natural variability of biologi-cal and chemical conditions in the Estuary, and

then separating these from any trends ofchange. A primary mechanism of naturalvariability in San Francisco Bay is river flow,which controls: the distribution of salt, nutri-ents, and other dissolved constituents (Petersonet al., 1985), horizontal patterns of watercirculation (Monismith et al., 1996), inputs ofsediments and other suspended particles(Conomos et al., 1985a), annual recruitment ofanimals at different levels of the estuarine foodweb (Jassby et al., 1993), variability of metalenrichment in biota (Luoma et al., 1985), andthe timing of biological events such as algalblooms (Cloern and Jassby, 1995). During thefirst three years of the RMP, flows into the Bay-Delta were highly variable. Here we describesome basic responses of the Estuary to thishydrologic variability, with emphasis on thedifferent seasonal patterns of change observedduring 1993, 1994, and 1995. This informationis provided as a foundation from which we canbegin the more difficult process of interpretingvariability of trace substances and their effects.

The Measurement ProgramDesign

This element of the RMP characterizeswater quality in the deep channel of the Bay-Delta system. It includes measurements at aseries of fixed stations spaced every 3–6 kilome-ters, from Rio Vista (lower Sacramento River;Figure 37), through Suisun Bay, CarquinezStrait, San Pablo Bay, the Central Bay, and theSouth Bay to the mouth of Coyote Creek.Vertical profiles are obtained at each stationwith a submersible instrument package, so thismeasurement program provides two-dimen-sional (longitudinal-vertical) descriptions ofspatial structure. Sampling along the 145 km

32


transect requires 12–15 hours, so measure-ments are taken during varying phases of thesemidiurnal tide cycle. Although it is logisti-cally difficult to synchronize sampling to aconstant tidal phase, we minimized the effectsof intratidal variability by sampling near theperiods of monthly minimum tidal energy.Therefore, this sampling program is biasedtoward neap-tide conditions; it provides noinformation about lateral variability across theshallow habitats (e.g., Powell et al., 1989); andit is confounded by intratidal variability that issuperimposed onto the spatial patterns alongthe axial transect (e.g., Cloern et al., 1989).However, even with these biases and errors,

this sampling design provides meaningfuldescriptions of the primary features of spatialvariability along the Estuary.

Water Quality Parameters

This element of the RMP includes measure-ments of five water quality parameters, eachreflecting a different set of processes of variabil-ity. Salinity measures the relative proportion offreshwater and seawater along the axialtransect, and it reflects the changing impor-tance of river flow as a source of dissolvedmaterials carried into the Bay-Delta fromrunoff produced in the Estuary’s watershed.The salinity distribution also provides a first-

Figure 37. Map showing locations of USGS sampling stations along theaxial transect of the San Francisco Bay-Delta, from the lowerSacramento River to the southern South Bay. Distances along the transectare referenced as positive values for the North Bay and negative values for theSouth Bay (see Figures 38–42), starting at the station south of Angel Island.

Water Monitoring

33

order description of water density, a primaryforce that drives horizontal circulation andtransport (Monismith et al., 1996) as well asstratification and vertical mixing (Cloern,1984). Salinity also has direct influence on therates of geochemical processes such as adsorp-tion-desorption and the flocculation of dissolvedsubstances into aggregates. Therefore, salinityis an index of the strength of riverine inputs, adescriptor of horizontal and vertical processesof transport, and a geochemical control. All ofthese processes influence the distribution,chemical form, solute-sediment partitioning, orbiological availability of toxic substances. Watertemperature is measured as another indicatorof mixing, and because the biological transfor-mations of reactive trace substances are tem-perature-dependent processes.

The concentration of suspended particles(as total suspended sediments, TSS) is one ofthe most dynamic quantities in estuariesbecause of the alternating cycles of particledeposition and re-suspension driven by thetidal currents, and because of episodic changescaused by wind-driven re-suspension(Schoellhamer, 1996). Superimposed onto thesevertical processes of particle movement arehorizontal processes associated with the river-ine input of new sediments during periods ofhigh flow. All three of these processes arerelevant to the RMP because many tracesubstances are reactive with particle surfaces.Consequently, the pathways of transport,retention, and incorporation of these contami-nants into the estuarine food web can beinfluenced by the transport of sediments. Themonthly measurement program providesinformation about the large-scale changes inthe spatial distribution of TSS associated withriver inputs. Variability at shorter time scalesis characterized by the continuous measure-ments of TSS by moored instruments at fixedlocations (Schoellhamer, 1996).

The phytoplankton community representsthe single largest component of living biomassin San Francisco Bay, and we measure thedistribution of chlorophyll a as an index of thisbiomass. Unlike salinity and TSS, chlorophyll a

is a non-conservative quantity that changes inresponse to processes of production and con-sumption as well as inputs and transports. Theproduction of phytoplankton biomass involvesthe uptake of inorganic forms of elements (CO2,NO3, PO4, etc.) dissolved in the water, and thentransformation of these inorganic raw materi-als into new organic matter packaged as algalcells. The partitioning of reactive elementsbetween dissolved and particulate forms can behighly influenced by the phytoplankton commu-nity in San Francisco Bay (Cloern, 1996), andchlorophyll a is a simple indicator of the neteffect of these biotransformations. Recentobservations in South San Francisco Bay showthat enhanced algal uptake during bloomsleads to rapid reductions in the concentrationsof trace metals such as Cd, Zn, and Ni (Luomaet al., in prep); similar dynamic responses areexpected for chlorinated hydrocarbons andother reactive trace substances.

Finally, we measure dissolved oxygen (DO)concentration as an indicator of the net trophicstatus of the Estuary. When the oxygen contentof water is undersaturated (less than that atequilibrium with atmospheric oxygen), thisindicates that organic matter is consumed bythe heterotrophs faster than it is produced bythe phototrophs—the Estuary is ‘net het-erotrophic’. Conversely, supersaturation ofoxygen indicates a condition of ‘net autotrophy’when the photosynthetic production of newplant biomass within the Estuary is faster thanall the processes of consumption. Therefore, DOconcentration is an index of the balance be-tween production and consumption, a keydescriptor of the status of the ecosystem.Episodes of DO supersaturation occur duringperiods of rapid phytoplankton primary produc-tion when the inorganic forms of elements (C,N, P, Si, Cd, etc.) are rapidly removed fromsolution and converted into particulate form.Therefore, DO provides a useful indicator of therate of phytoplankton-mediated transforma-tions of reactive elements in the water column.

34


Methods

Data for this RMP element were collectedwith an instrument package that includessensors for measuring: depth (Paroscientificpressure transducer), conductivity (Sea-BirdElectronics-4 conductivity sensor), temperature(Sea-Bird Electronics-3 thermistor), TSS (Sea-Bird Electronics-3 optical backscatter sensor),chlorophyll (Sea-Tech invivo fluorometer orWET Labs a-3 absorption meter), and DO (Sea-Bird Electronics-13 oxygen electrode). Thesesensors are integrated with a Sea-Bird Elec-tronics-9 data acquisition system that digitizesand records signals 24 times per second. Thepackage is lowered through the water columnat about 1 m/s, giving a vertical resolution ofabout 4 cm. Here, we report only the measure-ments made in the upper meter of the watercolumn as the mean of measurements madebetween 0.5 and 1.5 m.

The conductivity and temperature sensorswere calibrated by the manufacturer at thebeginning of each year of sampling. The opticalbackscatter sensor, fluorometer, and oxygenelectrodes were calibrated each sampling datewith discrete measurements. Near-surfacewater samples were collected by pump andaliquots analyzed for: TSS (gravimetric methodof Hager, 1993, from samples collected onto 0.4-mm Nuclepore filters); chlorophyll a (spectro-photometric method of Lorenzen, 1967, usingsamples collected onto Gelman A/E filters,extracted in 90% acetone, and calculated withthe equations of Riemann, 1978, to correct forpheopigments); and dissolved oxygen (auto-mated Winkler titration of samples collected in300-ml BOD bottles, following Granéli andGranéli, 1991). Values reported here are calcu-lated quantities based on calibrations of theoptical backscatter, fluorescence, and oxygensensors from linear regressions of measuredconcentrations versus voltage output of eachinstrument. We used the empirical equation ofBenson and Krause (1984) to calculate oxygensolubility as a function of salinity and tempera-ture.

Detailed methods and the complete datasets for this RMP element are published inannual reports for: 1993 (Caffrey et al., 1994),1994 (Edmunds et al., 1995), and 1995(Edmunds et al., 1996). Copies of these reportsare available from the USGS in Menlo Park. Bythe end of 1997 we expect to make these, andsubsequent water quality data, available overthe Internet through the USGS home page ofSan Francisco Bay activities (URL = http://sfbay.wr.usgs.gov).

ResultsHydrologic Variability

The RMP design includes three periods ofwater monitoring each year to characterizevariability of trace substances among theperiods of high flow (February or March),declining flow (April or May), and low flow(August or September). Therefore, a key featureof RMP design is the description of variabilityassociated with the seasonal hydrologic cycle.The seasonal cycles varied considerably amongwater years 1993, 1994, and 1995, so the firstthree years of RMP provides water qualitymeasurements over an extreme range of hydro-logic conditions. The water year 1993 wasclassified as a wet year in California withstatewide runoff at 125% of normal (Roos,1996). Runoff produced three peaks in Deltaoutflow, with the highest Delta Outflow Index(DOI) of 4,200 m3/s in late March 1993 (Figure38). The first RMP water sampling was in earlyMarch 1993, when the DOI averaged 995 m3/s(Table 1). The second sampling (mean DOI of776 m3/s) occurred during the spring transitionperiod, and the third sampling (mean DOI of123 m3/s) during the summer period of low flow.The second year, 1994, was critically dry whenstatewide runoff was only 40% of normal (Roos,1996). The RMP water samplings occurredduring a highly damped seasonal cycle ofrunoff, with DOI ranging from 402 m3/s duringthe February 1994 sampling to only 110 m3/sduring the August 1994 sampling (Table 1). Incontrast, 1995 was the second wettest yearrecorded this century, with runoff at 180% ofnormal (Roos, 1996). This hydrologic year

Water Monitoring

35

Rio Vista

Chipps Is.

Suisun Bay

Carquinez Str.

San Pablo Bay

Richmond Br.

Angel Is.

Bay Bridge

San Mateo Br.

Dumbarton Br.

Coyote Cr.

1993 1994 1995

-40

-20

0

20

40

60

80

Dis

tan

ce (

km)

fro

m A

nge

l Isl

an

d

0 4 8 12 16 20 24 28 32Surface Salinity (psu)

0

2000

4000

6000D

elta

Ou

tflo

w (

m3/s

)

RMP Water Samplings

Figure 38. Upper panel shows the daily Delta Outflow Index (from California Departmentof Water Resources) for 1993–1995; large circles show the timing of the nine RMP water-monitoring samplings. Lower panel shows the changing distribution of surface salinity along theUSGS transect (Figure 37). Intensity of shading is proportional to salinity, with darker shadingsindicating higher salinities. The vertical axis represents variability in space, from the lowerSacramento River (top of figure) to Central Bay (at kilometer 0) and then to the lower South Bay(bottom of vertical axis). The horizontal axis represents variability in time, matched to the flow-variability above. The thick solid line shows the changing position of the location where surfacesalinity was 2 psu.

36


RM

PS

am

ple

Nu

mb

er

RM

PS

am

ple

Da

tes

US

GS

Sa

mp

leD

ate

Me

an

De

ltaO

utf

low

(m3 /s

)

Sa

linity

(psu

)T

em

pe

ratu

re(°

C)

TS

S(m

g/l

)C

hlo

rop

hyl

l a

(mg

/m3 )

Dis

so

lve

dO

xyg

en

(% s

atu

ratio

n)

12

–1

2 M

arch

19

93

24

Fe

b.

19

93

99

51

0.8

(0.0

7–

22

.4)

10

.9(9

.3–

11

.9)

67

(11

–1

70

)1

.8(1

.3–

3.0

)9

3(7

9–

96

)2

24

–2

7 M

ay1

99

31

2 M

ay1

99

37

62

12

.9(0

.06

–2

5.8

)1

7.0

(13

.8–

18

.1)

25

(1–

10

3)

2.2

(1.5

–4

.98

9(8

3–

94

)3

13

–1

6 S

ep

t.1

99

38

Se

pt.

19

93

12

32

2.2

(0.0

9–

29

.7)

20

.9(1

8.1

–2

2.8

)9

(5–

27

)2

.9(0

.7–

11

.8)

94

(71

–1

10

)4

31

Jan

.–9

Fe

b. 1

99

41

6–

17

Fe

b.

19

94

40

21

6.8

(0.1

–2

8.1

)1

1.1

(9.8

–1

1.8

)1

9(7

–3

6)

2.0

(1.1

–4

.1)

98

(92

–1

04

)

51

9–

27

Ap

ril1

99

41

9 A

pril

19

94

27

31

8.0

(0.1

–2

8.6

)1

7.2

(14

.9–

18

.6)

25

(5–

76

)3

.7(1

.6–

9.1

)9

6(8

2–

10

2)

61

5–

23

Au

g.

19

94

30

–3

1A

ug

.1

99

4

11

02

3.2

(0.0

9–

32

.2)

20

.4(1

6.5

–2

1.7

)1

0(5

–2

4)

3.1

(1.7

–6

.2)

95

(85

–1

02

)

76

–1

5 F

eb

.1

99

57

Fe

b.

19

95

2,4

90

6.5

(0.0

7–

16

.3)

12

.2(1

0.9

–1

3.6

)4

9(6

–1

00

)1

.3(0

.7–

2.5

)8

8(8

2–

93

)8

18

–2

7 A

pr.

19

95

18

–1

9A

pr.

19

95

2,2

76

8.3

(0.0

7–

17

.4)

13

.6(1

2.4

–1

4.3

)4

9(1

0–

23

9)

8.2

(3.0

–1

8.0

)9

16

–2

3 A

ug

.1

99

51

6 A

ug

.1

99

53

14

15

.5(0

.25

–2

7.6

)2

1.2

(18

.5–

23

.0)

19

(8–

48

)3

.7(1

.2–

6.5

)9

1(7

9–

10

2)

Tab

le 1

. Su

mm

ary

of h

ydro

grap

hic

/wat

er q

ual

ity

con

dit

ion

s in

th

e S

an F

ran

cisc

o B

ay E

stu

ary

arou

nd

th

e p

erio

ds

of R

MP

wat

ersa

mp

lin

g, 1

993–

1995

. Col

um

ns

2 an

d 3

show

dat

es o

f R

MP

sam

plin

g an

d th

e co

rres

pon

din

g da

tes

of U

SG

S s

ampl

ing.

Del

ta o

utf

low

is t

he

mea

nD

elta

Ou

tflo

w I

nde

x (f

rom

Cal

ifor

nia

Dep

artm

ent

of W

ater

Res

ourc

es)

for

the

peri

od o

f R

MP

sam

plin

g. V

alu

es f

or s

alin

ity,

tem

pera

ture

, con

cen

trat

ion

of s

usp

ende

d so

lids

(T

SS

), c

hlo

roph

yll a

, an

d di

ssol

ved

oxyg

en a

re m

ean

val

ues

of

nea

r-su

rfac

e (1

m)

mea

sure

men

ts a

t al

l US

GS

sta

tion

s al

ong

the

tran

sect

fro

m R

io V

ista

to

Coy

ote

Cre

ek (

see

Fig

ure

37)

. Val

ues

in p

aren

thes

es s

how

th

e ra

nge

of

mea

sure

men

ts a

lon

g th

e tr

anse

ct.

Water Monitoring

37

included extremely large floods in January andMarch, and above-average Delta outflowthroughout the year. The first RMP watersampling of 1995 occurred after the Januaryflood peak (mean DOI of 2,490 m3/s during thesampling period). The second 1995 samplingoccurred after the extreme March flood whenDOI peaked over 10,000 m3/s. And the thirdsampling occurred during a period of unusuallyhigh summer flows (mean DOI of 314 m3/sduring the RMP sampling).

Hydrographic/Water Quality Variability

Results of the water quality sampling aresummarized in Table 1, which gives thebaywide mean and range of each constituentfrom the USGS monthly samplings that coin-cided with the nine periods of RMP watermonitoring. In 1993 there were lags (up to twoweeks) between USGS and RMP water moni-toring, but since 1994 the two sampling effortshave been closely coordinated. This table showsthat the RMP water monitoring was done overa broad range of hydrologic conditions, from aminimum DOI of 110 m3/s to a maximum of2,490 m3/s. This hydrologic variability wasreflected in the surface distributions of salinityin the Bay-Delta, with transect-mean salinityranging from 23.2 psu during the low-flowsampling of 1994, to only 6.5 psu after the peakflows in February 1995. Results from all theUSGS measurements are depicted in Figure 38,which shows the spatial-temporal patterns ofsalinity as grayscale shadings. The upper panelshows the daily record of the Delta OutflowIndex, with circles noting the timing of the nineRMP water samplings. The bottom panel showssalinity as a shaded contour image whereshading intensity is proportional to salinity(dark shading = high salinity). The vertical axisrepresents the longitudinal transect from thelower Sacramento River (top of image, atkilometer 92), to the Central Bay at AngelIsland (kilometer 0), and then to the lowerSouth Bay at the mouth of Coyote Creek(kilometer -52.7). The horizontal axis repre-sents temporal variability, with grid linesseparating the three annual periods of mea-surement. This shaded image is based oninterpolations of 1,175 measurements, and it

shows considerable detail in the changingsalinity distribution of the Bay-Delta. However,several large-scale features are relevant to theinterpretation of results from the other RMPelements:

1. Northern San Francisco Bay had a persis-tent longitudinal salinity gradient,whereas the South Bay often had relativelyhomogeneous salinity. This reflects the roleof Delta outflow as a continual source offreshwater flow into the North Bay.

2. The shape of the North Bay salinity gradi-ent changed rapidly in response to chang-ing flows, with the low-salinity regiondisplaced seaward during the high-flowseason, and then gradual upstream migra-tion of the salinity gradient as flow recededin summer. This seasonal migration of thesalinity gradient is illustrated with thesolid line in Figure 38, which shows thechanging position of the 2-psu isopleth (thelocation where surface salinity was 2 psu;this gives a rough index of the changingposition of X2, defined as the locationwhere bottom salinity is 2 psu). Note thatthe surface waters of 2-psu salinity werelocated upstream, into the SacramentoRiver (kilometer 92), during the low-flowseason of the dry year 1994. At the otherextreme, the 2-psu salinity was displacedseaward into the eastern San Pablo Bay(kilometer 25) during the high-flow sam-pling of February 1995.

3. The salinity distribution in the South Baychanged in response to inputs of freshwa-ter from local streams during storm events.This was evident, for example, during early1993 when surface salinity was depressedin the region below the Dumbarton Bridge(Figure 38). Therefore, the salt content ofthe South Bay can be diluted by twodifferent sources of freshwater, one arriv-ing from the northern connection to Delta-derived flows, and the other from runoff inthe local watershed. We might expectdifferent chemical changes associated withflows delivered to the South Bay from thesetwo sources.

38


Water temperature measurements showed avery different pattern of seasonal-spatial vari-ability because temperature change is causedprimarily by heat transfers at the water surfacerather than from point source inputs. Therefore,the patterns of temperature change in the Bay-Delta were dominated by the seasonal solar cycle(Figure 39). The direction of the spatial tempera-ture gradient shifted seasonally because theincoming river water was colder than the coastalocean during winter, but the river water waswarmer than the coastal ocean during summer.For the nine RMP periods of water monitoring,the transect-mean temperature ranged from aminimum of 10.9 °C in March 1993 to a maxi-mum of 21.2 °C in August 1995. Water tempera-tures were unusually high during the secondhalf of 1995 (Figure 39). Subtle details of thetemperature structure can give clues aboutmixing patterns in the Bay-Delta. For example,the persistent summer feature of a temperaturegradient near kilometer -20 in the South Bay isconsistent with the concept that the San BrunoShoal acts to retard horizontal exchangesbetween the South Bay and the Central Baysuch that water retained below the San BrunoShoal can develop its own character (Powell etal., 1986). We might expect to find gradients ofother constituents, including some trace sub-stances, across this topographic control ofmixing.

Although the concentrations of suspendedsediments (measured as TSS) are dynamic andpatchy in San Francisco Bay, results of themonthly sampling program can be used todescribe the seasonal distributions of suspendedparticles along the Estuary axis. The shadedimage of Figure 4 shows that the spatial-tempo-ral patterns of TSS concentration are complexand patchy, but strongly influenced by theriverine input of sediments. River inputs to theNorth Bay were evident during the high-flowperiods of early 1993 and early 1995, when TSSconcentrations in surface waters exceeded 150mg/liter (near-bottom concentrations were evenhigher). Concentrations of TSS were relativelylow during the dry season of 1993 and through-out the dry year 1994. Particle concentrations inthe upper Estuary (upstream of CarquinezStrait) were usually greater than 40 mg/liter

throughout all of 1995, reflecting the persistentsource of sediments delivered by the sustainedhigh flows that year (recall that the USGSsampling is done on neap tides, so these patternsof TSS distribution would show higher concentra-tions on the spring tides; Schoellhamer, 1996).Riverine inputs also influence the distributions ofTSS in the lower South Bay, with highest concen-trations (up to 240 mg/liter) observed followinginputs of sediment from local streamflow duringthe storms of early 1993 and 1995 (Figure 40). Apersistent spatial feature was the relatively lowconcentration of suspended solids in the CentralBay, far from the riverine supplies of sedimentsand far from the shallow habitats where wind-wave resuspension creates high turbidity. Giventhe large range of TSS concentration among theperiods of RMP water sampling (from 1-239 mg/liter; Table 1), we might expect to find associa-tions between the total concentrations of particle-reactive trace substances and the patterns of TSSdistribution shown in Figure 40.

Phytoplankton biomass was usually low inthe Bay-Delta, with concentrations of chlorophylla often less than 4 mg/m3 (Figure 41). Theprominent exceptions were the South Bay springblooms when biomass increased rapidly andreached maximum chlorophyll a concentrationsof 50–70 mg/m3. These large biological eventsrecur each year, but the spatial extent andduration of the spring bloom changes from yearto year, partly in response to annual fluctuationsin river flow (Cloern and Jassby, 1995). Thespring bloom of 1994 was confined below the SanBruno Shoal (kilometer -20), whereas the 1995spring bloom developed along the entire SouthBay and into Central Bay (Figure 41). Thesebloom events have a large geochemical influencebecause they act to remove dissolved inorganicconstituents (C, N, P, Si) and transform them intoparticulate organic forms (Cloern, 1996). Luomaet al. (in prep) measured rapid depletions of sometrace metals (Cd, Ni, Zn) during the 1994 springbloom, so these seasonal periods of high phy-toplankton biomass and productivity are periodsof rapid change in the chemical form of reactivetrace substances. The 1993 RMP sampling inMarch occurred in the early stage of bloomdevelopment, so the biogeochemical effect ofphytoplankton activity may not be evident from

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Rio Vista

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Figure 39. Delta outflow index (top panel) and temperature distribution (lower panel)along the USGS transect for the years 1993–1995 (see Figure 38). Intensity of shading isproportional to temperature, with lighter shadings indicating higher temperatures.

40


Rio Vista

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Figure 40. Delta Outflow Index (top panel) and concentrations of total suspended solids(lower panel) along the USGS transect for the years 1993–1995 (see Figure 38). Intensity ofshading is proportional to TSS, with darker shadings indicating higher concentrations of suspendedsolids.

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the RMP measurements of 1993. The 1994 RMPsampling in early February occurred well beforethe bloom began, and the April sampling oc-curred a month after the period of maximumalgal biomass. However, the 1995 RMP samplingin April occurred at the end of a two-monthbloom, so we would expect depletions of thedissolved forms of biologically-reactive tracesubstances then. Contrasts between the Febru-ary and April RMP samplings in 1995 should,therefore, provide a valuable set of observationsfor characterizing the role of phytoplanktonblooms as mechanisms of variability in thechemical form and the concentration of tracesubstances. On the other hand, we expect thatphytoplankton assimilation was a relativelyminor component of trace-substance variabilityin Suisun Bay, where phytoplankton biomass(Figure 41) and primary productivity (Alpine andCloern, 1992) are very low .

The distributions of dissolved oxygen wereconsistent with the inferred patterns of phy-toplankton productivity. The oxygen content ofsurface waters in the Bay-Delta was usuallybetween 90–100% of that at equilibrium withatmospheric oxygen (Figure 42). Large, positivedepartures from this range occurred in the SouthBay during spring blooms when high rates ofalgal photosynthesis led to DO supersaturation.These episodes of oxygen supersaturation, shownas light-shaded patches in Figure 42, indicateperiods of rapid algal activity that would removesome trace contaminants from solution. Theimage in Figure 42 also shows episodes ofreduced (< 80% saturation) oxygen concentra-tions that were associated with the events ofhigh flow and high turbidity. These events of lowDO imply that the estuarine food web wassupported by external sources of organic matter(Jassby et al., 1993). We expect the pathways oftrophic transfer of matter, including tracecontaminants, to be different between theseepisodes of strong heterotrophy compared to thepathways of trophic transfer during blooms,when the food web was supported primarily byphytoplankton production.

SummaryIn this chapter we have used results of the

monthly USGS measurement program to de-

scribe the key features of water quality variabil-ity in San Francisco Bay during the first threeyears of the Regional Monitoring Program. Thepatterns of water quality variability are dis-played as shaded images that show the annualcycles, the large year-to-year fluctuation of theannual cycles, and the spatial gradients of waterquality from the Sacramento River to the south-ern South Bay. The seasonal, annual, and spatialpatterns all changed in response to fluctuationsin river flow, and the extreme hydrologic variabil-ity from 1993–1995 provides a valuable opportu-nity to characterize the distribution and effects oftrace contaminants across a broad range of flowconditions.

The five water quality parameters describedhere were chosen as quantities that integrate theeffects of different processes of estuarine variabil-ity, so results from this program are the logicalfoundation from which to begin interpretation ofthe more complex patterns of variability in tracecontaminants and their effects. The salinitypattern is the simplest and clearest index of theeffect of river flow on the distribution of dissolvedconstituents. Temperate patterns can be a usefulindicator of mixing, and spatial temperaturegradients can be used to identify water massesthat have acquired their own character. Thepatterns of suspended solids show the strongeffect of flow events as mechanisms that delivernew sediments to the Estuary, and they will beuseful in interpreting the changing distributionsof those contaminants bound to particle surfaces.Biological processes of transformation are in-dexed in the patterns of chlorophyll variabilitybecause phytoplankton comprise the largestcomponent of living biomass in San FranciscoBay, and because phytoplankton production is akey agent of biological transformation of reactivesubstances such as trace metals and chlorinatedhydrocarbons. The patterns of DO variabilityshow events of enhanced algal productivity, andthey also reflect different pathways of trophictransfer in the upper North Bay and the SouthBay. Since many contaminants enter food websthrough trophic transfer (feeding), these DOpatterns might be useful for interpreting patternsof variability in the bioaccumulation of tracesubstances.

42


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Figure 41. Delta Outflow Index (top panel) and concentrations of chlorophyll a (lowerpanel) along the USGS transect for the years 1993–1995 (see Figure 38). Intensity of shadingis proportional to chlorophyll a, with darker shadings indicating higher concentrations.

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Figure 42. Delta Outflow Index (top panel) and concentrations of dissolved oxygen (lowerpanel) along the USGS transect for the years 1993–1995 (see Figure 38). Intensity of shadingis proportional to DO in the surface waters, with lighter shadings indicating higher concentrations.

44


Methods for Analysis of Spatial and Temporal Patterns:Summary and Conclusions 1

Alan D. JassbyDivision of Environmental Studies

University of California, Davis, California

Introduction

The purpose of this summary is to suggestways in which RMP data can be analyzed todescribe spatial patterns and temporal trends.Four specific questions are used to guide andorganize the data exploration:

1. How do we determine spatial boundarieswithin which the data can be summarizedand between which comparisons should bemade?

2. How can differences in space be detected?3. How can significant relationships between

trace substance concentrations and envi-ronmental characteristics be determined?

4. How can differences in time be detected?

Guided by these questions, we arrive at aset of recommendations for analyzing RMPdata with an underlying goal of facilitating theupcoming five-year review of the data andprogram. Due to the size of the data set, thecomplexity of the issues, and the limited timeavailable, we have not attempted to apply anyof these techniques exhaustively to the data setfor definitive answers. This is the task of thefive-year review. We do offer a specific exampleof each recommended approach.

We used water column near-total traceelement data collected and provided by RussFlegal and his group at the University ofCalifornia at Santa Cruz. Although based onthe trace element data, our recommendationsshould be applicable to other trace contami-nants as well.

Spatial Stratification

Horizontal stratification of the Estuary canbe of value in reducing the variance of global

estimates such as the mean. We investigatedmodel-based clustering of the trace elementdata as a means for choosing the strata in thecase of San Francisco Bay (Figure 43). Twoproblems were encountered. First, the data aresufficient to identify, at most, only two signifi-cant clusters for any sampling event. Second,the clusters change both with the trace elementin question and the sampling event. The firstproblem is a consequence of the limited data.The second problem is an underlying feature ofthe Estuary. As a result, we believe that the useof clustering in this context is unlikely to be ofhelp, and is prone to mislead unless clusterstatistical significance is also assessed. Notethat stratification of the Estuary does not haveto be optimal in order to be effective in reducingvariance so that clustering and other “objective”approaches are not actually necessary.

1 This summary contains excerpts from a more extensive report available from SFEI. Space limitations did not allow fullelaboration of statistical methods in this summary—see the full report for more detail.

Eve nt S tart Finish

1 2 Apr. 1989 2 Apr. 19892 9 Aug. 1989 11 Aug. 19893 2 Dec. 1989 2 Dec. 19894 15 Jun. 1990 15 Jun. 19905 19 Sep. 1990 21 Sep. 19906 12 Jun. 1991 14 Jun. 19917 8 Apr. 1992 11 Apr. 19928 3 Mar. 1993 6 Mar. 19939 25 May 1993 28 May 1993

10 14 Sep. 1993 17 Sep. 199311 31 Jan. 1994 9 Feb. 199412 19 Apr. 1994 29 Apr. 199413 16 Aug. 1994 25 Aug. 199414 7 Feb. 1995 16 Feb. 199515 19 Apr. 1995 28 Apr. 1995

Table 2. RMP and pilot sampling events.

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Figure 43. Example of RMP station clusters for mercury and nickel based onsampling events 7–15 (Table 2). Spherical and unconstrained: refer to clusteringalgorithms; AWE: approximate weight of evidence for determining number of significantclusters. See full report for details.

46


In any case, stratification to reduce vari-ance is currently a moot point as the RMPstations are not a probability-based sample tobegin with and cannot provide proper estimatesof the Estuary’s mean and variance. Thedesirability of such global estimates and apossible redesign of station siting needs to beconsidered carefully.

If global estimates are desired, the stationsshould be laid out so that proper estimates canbe made of global properties such assubembayment means. Given the experience inother systems with significant spatialautocorrelation, a systematic (regular) grid ofstations is to be preferred over a random one.This “primary” set of stations should be supple-mented with a “secondary” set locatednearshore by effluents suspected to be impor-tant sources of one or more contaminants. Thepurpose of the primary set is to establishregional status and trends. The purpose of thesecondary set is to provide important supple-mental local information that could bear oncausality.

The number of primary stations needs to bedetermined on the basis of a model for thedesign and the desired performance in terms oftrend detection. An important requirement forthis determination is inclusion of the spatialcorrelation structure. The primary grid ofstations remains fixed through time, althoughthe exact subset of these stations sampled eachyear may cycle in some way.

Secondary stations, on the other hand, aredetermined by an understanding of possiblesources. The secondary set may change fromyear to year in a flexible way depending on theaccumulated data and changes in activitieswithin the watershed.

Regional Differences

Spatial stratification can also be pursuedfor other reasons, such as to identify local pointsources. A visual examination of the total traceelement spatial patterns, as well as consider-ation of hydrology and physiography, leads tothe choice of three or four subregions: 1. southof San Bruno Shoal (SB); 2. San Bruno Shoal

through Point San Pablo (CB); 3. north of PointSan Pablo (NB). The latter stratum can befurther subdivided between Honker and Grizzlybays, although this leaves only three stations inthe upstream stratum (Figure 44).

Spatial autocorrelation in estuaries poten-tially precludes the use of classical ANOVA forassessing subregion differences. Spatial ANOVA,in which individual sites are influenced not onlyby their location within subregions, but also bythe values at neighboring sites, provides thesolution. We examined the data for ten traceelements during 3 sampling events. We were ableto determine well-behaved models in 24 of the 30cases; 4 of the 24 cases required incorporation ofspatial autocorrelation effects. In 22 of the 24cases, we found evidence for distinct spatialsubregions. Further analyzing the pairwisedifferences, the most common pattern (18 of 24cases) was a depression of “Central Bay” (stra-tum 2 above) concentrations with respect to both“South” and “North” bay levels; means of thelatter two were not significantly different inthese cases (Table 3).

Causal Mechanisms

Anomalous stations for any trace elementand sampling event can be identified using theMoran scatterplot. Using a robust fit to theMoran scatterplot, we identified the most impor-tant positive anomalies for each trace elementduring sampling event 13. Positive anomaliescan be interpreted as important sources. The SanJose station was the most common anomaly,followed by the Petaluma River (Figure 45).

Spatial autocorrelation in estuaries willresult in potentially spurious correlations be-tween almost any two variables. The partialMantel test can be used to examine correlationsamong variables that are also spatiallyautocorrelated. As an example, 9 of 10 traceelements were correlated with TSS duringsampling event 12, but only one associationremained after spatial autocorrelation wasaccounted for using the partial Mantel statistic(Table 4). Accounting for spatial autocorrelationresults in a conservative test for associationbetween two variables; the actual causal relation

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Figure 44. Total mercury distributions mapped in UTM coordinates. Each mapcorresponds to a single element and single RMP sampling event. The area of each square isproportional to the concentration, expressed as a fraction of the largest value found in eachsampling event. The dashed line at 4,160 km separates out all stations south of the SanBruno Shoal. The dashed line at 4,200 km separates out all stations in the North Bay.

48


Table 3. Summary of spatial ANOVA results. See full report for details.

Ele me nt Eve nt Mode l Subre gions Diffe re nt? Pairwise Diffe re nce s

Ag 12 OLS y NB>CB, SB>CB13 -1 - -14 OLS y NB>CB, SB>CB

As 12 OLS -2 -13 LAG y NB>CB, SB>CB14 OLS n NB>CB

Cd 12 OLS n none13 -1 - -14 OLS y SB>CB, SB>NB

Cr 12 OLS y NB>CB, SB>CB13 OLS y NB>CB, SB>CB14 OLS y NB>CB, SB>CB, NB>SB

Cu 12 OLS y NB>CB, SB>CB13 OLS y NB>CB, SB>CB14 OLS y NB>CB, SB>CB

Hg 12 OLS y NB>CB, SB>CB, NB>SB13 ROBUST y NB>CB, SB>CB14 OLS y NB>CB, SB>CB

Ni 12 OLS y NB>CB, SB>CB13 OLS y NB>CB, SB>CB14 OLS y NB>CB, SB>CB

Pb 12 OLS y NB>CB, SB>CB13 LAG y NB>CB, SB>CB14 OLS y NB>CB, SB>CB

Se 12 LAG y SB>NB13 -1 - -14 LAG -3 -

Zn 12 OLS y NB>CB, SB>CB13 LAG y NB>CB, SB>CB14 LAG -3 -

1Diagnostics suggested higher-order process.2Non-normal.3Heteroscedastic.

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Figure 45. Moran scatterplots for each trace element duringsampling event 13. The dashed line is the linear regression line. The solidline is the least trimmed squares regression line. Three points aredesignated by their station codes rather than by circles. These have thethree most negative residuals with respect to the least trimmed squares line.

Association Ag As Cd Cr Cu Hg Ni Pb Se

TE·COG 0 .7 1 0 .7 9 0 .3 4 0 .9 8 0 .9 3 0 .9 7 0 .9 1 0 .8 6 -0.12TE·SPACE 0 .1 5 0.08 0 .3 3 0 .1 5 0.12 0 .1 6 0.12 0 .1 4 0 .5 9COG·SPACE 0 .1 4 0 .1 4 0 .1 4 0 .1 4 0 .1 4 0 .1 4 0 .1 4 0 .1 4 0 .1 4(TE·COG)·SPACE 0.06 0.06 -0.39 0 .7 2 0.41 0.56 0.34 0.41 -0.54(COG·SPACE)·TE -0.31 0.12 -0.18 -0.3 0.01 -0.66 -0.11 0.11 0.13(TE·SPACE)·COG -0.09 -0.25 0.25 -0.49 -0.37 -0.4 -0.32 -0.18 0.61

Table 4. Mantel tests of association between trace element totals, TSS and spatialposition for sampling event 12. TE, COG and SPACE refer to the respective distancematrices for the trace element, TSS and spatial position. X·Y denotes the Mantel statistic forX and Y. (X·Y)·Z denotes the partial Mantel statistic for X and Y given Z. Statisticssignificant at the p=0.05 level are in bold.

50


individual trends can guide selection of stationgroupings. A correction must be made for thecovariance among stations, similar to thecorrection for covariance among months in theconventional use of the seasonal Kendall test.An example is given with copper.

The power of trend tests can be increasedby removing exogenous sources of short-termvariance. Residuals are determined for aparametric (regression) or nonparametric(LOWESS) fit of the data and a Mann-Kendalltest is applied to the residuals. An example isgiven using Net Delta Outflow (NDO) andcadmium. NDO has a negative effect on cad-mium at all stations (Figure 47). Before ac-counting for NDO, only the San Joaquin stationexhibited a (down) trend. After accounting forNDO, this station no longer had a significanttrend while two stations near the Napa Rivershowed significant uptrends. Selection of theexogenous variable depends on the exactquestion being asked and must be consideredcarefully.

Seasonality may also contribute to short-term variability, even after correcting forseasonal exogenous variables such as flow. Thedata set is too small at present to correct forseasonality using a dummy variable approach.At certain stations, data may be sufficient fortrend tests using second-quarter data only, thusaverting the issue of seasonality (Table 5).

may be significant but simply cannot be verifiedstatistically.

Proper statistical testing of causal connectionbetween two variables does not consist of a singleassociation test, even if it incorporates a correc-tion for spatial autocorrelation. A causal analysisincludes an array of possible models, as well asthe associations, lack of associations, and arith-metic relationships among associations thataccompany each model. The RMP data is verylimited in its ability to support such a causalanalysis, primarily because of low power. How-ever, the data is sufficient to narrow down therange of possible models. An example usingchromium supports a direct effect of TSS onchromium. In general, though, the RMP shouldnot expect any definitive causal analysis result-ing from statistical analysis of the RMP data set.

Additional stations can only help, but it isdifficult to know how many are really necessary,and there is a possibility of wasting any effort onmore stations, at least in this particular context.Regardless of the success of a statistical analysis,an understanding of these causal relationshipsmust be founded also on general chemical andecological understanding, as well as non-RMPdata sets and experimental work. As the RMPencounters the limits of its baseline data collec-tion program in assessing causality on a statisti-cal basis, more attention should be given to howother kinds of field measurements and experi-ments can narrow down even further the set ofpossible models.

Temporal Trends

The Mann-Kendall test is an appropriateway for determining trace element trends atindividual sites. Individual site trends are by andlarge not significant. When trends are mapped inspace, however, trends of the same sign tend tooccur contiguously in apparently nonrandomclusters and suggest systematic changes forsubregions of the Estuary (Figure 46).

The seasonal Kendall test can be adapted totest for an overall trend in groups of stations.The increase in the power is such that an overalltrend may exist even when no trends can bedetected for individual sites. Mapping of the

Table 5. Number of sampling eventsper calendar year quarter.

Ye ar Q1 Q2 Q3 Q4

1989 0 1 1 11990 0 1 1 01991 0 1 0 01992 0 1 0 0

1993 1 1 1 01994 1 1 1 01995 1 11996

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Figure 46. Trends in various trace element totals during 1991–1995. Upright triangle represent uptrends and inverted trianglesrepresent downtrends. Weaker trends (p>0.1) are designated by smalltriangles, stronger trends (p≤0.1) by large triangles.

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Figure 47. Total cadmium versus Net Delta Outflow. Thestraight line in each panel is a linear regression fit.

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Time Series of Trace Element ConcentrationsCalculated from Time Series of Suspended Solids

Concentrations and RMP Water Samples:Summary and Conclusions 1

David H. SchoellhamerUnited States Geological Survey, Sacramento, California

IntroductionThe supply and fate of trace elements in San

Francisco Bay, which are partially dependentupon particulate matter in the Estuary, areimportant management issues. San FranciscoBay receives many waste water discharges,especially in areas south of the DumbartonBridge, that contain trace elements that accumu-late in benthic organisms (Luoma et al., 1985;Brown and Luoma, 1995). Trace elements tend toadsorb particulate matter (Kuwabara et al.,1989), so the fate of trace elements is partlydetermined by the fate of suspended solids.Concentrations of dissolved trace elements aregreater in the South Bay than elsewhere in SanFrancisco Bay, and bottom sediments are be-lieved to be a significant source (Flegal et al.,1991). The concentration of suspended particu-late chromium in the Bay appears to be con-trolled primarily by sediment re-suspension(Abu-Saba and Flegal, 1995). Water qualitystandards for trace elements in the Bay arewritten in terms of total or near-total traceelement concentrations (TEC).

This summary has two objectives. The firstis to demonstrate the relationship betweensuspended solids concentration (SSC) and TECby developing equations relating SSC to total (ornear-total) concentrations of trace elementsbased on Regional Monitoring Program (RMP)data collected during 1993 and 1994. The secondobjective is to demonstrate the temporal variabil-ity of TEC that are linearly correlated (LCTEC)with SSC by presenting time-series informationon LCTEC based on nearly continuous SSCmeasurements collected during the 1995 wateryear (October 1, 1994 to September 30, 1995) andthe SSC-LCTEC equations.

Data CollectionDuring 1993 and 1994, the RMP conducted

six sampling trips in San Francisco Bay duringwhich water quality samples were collectedand analyzed for many constituents, includingSSC and TEC (SFEI, 1994; SFEI, 1996). TheUSGS has also established several SSCmonitoring sites in San Francisco Bay atwhich SSC is measured every fifteen minutes.(Buchanan and Schoellhamer, 1995; Buchananet al., 1996).

Relations Between RMP SSCand TEC Data

Linear regression was used to determineequations relating RMP SSC and TEC data.The equations were applied to the USGS SSCmeasurements in Bay waters, so outlying datacollected in tributary streams were discarded.

Excellent correlations with SSC werefound for seven trace elements—silver, chro-mium, copper, mercury, nickel, lead, and zinc.For example, the linear regression for mercuryis shown in Figure 48 (115 samples, r2 is 0.90).All regressions are significant at less than the0.001 level. SSC accounts for approximately 90percent of the variability in the LCTEC. Poorcorrelations with SSC were found for the otherthree trace elements measured by the RMP—arsenic, cadmium, and selenium.

Outlying data from tributaries had eitherlow or high LCTEC compared to the predictedvalues based on SSC (‘x’ symbols in Figure 48).These data probably reflect the influentwaters, not Bay waters, and therefore werediscarded. For example, influent from wastewater treatment plants sometimes had agreater ratio of LCTEC to SSC than Bay

1 This summary contains excerpts from a more extensive report available from SFEI.

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waters, and influent from natural riverssometimes had a smaller ratio of LCTEC to SSC thanBay waters. Not all data collected at the tribu-tary sites are outliers because Bay waters maybe present at the sites (during flood tides forexample), the tributary discharge may be small,or the ratio of LCTEC to SSC of the influentwater may be close to that of Bay waters.

USGS SSC DataAn example time series of measured SSC

data from mid-depth at Point San Pablo is shownin Figure 49. The high frequency variations werecaused by tidal advection and tidal re-suspensionof suspended solids. The fortnightly variationwas caused by the spring-neap cycle. About one-half the variance of SSC was caused by thespring-neap cycle, and SSC lags the spring-neapcycle by about 2 days (Schoellhamer, 1996). Therelatively short duration of slack water limitedthe duration of deposition of suspended solidsand consolidation of newly deposited bed sedi-ment during the tidal cycle, so suspended solids

accumulated in the water column as a spring tidewas approached and slowly deposit as a neap tidewas approached. High concentrations in Januaryand March were the result of runoff from theCentral Valley, which transported suspendedsediments to the Bay. Stronger winds duringspring and summer increased sediment re-suspension in shallow water and thus increasedSSC throughout the Bay.

Calculated LCTEC During WaterYear 1995

LCTEC and SSC vary similarly in timebecause they are linearly related. An examplecalculated LCTEC time series for mercury atmid-depth at Point San Pablo is shown in Figure49. Total mercury concentration varied because oftidal advection and tidal re-suspension of sus-pended solids and associated mercury, the fort-nightly spring-neap cycle, and the seasonallystronger summer winds. The high inflow duringJanuary and March increased SSC and, assum-ing that the relationship between SSC and total

Figure 48. Correlation of SSC and total or near-total concentrations ofmercury. Outliers from samples taken from influent waters are indicated with an ‘X’

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mercury concentration was unchanged at PointSan Pablo, increased total mercury concentra-tion. RMP data collected in February and Aprilof 1995 in the Northern Estuary (SFEI, 1995)indicates that the relationship was virtuallyunchanged in the open Bay waters. As with SSC,about one-half the variance of LCTEC wascaused by the spring-neap cycle.

Discussion and ConclusionsSeven TEC are well correlated with SSC for

Bay waters. Influent waters from waste watertreatment plants sometimes had a greater TECto SSC ratio than Bay waters, and naturaltributaries sometimes had a smaller ratio thanBay waters. Linear equations relating LCTECand SSC can be applied to the nearly continuoustime series of SSC collected by the USGS toproduce similar time series of LCTEC.

Because of their relationship with SSC,LCTEC vary with time because of tides, thespring-neap cycle, seasonal winds, and water-shed runoff. Frequent sampling, on the order of

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200

300

400

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ER

CU

RY

CO

NC

EN

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AT

ION

, IN

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/L

SU

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EN

DE

D−

SO

LID

S C

ON

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TIO

N, I

N M

G/L

OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP1994 1995

Figure 49. Time series of mid-depth SSC (measured) and total mercuryconcentration (calculated) at Point San Pablo, water year 1995.

minutes, is required to observe these variations,but such a TEC sampling program would beprohibitively expensive. The combination of theexisting RMP sampling data and USGS SSCdata produces computed LCTEC every 15minutes at the USGS SSC monitoring sites.These computed LCTEC can be used to monitortemporal variations in LCTEC that the RMPsampling program can not observe and thusenhance the existing direct RMP TEC measure-ments by helping to place them in a propercontext.

Acknowledgments

Operation of the SSC monitoring sitesduring water year 1995 was supported by theUS Army Corps of Engineers; the CaliforniaRegional Water Quality Control Board, SanFrancisco Bay Region; the USGS Federal/StateCooperative Program; and the USGS SanFrancisco Bay Ecosystem Initiative. I would liketo thank Alan Jassby for his helpful comments.

56


Toxic Phytoplankton in San Francisco BayKristine M. Rodgers and David L. Garrison,

University of California, Institute of Marine Sciences, Santa Cruz, CAand James E. Cloern, United States Geological Survey, Menlo Park, CA

Introduction

The Regional Monitoring Program (RMP)was conceived and designed to document thechanging distribution and effects of tracesubstances in San Francisco Bay, with focus ontoxic contaminants that have become enrichedby human inputs. However, coastal ecosystemslike San Francisco Bay also have potentialsources of naturally-produced toxic substancesthat can disrupt food webs and, under extremecircumstances, become threats to public health.The most prevalent source of natural toxins isfrom blooms of algal species that can synthesizemetabolites that are toxic to invertebrates orvertebrates. Although San Francisco Bay isnutrient-rich, it has so far apparently beenimmune from the epidemic of harmful algalblooms in the world’s nutrient-enriched coastalwaters. This absence of acute harmful bloomsdoes not imply that San Francisco Bay hasunique features that preclude toxic blooms. Nosampling program has been implemented todocument the occurrence of toxin-producingalgae in San Francisco Bay, so it is difficult tojudge the likelihood of such events in thefuture. This issue is directly relevant to thegoals of RMP because harmful species ofphytoplankton have the potential to disruptecosystem processes that support animalpopulations, cause severe illness or death inhumans, and confound the outcomes of toxicitybioassays such as those included in the RMP.Our purpose here is to utilize existing data onthe phytoplankton community of San FranciscoBay to provide a provisional statement aboutthe occurrence, distribution, and potentialthreats of harmful algae in this Estuary.

A Brief Review of the RegionalProblem

The incidence of toxic or noxious algalblooms is increasing worldwide, especially inestuaries and shallow inshore waters that areimpacted by human activities that lead tonutrient enrichment or the introduction ofexotic species (Smayda, 1990; Hallegraeff, 1993;Anderson, 1995). Harmful algal blooms arecaused by those species of planktonicmicroalgae that produce toxic or noxioussubstances; develop high density blooms thatdegrade water quality; or, because they areunsuitable prey species, disrupt food webs.Toxin-producing species are the most widelyrecognized, but these represent only about 40 ofover 5000 phytoplankton species (Hallegraeff,1995). For some species, their “harmfulness” issituational. For example, some diatoms(Chaetoceros spp.) have long spines that candamage the gills of fishes (Horner et al., inpress). Some phytoplankton (e.g., Heterosigmaakashiwo; Maestrini and Bonin, 1981) producebioactive compounds that affect other phy-toplankton species, while others producesubstances that directly affect the health offish, birds, mammals, or even humans.

In coastal waters of western NorthAmerica, dinoflagellates of the genusAlexandrium produce saxitoxins, the causativeagent of Paralytic Shellfish Poisoning (PSP).The seasonal toxicity of shellfish was wellknown by coastal tribes of native Americans,and PSP was reported by early Europeanexplorers (Price et al., 1991). Blooms ofAlexandrium are common events; Price et al.(1991) reported that PSP-toxic blooms weredetected in 22 of the 28 years between 1962 and1989. PSP toxins accumulate in the tissues offilter-feeders, and toxin levels in mussels(Mytilus californianus) are monitored along the

Water Monitoring

57

coast by the California Department of HealthServices (Langlois, 1992).

Domoic acid-producing diatoms that resultin Amnesic Shellfish Poisoning (ASP) are arecently recognized problem in Californiawaters (Todd, 1993). In September of 1991,more than 100 brown pelicans and Brandt’scormorants were found dead or suffering fromunusual neurological symptoms caused bydomoic acid in Monterey Bay (Fritz et al., 1992;Work et al., 1993). This event was followed byoccurrences of domoic acid poisoning along thecoasts of Oregon and Washington, in whichhumans were afflicted after consuming domoicacid-contaminated clams (Todd, 1993). The1991 domoic acid-poisoning event in centralCalifornia was attributed to a bloom of Pseudo-nitzschia australis (Buck et al., 1992; Fritz etal., 1992; Garrison et al., 1992). Domoic acidproduction has now been reported for fivespecies of Pseudo-nitzschia: P. australis, P.pungens f. multiseries, P. pseudodelicatissima,and P. seriata. These species all occur along thewest coast of North America.

Red tides (blooms discoloring the water) arealso common on the central and southernCalifornia coast. Several dinoflagellate species,including Lingulodinium polyedrum (=Gon-yaulax polyedra), Prorocentrum micans,Gymnodinium splendens, G. flavum, Ceratiumfurca, C. fusus, and Protoperidinium spp., havebeen reported to form dense blooms at varioustimes and locations (Horner et al., in press).Visible blooms of the pigmented ciliateMesodinium rubrum occur in San FranciscoBay, especially during years of heavy rainfall(Cloern et al., 1994). All of the red tides re-ported in California waters have been formedby non-toxic species. However, zooplanktonavoid dense populations of some red tide algae(Fiedler, 1982) and some species may be harm-ful to filter-feeders, including pelagic larvae(Cardwell et al., 1979). Species of Dinophysis(associated with Diarrhetic Shellfish Poison-ing), noxious bloom-forming species such asPhaeocystis pouchetii, and diatom species thatdamage fish gills (e.g., Chaetoceros convolutus,C. concavicornis, and C. danicus), are also

common in California waters but have not beenassociated with any adverse conditions here.

There is little information about the occur-rence of these toxic or harmful species ofphytoplankton in San Francisco Bay. Sincethere is free exchange of waters through theGolden Gate, it is likely that harmful marinespecies are regularly introduced into the Bayfrom adjacent coastal waters. Moreover, withinflows from the Sacramento-San JoaquinRivers, freshwater cyanobacteria (Codd et al.,1995) could also develop blooms and produceharmful or toxic conditions in the northernregions of the Bay-Delta. As a first step toaddress these hypotheses, we analyzed anhistorical phytoplankton database. Our objec-tives were to (1) review recent information todetermine the occurrence and distribution ofphytoplankton species known to produce toxinsor degrade water quality, and (2) to give aprovisional judgment about the potential effectsof harmful blooms in the context of the broaderRMP objectives of understanding the origin andeffects of toxic substances in the San FranciscoBay-Delta.

The Phytoplankton Database

From 1992 through 1995, phytoplanktonsamples were collected monthly at a series ofstations in San Francisco Bay (Figure 37) bythe United States Geological Survey (USGS).Sampling in 1993 was supported as a pilotprogram of the San Francisco Estuary RegionalMonitoring Program for Trace Substances(SFEI, 1994; Caffrey et al., 1994). Additionalsamples, up to several samplings per month,were collected in South San Francisco Bayduring the spring blooms. Water samples forplankton analysis were collected in the surfacelayer by pump or Niskin bottle, and subsampleswere preserved with Lugol’s iodine solution(1%) or glutaraldehyde. Aliquots examined forspecies counts ranged from 2–5 mL dependingon sample turbidity. Cells were concentrated insedimentation chambers and then counted andidentified using a phase-contrast invertedmicroscope. Phytoplankton cells greater than30 µm in diameter were enumerated at 125X

58


magnification. Smaller cells were counted at1250X. At least 100 cells of the most numeroustaxa were counted using the strip count methodat 1250X (American Public Health Association,1989). Identifications of diatoms and dinoflagel-lates were made after the cell contents werecleared in 30% hydrogen peroxide.

The USGS database listed 231 algal spe-cies. To simplify the spatial analysis, wegrouped stations by region: South Bay (SB)included USGS stations 21–36; Central Bay(CB) included stations 15–18; and North Bay(NB) stations 2–14 and the Sacramento Riverstation 657 (Figure 37). The sampling dates foreach region are summarized in Table 1, alongwith notations of harmful bloom events innearby coastal waters.

Results and Analysis

Over twenty algal taxa regarded to beharmful, noxious, or toxin-producing werereported in the USGS database (Table 6). Theoccurrences of these taxa ranged from commonto relatively rare, and some reached moderatelyhigh densities. Some species showed markedvariations in abundance and frequency ofoccurrence among the different regions withinSan Francisco Bay.

Toxic species

Alexandrium species that produce saxitox-ins causing Paralytic Shellfish Poisoning (PSP)were the most prevalent toxic forms in SanFrancisco Bay. Alexandrium cells were abun-dant during spring in the South and CentralBays, reaching densities of 105 cells/L (Table 6,Figure 50). This group of dinoflagellates waspersistent in South San Francisco Bay duringthe prolonged spring bloom of 1995 (Cloern etal., 1996). PSP toxin levels in Mytiluscalifornianus are monitored by the CaliforniaDepartment of Health Services (CDHS), but nosamples have been taken from San FranciscoBay in recent years. PSP toxins were detectedin mussels sampled north of San Francisco Bayin Marin County and south of San FranciscoBay in San Mateo County (Figure 51) duringMay–June, roughly corresponding to the

periods when Alexandrium was reported in SanFrancisco Bay. The seasonal coherence of thesedata may indicate a connection between oceanicand estuarine blooms, but the correlation oftoxin levels from the outer-coast withAlexandrium abundances in South San Fran-cisco Bay is weak. For example, the persistentlyhigh abundances of Alexandrium during thespring of 1995 (Figure 50) were not matched byhigh PSP levels in coastal mussels (Figure 51).

Alexandrium blooms are generally believedto originate from resuspended benthic restingstages (Price et al., 1991), but there is noinformation about the occurrence of benthicseed stocks within the Bay. The pattern of toxinaccumulation in filter-feeding animals of otherCalifornia estuaries and embayments suggeststhat Alexandrium blooms develop in oceanwaters and are advected into embayments bytidal currents (e.g., Drakes Bay: Price et al.,1991; Langlois, 1992). Alexandrium abun-dances in California ocean waters are deducedfrom toxin accumulation in shellfish (Price etal., 1991), but there is little direct informationabout actual population densities. Cell countsfrom samples collected off the Santa Cruzwharf suggest that Alexandrium catenelladensities rarely exceed 200 cells/L in MontereyBay (Chris Scholin, pers. comm.; Monterey BayAquarium Research Institute). The high densi-ties of Alexandrium found in South San Fran-cisco Bay (one or two orders of magnitudegreater), and the weak correlation betweentoxin levels in coastal mussels andAlexandrium abundances in the South Bay,suggest that the high Alexandrium abundancesare the result of population growth within theEstuary.

We were surprised to find low frequenciesof domoic acid-producing diatoms (Pseudo-nitzschia) in the records from San FranciscoBay (Figure 52, Table 6). There was a wide-spread bloom of Pseudo-nitzschia australisalong the open coast during the autumn of 1991(Buck et al., 1992; Garrison et al., 1992; Walz etal., 1994). Populations in Marin County andMonterey Bay were abundant at several peri-ods during 1992-1995 (Table 7). Within San

Water Monitoring

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AREA=CB

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

1992–1995

Log

10 (

cells

/L)

6

5

4

0

1

2

3

Figure 50. Abundance (x10n cells/L) of Alexandrium spp. cellsat South Bay (a), Central Bay (b), and North Bay (c) locationsduring the study period (1992–1995). Points (•) indicate samplingdates in each region.


1992–1995

AREA=SB

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Francisco Bay, CDHS reported blooms of aPseudo-nitzschia species, tentatively identifiedas P. pseudodelicatissima, with densities of4.6x106 cells/L in the Berkeley Marina duringJuly–August 1993 (Table 7). None of theseevents were reflected in the San Francisco Bayrecords, however, because USGS did not collectsamples at the times and locations of thesePseudo-nitzschia blooms.

Oscillatoria, a freshwater cyanobacteriumthat produces neurotoxin, was present at NorthBay stations where freshwater is brought intothe Estuary (Figure 53). Another toxic freshwa-ter cyanobacterium, Anabaena spp., wasoccasionally found in the San Francisco records(Table 6).

Red-tides

Red tide-forming dinoflagellates weregenerally poorly represented in the datarecords from San Francisco Bay, althoughvisible red tides formed by the protozoanMesodinium rubrum were documented duringthis period (Cloern et al., 1994). A Ceratiumspp. was found at high densities but with only afew observations. In the South Bay,

Prorocentrum spp. was common at high densi-ties from 1992–1995 as part of the springphytoplankton assemblage, and this genus wasalso persistent during the prolonged springbloom of 1995 (Figure 54). The low frequencyand abundance of red tide-forming dinoflagel-lates probably reflects a bias in the samplingprogram rather than an absence of these formsfrom San Francisco Bay. Red tides in centralCalifornia are most common during the sum-mer and autumn months and are associatedwith stratification following a relaxation ofcoastal upwelling (Bolin and Abbott, 1963;Horner et al., in press). However, the USGSsampling was most intensive during the springbloom periods, and in some years late summersamples were absent or very sparse (Table 7,Figures 50, 52–54).

Other Harmful or Noxious Species

Most of the potentially harmful or noxiousspecies of phytoplankton within San FranciscoBay (e.g., species of Aphanizomenon,Coscinodiscus, Cerataulina pelagica,Dinophysis, Distephanus, Noctiluca, andSchizothrix in the North Bay) had few occur-

Figure 51. Paralytic Shellfish Poisoning (PSP) toxin levels, measured as µg/100gof shellfish tissue, from the California Department of Health Services (CDHS)Toxic Phytoplankton Monitoring Program on the outer coast of California.Observed levels are taken from Marin and San Mateo Counties from 1992–1995.

PSP Levels from Coastal Areas2000

1800

1600

1400

1200

1000

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evel

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1992–1995


Water Monitoring

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Table 6. Maximum abundance and number of occurrences of harmful, toxic, or noxiousmicroalgal taxa in three regions of San Francisco Bay. Total numbers of samples collected in eachregion are shown in parentheses (see Table 7).

Ce ntral Bay North Bay South BaySpe cie s Maximum

Abundance(cells/L)

Occurrences(of 18samples)

MaximumAbundance(cells/L)


MaximumAbundance(cells/L)


Alexandrium spp. 35200 13 93400 7 104000 35Anabaena spp. - - 98000 7 - -Aphanizomenon flos-aquae - - 38000 1 - -Cerautulina pelagica - - - - 3000 1Ceratium furca - - 1200 1 - -Ceratium minutum 19600 4 500 1 1200 2Chaetoceros debile 10800 4 187800 2 72500000 7Chaetoceros socialis 1800 3 179000 4 8125000 14Dinophysis spp. 1200 4 200 2 2400 3Coscinodiscus concinnus - - - - 104800 2Cylindrotheca closterium 125000 9 62500 2 766025 19Dictyocha speculum 1600 3 - 200 1Gymnodinium spp. 36400 6 1062500 5 24000 12Planktolyngbya subtilis 344000 1 137600 1 - -Mesodinium rubrum 10000 7 344300 13 4601333 42Noctiluca sp. 3400 4 400 1 5300 6Oscillatoria spp. - 6019000 10 74000 5Peridinium sp. 200 1 1800 1 23000 3Phormidium sp. - - 206400 1 - -Prorocentrum spp. 20400 10 34400 4 1376000 34Protoperidinium spp. 7000 10 600 2 500000 27Pseudo-nitzschia sp. 32400 5 1600 1 960000 8Schizothrix sp. - - 500000 2 - -

62


Ye ar Month Ce ntralBay

NorthBay

SouthBay

Othe r Toxic Eve nts in the Re gion

1992 JanuaryFebruaryMarchApril 1 2 8 *Elevated PSP levels, Drakes BayMay 2June *Elevated PSP levels, Stinson BeachJulyAugustSeptemberOctober **Pseudo-nitzschia in Monterey BayNovember **Pseudo-nitzschia in Monterey BayDecember

1993 JanuaryFebruary 1 3 2March 2 8 *Elevated PSP levels in Marin, Sonoma, Mendocino Co.April 1 3 10 *March-May Quarantine in Marin, Sonoma, Mendocino Co.May **Pseudo-nitzschia in Monterey BayJune 1 7 5 *Elevated PSP levels, Drakes BayJuly *Berkeley marina Pseudo-nitzschia bloomAugust 1 3 2SeptemberOctober 1 7 4NovemberDecember 1 3 2

1994 January *Elevated PSP levels, Drakes BayFebruary 1 3 3 *Pseudo-nitzschia abundant in Drakes EsteroMarch 3 *Elevated PSP levels, Drakes BayApril 1 3 4 *Elevated PSP levels, Drakes BayMayJune 1 4 2JulyAugust 1 4 4 *Elevated PSP levels Marin, San Mateo Co.September *Elevated PSP levels, Drakes BayOctoberNovemberDecember

1995 January 1 4 5February 1 3 14March 1 3 13April 1 3 19May 1 3 10JuneJuly 1 3 3 *Elevated PSP levels Marin (Rodeo Beach)August *"Red tide" of Gymnodinium splendensSeptember 1 3 2OctoberNovember *Pseudo-nitzschia abundant in Marin, SF Co. (Ocean)December *Pseudo-nitzschia abundant in Marin Co., Farallone Is.TOTALS 18 66 125

Table 7. Phytoplankton sampling dates in San Francisco Bay, 1992–1995. Columns 2–4 show thetotal number of samples taken, by region, for each month. Other toxic events were those reported by theCalifornia Department of Health Services* or by Walz et al. (1994)**.

Water Monitoring

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1992–1995

AREA=NB

Log

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/L)

6

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J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D1992–1995

AREA=CB

Log

10 (

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/L)

6

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Figure 52. Abundance (x10n cells/L) of Pseudo-nitzschia spp.cells at South Bay (a), Central Bay (b), and North Bay (c)locations during the study period (1992–1995). Points (•) indicatesampling dates in each region.


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64



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Figure 53. Abundance (x10n cells/L) of Oscillatoria spp. cells atNorth Bay (a) and South Bay (b) locations during the studyperiod (1992–1995). No observations from Central Bay. Points (•)indicate sampling dates in each region.

7

7

rences and were recorded at relatively lowdensities (Table 6). Other taxa, such asChaetoceros, Planktolyngbya subtilis, andPhormidium, however, were found frequentlyin San Francisco Bay. Two species ofChaetoceros, C. debile and C. socialis, producemucilaginous colonies harmful to larval fish,and these occurred in high densities duringMarch and April. Cylindrotheca closterium, adiatom species associated with blooms produc-ing water discoloration and mucilaginousaggregates (Hasle and Fryxell, 1995), was alsofound in the South Bay at high densities.

The Potential for Harmful Algal Blooms inSan Francisco Bay

So far there have been no reports of serioustoxic or harmful phytoplankton blooms in San

Francisco Bay. However, our examination ofrecent data shows that a number of speciesresponsible for such blooms in other locationsdo exist in San Francisco Bay waters, and attimes these species reach high abundances.Thus the potential exists for toxic or noxiousbloom problems. Moreover, the present studyshould be regarded as conservative because ofbiased temporal sampling (i.e. the low fre-quency of sampling in late summer and au-tumn) and the focus on identifying and enu-merating the dominant species (e.g., manyharmful species may be present at low densi-ties as part of the “hidden flora”).

The primary toxin-producing algae in SanFrancisco Bay appear to be dinoflagellates ofthe genus Alexandrium. Abundances of these


Water Monitoring

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1992–1995

Log

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/L)

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Figure 54. Abundance (x10n cells/L) of Prorocentrum spp. cellsat South Bay (a), Central Bay (b), and North Bay (c) locationsduring the study period (1992–1995). Points (•) indicatesampling dates in each region.

AREA=CB

66


species were seasonally correlated with toxicperiods in nearby coastal marine waters, butthe separate sampling designs of the USGS andCDHS programs do not allow us to address thehypothesis that coastal blooms propagate intothe Bay. The high densities of Alexandrium inSouth San Francisco Bay may indicate popula-tion growth or retention within the Estuary,since densities in ocean waters are typicallylower than those observed during the peakabundances in the South Bay. Whereas theCDHS monitoring program is appropriate forassessing PSP toxins on the open coast, anindependent Alexandrium bloom in the SanFrancisco estuarine system could go undetec-ted. Moreover, if cell densities in the Bay reachlevels higher than on the open coast (as dis-cussed above), there is the potential for hightoxin accumulation in estuarine benthic con-sumers. For example, a bloom of Alexandriumcatenella in the Beagle Channel (Argentina) atdensities of 8.2 x 105 cells/L (similar to peakabundances recorded in San Francisco Bay)resulted in high toxin levels in mussels Mytiluschilensis (Benavides et al., 1995).

Because toxic species of Pseudo-nitzschiaare common in adjacent coastal ocean waters(Walz et al., 1994), and these diatoms developblooms in Oregon and Washington estuaries(Sayce and Horner, 1996), there is a potentialfor domoic acid-producing blooms in SanFrancisco Bay. The absence of such events inthe USGS database is likely a result of tempo-ral bias in the sampling program. Pseudo-nitzschia blooms are most common in latesummer and autumn (Buck et al., 1992; Walz etal., 1994), and therefore could have beenmissed in the USGS surveys. Blooms within theBay, such as the Pseudo-nitzschia bloom in theBerkeley Marina (July 1993), may be limited

spatially as well as temporally and thus escapedetection during monthly surveys with limitedspatial coverage. The nutrient concentrationsin South San Francisco Bay may be an impor-tant regulator of domoic acid-producing blooms,should they develop. Domoic acid concentra-tions within Pseudo-nitzschia cells depend onsilicate-limited conditions with an excess ofnitrogen (Bates et al., 1991; Pan et al., 1996).Coastal waters receiving anthropogenic inputsof nitrogen can have low silicate:nitrogen ratiosthat are optimal for domoic acid-producingblooms (Garrison et al., 1992).

In summary, our analysis of recent datashows that toxin-producing species of phy-toplankton occur in Bay-Delta waters, some-times at abundances that could have harmfuleffects on invertebrate and vertebrate animals.Persistent and abundant occurrences of someforms, such as the dinoflagellates Alexandriumand Prorocentrum during spring of 1995,suggest that populations of harmful algaedevelop within the Bay. However, these infer-ences are made from a data set that has incom-plete spatial and temporal coverage. Therefore,the existing information is inadequate fordeveloping a definitive statement about theecological significance of these harmful algae inSan Francisco Bay. The existing informationdoes suggest that RMP managers shouldconsider a new element of Bay monitoring tocharacterize the phytoplankton community,especially at those times/locations when waterand sediment samples are taken for bioassays.The existing information also shows thatharmful species are present in San FranciscoBay, so RMP participants should recognize thepotential for acute events of algal-causedanimal mortality in this nutrient-rich coastalsystem.

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Comparison of two water (BA10 & BD15) and Sediment (BA21) PCBCongener Profiles

Per

cent

com

posi

tion

Petaluma River Water Cruise 8

Coyote Creek Water Cruise 8

South Bay Sediment Cruise 4

PC

B 8

PC

B 1

8

PC

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1

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9

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01

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10

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18

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B 1

38

PC

B 1

49

PC

B 1

53

PC

B 1

74

PC

B 1

77

PC

B 1

80

PC

B 1

87

0

2

4

6

8

10

12

14

16

18

20

Observations on Trace Organic Concentrations inRMP Water Samples

Walter M. Jarman, University of California Santa CruzJay A. Davis, San Francisco Estuary Institute

This section supplements the discussion oftrends in trace organic contaminants presentedin the Water Monitoring Discussion section ofthis report, and includes a more detaileddiscussion of some of the points mentioned andoffers some additional observations.

Polychlorinated Biphenyls(PCBs)

In addition to simply analyzing concentra-tions of the sum of individual congeners(ΣPCBs), information on spatial variation andsources of organic contaminants can also beobtained by examining the “profiles”, or relativeproportions of individual compounds, withinthe major classes of organics. Spatial variation

in PCB congener profiles is discussed here as itappears to relate to PCB sources.

PCBs were sold and used as mixturesknown as Aroclors. There were several differentclasses of Aroclors, and these classes haddifferent congener profiles. If the sources ofAroclors contributing to PCB contamination inthe Estuary were variable, as could reasonablybe hypothesized, then it should be possible tofind different profiles in different parts of theEstuary.

Two of the highest levels of ΣPCBs in waterduring the 1995 RMP were found at thePetaluma River (BD15) in the Northern Estu-ary and Coyote Creek (BA10) in the South Bay.Despite the difference in location, the PCB

Figure 55. Comparison of PCB congeners in water from Coyote Creek (BA10)and Petaluma River (BD15; April samples) and in sediment from South Bay(BA21; February 1994 sample). Concentrations expressed a percentage of ΣPCB.

68


profiles are very similar (Figure 55). PCBcongener data for sediment from the South Baysite (BA21, Cruise 4, 1994) also share this sameprofile (Figure 55). In the sediment samplesPCBs 8, 18, 28, 44, 66, 95, and 174 were notdetected throughout the Estuary. One explana-tion for this general similarity is that the PCBsources in the northern and southern Bay havesimilar congener compositions. Another possi-bility is that the sediments are the source ofPCBs found in the water column, and despitepast differences in the composition of inputs(i.e., different Aroclors), the mixing of sedimentover time and the degradation of the Aroclormixtures has resulted in similar profiles in thetwo locations. This latter hypothesis wouldmake the historical deposition and accumula-tion of PCBs into the sediments the majorsource of PCBs in the water column, as alsosuggested by Risebrough (this report). A moredetailed analysis of PCB “fingerprints” in theEstuary will be conducted in 1997, and willreveal whether the similarities among thestations discussed here are coincidental or not.

It is also possible to obtain information onPCB dynamics in the Estuary by examiningtemporal trends in congener profiles. Someseasonal variation in congener profiles can beseen. The congener-specific analysis (for allcongeners greater than 3% of the ΣPCB) for thefour regions in 1995 is presented by cruise inFigure 56. The highest concentrations of ΣPCBswere measured the spring. In the South Bay,Central Bay, and Northern Estuary this cruisealso had the highest average TSS. The SouthBay wet-season sampling yielded a low concen-tration of total suspended sediments (TSS) andthis is reflected by the high percentage oflighter chlorinated congeners which tend todissolve in the water column to a greater extentthan the more heavily chlorinated congeners.Although concentrations of congeners aresimilar in the Central Bay for all three cruises,the patterns are not. This is probably due to thelow concentrations, which are near the detec-tion limit and thus have greater variability.

One historical data set that can be used forcomparisons of PCBs and other organic con-

taminants in Estuary waters is that of deLappe et al. (1983b). In a study for the City andCounty of San Francisco, prior to the construc-tion of the Southwest Ocean Outfall, de Lappeet al. examined the baseline concentrations oforganic contaminants both outside and insidethe Estuary. Of particular relevance are the“vicinity of Angel Island” and Golden GateChannel stations sampled for PCBs (Aroclor-based measurements) in August 1980. Usingsampling equipment roughly comparable tothat currently used in the RMP (glass fiberparticulate filter and polyurethane foam) deLappe et al. (1983) reported a ΣPCB concentra-tion of 647 pg/L at the Golden Gate. A liquid/liquid extraction of whole water at the GoldenGate yielded a value of 850 pg/L. At AngelIsland a ΣPCB concentration of 664 pg/L wasreported.

In tissue samples from wildlife, Aroclor-based ΣPCB results are two or more timeshigher than the ΣPCB based on the sum ofindividual congeners in the same sample (Turleet al., 1991). It is not known if this is true inwater samples, but it is probably similar in thatAroclor-based values would be higher thancongener-based ΣPCB values from the samesamples. The average concentration of conge-ner-based ΣPCBs in the Central Bay for RMPcruises has been approximately 400 pg/L.Congener-based ΣPCB concentrations in otherregions of the Estuary are frequently muchhigher. The concentrations detected in theseolder studies and those detected currently inthe RMP are roughly equivalent. Despitevariations in both sampling and analyticalmethodology these data indicate that PCBconcentrations have not declined appreciablysince the early 1980s.

Pesticides

Average total (particulate plus dissolved)concentrations of the most commonly detectedpesticides for each reach are presented inFigure 57.

The concentrations of diazinon, dacthal,and oxadiazon reported in the RMP must beinterpreted with caution. No studies of the

Water Monitoring

69

Figure 56. Congener-specific PCBconcentrations (totals) for 1995, by reach.

Cruise 7

Cruise 8

Cruise 9

Cruise 7

Cruise 8

Cruise 9

Northern Estuary

Rivers

Central Bay

South Bay

Cruise 7

Cruise 8

Cruise 9

50

100

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300

0

0

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70

Cruise 7

Cruise 8

Cruise 9

PC

B 8

PC

B 1

8

PC

B 2

8

PC

B 3

1P

CB

44

PC

B 4

9P

CB

52

PC

B 6

6P

CB

70

PC

B 8

7P

CB

95

PC

B 1

01P

CB

110

PC

B 1

18P

CB

138

PC

B 1

49P

CB

153

PC

B 1

74

PC

B 1

77P

CB

180

PC

B 1

87

Tota

l Con

cent

ratio

n (p

g/L)

70


Figure 57. Total concentrations of pesticides inwater for each reach of the Estuary, 1995.

Cruise 7

Cruise 8

Cruise 9

Rivers

Northern Estuary

Central Bay

Cruise 7

Cruise 8

Cruise 9

Cruise 7

Cruise 8

Cruise 9

South Bay

0

1000

2000

3000

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70008000

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Tota

l Con

cent

ratio

n (p

g/L)

Cruise 7

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Cruise 9

Sum

DD

Ts

Sum

Chl

orda

nes

Sum

HC

Hs

Dac

thal

Oxa

diaz

on

Dia

zino

n

Water Monitoring

71

relative recoveries of these compounds havebeen undertaken with the glass fiber filter/polyurethane foam water sampler used in theRMP since 1993. The values reported must beconsidered preliminary until sampling effi-ciency has been documented. However,Domagalski and Kuivila (1993) reported levelsof diazinon in San Francisco Bay collected in1991 in the Northern Estuary (CarquinezStrait, Suisun Bay, and Chipps Island) andfound very similar levels (4,600–13,000 pg/L) inthe dissolved phase to those reported in theRMP. In addition, diazinon is the only pesticidein the RMP water samples that is quantified bygas chromatography/mass spectrometry(GCMS), the most reliable (least likely to give afalse positive) way to quantify analytes. Al-though these diazinon concentrations seemhigh, assuming the total volume of water inSan Francisco Bay to be approximately 6.66 X109 m3 (Conomos et al., 1985a), it takes only 66kg of diazinon to contaminate the Bay to anaverage concentration of 10,000 pg/L in thewater.

The pesticide with the second highestconcentrations reported in 1995 was oxadiazonin the South Bay during February (Figure 57).However, this average is skewed by two ex-tremely high stations (Coyote Creek [BA10] at3100 pg/L and Dumbarton Bridge [BA30] at14,000 pg/L). These values should be confirmedby GCMS before any conclusions can be drawn.Oxadiazon has been detected in biota in South-ern California (Crane and Younghans-Haug,

1992). Oxadiazon is a pre-emergent herbicide.Pesticide use data collected by the CaliforniaEnvironmental Protection Agency (Cal EPA) in1993 indicate that 19,000 pounds of oxadiazonwere applied in California by licensed applica-tors, mostly for landscape maintenance (CALEPA, 1996).

Dacthal (also known as “chlorthal-dim-ethyl”) concentrations during 1995 were similarfor the four areas and show a decrease fromFebruary to August, similar to diazinon (Figure57). Dacthal is a pre-emergent herbicide, andthus it would be expected that the highestconcentrations found in the Estuary wouldoccur in the winter. Cal EPA pesticide-use datashow that 660,000 pounds of dacthal wereapplied by licensed applicators in California in1993, mostly on food crops such as broccoli andonions (CAL EPA, 1996).

As mentioned above, de Lappe et al. (1983b)measured selected organic contaminants inwater, including pesticides, in the Central Bay(Golden Gate and Angel Island) in the summerof 1980. A comparison of these results to thoseof the two summer RMP cruises are presentedin Table 8. As opposed to the PAHs and PCBs,in both the chlordanes and DDTs (two bannedclasses of organochlorine pesticides), thereseems to have been a downward trend. Thehexachlorocyclohexanes (HCHs), another classof organochlorine insecticide, however, do notseem to be decreasing. This might be attributedto high deposition of atmospheric HCHs, asreported in other areas (Wittlinger and

deLa pp e et al. (1983) RMP 1994 and 1995Golden Gate 1980 Angel Island

1 9 8 0Cent. Bay

dr y -seasonCent. Bay

dr y -seasonPart. +

DissolvedWhole water Part. +

DissolvedPart. +

DissolvedPart. +

Dissolved

Sum DDT 260 320 206 190 100Sum HCH 730 1160 1700 825 660Sum Chlordane* 250 310 200 36 40

* trans and cis chlordane, and trans nonachlor

Table 8. Concentrations of pesticides in the Central Bay, 1980–1995. Data in pg/L.

72


Concentrations of Alkanes for the Each RegionCruise 9

Con

cent

ratio

n (p

g/L)

South Bay

Central Bay

Northern Estuary

Rivers

C11

C12

C13

C14

C15

C16

C17

Pris

tane

C18

Phy

tane

C19

C20

C21

C22

C23

C24

C25

C26

C27

C28

C29

C30

C31

C32

0

10000

20000

30000

40000

50000

60000

Ballschmiter, 1990; Hinckley and Bidleman,1991).

One interesting form of seasonal variationwas observed for p,p’-DDE, one of the predomi-nant forms of DDT. Regressions of p,p’-DDEversus TSS were performed for each cruise, andthe regression line for the spring cruise (April)had a markedly higher slope than the lines forthe other cruises (discussed further in “GeneralSpatial Patterns of Trace Organics” below). Theslopes of the lines in February and April weresignificantly different (their 95% confidenceintervals did not overlap), while the slope of theline for the dry-season (August) had a widerconfidence interval and was not significantlydifferent from the slope for the spring cruise(April). These results suggest that the sus-pended solids circulating in the Estuary wererelatively more contaminated with p,p’-DDE inApril. Since freshwater runoff into the Estuarywas extremely high during April, a plausibleexplanation for this pattern is that relativelycontaminated sediments were being washedinto the Estuary from upstream portions of thewatershed.

Hydrocarbons

In general, higher molecular weight hydro-carbons can be derived from either biogenic(produced from living organisms) or petroleumsources. The hydrocarbons measured in theRMP can be broken into two major classes: thealiphatic hydrocarbons (AHC), which arestraight-chain or branched hydrocarbons, andthe polycyclic aromatic hydrocarbons (PAHs),which are fused aromatic rings. The AHCs areproduced by higher plants, bacteria, andplankton; in addition they are also majorconstituents of petroleum products. The PAHsare major components of petroleum, products ofcombustion, and products of the degradation oforganic matter; they are primarily of anthropo-genic origin in the Estuary.

In the RMP approximately 24 individualAHCs and 14 PAHs are measured in water. Thepatterns of both the AHCs and PAHs and theirrelative concentrations can yield informationregarding the source (i.e., biogenic or petro-leum-derived) of the hydrocarbons in the waterof the Estuary. For example, the AHCs derivedfrom biogenic sources have a large odd-to-even

Figure 58. Total concentrations of aliphatic hydrocarbons (AHCs) in RMPwater samples, August 1995. Concentrations are averages for each reach.

Water Monitoring

73

alkane ratio; this is sometimes called a carbonpreference index. This is because the biogenicsources produce a greater proportion of the odd-number alkanes (e.g., n-C15, n-C17, n-C19 ifderived from algae, n-C25-n-C35 if derived fromhigher plant waxes). Another example is theuse of the pristane to phytane ratio to deter-mine recent biogenic hydrocarbons; pristaneand phytane are branched AHCs produced byplankton. In unpolluted biogenic sources thepristane concentration is much greater than thephytane concentration. The pattern of thePAHs are also characteristic of their source (seeRMP News Summer 1996).

The profiles of the total (dissolved plusparticulate) water AHCs for the August cruiseare presented in Figure 58. The river profilesfor the AHCs in August show a distinct patternof biogenic input; the profile is dominated by n-C15, n-C17, and pristane, probably as a result ofspring and summer plankton blooms. Theprofile from the Northern Estuary shows apredominance of n-C15, also probably as a resultof plankton. Of interest is the characteristicpattern of plant wax alkanes (n-C25, n-C27, n-C29, and n-C31) in all areas of the Estuary,except the Central Bay. The southern andCentral Bay show no odd/even preferences(except for the plant waxes) which is probablythe result of no fresh biogenic source of AHCs.

The patterns of PAHs for 1995 are pre-sented in Figure 59. As with the PCBs, thePAHs are highly correlated with TSS, and thusin general, the levels in the samples are corre-lated with TSS concentration. The dominantPAHs in the water are phenanthrene (PHN),sum methylphenanthrene (sum MPH),fluoranthene (FLA), pyrene (PYR),benzo[B]fluoranthene (BBF), and indeno[1,2,3-cd]pyrene (IND). However, the relative propor-tions of these PAHs varies greatly within theEstuary and by season. These PAHs are ingeneral representative of petroleum combus-tion, but there are some notable differences andsimilarities. As with the PCBs, the patterns inthe Northern Estuary and South Bay aresimilar for April. In the River stations thepattern varies greatly with season. DuringApril the dominant PAH in the River stationsand South Bay was IND, which has beenreported to be the dominate PAH in sedimenttraps deployed near metal refineries in Sweden(Näf et al., 1992). The very different patterns ofPAHs in the Estuary reflect the many possiblesources of PAHs (e.g., petroleum, automobile,refineries, and runoff: Readman et al., 1986).

A comparison of the patterns of PAHs foundin the sediments and water (total concentra-tions) for the South Bay and Northern Estuaryis presented in Figure 60. Despite the fact that

deLa pp e et al. (1983) RMP 1994 and 1995Golden Gate 1980 Angel

Island 1980Cent. Bay

dr y -seasonCent. Bay

dr y -seasonPart. +

DissolvedWhole water Part. +

DissolvedPart. +

DissolvedPart. +

Dissolved

n-C15 310 800 330 14000 5900n-C17 33000 2400 4860 11000 5900n-C18 1300 1100 1700 3200 1400nC-29 6000 10000 14000 9700 1300pristane 780 1400 2900 2900 1900phytane 840 900 2000 1700 900S-resolved alkanes 92000 100000 150000 120000 239000phenanthrene 5000 3800 3100 1300 8700anthracene 240 700 500 600 0pyrene 3900 700 5600 2300 2500

Table 9. Concentrations of hydrocarbons in the Central Bay, 1980–1995. Data in pg/L.

74


Figure 59. Total concentrations of PAHs in RMP watersamples, 1995. Concentrations are averages for each reach.

Cruise 7

Cruise 8

Cruise 9

05000

10000

2000015000

2500030000

35000400004500050000

0

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South Bay

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Tota

l Con

cent

ratio

n (p

g/L)

PH

N

AN

T

1-M

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sum

MP

H

FLA

PY

R

BA

A

CH

R

BB

F

BK

F

BE

P

BA

P

IND

DB

A

Water Monitoring

75

Figure 60. Comparison of PAH profiles in water and sediment from a) the NorthernEstuary, and b) the South Bay. Concentrations expressed as percent of ΣPAH. NorthernEstuary sediment collected in San Pablo Bay (BA21), February 1994, and water from thePetaluma River station (BD15), February 1995. South Bay sediment collected from stationBA21, February 1994, and water from Coyote Creek (BA10), February 1995.

PH

N

AN

T

1-M

PH

sum

MP

H

FLA

PY

R

BA

A

CH

R

BB

F

BK

F

BE

P

BA

P

IND

DB

A

0

5

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250

5

10

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South BayPer

cent

Com

posi

tion

Northern Estuary

Water

Sediment

Water

Sediment

76


these sediment and water samples were col-lected one year apart, and they represent onlyone sample each, there are some obviouspatterns. Although not as similar as the PCBsediment and water profiles (Figure 60), thepatterns in the sediment and water are similarfrom both areas of the Bay, suggesting thatsediments may be a source of the PAHs to thewater column. However, atmospheric transportand deposition has been reported to be asignificant source of PAHs (and PCBs) to lakes(Sanders et al., 1996), and must be included asa potential source along with the rivers andurban runoff. Atmospheric deposition of tracecontaminants in the Bay region will be investi-gated in an RMP pilot study in 1997 that willinclude deposition measurements in the field.Unlike the PCBs, the patterns from the Northand South Bay for both sediment and waterdiffer by region. This is probably due to differ-ent sources of PAHs, different stability of thePAHs (e.g., selective degradation in the sedi-ments), or the differential partitioning of theindividual PAHs into the water column becauseof their different water solubilities.

de Lappe et al. (1983b) reported totalsaturated hydrocarbon (resolved and unre-solved) and selected AHCs (n-C15, n-C17, n-C18,n-C29, pristane, and phytane) and PAHs (PHN,ANT, and PYR) in particulate, dissolved, andwhole water samples from sites at the GoldenGate and in the “vicinity of Angel Island”. Table9 compares the hydrocarbon values reported byde Lappe et al. (1983) collected in the summerof 1980 and the data from the RMP summercruises for the Central Bay in 1994 and 1995.Despite different sampling methodologies,different analytical methodologies, and differ-ent instrumentation, in general, the levels arevery similar over a 15-year period (Table 10).Although n-C15 and n-C17 vary over an order ofmagnitude, this can be explained by the factthey are produced by algae and their concentra-tions are dependent on algal production; mostof the rest of the hydrocarbons measured showvalues which are within a factor of two. Theconcentrations (and ratios) of PHN, ANT, andPYR are very consistent. The similarity of the

patterns and levels of hydrocarbons (in thislimited data set) in the Central Bay over thepast 15 years indicates that the magnitude andcomposition of hydrocarbon sources to theEstuary have not changed dramatically in therecent past.

General Spatial Patterns of TraceOrganics

Spatial variation in total concentrations ofthe hydrophobic trace organics is more appar-ent when the influence of TSS is removed usinglinear regression. Regressions of TSS versusthese contaminants were highly significant (pvalues for these regressions were all less than0.00004), accounting for 33% of the variance forPCB 153 (used as an indicator for PCBs as agroup), 37% for ΣPAH, 52% for Σchlordanes,and 83-95% for p,p’-DDE (for p,p’-DDE regres-sions were performed for each cruise, since theregression line for one cruise had a markedlydifferent slope than lines for the other cruises).The adjusted concentrations of PCB 153 (Fig-ure 61a) and ΣPAH (Figure 61b) had similarspatial patterns, with consistently high valuesin the South Bay from BA10 to BA30, highvalues at the Petaluma River (BD15), interme-diate values in the Central Bay, and consis-tently low values in the Rivers and NorthernEstuary. These data suggest the existence ofrelatively high concentrations of PCBs andPAHs in the South Bay and at the PetalumaRiver station (BD15). Adjusted p,p’-DDEconcentrations (Figure 61c) were consistentlyhigh in the Rivers and Northern Estuary,consistently low at Redwood Creek (BA40), andgenerally inconsistent at other stations. Ad-justed ∑chlordanes (Figure 61d) were highestin the South Bay (especially at Coyote Creek—BA10) and lowest at the Sacramento River(BG20).

Overall, the dissolved and TSS-adjustedtrace organics data clearly indicate the pres-ence of elevated concentrations in the SouthBay for all of the organics and at the Rivers forDDTs. Through modeling or detailed statisticalanalysis it might be possible to determinewhether these elevated concentrations are a

Water Monitoring

77

result of remobilization from deposited sedi-ment, but such an analysis is beyond the scopeof this report. It is also possible that traceorganics in the waters of the Estuary originatefrom other sources, such as inputs from con-

Figure 61. RMP water trace organic concentrations (1995) normalized to TSSthrough linear regression. Concentrations are represented by the residuals of regressionsof TSS with each contaminant. a) PCB 153, b) ΣPAH, c) p,p'-DDE, d) Σchlordanes

taminated areas further upstream in thewatershed, atmospheric deposition, or otherpathways, but the existing RMP samplingarray may be inadequate for distinguishingamong these possibilities.

a) PCB 153

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

BA

10

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BC

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60

BD

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30

TS

S-n

orm

aliz

ed c

once

ntra

tions

FebruaryAprilAugust

b) ΣPAH

-1.2

-1-0.8

-0.6

-0.4-0.2

00.2

0.4

0.60.8

1

BA

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40

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60

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orm

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tions

FebruaryAprilAugust

c) p,p'-DDE

-0.4

-0.3

-0.2

-0.1

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0.3

BA

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60

BD

20

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orm

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ed c

once

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tions

FebruaryAprilAugust

d) Σchlordanes

-0.6

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-0.2

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orm

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ed c

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ntra

tions

FebruaryAprilAugust

78


Water Monitoring Discussion

One theme that is present in the WaterMonitoring section is that information on trendsin environmental variables other than contami-nants can be extremely valuable in determiningtrends in contaminant concentrations. Jassby(this report) discussed how short-term variabilityin exogenous variables (e.g., Delta outflow andTSS) can disguise broader-scale trends. As anexample he demonstrated the linear correlationbetween Delta outflow and cadmium, and showedthat by adjusting the cadmium data to Deltaoutflow, increasing trends in cadmium wererevealed at two stations.

Total suspended sediments (TSS) is anotherexogenous variable that exerts a strong influenceon the total (dissolved + particulate) waterconcentrations of many trace elements and traceorganics. Schoellhamer (this report) discussed theclose relationship between TSS and total concen-trations of certain trace elements. He exploitedthis close relationship to predict short-termvariability in total trace element concentrationsbased on detailed TSS data. He also observed thatthere was a clear spatial pattern in the residualsof linear regressions of many trace elements withTSS. In other words, after removing the effect ofTSS on the total trace element concentrations,clear spatial patterns became evident. Thisapproach was based on linear regression andresidual analysis, the same approach used byJassby (this report) for cadmium and Deltaoutflow.

TSS is also closely related to total waterconcentrations of hydrophobic trace organics(Jarman and Davis, this report). As with the traceelements, removal of the effect of TSS on totalconcentrations of hydrophobic trace organicsreveals a clearer picture of other variability,including spatial and temporal variation.

Trace ElementsSpatial patterns

TSS concentrations are the primary determi-nant of concentrations of many trace elements.Variation in total (dissolved + particulate) concen-

trations of these elements are therefore prima-rily related to variation in sedimentresuspension in the Estuary. Dissolved traceelement concentrations are useful in assessingspatial patterns because they are relativelyindependent of spatial variation in TSS concen-trations, and therefore provide a better mea-sure of actual differences in degree of contami-nation. In 1995, dissolved trace elementconcentrations during all cruises were gener-ally elevated at the Southern Slough stations(San Jose, C-3-0 and Sunnyvale, C-1-3) and theSouth Bay stations (from BA10 to BB70)compared to other RMP stations. The principalsource of these high concentrations appears tobe a combination of waste water inputs,remobilization of contaminants from depositedsediments, and urban and non-urban runoff(Flegal, this report).

Silver (Ag) was the only exception to thisprevailing pattern of high concentrations in thesouthern portion of the Estuary. Dissolved Agconcentrations exhibited distinct seasonalvariability. In February, concentrations werehigh in the Southern Sloughs (especiallySunnyvale, C-1-3), but only slightly elevated inthe South Bay relative to the rest of the Estu-ary. In April, concentrations were fairly uniformthroughout the Estuary. Only in August wereconcentrations in the South Bay were substan-tially higher than most of the other measure-ments for the entire year.

Sources of trace element contamination inthe water column, indicated by the presence ofhigh concentrations relative to the rest of theEstuary, were only observed in a few instancesfor other regions of the Estuary. Dissolvedcadmium concentrations in the Central Baywere high relative to stations further upstreamand comparable to South Bay concentrations;ocean waters on the California coast are rela-tively enriched with this element. Dissolved Agconcentrations in a few Central Bay andNorthern Estuary stations (BC30, BC41, BC60,BD15, BD20) were relatively high in August,

Water Monitoring

79

suggesting the presence of a source in thisregion at that time. Concentrations of dissolvedAs, Cu, and Ni were much higher at the Peta-luma River station (BD15) than at adjacentstations. This pattern also held for Cu and Niin all 1994 cruises, but for only one cruise forAs. These data strongly indicate the presence ofa source of Cu and Ni near this station. Theonly elements found at high relative concentra-tions in the River stations were Pb (especiallythe Sacramento River station, BG20) and Hg(the San Joaquin River station, BG30, in April).

As, Cd, and Se occur mostly in the dissolvedfraction, so spatial patterns for total concentra-tions are the same as for the dissolved fraction.However, total concentrations of the otherelements (Cr, Cu, Pb, Hg, Ni, Ag, and Zn) aremuch higher than dissolved. The spatial distri-bution of total concentrations of these elementsresembles the distribution for TSS, with thehighest concentrations in the Southern Sloughsand at the Petaluma River, intermediateconcentrations at the Northern Estuary andRiver stations, and lowest concentrations in theCentral Bay. After removing the influence ofTSS through linear regression, the TSS-ad-justed data showed that Ag, Cu, Hg, Ni, Pb, andZn were highest in the South Bay and that Cuand Zn had local maxima in the North Bay(Schoellhamer, this report). These findings aregenerally consistent with the conclusions onspatial patterns based on dissolved concentra-tions.

Temporal trendsSeasonal Variation

Clear seasonal variation was observed forAs, Cd, and dissolved Ag. As and Cd concentra-tions throughout the Estuary were high inAugust. This same pattern was observed in1994. For Cd this pattern could be due to theincreased influence in the dry season of oceanwater, which is relatively high in Cd. Arsenic,in contrast, is not present in high concentra-tions in the ocean. High As concentrations inAugust may be due to the increased influence ofsources such as outfalls or atmospheric deposi-tion that become more obvious in the absence of

runoff. Ag concentrations were also elevated inAugust, especially in the South Bay. Thispattern was not evident in the 1994 sampling,but suggests the presence of a continuoussource of Ag in the South Bay during thisperiod. Total concentrations of the elementsthat tend to be particle-associated (Cr, Cu, Pb,Hg, Ni, Ag, and Zn) were often highest in April,coinciding with high concentrations of TSS.

Long-term Trends

Long-term trends in total trace elementconcentrations were examined in detail usingdata collected from April 1989 to April 1995under the RMP and pilot studies that precededthe RMP (Jassby, this report). Trends wereessentially nonexistent in the raw data. In astation-by-station analysis of trends for all ofthe trace elements only 3 of 240 tests showedsignificant trends, even fewer than would beexpected due to chance alone. Contiguousstations often showed consistent, though non-significant, trends. Jassby examined whethercontiguous stations could be grouped in order todetect statistically significant trends, but theresults for Cu, which appeared to show consis-tent trends among stations in subregions of theEstuary, were not significant. Plots that sum-marize trace element data collected in the pilotstudies and the RMP are shown in Figures 62–71.

As mentioned above, variability in exog-enous factors, such as Delta outflow, can masktrends in trace element concentrations, andstatistical removal of the influence of suchfactors can provide a better representation oftemporal trends (Jassby, this report). Indeed,the absence of significant trends in traceelement concentrations after six years ofsampling suggests that the only way to detecttrends with the present sampling regime,without waiting decades, is to establish thequantitative relationships of trace elementconcentrations with important environmentalfactors and then remove the effect of thosefactors statistically.

80


Figures 62 and 63. Plots of average arsenic and cadmium concentrations (parts perbillion, ppb) in water in each Estuary reach from 1989–1995. Note that arsenic was notsampled during 1990–1992. The vertical bars represent ranges of values. Sample sizes for arsenicare as follows: South Bay 1989 and 1993 n=4, 1994–1995 n=7; Central Bay 1989 n=1, 1993 n=4,1994–1995 n=5; Northern Estuary 1989 n=4, 1993 n=6, 1994–1995 n=8; Rivers 1989 n=1, 1993–1995n=2. Sample sizes for cadmium are as follows: South Bay 1989–1993 n=4, 1994–1995 n=7; CentralBay 1989–1990 n=1, 1991 n=3, 1992–1993 n=4, 1994–1995 n=5; Northern Estuary 1989–1990 n=4,1991–1992 n=7, 1993 n=6, 1994–1995 n=8; Rivers 1989–1990 n=1, 1991–1995 n=2.

Total Arsenic, µg/L Near-Total Cadmium, µg/L4/

89

8/89

12/8

9

3/93

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2/94

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Water Monitoring

81

Total Chromium, µg/L Near-Total Copper, µg/L

Figures 64 and 65. Plots of average chromium and copper concentrations (parts perbillion, ppb) in water in each Estuary reach from 1989–1995. Note that chromium was notsampled prior to 1993. The vertical bars represent ranges of values. Sample sizes for chromium areas follows: South Bay 1993 n=4, 1994–1995 n=7; Central Bay 1993 n=4, 1994–1995 n=5; NorthernEstuary 1993 n=6, 1994–1995 n=8; Rivers 1993–1995 n=2. Sample sizes for copper are as follows:South Bay 1989–1993 n=4, 1994–1995 n=7; Central Bay 1989–1990 n=1, 1991 n=3, 1992–1993 n=4,1994–1995 n=5; Northern Estuary 1989–1990 n=4, 1991–1992 n=7, 1993 n=6, 1994–1995 n=8;Rivers 1989–1990 n=1, 1991–1995 n=2.* indicates different scale.

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82


Near-Total Lead, µg/L Total Mercury, µg/L

Figures 66 and 67. Plots of average lead and mercury concentrations (parts per billion,ppb) in water in each Estuary reach from 1989–1995. The vertical bars represent ranges ofvalues. Sample sizes for lead and mercury are as follows: South Bay 1989–1993 n=4, 1994–1995n=7; Central Bay 1989–1990 n=1, 1991 n=3, 1992–1993 n=4, 1994–1995 n=5; Northern Estuary1989–1990 n=4, 1991–1992 n=7, 1993 n=6, 1994–1995 n=8; Rivers 1989–1990 n=1, 1991–1995 n=2.

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Water Monitoring

83

Near-Total Nickel, µg/L Total Selenium, µg/L

Figures 68 and 69. Plots of average nickel and selenium concentrations (parts per billion,ppb) in water in each Estuary reach from 1989–1995. The vertical bars represent ranges ofvalues. Sample sizes for nickel are as follows: South Bay 1989–1993 n=4, 1994–1995 n=7; CentralBay 1989–1990 n=1, 1991 n=3, 1992–1993 n=4, 1994–1995 n=5; Northern Estuary 1989–1990 n=4,1991–1992 n=7, 1993 n=6, 1994–1995 n=8; Rivers 1989–1990 n=1, 1991–1995 n=2. Sample sizes forselenium are as follows: South Bay 1991 and 1993 n=4, 1994–1995 n=7; Central Bay 1991 n=3, 1993n=4, 1994–1995 n=5; Northern Estuary 1991 n=7, 1993 n=6, 1994–1995 n=8; Rivers 1991 & 1993–1995 n=2. * indicates different scale.

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84


Near-Total Silver, µg/L Near-Total Zinc, µg/L

Figures 70 and 71. Plots of average silver and zinc concentrations (parts per billion, ppb)in water in each Estuary reach from 1989–1995. The vertical bars represent ranges of values.Sample sizes for silver and zinc are as follows: South Bay 1989–1993 n=4, 1994–1995 n=7; CentralBay 1989–1990 n=1, 1991 n=3, 1992–1993 n=4, 1994–1995 n=5; Northern Estuary 1989–1990 n=4,1991–1992 n=7, 1993 n=6, 1994–1995 n=8; Rivers 1989–1990 n=1, 1991–1995 n=2.

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Water Monitoring

85

Trace Organics

Spatial patterns

In principle, dissolved trace organicsconcentrations can be used to indicate sourcesin a manner similar to the dissolved traceelement concentrations. However, two featuresof the RMP dissolved organics data limit theirvalue in this regard. First, the variance at agiven station for trace organics is generallygreater than for trace elements. Second, thefilter used to separate particles from thedissolved fraction for the water organicssamples has a pore size of 1 µm, significantlygreater than the 0.45 µm filters used for traceelements, making the measured “dissolved”fraction a looser representation of the “true”dissolved fraction.

In spite of these limitations, general spatialpatterns are evident in the dissolved traceorganic data. Like the dissolved trace elements,most dissolved trace organics, including PCBs,chlordanes, DDTs, HCHs, and diazinon, wereelevated in the South Bay relative to otherreaches of the Estuary, with concentrationsprogressively decreasing from the Coyote Creekstation (BA10) to the Golden Gate station(BC20). In the Northern Estuary dissolvedconcentrations of DDTs were consistently high,dissolved diazinon was relatively high in Apriland August, and dissolved chlordanes werehigh in April relative to other reaches of theEstuary. The River stations (BG20 and BG30)were occasionally high in dissolved pesticides(chlordanes, DDTs, and diazinon). Februaryconcentrations of diazinon were apparentlyuniformly high throughout the Estuary, even atthe Golden Gate station (BC20). DissolvedHCHs were much lower at the River stationsthan in the rest of the Estuary, including theGolden Gate station.

Diazinon and HCHs occur mostly in thedissolved fraction, so spatial patterns for totalconcentrations are the same as for the dissolvedfraction. Total concentrations of the morehydrophobic trace organics (PAHs, PCBs,DDTs, and chlordanes) generally displayed thesame spatial pattern as TSS (Figure 1), with

high concentrations in the South Bay, lowconcentrations in the Central Bay, high concen-trations in the Northern Estuary, and interme-diate concentrations in the Rivers. The highesttotal concentrations of the hydrophobic organicswere measured at stations with the highestTSS concentrations (BA10, BA30, and BD15 inApril).

Spatial variation in total concentrations ofthe hydrophobic trace organics is more appar-ent when the influence of TSS is removed usinglinear regression (Jarman and Davis, thisreport). The TSS-adjusted concentrations ofPCBs and PAHs had similar spatial patterns,with consistently high values in the South Bayfrom BA10 to BA30, high values at thePetaluma River (BD15), intermediate values inthe Central Bay, and consistently low values inthe Rivers and Northern Estuary. These datasuggest the existence of sources of PCBs andPAHs in the South Bay and at the PetalumaRiver station (BD15). Adjusted DDT concentra-tions were consistently high in the Rivers andNorthern Estuary, consistently low at RedwoodCreek (BA40), and generally inconsistent atother stations. Adjusted chlordane concentra-tions were highest in the South Bay (especiallyat Coyote Creek—BA10) and lowest at theSacramento River (BG20). Overall, the dis-solved and TSS-adjusted trace organics dataclearly indicate the presence of sources in theSouth Bay for all of the organics and at theRivers for DDTs.

Temporal trendsSeasonal Variation

Some of the dissolved trace organics dis-played obvious seasonal variation. DissolvedΣPAHs were much higher at all stations inAugust than in February and April. The expla-nation for this variation is not obvious. Onlythe dissolved fraction was high in August; theparticulate fraction was generally highest inApril. High water temperatures occured inAugust, but these would have similarly affecteddissolved ΣPAH concentrations in 1994 andAugust concentrations were not elevated inthat year. Diazinon concentrations were uni-

86


formly high in February, intermediate in April,and low in August. More information on thepersistence of diazinon in Bay waters andseasonal variation in local use of diazinonwould be needed to interpret whether theobserved variation corresponds with seasonalvariation in diazinon loadings to the Estuary.

Total concentrations of the trace organicsthat tend to be particle-associated (PAHs,PCBs, chlordanes, and DDTs) were oftenhighest in April, coinciding with high concen-trations of TSS. Examination of the relation-ship between TSS and DDTs during each cruisesuggested that large freshwater flows in Aprilcarried relatively contaminated sediments intothe Estuary (Jarman and Davis, this report).

Long-term Trends

A detailed statistical analysis of long-termtrends, as was conducted for the trace ele-ments, has not been conducted for the traceorganics. Figures 72–77 are summary plots ofavailable RMP data for total (dissolved +particulate) concentrations of trace organics inwater. From visual inspection of these plotsthere are two cases where declines seempossible. First, diazinon at the Rivers wasmuch higher in February 1994 than in subse-quent sampling events. Since diazinon loads tothe Estuary are highly episodic, however, thehigh concentrations in February 1994 maysimply have been due to sampling coincidingwith transport of a pulse of diazinon fromupstream. Second, ΣDDTs at the Rivers washigher in February 1993 than in subsequentsampling. With only one point elevated abovethe others, however, many hypotheses otherthan an actual long-term trend could provide aplausible explanation for these results.

Overall it is likely that, similar to the traceelements, a rigorous analysis of trends in thetotal trace organics data would not detectstatistically significant trends. Also, similar tothe trace elements, it is likely that the best wayto attempt to uncover trends in the water traceorganics will be to establish their relationshipswith important exogenous variables and then

remove the influence of those variables, leavinga clearer picture of temporal variation.

For certain persistent trace organics, thelong-term rate of decline in concentrationsappears to be very slow (see Jarman and Davis,this report, for a more detailed discussion). Thehistoric water data are particularly relevant(Risebrough, this report). Mean Aroclor-basedΣPCB concentrations measured in the CentralBay in 1975 were approximately 900 pg/l. In1980 de Lappe et al., (1983) measured Aroclor-based ΣPCB concentrations in the Central Bay,obtaining values of 647 pg/L at the Golden Gateand 664 pg/L at Angel Island. The averageconcentration of congener-based ΣPCBs in theCentral Bay for RMP cruises has been approxi-mately 400 pg/L. Congener-based ΣPCB concen-trations in other regions of the Estuary arefrequently much higher. Since Aroclor-basedΣPCB values are inherently probably two ormore times higher than congener-based ΣPCBvalues, the concentrations detected in theseolder studies and those detected currently inthe RMP are roughly equivalent. These dataindicate that PCBs levels have not declinedappreciably since the mid-1970s.

Comparison to Water QualityGuidelines

This section provides an overview of how1995 RMP data compare to water qualityguidelines (i.e., criteria and objectives). Guide-lines used for these comparisons are shown inTables 10–12. It should be noted that in anumber of cases RMP data are not strictlycomparable to the available guidelines, asdiscussed in the Background section of thischapter.

Of the ten trace elements measured,concentrations of Cr, Cu, Pb, Hg, and Ni werehigher than guidelines on one or more occasions(Table 13). Cu, Hg, and Ni were most frequentlyabove guidelines, with high concentrationsoccurring especially in the Southern Sloughs,South Bay, and the Northern Estuary. Severalclasses of trace organics also had concentra-tions above guidelines, including PCBs, PAHs,DDTs, chlordanes, dieldrin, and diazinon.

Water Monitoring

87

Total PAHs, pg/L Total PCBs, pg/L

Figures 72 and 73. Plots of average PAH and PCB concentrations (parts per quadrillion,ppq) in water in each Estuary reach from 1993–1995. The vertical bars represent ranges ofvalues. Sample sizes are as follows: South Bay 1993 n=2, 1994–1995 n=4; Central Bay 1993 n=2,1994–1995 n=4; Northern Estuary 1993 n=5, 1994–1995 n=6; Rivers 1993–1995 n=2. * indicatesdifferent scale.

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Total Diazinon, pg/L Total Chlorpyrifos, pg/L

Figures 74 and 75. Plots of average diazinon and chlorpyrifos concentrations (parts perquadrillion, ppq) in water in each Estuary reach from 1993–1995. The vertical bars representranges of values. Sample sizes are as follows: South Bay 1993 n=2, 1994–1995 n=4; Central Bay1993 n=2, 1994–1995 n=4; Northern Estuary 1993 n=5, 1994–1995 n=6; Rivers 1993–1995 n=2. *indicates different scale.

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Water Monitoring

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Total DDTs, pg/L Total Chlordanes, pg/L

Figures 76 and 77. Plots of average DDT and chlordane concentrations (parts perquadrillion ppq) in water in each Estuary reach from 1993–1995. The vertical bars representranges of values. Sample sizes are as follows: South Bay 1993 n=2, 1994–1995 n=4; Central Bay1993 n=2, 1994–1995 n=4; Northern Estuary 1993 n=5, 1994–1995 n=6; Rivers 1993–1995 n=2. *indicates different scale.

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1,500

2,000

2,500

3,000South Bay

3/93

2/94

4/94

8/94

2/95

4/95

8/95

0

200

400

600

800

1,000

1,200

1,400South Bay

90


FRESH WATERParameter Instantaneous

Maximum24-hour avera g e

1-hour avera g e

4-day avera g e

A g 1.2 . . .As . . 360 190C d . . e(1.128H - 3.828) e(0.7852H - 3.4590)

Cr . . 16 11C u . . e(0.9422H - 1.464) e(0.8545H - 1.465)

H g . . 2.4 0.025Ni 1100 56 e(0.846H + 3.3612) e(0.846H + 1.1645)

P b . . e(1.273H - 1.460) e(1.273H - 4.705)

Z n 170 58 e(0.8473H - 0.8604) e(0.8473H - 0.7614)

TOTAL PAHs A . 15 . .

SALT WATERParameter Instantaneous

Maximum24-hour avera g e

1-hour avera g e

4-day avera g e

A g 2.3 . . .As . . 69 36C d . . 43 9.3Cr . . 1100 50C u . . 4.9 .H g . . 2.1 0.025Ni 140 7.1 . .P b . . 140 5.6Z n 170 58 . .

TOTAL PAHs A . 15 . .A Compounds identified in EPA Method 610.

Table 10. Basin Plan water quality objectives for toxic pollutants in surfacewaters. From San Francisco Bay Basin (Region 2), Water Quality Control Plan (June21, 1995). Values are in µg/L. H = hardness. Refer to Basin Plan for furtherinformation.

Convert Total to DissolvedParameter Fresh Water Salt Water

1-hour average 4-day average 1-hour average A

Ag 0.85 . 0.85As 1 1 1Cd 1.136672-[(ln(H)*(0.041838)] 1.101672-[(ln(H)*(0.041838)] 0.994Cr 0.982 0.962 0.993Cu 0.96 0.96 0.83Hg na B na B na B

Ni 0.998 0.997 0.99Pb 1.46203-[(ln(H)*(0.145712)] 1.46203-[(ln(H)*(0.145712)] 0.951Se . . 0.998Zn 0.978 0.986 0.946

A Conversion factors for 4-day salt water averages are not currently available. Use 1-hour conversion factors.B Mercury is judged on a total basis as the objective is based on mercury residues in aquatic organisms rather than toxicity.

Table 11. Conversion factors for trace elements in water. From the May 4, 1995Federal Register, Part IV- EPA 40 CFR Part 131, pg. 22231 (Table 2: freshwater and Table 3:saltwater). H = hardness.

Water Monitoring

91

Aquatic Life Human Health (10-6 risk for carcinogens)

ParameterFresh Water Salt Water Fresh

W a t e rSalt and

Fresh Water1-hour average

4-day average

1-hour average

4-day average

Water & Organisms

Organisms only

Ag e(1.72H -6.52) . 2.3 . . .As 360 190 69 36 0.018 0.14Cd e(1.128H - 3.828) e(0.7852H - 3.4590) 43 9.3 . .Cr 16 11 1100 50 . .Cu e(0.9422H - 1.464) e(0.8545H - 1.465) 2.9 2.9 . .Hg 2.4 0.012 2.1 0.025 0.14 0.15Ni e(0.846H + 3.3612) e(0.846H + 1.1645) 75 8.3 610 4600Pb e(1.273H - 1.460) e(1.273H - 4.705) 220 8.5 . .Se 20 5 300 71 . .Zn e(0.8473H - 0.8604) e(0.8473H - 0.7614) 95 86 . .

Anthracene . . . . 0.00012 0.00054Benz(a)anthracene . . . . 0.0028 0.031Benzo(a)pyrene . . . . 0.0028 0.031Benzo(b)fluoranthene . . . . 0.0028 0.031Benzo(k)fluoranthene . . . . 0.0028 0.031Chrysene . . . . 0.0028 0.031Dibenz(a,h)anthracene . . . . 0.0028 0.031Fluoranthene . . . . 300 370Indeno(1,2,3-cd)pyrene . . . . 0.0028 0.031Phenanthrene . . . . . .Pyrene . . . . 960 11000

Alpha-HCH . . . . 0.0039 0.013Beta-HCH . . . . 0.014 0.046Chlordane 2.4 0.0043 0.09 0.004 0.00057 0.00059Delta-HCH . . . . . .Dieldrin 2.5 0.0019 0.71 0.0019 0.00014 0.00014Endosulfan I 0.22 0.056 0.034 0.0087 0.93 2Endosulfan II 0.22 0.056 0.034 0.0087 0.93 2Endosulfan Sulfate . . . . 0.93 2Endrin 0.18 0.0023 0.037 0.0023 0.76 0.81Gamma-HCH 2 0.08 0.16 . 0.019 0.063Heptachlor 0.52 0.0038 0.053 0.0036 0.00021 0.00021Heptachlor Epoxide 0.52 0.0038 0.053 0.0036 0.0001 0.00011Hexachlorobenzene . . . . 0.00075 0.00077p,p'-DDD . . . . 0.00083 0.00084p,p'-DDE . . . . 0.00059 0.00059p,p'-DDT 1.1 0.001 0.13 0.001 0.00059 0.00059

Total PCBs A . 0.014 . 0.03 0.000044 0.000045A Total PCBs are not in the Federal Register, but individual Aroclors are. All Aroclors have the same value.

Table 12. EPA (“National Toxics Rule”) water quality criteria for priority toxic pollutants. FromFederal Register, December 22, 1992—Vol. 57, No. 246. Rules and Regulations.

92


Tab

le 1

3. S

um

mar

y of

con

tam

inan

ts t

hat

wer

e ab

ove

wat

er q

ual

ity

obje

ctiv

es o

r cr

iter

ia a

t ea

ch 1

995

RM

P w

ater

sam

pli

ng

stat

ion

.T

race

ele

men

t ob

ject

ives

are

fro

m t

he

Bas

in P

lan

(Ta

ble

10).

Th

e B

asin

Pla

n d

oes

not

hav

e an

obj

ecti

ve f

or s

elen

ium

. Th

is c

rite

rion

com

es f

rom

th

eE

PA (

Fed

eral

Reg

iste

r, M

ay 4

, 199

5). T

race

org

anic

s re

sult

s ar

e co

mpa

red

to t

he

hu

man

hea

lth

(10

-6 r

isk

for

carc

inog

ens)

, fre

sh a

nd

salt

wat

ercr

iter

ia f

or t

he

con

sum

ptio

n o

f or

gan

ism

s on

ly, f

oun

d in

th

e E

PA F

eder

al R

egis

ter,

May

4, 1

995.

Th

e to

tal P

AH

s ob

ject

ive

is f

rom

th

e B

asin

Pla

n a

sth

e F

eder

al R

egis

ter

does

not

hav

e a

crit

erio

n f

or t

otal

PA

Hs.

Th

e di

azin

on g

uid

elin

e is

fro

m t

he

Nat

ion

al A

cade

my

of S

cien

ces.

W =

Wet

sea

son

(Feb

ruar

y),

S =

Spr

ing

sam

plin

g (l

ate

May

), D

= D

ry s

easo

n (

Au

gust

), -

= n

ot a

bove

gu

idel

ine,

* =

not

ava

ilab

le o

r n

ot s

ampl

ed.

Chromium

Copper

Mercury

Nickel

Lead

Selenium

Zinc

Anthracene

Benzo(a)pyrene

Benzo(b)fluoranthene

Gu

ide

lin

e5

04

.90

.02

57

.15

.65

58

54

03

10

00

31

0S

tatio

n

Na

me

Sta

tion

C

od

eµ

g/L

µg

/Lµ

g/L

µg

/Lµ

g/L

µg

/Lµ

g/L

pg

/Lp

g/L

pg

/Lp

g/L

pg

/Lp

g/L

pg

/Lp

g/L

pg

/Lp

g/L

pg

/Lp

g/L

Sun

nyva

leC

-1-3

-,S

,--,

-,-

-,S

,D-,

-,D

-,-,

D-,

-,-

-,-,

-*

**

**

**

**

**

*S

an J

ose

C-3

-0-,

S,-

-,-,

--,

S,D

-,-,

D-,

-,D

-,-,

--,

-,-

**

**

**

**

**

**

Coy

ote

Cre

ekB

A1

0-,

-,-

-,S

,D-,

S,-

W,S

,--,

S,-

-,-,

--,

-,-

-,S

,--,

S,-

-,S

,--,

-,-

-,-,

DW

,S,-

-,S

,--,

S,-

-,S

,--,

-,-

W,S

,DW

,S,D

Sou

th B

ayB

A2

0-,

-,-

-,S

,--,

S,-

-,S

,D-,

-,-

-,-,

--,

-,-

**

**

**

**

**

**

Dum

bart

on B

ridge

BA

30

-,-,

--,

S,-

-,S

,D-,

S,D

-,-,

--,

-,-

-,-,

--,

S,-

-,S

,--,

S,-

-,-,

--,

-,-

-,-,

--,

S,-

-,-,

--,

S,-

-,-,

-W

,S,D

W,S

,DR

edw

ood

Cre

ekB

A4

0-,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

W,S

,D-,

S,D

San

Bru

no S

hoal

BB

15

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-*

**

**

**

**

**

*O

yste

r P

oint

BB

30

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-*

**

**

**

**

**

*A

lam

eda

BB

70

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-W

,S,D

-,-,

-Y

erba

Bue

na Is

land

BC

10

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,*

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-W

,S,D

-,-,

-G

olde

n G

ate

BC

20

-,-,

--,

-,-

-,-,

*-,

-,-

-,-,

--,

-,*

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

W,-

,--,

-,-

-,-,

--,

-,-

-,-,

-W

,S,D

-,-,

-R

icha

rdso

n B

ayB

C3

0-,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

**

**

**

**

**

**

Poi

nt Is

abel

BC

41

-,-,

--,

-,-

-,-,

--,

S,-

-,-,

--,

-,*

-,-,

-*

**

**

**

**

**

*R

ed R

ock

BC

60

-,-,

*-,

-,-

-,-,

--,

-,-

-,-,

--,

-,*

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-W

,S,D

-,-,

-P

etal

uma

Riv

erB

D1

5W

,S,-

-,-,

-W

,S,D

-,-,

D-,

-,-

-,-,

--,

-,-

-,S

,--,

S,-

-,S

,-W

,-,-

-,-,

-W

,-,-

-,S

,--,

S,-

-,S

,--,

S,-

W,S

,DW

,S,D

San

Pab

lo B

ayB

D2

0-,

-,-

-,S

,--,

S,-

-,S

,--,

-,-

-,-,

*-,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-W

,-,-

-,-,

--,

-,-

-,S

,--,

-,-

W,S

,D-,

S,-

Pin

ole

Poi

ntB

D3

0-,

S,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

S,-

-,-,

--,

-,-

-,S

,--,

-,-

W,S

,D-,

-,-

Dav

is P

oint

BD

40

-,S

,-W

,-,-

-,S

,-W

,-,-

-,-,

--,

-,-

-,-,

*-,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

S,-

-,-,

-W

,S,D

-,S

,-N

apa

Riv

erB

D5

0-,

-,-

W,S

,--,

-,-

W,S

,--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,S

,--,

-,-

W,S

,DW

,-,-

Pac

heco

Cre

ekB

F1

0-,

-,-

W,S

,--,

-,-

W,-

,--,

-,-

-,-,

--,

-,-

**

**

**

**

**

**

Griz

zly

Bay

BF

20

-,-,

-W

,S,-

-,S

,--,

S,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

W,-

,--,

-,-

-,-,

--,

S,-

-,-,

-W

,S,D

-,-,

-H

onke

r B

ayB

F4

0-,

-,*

W,S

,--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

**

**

**

**

**

**

Sac

ram

ento

Riv

erB

G20

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,*

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,D

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-W

,S,D

-,-,

-S

an J

oaqu

in R

iver

BG

30-,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

--,

-,-

-,-,

-W

,-,-

-,-,

--,

-,-

-,-,

--,

-,-

W,S

,D-,

-,-

Diazinon

Dieldrin

Heptachlor Epoxide

Indeno(1,2,3-cd)pyrene

p,p'-DDD

p,p'-DDE

p,p'-DDT

Total PCBs (SFEI)

Total PAHs (SFEI)

90

00

14

01

10

31

00

08

40

59

05

90

45

31

00

0

Water Monitoring

93

Congener-based ΣPCBs were well above theAroclor-based 45 pg/L guideline in all RMPsamples. The lowest ΣPCB concentration mea-sured in the RMP was 83 pg/L at the GoldenGate (BC20) in August, still well above theguideline. ΣPAHs were above the 31,000 pg/Lguideline at several stations, and during allcruises at Coyote Creek (BA10), DumbartonBridge (BA30), and Petaluma River (BD15).Concentrations of some individual DDT isomersand individual PAHs were above guidelines inApril, coinciding with high TSS concentrationsin a very wet period. Diazinon was above the9,000 pg/L NAS guideline in one sample fromthe Petaluma River (BD15) in February. Thestations with the largest numbers of concentra-tions above guidelines were Coyote Creek(BA10), the Dumbarton Bridge (BA30), and thePetaluma River (BD15). Unusually high TSS atthe Petaluma River station (BD15) was partiallyresponsible for the occurrence of high concentra-tions of several contaminants there in April.

In some cases different guidelines are usedin this report than were used in the 1994 report,so the frequencies of guideline exceedancesincluded in the 1994 report may not be directlycomparable to those in this report. For a directcomparison of 1994 and 1995, the same criteriaused in this report were applied to the 1994 data(data not shown). The overall pattern ofexceedances was very similar in the two years,with the following exceptions. Concentrations ofCu, Ni, diazinon, and dieldrin were aboveguidelines distinctly more frequently in 1994.On the other hand, concentrations of p,p’-DDEand heptachlor epoxide were above guidelinesmore frequently in 1995. In 1994, as in 1995,Coyote Creek (BA10), Dumbarton Bridge(BA30), and Petaluma River (BD15) frequentlyhad concentrations above guidelines, but theGrizzly Bay (BF20), Pinole Point (BD30), and

San Pablo Bay (BD20) stations were alsofrequently above guidelines.

Effects of Water Contamination

Aquatic toxicity was observed in only onewater sample in 1995, in a Mysidopsis test ofSan Joaquin River (BG30) water collected inFebruary (Figure 36). While this result wasstatistically significant, its biological signifi-cance may be questioned, since the reduction insurvival of test organisms relative to controlswas not large. Many of the attempted tests didnot produce usable results due to poor mussellarvae survival in some February controls andproduction of inviable sperm or eggs by oysterstocks in August.

The presence of some contaminants inwaters of the Estuary, such as the organophos-phate insecticides, is known to be episodic, withhigh concentrations entering the Estuaryduring periods of heavy use and/or high runoff.With just three sampling events that were nottargeted at specific contaminants, the likeli-hood is low that short-duration contaminationevents would have been detected. The lack ofsignificant results in 1995, therefore, does notnecessarily mean that the Estuary was free ofambient toxicity for the entire year. Resultsobtained in February 1996, in contrast to 1995results, showed clear statistically and biologi-cally significant toxicity in the Mysidopsis testat the Sacramento River (BG20), San JoaquinRiver (BG30), and Grizzly Bay (BF20) stations.In a special study begun in late 1996, a moretargeted approach is being taken, with toxicitytesting of water samples collected during stormevents. This sampling strategy should providevaluable information on the acute toxicityassociated with storm runoff, which may be animportant source of many contaminants ofconcern in the Estuary.

94


CHAPTER THREE

Sediment Monitoring

Sediment Monitoring

95

BackgroundSediment quality, trace elements, and trace

organic contaminants were measured at 22RMP base program stations. In addition, traceelements were measured at two stations in thesouthern end of the Estuary in cooperation withthe Regional Board and the Cities of San Jose(C-3-0) and Sunnyvale (C-1-3). Conductivity,temperature, and depth profiles were alsotaken in the water column at all RMP stations(station depth is reported in Appendix C, Table11). Station locations are shown on Figure 1 inChapter One: Introduction. Sediment sampleswere collected during the wet-season (Febru-ary) and dry-season (August). Sampling datesare shown on Table 3 in Chapter One: Introduc-tion. Detailed methods of collection and analy-sis are included in Appendix A. Measurementsmade on sediment samples are listed in Table 3in Chapter One: Introduction.

This section contains graphs and datatables for sediment trace elements (Figures 1–

10) and trace organic contaminants (Figures11–13). Tabulated data for sediment qualityparameters, such as grain-size and organicmaterial, are included in Appendix C. New in1995 are data on ammonia and sulfides inEstuary sediments.

In order to compare results among themajor areas, or reaches of the Estuary, theRMP stations are separated into six groups ofstations based subjectively on geography,similarities in sediment types, and patterns oftrace contaminant concentrations.

The five Estuary reaches are: the SouthernSloughs (C-1-3 and C-3-0), South Bay (sixstations, BA10 through BB70), Central Bay(five stations, BC11 through BC60), NorthernEstuary (eight stations, BD15, through BF40),and Rivers (BG20 and BG30). The coarsesediment stations (BC60, BD41, BF10, andBG20) showed different sediment chemistryand were grouped separately for analyticalcomparisons.

0

2

4

6

8

10

12

14

16

18

20

C-1

-3

C-3

-0

BA

10

BA

21

BA

30

BA

41

BB

15

BB

30

BB

70

BC

11

BC

21

BC

32

BC

41

BC

60

BD

15

BD

22

BD

31

BD

41

BD

50

BF

10

BF

21

BF

40

BG

20

BG

30

FebruaryAugust

❊❊❊ ❊

Figure 1. Arsenic (As) concentrations in sediment in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sediment stations.Arsenic concentrations ranged from 2.00 to 18.23 ppm. The highest concentration was sampled atPetaluma River (BD15) in August and the lowest at Sunnyvale (C-1-3) in February. Averageconcentrations were highest in the Northern Estuary in August (13.36 ppm). Concentrations werehighest in August for the Southern Slough stations, but there was no consistent seasonal trend inother Estuary reaches. Arsenic concentrations were below the ERM value of 70 ppm at all stations.However, concentrations were above the ERL value of 8.2 ppm at 17 stations in February and 21stations in August.

Southern

SloughsSouth Bay Central Bay Northern Estuary Rivers

Ars

enic

, mg/

kg d

ry w

eigh

t

Arsenic in Sediment 1995

96


Sediment Quality GuidelinesThere are currently no Basin Plan objectives or

other regulatory criteria for sediment contaminantconcentrations in the Estuary. However, the USEPA has produced draft objectives for five tracecontaminants: three PAHs—acenapthene,fluoranthene, and phenanthrene—and two pesti-cides—dieldrin and endrin (EPA, 1991). Those draftobjectives, along with the National Oceanic andAtmospheric Administration’s (NOAA) EffectsRange-Median (ERM) and Effects Range-Low(ERL) values (Long and Morgan, 1990; Long et al.,1995) are used in this report as guidelines for theinterpretation and assessment of sediment con-taminant concentrations in the Estuary. Thesevalues are intended to be used as informal screen-ing tools and hold no regulatory status.

The NOAA guidelines are based on data com-piled in numerous studies in the United States thatincluded sediment contaminant and biologicaleffects information. The guidelines were developedto identify concentrations of contaminants thatwere associated with biological effects in laboratory,field, or modeling studies. The ERL is the concen-

tration above which 10% of the studies showedeffects, and the ERM is the concentration abovewhich 50% of the studies showed effects. Concen-trations between the ERL and ERM are inter-preted to indicate a “possible effects range”within which effects would occasionally occur.Concentrations above the ERM are interpretedto indicate a “probable effects range” withinwhich effects frequently occur (Long et al., 1995).

There are no sediment guidelines for severalcontaminants. Earlier versions of the ERLs(Long and Morgan, 1990) included guidelines forchlordanes, aldrin, and endrin, but they were notincluded in the more recent guidelines because ofinsufficient data. Further, effects range valuesfor nickel and DDTs have low levels of confidenceassociated with them. There are no ERLs orERMs for selenium, but the Regional Board hassuggested that concentrations below 1.4 ppm areacceptable for wetland creation when covered bythree feet of sediments with concentrationsbelow 0.7 ppm (Wolfenden and Carlin, 1992).Therefore, it should be recognized that theNOAA guidelines do not provide comprehensiveguidelines for all sediment contaminants.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

C-1

-3

C-3

-0

BA

10

BA

21

BA

30

BA

41

BB

15

BB

30

BB

70

BC

11

BC

21

BC

32

BC

41

BC

60

BD

15

BD

22

BD

31

BD

41

BD

50

BF

10

BF

21

BF

40

BG

20

BG

30

FebruaryAugust

❊ ❊ ❊ ❊

Figure 2. Cadmium (Cd) concentrations in sediment in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sediment stations.Cadmium concentrations ranged from 0.041 to 0.75 ppm. The highest concentration was sampled at SanJose (C-3-0) in August and lowest at Red Rock (BC60) in August. Average concentrations were highest inthe Southern Sloughs in August (0.46 ppm). In general, concentrations were higher in February than inAugust. Cadmium concentrations were all below the ERM value of 9.6 ppm and the ERL value of 1.2 ppm.

Southern


Cadmium in Sediment 1995

Cad

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Sediment Monitoring

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❊ ❊ ❊ ❊

Figure 3. Chromium (Cr) concentrations in sediment in parts per million, dry weight(ppm) at 24 RMP stations sampled in February and August of 1995. ❊ indicates coarsesediment stations. Chromium concentrations ranged from 55.63 to 102.74 ppm. The highestconcentration was sampled at Pinole Point (BD31) in February and the lowest concentration was atSunnyvale (C-1-3) in February. Average concentrations were highest in the Northern Estuary inFebruary (87 ppm). Concentrations were higher in August in the Southern Sloughs, but there was noconsistent seasonal trend in other Estuary reaches. Chromium concentrations were below the ERMvalue of 370 ppm at all stations. However, concentrations were above the ERL value of 81 ppm at 10stations in February and 11 stations in August.

Southern


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Chromium in Sediment 1995

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FebruaryAugust

❊ ❊❊ ❊

Figure 4. Copper (Cu) concentrations in sediment in parts per million, dry weight (ppm)at 24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sedimentstations. Copper concentrations ranged from 7.20 to 70.62 ppm. The highest concentration wassampled at Pinole Point (BD31) in February and the lowest at Red Rock (BC60) in August. Averageconcentrations were highest in the Northern Estuary in February (50.25 ppm). Concentrations werehigher in August for the Southern Sloughs and in Febuary for most stations in the Northern Estuary,but there was no consistent seasonal trend in other Estuary reaches. Copper concentrations werebelow the ERM value of 270 ppm at all stations. However, concentrations were above the ERL valueof 34 ppm at 14 stations in February and 16 stations in August.

Southern


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Copper in Sediment 1995

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FebruaryAugust

❊ ❊❊ ❊

Figure 5. Lead (Pb) concentrations in sediment in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sedimentstations. Lead concentrations ranged from 5.86 to 50.60 ppm. The highest concentration wassampled at San Jose (C-3-0) in August and the lowest concentration at Pacheco Creek (BF10) inFebruary. Average concentrations were highest in the Southern Sloughs in August (36.50 ppm) butwere also high at the South Bay stations in August (29.41 ppm). In general, concentrations werehigher in August than in February for all Estuary reaches. Lead concentrations were below the ERMvalue of 218 ppm at all stations. However, concentrations were above the ERL value of 46.7 ppm atone station in August.

Lead in Sediment 1995

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FebruaryAugust

❊ ❊❊❊

Figure 6. Mercury (Hg) concentrations in sediments in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sediment stations.Mercury concentrations ranged from 0.03 to 0.48 ppm. The highest concentration was sampled atCoyote Creek (BA10) in August and the lowest at Red Rock (BC60). Average concentrations werehighest in the South Bay in August (0.356 ppm), but were nearly as high in the Southern Sloughs andNorthern Estuary stations in August. Concentrations were higher in August than in February in theSouthern Sloughs, but there was no consistent seasonal trend in the other Estuary reaches. Mercuryconcentrations were below the ERM value of 0.71 ppm at all stations. However, concentrations wereabove the ERL value of 0.15 ppm at 18 stations in February and 19 stations in August.

Southern


Mer

cury

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Mercury in Sediment 1995

Sediment Monitoring

99

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FebruaryAugust

❊ ❊ ❊❊

Figure 8. Selenium (Se) concentrations in sediments in parts per million, dry weight(ppm) at 24 RMP stations sampled in February and August of 1995. ❊ indicates coarsesediment stations. Selenium concentrations ranged from 0.05 to 0.66 ppm. The highest concentrationwas sampled at Petaluma River (BD15) in February and the lowest concentration was at Red Rock(BC60) in August. Average concentrations were highest in the South Bay in February (0.42 ppm), butwere nearly as high in the Northern Estuary stations in February (0.40 ppm). Concentrations werehigher in August than in February in the Southern Sloughs, but there was no consistent seasonaltrend in the other Estuary reaches. There are no ERM and ERL values for selenium.

Southern


Sel

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Selenium in Sediment 1995

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FebruaryAugust

❊❊❊ ❊

Figure 7. Nickel (Ni) concentrations in sediments in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sedimentstations. Nickel concentrations ranged from 49.90 to 117.54 ppm. The highest concentration wassampled at Pinole Point (BD31) in February and the lowest concentration at Yerba Buena Island(BC11) in February. Average concentrations were highest in the Northern Estuary in February(92.55 ppm). Concentrations were higher in August than in February for Southern Slough stationsbut ther was no consistent seasonal trend in other Estuary reaches. Nickel concentrations wereabove the ERM value of 51.6 ppm for all stations in August and all but one (BC11) in February. Thatconcentration was above the ERL value of 20.9 ppm.

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FebruaryAugust

❊ ❊ ❊❊

Figure 9. Silver (Ag) concentrations in sediments in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sedimentstations. Silver concentrations ranged from 0.01 to 0.96 ppm. The highest concentration was sampledat San Jose (C-3-0) in August and the lowest concentration at Red Rock (BC60) in August. Averageconcentrations were highest in the Southern Sloughs in August (0.59 ppm). Concentrations werehigher in August than in February for Southern Slough stations, but there was no consistentseasonal trend in other Estuary reaches. Silver concentrations were below ERM value of 3.7 ppmand ERL value of 1 ppm at all stations.

Silv

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Silver in Sediment 1995

Southern


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FebruaryAugust

❊ ❊ ❊❊

Figure 10. Zinc (Zn) concentrations in sediments in parts per million, dry weight (ppm) at24 RMP stations sampled in February and August of 1995. ❊ indicates coarse sedimentstations. Zinc concentrations ranged from 55.0 to 148.0 ppm. The highest concentration was sampledat San Jose (C-3-0) in August and the lowest concentration was at Red Rock (BC60) in August.Average concentrations were highest in the Northern Estuary in February (118.0 ppm).Concentrations were higher in August than in February in the Southern Sloughs, but there was noconsistent seasonal trend in the other Estuary reaches. Zinc concentrations were below the ERMvalue of 410 ppm and the ERL value of 150 ppm at all stations.

Zin

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Zinc in Sediment 1995

Southern


Sediment Monitoring

101

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FebruaryAugust

❊ ❊❊❊

Figure 11. Total PAH concentrations in sediment in parts per billion, dry weight (ppb) at22 RMP stations sampled in February and August of 1995. ❊ indicates coarse sedimentstations. Total PAH concentrations ranged between 16 and 3722 ppb. The highest concentration wassampled at Alameda (BB70) in Febuary and the lowest concentration was measured at Red Rock(BC60) in August. Average concentrations were highest in the South Bay in August (2,544 ppb) andlowest at the River stations in August. Concentrations were highest in Febuary for all stations in theSouth and Central Bay stations except BA10. There was no consistent seasonal trend in otherEstuary reaches. Total PAH concentrations were below the ERM value of 44,792 ppb and the ERLvalue of 4,022 ppb at all stations.

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FebruaryAugust

★ ★★★ ★ ★ ★

❊ ❊❊❊

Figure 12. Total PCB concentrations in sediment (ppb, dry weight) at 22 RMP stationssampled in Febuary and August 1995. ❊ indicates coarse sediment stations. Total PCBconcentrations ranged between not detected (★) and 21 ppb (see Appendix B, Table 3 for MDLs). Thehighest concentration was sampled at Dumbarton Bridge (BA30) in August and the lowestconcentration was "below detection limits" at several stations. Total PCBs were not detected atRichardson Bay (BD30), Sacramento River (BG20) and San Joaquin River (BG30) in Febuary andneither sampling period at Davis Point (BD41) and Red Rock (BC60). Concentrations were highest inthe South Bay in August (14 ppb) and lowest at the River stations in August. Concentrations werehighest in August for all South Bay stations except Alameda (BB70). There was no consistentseasonal trend in other Estuary reaches. Total PCB concentrations were below the ERM value of 180ppb and the ERL value of 22.7 ppb at all stations.

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Total PCBs in Sediment 1995


102


Sediment BioassaysTwo sediment bioassays were conducted at

12 of the RMP stations (Figure 14) in Februaryand again in August of 1995. Sampling dates arelisted in Table 3 in the Introduction.

Amphipods (Eohaustorius estuarius) wereexposed to whole sediment for 10 days withpercent survival as the endpoint. Larval mussels(Mytilus edulis) were exposed to sedimentelutriates (water-soluble fraction) for 48 hourswith percent normal development as the end-point. Detailed methods of collection and testingare described in Appendix A, and quality assur-ance information is included in Appendix B,Table 6.

The designation of “toxic” used in the 1995RMP sediment bioassays is different than thatused in previous Annual Reports. Previously,toxicity was indicated when a statisticallysignificant difference between the test resultsand laboratory controls was obtained. However,this practice sometimes resulted in designationsof toxicity when the variance among the controlreplicates was low. For example, if the laboratory

sediment control produced 98 % + 2 % (standarddeviation) survival, then any test below about 94%would be considered toxic. It is unrealistic toconclude that such survival would indicate toxicity.

Most laboratories conducting sediment bioas-says now indicate toxicity if two criteria are met:

1. There is a significant difference between thelaboratory control and the test using a t-test,as used in past RMP reports, and

2. Mean organism response in the bioassay testwas less than 80% of the laboratory controlvalue.

Application of the second criterion eliminatesthe problem of designating toxicity based only oncomparison to controls with low replicate variance.The 1995 RMP sediment bioassays were evaluatedin this way.

The 80% of control criterion was established bystatistical analysis of many amphipod data sets byother investigators (e.g., Thursby and Schlekat,1993). The two criterion approach is currentlybeing used by the US EPA’s EMAP (Schimmel etal., 1994), and by the State’s Bay Protection andToxic Clean-up Program (BPTCP).

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FebruaryAugust

★★

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Figure 13. Total DDT concentrations in sediment in parts per billion, dry weight (ppb) at22 RMP stations sampled in February and August 1995. ❊ indicates coarse sediment stations.DDT concentrations ranged between not detected (★) and 6.87 ppb (see Appendix B, Table 3 forMDLs). The highest concentration was sampled at Coyote Creek (BA10) in August (6.87). DDTs werenot detected at several stations. Average concentrations were highest in the South and Central Bay inAugust (4 ppb). Concentrations were consistently higher in August than in Febuary throughout theEstuary. Total DDT concentrations were below the ERM value of 46 ppb. However, concentrationswere above the ERL value of 1.58 ppb at 1 station in February and 16 stations in August.

Tota

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Total DDTs in Sediment 1995


Sediment Monitoring

103

Figure 14. Chart showing results of sediment bioassays at selected RMP stations.The control used in the Eohaustorius amphipod test was home sediment from Yaquina Bay, Oregonwhere the amphipods were collected. The control used for the Mytilus (mussel) test was cleanGranite Canyon, California seawater. See Appendix A for a description of the tests used. The 1995results showed that sediments were toxic (see text) at many Estuary stations. There was noindication of sediment toxicity at San Bruno Shoal (BB15), Horseshoe Bay (BC21), Davis Point(BD41), or Napa River (BD50) in 1995. The amphipod test indicated toxicity at three stations inFebruary and two stations in August, all in the Central and South Bay. Redwood Creek (BA41) wastoxic to amphipods in both sampling periods. The mussel larvae development test indicated toxicityat four stations in February and five stations in August, but none of the South Bay stations weretoxic. Grizzly Bay (BF21), Sacramento and San Joaquin Rivers (BG20, BG30) were toxic to mussellarvae during both sampling periods. Yerba Buena Island (BC11) was toxic to both amphipods andbivalve larvae in August.

0102030405060708090

100Sacramento River—BG20

0102030405060708090

100Grizzly Bay—BF21

*

*

0102030405060708090

100Napa River—BD50

0102030405060708090

100Davis Point—BD41

0102030405060708090

100Red Rock—BC60

*

1995Sediment Bioassays

*

Eohaustorious %survival, February

Eohaustorious %survival, August

Mytilus, % normal development, February

Mytilus, % normal development, August

Sample was toxic(see text).

*

0102030405060708090

100110

Bioassay Controls

0 *

* *

*

0102030405060708090

100Yerba Buena Is.—BC11

**

0102030405060708090

100Horseshoe Bay—BC21

0102030405060708090

100Alameda—BB70

**

0102030405060708090

100San Bruno Shoal—BB15

0102030405060708090

100Redwood Creek—BA41

**

0102030405060708090

100South Bay—BA21

*

102030405060708090

100San Joaquin River—BG30

* *

104


Patterns in Sediment Toxicity1991–1995

Bruce Thompson, San Francisco Estuary InstituteJohn Hunt and Brian Anderson, University of California, Santa Cruz

The RMP has been conducting sedimentbioassays since the program began in 1993.Prior to that, the State’s Bay Protection andToxic Cleanup Program (BPTCP) conductedsediment bioassays at most of the RMP sites asPilot Studies in 1991 and 1992. Informationfrom both surveys was combined to identify keypatterns in sediment toxicity over the past sixyears.

Incidence of Toxicity

Bioassays conducted over the past six yearsin the San Francisco Estuary have indicatedthat toxicity (less than 80% of control value) inEstuary sediments was widespread in spaceand time. Overall, the highest incidence oftoxicity occurred at Grizzly Bay (BF21) wheresediments were toxic in 60% of the tests.Toxicity occurred much less frequently in theCentral Bay, and sediments were never toxic atDavis Point (BD41), probably due to the lowcontamination in sandy sediments (Figure 15).

Although the results of the amphipod andlarval bivalve tests were significantly corre-lated (r=.24, p=.009), there were considerabledifferences in the patterns of toxicity betweenthem. Ninety percent of the amphipod testswere toxic at Redwood Creek (BA41). Therewas no amphipod toxicity at the coarse sedi-ment stations (Red Rock, BC60; Davis Point,BD41) or at the San Joaquin River (BG30).Sediments were always toxic to bivalve larvaeat the Rivers confluence stations (BG20, BG30).No bivalve toxicity was observed at PinolePoint (BD31), Davis Point (BD41), or SanBruno Shoal (BB15).

There were also temporal differences intoxicity. Incidence of amphipod toxicity gener-ally decreased between 1991–1995. There wasalways more toxicity to amphipods during thewet-season sampling than in the following dry-

season suggesting that runoff may contributesubstantially to sediment toxicity. Larvalbivalve toxicity generally remained constantthrough the six years, but was more frequent inthe dry-seasons than the wet-seasons between1994–1996.

Relationship to SedimentGuidelines

Since sediments contain mixtures of numer-ous contaminants, the cause(s) of the observedtoxicity is not readily obvious. Analysis of theserelationships is underway using the 1991–1996data base. The relationships between theEffects Range Guidelines (Long, et al., 1995)used in the RMP and sediment toxicity wereevaluated first.

In theory, any individual contaminantpresent in sediments in high enough concentra-tions could cause toxicity. However, as dis-cussed in the Annual Reports, only nickel insediments generally exceeds the ERMsthroughout the Estuary, and arsenic, chro-mium, copper, mercury, nickel, and total DDTsusually exceed ERLs at most stations.

Two qualifications must be made in inter-preting ERLs and ERMs: 1) the effects rangesfor nickel and DDTs are not considered to bevery accurate and should be used with caution,and 2) Effects Ranges for some of the total traceorganic concentrations (e.g., PCBs, DDTs,PAHs) are based on sums of different sets ofindividual compounds from those used by theRMP, but these differences are considered to beslight.

Evaluation of how well exceedances of theERL guidelines predict toxicity was conductedby examining the relationship between thesediment bioassay endpoints and ERLs. For theamphipod test, there was a significant inverserelationship between amphipod survival and

Sediment Monitoring

105

Figure15. Percentage of sediment bioassays (larval bivalve and Eohaustorius tests) that weretoxic (less than 80% of control value) at RMP stations from 1991–1996. Shaded sites show where testswere conducted in all sampling periods (n=10 tests). At least five tests were conducted at the unshaded sites.

50 70

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Legend

AmphipodBioassay

LarvalBivalve

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Incidence of Sediment Toxicity1991–1996

20 100

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106


Figures 16. Plots showing relationships between the number of ERL exceedancesand bioassay endpoints at each RMP station, 1993–1995.

5 0

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0 5 1 0 1 5 2 0Number of Sediment Contaminants Above ERLs

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Number of sediment contaminants above ERLs

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r = 0.25p = .046n = 64

Sediment Monitoring

107

the number of contaminants that exceeded theERL at each stations (Figure 16). This plotpredicts that when there are more than sevenERL exceedances at a station, toxicity shouldbe observed (using 80% of control survival).Although the overall relationship is statisticallysignificant, only 7 of the 64 samples had morethan seven ERL exceedances, therefore thisrelationship should be interpreted cautiously.

These results suggest that toxicity may becaused by additive effects from low concentra-tions of several contaminants. There is growingevidence from other studies that such additiveeffects may cause toxicity (Swartz 1988, 1995;Plesha, 1988). Arsenic, chromium, copper,mercury, nickel, and DDTs are usually aboveERLs at most stations (Table 2 in SedimentMonitoring Discussion section) and may con-tribute to toxicity. Interestingly, all of the pointson Figure 16 with more than eight ERLexceedances occurred in February of 1994,where in addition to the contaminants namedabove, there were exceedances of numerousPAH compounds. The reasons for this increasein PAHs was not determined.

While the ERLs appear to be a good predic-tor of amphipod toxicity, they are not a goodpredictor for the larval bivalve bioassay (Figure16). There was a direct, significant relationshipbetween percent normal development andnumber of ERL exceedances, whereas aninverse relationship should be expected. This is

probably because ERLs are based on bulksediment measurements, but the elutriatesused in the bivalve bioassays represent only thewater-soluble fraction, and no chemical mea-surements were made on sediment elutriates.However, this test provided potentially impor-tant information about sediment toxicity,particularly at the northern Estuary RMPstations, and should continue to be used.Clearer relationships may be found usingelutriate chemistry in similar analyses. TheRMP should consider measuring elutriatechemistry at some of the test stations in orderto improve the ability to interpret this test inthe future.

One problem with interpreting theseresults is that measurements of contaminantconcentrations in bulk sediment samples maynot be good estimates of the bioavailablefractions that could cause toxicity. Some metalsmay be bound to sulfides in sediments, andorganic contaminants may be bound to organicmaterial in sediments, thereby decreasing theconcentrations dissolved in pore water avail-able to organisms. Measurements of acidvolatile sulfides and simultaneously extractedmetals (AVS / SEM), or normalizing organiccontaminants to organic carbon may providebetter estimates of contaminant concentrationsthat may cause toxicity. These methods shouldbe investigated in future RMP data analyses.

108


Further Development of a Chronic Ampelisca abditaBioassay as an Indicator of Sediment Toxicity:

Summary and Conclusions 1

Donald P. Weston, University of California, Berkeley

Introduction

Sediment toxicity tests are a critical compo-nent in many programs to assess environmen-tal quality. Recently there has been interestexpressed in using growth rates of the amphi-pod Ampelisca abdita as a potential measure ofsediment toxicity (Scott and Redmond, 1989;Redmond et al., 1994). The use of an A. abditagrowth toxicity test offers several attractivefeatures.

• A chronic growth rate test could be amore sensitive indicator of pollution thanacute mortality, and thus the use of agrowth test may provide a greater degreeof environmental protection.

• Standardized procedures for collectionand laboratory maintenance are alreadyestablished (ASTM, 1993; EPA, 1994).

• Some information already exists onsensitivity to toxicants. Exposure tocontaminated harbor sediments hascaused a reduction in growth rate andreduced egg production by the smallerfemales (Scott and Redmond, 1989),demonstrating that an impaired indi-vidual growth rate can have negativeconsequences at the population level.

As a dominant organism in the Bay, A.abdita is a particularly attractive species forsediment toxicity testing because of the directand immediate relevance of results to the Bayecosystem. If growth rate can be shown to be asensitive indicator of sediment toxicity, then itmay be possible to acquire similar data fromsize-frequency analysis of field populations. Theuse of the same endpoint for both laboratorytoxicity tests and monitoring of field popula-tions is an attractive unifying concept that hasbeen largely unexplored.

This report provides data on one componentof a larger study funded by the RMP to developan A. abdita sediment toxicity test usinggrowth rate and chronic survival as endpoints.Earlier results have already been presented(RMP, 1995) and include the following conclu-sions:

• A. abdita juveniles have been readilyavailable in collections to date (May–September).

• Greater than 90% survival is consistentlyachieved in a wide variety of Bay sedi-ments having very different grain sizedistributions and organic contents.

• Growth rates of about 1 mm/month areobserved in the laboratory populationsfed an algal diet.

• Bay sediments considered to be non-toxicbased on A. abdita growth have also beenshown to be relatively unimpacted basedon chemical analyses and benthic com-munity structure.

If A. abdita growth is to be used for sedi-ment toxicity testing in the Bay, it is importantthat a growth rate test be of equal or greatersensitivity than acute mortality tests and thatthe species be no less sensitive to toxicantsthan other amphipod species that have beenroutinely used for toxicity testing such asRhepoxynius abronius and Eohaustoriusestuarius. Since E. estuarius is currently usedin the RMP, comparative sensitivity to thisspecies is of particular concern. This reportprovides results on comparative toxicity tests,using sediments spiked with cadmium, DDT, orcrude oil. Results are described within twoexperimental series. Experiment 1 was con-ducted to establish if the growth endpoint is amore sensitive measure of toxicity (i.e., effectsdemonstrable at lower toxicant concentration)

1 This document is an excerpt of a longer report. Readers desiring more details may request the full report from the SanFrancisco Estuary Institute.

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than 10-day mortality for A. abdita. Sedimentswere spiked with cadmium or crude oil. Parallelstandard 10-day mortality and 17-day growthtests were also conducted. Experiment 2 wasconducted to establish if A. abdita was more orless sensitive to the toxicants than the otherspecies. Sediments were spiked with cadmium,DDT, or crude oil. Parallel tests with all threespecies under identical conditions were con-ducted.

The RMP is also in the midst of regularmonitoring of a San Francisco Bay A. abditapopulation in order to establish if juveniles areavailable throughout the year for growth-basedtoxicity tests and if laboratory growth rates areindependent of the time of collection providedconstant exposure conditions (e.g., tempera-ture, food supply) are maintained. Theseresults are not included here, but will beprovided in later RMP reports.

ResultsExperiment 1—Mortality

Experiment 1 was intended to determine ifuse of 17-day mortality and growth endpointsprovided more sensitive indicators of cadmiumand crude oil toxicity than the standard 10-day

mortality test. Mortality results are provided inTable 1.

Good survival was obtained in the homesediment (Alameda control) in most of theExperiment 1 trials. After a 10-day exposure,survival rates were 93% and 91% for cadmiumand crude oil experiments, respectively. After a17-day exposure, the equivalent survival rateswere 88% and 83%. The latter value is slightlylower than typical for our laboratory (88–95%).

Cadmium significantly decreased survival(70–75%) at the lowest concentration used of 22mg kg-1. The 10-day exposures were noteworthyin that this survival rate remained essentiallyconstant from 22 through 180 mg kg-1, ratherthan following a typical dose-response relation-ship. A preliminary study in our lab using thesame sediment also found ~70% survival to bethe case up to 270 mg kg-1, but with near totalmortality at 810 mg kg-1. The results from the17-day exposures followed the more typicalpattern of increasing mortality with increasingdosage, although the dose-response relationshipwas interrupted by the absence of significantmortality at 45 mg kg-1.

In the weathered crude oil exposures,survival remained comparable to the control at

Se dime nt 1 0 -day 1 7 -day

CadmiumHome (Alameda) 93 ± 12 88 ± 522 mg kg-1 75 ± 6* 70 ± 85*45 mg kg-1 71 ± 6* 74 ± 1490 mg kg-1 59 ± 10* 45 ± 6*180 mg kg-1 75 ± 7* 15 ± 18*

Weathered crude oilHome (Alameda) 91 ± 9 83 ± 9150 mg kg-1 90 ± 12 94 ± 6460 mg kg-1 90 ± 11 85 ± 71400 mg kg-1 79 ± 12 88 ± 104200 mg kg-1 25 ± 11* 33 ± 15*

Table 1. Percent survival of A. abdita in Experiment 1 usingAlameda home sediments, and cadmium or crude oil-spikedhome sediments. Values shown are means and standard deviations.Those treatments significantly different from the home sedimentcontrol at p<0.05 are denoted with *.

110


concentrations of 150, 460, and 1,400 mg kg-1. Adramatic reduction in survival to 25–33%occurred at 4,200 mg kg-1 in both the 10- and17-day exposures.

10-day and 17-day experiments providedvery similar results. With only one exception(45 mg kg-1 cadmium) the concentrations whichproduced significant 10-day mortality were thesame ones that produced significant 17-daymortality. For the single exception, 17-daysurvival was marginally higher, not lower asmight be expected. In non-toxic sediments,mean survival of amphipods in the 17-day testswas higher than after 10 days in two of the fivecases.

Experiment 1—growth

Growth in the cadmium tests of Experiment1 was atypically rapid, probably because of thesmall size of the amphipods collected at thattime. The amphipods used had an initial meanbody length of 2.3 mm (s.d. ± 0.6). Within the 17days of the test, average length in controlsediments had increased to 3.8 mm (± 0.7), oran increase in length of 65%. The oil exposureswere conducted approximately 40 days later,but in the intervening period the animals in thesource population had grown to a mean lengthof 3.2 mm (± 0.5). Over the 17 days of the oilexposure tests, animals in the control sedimentgrew to an average length of 3.9 mm (± 0.5), or22%.

Relative to the control sediment, cadmiumconcentrations of 22 and 45 mg kg-1 had noeffect on rate of growth. Animals held at 90 mgkg-1 had a size-frequency distribution that wassignificantly shifted towards smaller animalsafter 17 days.

A crude oil concentration of 1,400 mg kg-1

depressed the growth of A. abdita to the pointthat there was little change in body length overthe 17-day exposure. Mean body length of boththe initial population and the individualsexposed to 1,400 mg kg-1 for 17 days wereidentical (3.2 ± 0.5). It is possible that growthwas impaired at lower concentrations of crudeoil, but high interreplicate variability preventedstatistical analysis. The size-frequency distri-

butions of animals in both the 150 and 460 mgkg-1 treatments appeared to contain smallerindividuals than the control, but it was notpossible to attain a homogeneous population forthese treatments without elimination of two ormore replicates. This situation prevents determi-nation of growth effects.

Experiment 2—mortality

Experiment 2 was intended to determine therelative toxicant sensitivity of A. abdita, E.estuarius and R. abronius, when all three specieswere tested under identical conditions. The threeamphipod species tested differ in their preferredsediment type, thus finding a single sedimentsuitable for all species was problematic. TheBodega Bay sediment used for the Bodegacontrol and all toxicant spikes appeared to beacceptable for all species. For E. estuarius,survival in Bodega control sediment was identi-cal to that in the control (93%). For R. abronius,survival tended to be lower in the Bodega control(79% vs. 92% in home sediment), but because ofinterreplicate variability these means were notstatistically different. The survival rate of A.abdita in Bodega control sediment was 89%,higher than the home sediment, and typical foruncontaminated sediments tested in our labora-tory.

Solvent control survival rates were indistin-guishable from the Bodega control for E.estuarius and R. abronius, demonstrating noacute toxicity of the acetone carrier solvent usedfor the DDT spikes. Solvent control survival wasless than Bodega control only in the A. abditatests, but the lower concentration DDT treat-ments had survival rates as high as the Bodegacontrol, suggesting that the mortality in thesolvent control was unrelated to the acetone.

Survival data upon exposure to the threetoxicants are shown in Table 2 and Figure 17. Itshould be recognized that the E. estuarius and R.abronius tests were done for 10 days usingstandard protocols (ASTM, 1993; EPA, 1994),while the A. abdita tests represent a 17-dayexposure since survival data were collected aspart of a growth test. Previous work in ourlaboratory has shown that survival rates of A.

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abdita in uncontaminated sediments arecomparable between 10 and 30 days, and inExperiment 1, exposures to cadmium and crudeoil, there was little difference between 10- and17-day mortality rates. Thus, mortality com-parisons between the three species should bevalid in spite of the different exposure periods.

Concentrations of cadmium up to 330 mgkg-1 had no effect on mortality rates for any ofthe amphipod species. An increase in cadmiumconcentration to 1,000 mg kg-1 resulted in thecomplete mortality of R. abronius in all repli-cates, and an average survival rate of only 19%for A. abdita. E. estuarius, was unaffected bythe highest cadmium concentration used of

1,000 mg kg-1 with a survival rate of 94%, avalue comparable to the unspiked controls.

Despite the insensitivity of E. estuarius tocadmium, it was the first species to showdecreased survival with increasing sedimentconcentrations of DDT. At a DDT concentrationof 370 µg kg-1, survival rates for the speciesdropped from 93% (Bodega control) to 77%.Survival rates of the other two species re-mained indistinguishable from the controls. Ata concentration of 1,100 µg kg-1, the survivalrates of all species dropped precipitously(means of 9 to 35% survival). No individual ofany species survived exposure to DDT concen-trations of 3,300 µg kg-1 or more.

Table 2. Percent survival of the three species tested in their respective homesediments, Bodega control sediment (used for all spiked treatments), thesolvent control (acetone carrier used in DDT spikes), and the various spikedtreatments. Values shown are means and standard deviations. Those treatmentssignificantly different from the Bodega control (or solvent control in the case of DDTexposures for A. abdita) at p<0.05 are denoted with *.

Se dime nt orTre atme nt

A. abdita E . e stuarius R. abronius

Home sediment 75 ± 13* 93 ± 8 92 ± 9Bodega control 89 ± 5 93 ± 3 79 ± 16Solvent control 79 ± 4* 97 ± 4 74 ± 17

Cadmium12 mg kg-1 83 ± 19 86 ± 4 74 ± 1737 mg kg-1 89 ± 14 92 ± 4 84 ± 17110 mg kg-1 95 ± 6 95 ± 5 84 ± 2330 mg kg-1 83 ± 6 93 ± 8 67 ± 161,000 mg kg-1 19 ± 19* 94 ± 7 0 ± 0*

DDT120 µg kg-1 79 ± 13 95 ± 6 78 ± 4370 µg kg-1 88 ± 8 77 ± 7* 80 ± 81,100 µg kg-1 14 ± 7* 9 ± 2* 35 ± 12*3,300 µg kg-1 0 ± 0* 0 ± 0* 0 ± 0*10,000 µg kg-1 0 ± 0* 0 ± 0* 0 ± 0*

Weathered crude oil60 mg kg-1 83 ± 15 91 ± 7 85 ± 10180 mg kg-1 84 ± 10 88 ± 6 73 ± 12530 mg kg-1 44 ± 17* 42 ± 10* 31 ± 10*1,000 mg kg-1 5 ± 6* 23 ± 12* 14 ± 23*5,000 mg kg-1 1 ± 2* 1 ± 2* 5 ± 11*

112


Figure 17. Mortality of the three amphipod species withincreasing concentrations of cadmium, DDT, and crude oil.The values shown are means. Error bars are not provided for thesake of graphical clarity, but the data are available in Table 4.

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The toxicity of weathered crude oil was veryconsistent among the three species, with no mea-surable affect of 180 mg kg-1, and about 40% sur-vival at a concentration of 530 mg kg-1. Survivalcontinued to decline in all species with increasingcrude oil concentrations, with only a few individu-als surviving exposure to 5,000 mg kg-1.

Differences in sensitivity among the threespecies are illustrated in Table 3 on the basis ofLC50 values. The cadmium LC50 for E. estuarius isshown only as >1,000 mg kg-1, since the highestconcentration used in this study had no affect onmortality rate of the species.

Experiment 2—growth

A. abdita individuals that survived exposures tothe controls or spiked sediments were measuredand used to determine a growth rate endpoint inaddition to the mortality endpoint discussed above.Individuals used in the growth assays had an initialmean body length of 3.2 mm (s.d.=0.6). After 17days in the Bodega control sediment their lengthhad increased to an average of 4.2 mm (s.d.=0.6), ora gain of 31%. Body sizes of animals in the acetonecontrol were indistinguishable from the Bodegacontrol (p>0.05, all size comparisons byKolmogorov-Smirnov test). Body size was greater inhome sediment (mean = 4.6 mm ± 0.6) than inBodega control even though the survival rate wasreduced, perhaps suggesting differential mortalityof smaller individuals.

In the cadmium treatments the size-frequencydistribution after exposure to the 37 mg kg-1 treat-

ment was significantly shifted towards smallerindividuals relative to the Bodega control. Thesame was true of the 110 mg kg-1 cadmiumtreatment, but the difference was marginallynon-significant (0.1>p>0.05). At a concentrationof 330 mg kg-1 the difference was significantonce again (p<0.05).

DDT had no adverse affect on growth rateat the two lowest concentrations, 120 and 370µg kg-1. At the next highest concentration of1,100 µg kg-1 there was an 86% mortality,leaving too few individuals to reliably estimategrowth rates.

Weathered crude oil did not adversely affectgrowth rates at concentrations of 180 mg kg-1 orless. Significant effects (p<0.05) were apparentat 530 mg kg-1.

DiscussionCadmium LC50 values were quite variable,

both among the two sediments used in theseexperiments and in comparison to literaturevalues. Our sediment cadmium 10-day LC50 of479 mg kg-1 for R. abronius is far higher thanthe 10-day LC50 of 6.9 mg kg-1 reported for thespecies by Swartz et al. (1985) for Yaquina Baysediment. Conversely, our sediment cadmiumLC50’s for A. abdita of >180 (Experiment 1, 10day), 91 (Experiment 1, 17 day) and 643 mg kg-1

(Experiment 2) are far less than the values of1,070 to 2,850 mg kg-1 using sediments fromNew England (DiToro et al., 1990). Thesedifferences may reflect variations in sensitivity

Toxicant A. abdita LC 50

E . e stuariusLC 50

R. abroniusLC 50

Cadmium 643 >1,000 479(mg kg-1) (632–654) (426–538)

DDT 769 554 1,036(µg kg-1) (708–835) (510–601) (882–1217)

Crude oil 528 630 505(mg kg-1) (444–627) (540–735) (429–594)

Table 3. LC50 values and 95% confidence intervals for the threeamphipod species exposed to cadmium, DDT and weatheredcrude oil in Experiment 2.

114


among populations of the test animals, or mayreflect variation in cadmium bioavailabilityamong the sediments. The work of DiToro et al.(1990) suggests bioavailability differences maybe related to the concentrations of acid volatilesulfides (AVS) in the sediments. These AVSanalyses, however, are still in progress with oursediments, so consideration of this possibility ispremature.

Crude oil toxicity to A. abdita also variedamong sediments from a 17-day LC50 of 3,334mg kg-1 in the Alameda sediment to 528 mg kg-1

in the Bodega Bay sediment. In part thesedifferences may be related to differing organiccontents of the sediments and its affect onbioavailability. Normalization of the LC50

values to organic carbon reduced the differencebetween the sediments from 6-fold to 4-fold(0.95% TOC at Alameda = LC50 of 350 mg g-1

o.c.; 0.55% TOC at Bodega Bay = LC50 of 96 mgg-1 o.c.).

When normalized to organic carbon, ourLC50 measurements for DDT show remarkableconsistency with other data reported in theliterature. Based on an organic carbon contentof 0.55% in the Bodega Bay sediment, our DDT17-day LC50 values were 101 µg g-1 o.c. (E.estuarius), 140 µg g-1 o.c. (A. abdita), and 188 µgg-1 o.c. (R. abronius).

There have been few attempts to comparetoxicant sensitivity of the various amphipodspecies used in sediment toxicity testing. Inmost cases, comparisons among studies iscomplicated by differences in test conditions,and often made uninterpretable because ofpotential bioavailability differences amongsediments. In our experiments all conditions(e.g., temperature, salinity, light regime,feeding, water source, sediment) were heldconstant for tests with all three species. Thetests differed only in the duration of exposure(17-day for A. abdita and 10-day for the otherspecies), and Experiment 1 data have shownthis difference to be of little consequence forcadmium and crude oil. Data are lacking for 10-day versus 17-day mortality for DDT.

In comparing the relative toxicant sensitivi-ties of the three species, it is apparent that noone species is consistently more or less sensi-tive than the others across all toxicants. If

relative sensitivity is defined on the basis of LC50

values, then these experiments yield the followingranking:

Cadmium sensitivity:R. abronius > A. abdita >> E. estuariusDDT sensitivity:E. estuarius > A. abdita > R. abroniusCrude oil sensitivity:R. abronius = A. abdita = E. estuariusR. abronius is the most sensitive species to

cadmium toxicity, but is only slightly more sensi-tive than A. abdita. One of the most strikingobservations in this study is the dramatic toler-ance of E. estuarius to cadmium. A sedimentconcentration of 1,000 mg kg-1 (0.1% cadmium) hadno affect on acute mortality of E. estuarius, yetresulted in 81% mortality in A. abdita and 100%mortality in R. abronius. This tolerance to cad-mium was also apparent in the water-only 96-hrexposures in which the LC50 for E. estuarius wasan order-of-magnitude higher than for the otherspecies. These data indicate that E. estuarius is apoor choice for toxicity testing if cadmium isamong the potential toxicants. Relative sensitivityto the other metals is unknown but would meritfurther evaluation.

E. estuarius is the most sensitive of the threespecies to DDT, yet the differences in sensitivityamong the three species are relatively small. AllDDT LC50 values varied by less than a factor of 2.The three species are equally sensitive to crude oil,with LC50 values being essentially indistinguish-able.

Taken together, the data show that the use ofA. abdita for sediment toxicity testing does notresult in any appreciable loss in sensitivity relativeto R. abronius or E. estuarius for the contaminantstested. To the contrary, use of the species providesa substantial increase in sensitivity relative to E.estuarius in cases of cadmium toxicity. Thetubiculos nature of A. abdita does not appear tocompromise its usefulness for toxicity testing.Either the tube wall is not a barrier to diffusion ofsediment-associated toxicants, or exposure via thenear-bottom waters within a few millimeters of thesediment-water interface is comparable to that ofthe pore water exposure experienced by the twofossorial species.

The data from these experiments permitconsideration of whether a growth endpoint

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provides greater sensitivity to toxicants than amortality endpoint (either 10- or 17-day expo-sure). Neither growth nor mortality endpointsprovided a clear advantage in two of the fivetrials involving the three toxicants examined(Table 4). In two other cases, growth was themore sensitive endpoint; i.e., the toxicant con-centrations necessary to depress growth rateswere less than those necessary to cause mortal-ity. Finally, in one case (cadmium, Experiment1), growth was a less sensitive endpoint. Inter-pretation of results in this one case are problem-atic. First, there is no apparent mechanism formortality to be a more sensitive endpoint ofcadmium toxicity in one sediment (Alamedasediment of Experiment 1), but growth to be amore sensitive endpoint in another sediment(Bodega Bay sediment of Experiment 2). It isplausible that the most sensitive endpoint woulddepend upon the toxicant (e.g., one which wouldimpair growth and another whose toxic effectsare through other growth-independent mecha-nisms), but it does not seem reasonable that the

most sensitive endpoint would be sedimentdependent. Secondly, a cadmium concentrationof 22 mg kg-1 was sufficient to increase mortal-ity in both the 10- and 17-day exposures, yetthere was no increased mortality after 17 daysat 45 mg kg-1. Thus, the lack of a consistentdose-response relationship makes interpreta-tion of the cadmium mortality data difficult atthe lower concentrations.

While a growth endpoint was a moresensitive measure than acute toxicity for somecontaminants and sediments, it was not demon-strated to be consistently so in all cases. Onereason for this may have been the 3x intervalsused in sediment spiking (e.g., 12, 37, 110, 330,and 1,000 mg kg-1 cadmium). While theseintervals would have been sufficient to detectlarge differences in sensitivity between theendpoints based on NOEC/LOEC values, thedemonstration of more subtle differences wouldrequire more closely spaced intervals.

Table 4. Minimum effective concentration of the toxicants used in theexperiments as based on each of the three endpoints. Values shown are NOEC andLOEC, with the minimum concentration necessary to elicit a response expected to fallbetween these two points. In cases where one endpoint provides a more sensitive measurethan the others, the effective concentration is in bold type. Concentrations are: Cd = mgkg-1; DDT = µg kg-1; and weathered crude oil = mg kg-1.

Toxicant 1 0 -day survival 1 7 -day survival 1 7 -day growth

Cadmium (Exp. 1) 0 – 2 2 45–90a 45–90Cadmium (Exp. 2) 330–1,000 1 1 0 – 3 3 0 b

DDT (Exp. 2) 370–1,100 >370c

Crude oil (Exp. 1) 1400–4200 1,400–4,200 <1 4 0 0 d

Crude oil (Exp. 2) 180–530 180–530

aMortality was significantly greater than the control at 22 and 90 mg kg-1, but not at 45 mg kg-1. There-fore, the more conservative interpretation is taken here in presenting 45 and 90 mg kg-1 as the NOECand LOEC, respectively.

bThe size frequency distribution contained significantly smaller individuals relative to the control at 37and 330 mg kg-1. At 110 mg kg-1, however, the effect was marginally non-significant (0.05<p<0.1).Therefore, the more conservative interpretation is taken here in presenting 110 and 330 mg kg-1 as theNOEC and LOEC, respectively.

cThe LOEC is unknown since at DDT concentrations greater than 370 µg kg-1 the mortality rate was toogreat to provide sufficient individuals for growth determination.

dAt oil concentrations of 150 and 460 mg kg-1 growth superficially appeared less than the control, buthigh interreplicate variability prohibited demonstration of statistical significance. Growth impairmentwas clearly evident at 1,400 mg kg-1, and that value is shown above, but the actual effective concentra-tion may be much lower.

116


1995 Benthic Pilot StudyBruce Thompson, San Francisco Estuary Institute;

Heather Peterson, Department of Water Resources; andMichael Kellogg, City and County of San Francisco

Figure 18. Benthic sampling sites.

Introduction

The RMP Benthic Pilot Study continued in1995 with only a few changes from the 1994study described in the 1994 Annual Report. Theobjective of this pilot study remains the same:to evaluate the use of benthic information fordetermining environmental conditions in theEstuary. Benthos may respond to many differ-ent environmental changes, thus a major goalof this pilot study is to learn how to interpretthose responses by the benthos, not just tocontaminants, but to all major environmentalchanges such as salinity, sedimentation, anddredging.

In order to understand benthic changes, itis important to define what a “normal” benthicassemblage is in the Estuary. Knowledge ofsuch a “reference” provides context againstwhich to compare sites suspected of contamina-tion or other impacts. Because the Estuary ishighly variable in space and time, there areprobably several normal assemblages, eachcharacteristic of a different set of ecologicalconditions such as salinity regimes or sedimenttypes.

The following is a working definitionproposed for a “normal” benthic assemblage:An assemblage of organisms that includesspecies known to be sensitive to contamination,does not include species known to be tolerant ofcontamination, but exhibits natural fluctuationsin abundances of species in response to changesin salinity, sediment type, or the influx of otherspecies.

This definition assumes knowledge ofnatural variations in space and time, related tonon-contaminant or other anthropogenicfactors, and expected responses to contami-nated sediments. Decades of study of SanFrancisco Estuary benthos have provided muchof the information needed to determine the

range of natural variation (e.g., Nichols andPamatmat, 1988; Hymanson, et al., 1993).Responses to contamination have been wellstudied throughout the world and provide theinformation necessary for such a determination.Table 5 lists several benthic parameters com-monly used to determine both contaminantimpacts and “reference” conditions. This reportfocuses on analyses that may identify referenceassemblages in the Estuary.

Methods

Methods of sampling, processing, and dataanalysis were detailed in the 1994 AnnualReport. Collaboration continued with theDepartment of Water Resources’ (DWR) compli-ance monitoring program that sampled ninestations monthly in the Northern Estuary andDelta (Figure 18). Similarly, there was collabo-ration with the Bay Area DischargersAssociation’s (BADA) Local Effects MonitoringProgram which sampled three stations neareach of the City and County of San Francisco(CCSF), East Bay Municipal Utility District(EBMUD), and the Contra Costa CentralSanitary District (CCCSD) outfalls in Februaryand August. Nine RMP stations were sampled

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in February and August. In 1995, sampling atthe RMP Petaluma River station (BD15) wasadded. The Regional Board’s reference stationsin San Pablo Bay and at Paradise Cove werenot sampled in 1995.

Included in this year’s data analysis werefour stations sampled in 1992 at Castro Cove bythe Regional Board’s Bay Protection and ToxicCleanup Program (BPTCP). These stations hadelevated levels of contamination (mainly PAHs)in the sediments which were highly toxic(Carney et al., 1994). These sites were includedfor contrast to potential “reference” sites inorder to evaluate how ordination and classifica-tion analysis would identify and separate thestations.

All of the sites listed above were included inthe data analysis. Eventually, evaluations maybe made of how annual and seasonal variation,sediment type, other spatial heterogeneity, anddegrees of contamination affected the benthos.However, not all of the necessary data areavailable.

As discussed in the Water Monitoringsection of this report, 1995 was a very wet year.In contrast, 1994 was a critically dry year.These opposite water-year types provided agood opportunity to observe how the benthos inthe Estuary change in relation to delta outflowand increased runoff in the other parts of theEstuary. Using multivariate ordination and

classification methods, those differences wereexpected to produce site groupings that re-flected environmental differences.

Results

Four major benthic assemblages wereidentified based on ordination and classificationanalysis of the 1994 and 1995 benthic samples(Table 6). Each assemblage contains similarspecies composition and abundances. However,they also included sub-assemblages wherethere were shifts in the most abundant organ-isms.

Delta and Rivers Assemblage

This assemblage included samples from theDWR Delta and River stations (Table 6). Thebenthos inhabiting those stations had similarspecies composition and abundances. However,there were shifts in dominance among samplescollected within and between each station. TheSacramento River station (D4C) had sandysediments which indicate a dynamic environ-ment, and had greatly reduced abundancesforming a sub-assemblage. In general, the 1994and 1995 samples grouped together suggestingno major seasonal or annual differences inspecies composition within this assemblage,although many of the species had fluctuatingabundances.

Table 5. Characteristics of “normal” or reference benthic assemblages and those impacted bycontaminants. Compiled from Word et al., 1977; Nichols and Pamatmat, 1978; Chapman, et al., 1987;Canfield et al., 1996.

Indicators of Normal or Reference Indicators of ImpactedBenthic Assemblages Benthic Assemblages

Relatively moderate to high numbers of species and abundances. Relatively reduced numbers of species.Presence of amphipods and/or echinoderms. Absence of amphipods and echinoderms.

Presence of:Marine/Estuarine: Freshwater: Marine/Estuarine: Freshwater:Spiophanes missionensis Rhyacodrilus sp. Capitella spp. Limnodrilus sp.Tellina sp. Stylodrilus heringianus Oligochaetes Midge deformitiesMonoculoides sp. Streblospio benedicti Chironomus spp.

Polydora ligni Cricotpus spp.

118


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Sediment Monitoring

119

Estuarine Assemblage

This assemblage included most of themoderate salinity estuarine stations in theNorthern Estuary and South Bay (Table 6). Thespecies composition and abundances weregenerally similar among these stations andover time. The Grizzly Bay station (D7C) wasalso inhabited by some species found in theDelta and Rivers, thus it is considered a transi-tional sub-assemblage. Grizzly Bay is locatedwithin the range of the entrapment zone wheresalinities fluctuate greatly depending on Deltaoutflow. The stations near the CCCSD outfallwere also included in this assemblage. Thestations at Castro Cove were included in thisassemblage as they were inhabited by many ofthe same species. However, several indicators ofcontamination (Table 5) were sampled there,thus it is considered to represent a moderatelycontaminated sub-assemblage.

Central Bay, Fine Sediment Assemblage

This assemblage included all sites in theCentral Bay (Table 6). All of these sites hadfine, silty, clay sediments. One sub-assemblageconsisted of sites on the periphery of theCentral Bay, at Paradise Cove (SF01), SanBruno Shoal (BB15), and Redwood Creek(BA41), and appears to represent a transitionalassemblage between the estuarine and theCentral Bay assemblages. Another interestingsub-assemblage included the samples collectedat CCSF and EBMUD outfalls, Yerba BuenaIsland (BC11), and Alameda (BB70) collected inAugust 1995. These sites were dominated bythe amphipods Corophium acherusicum andAmpelisca abdita. Another sub-assemblageconsisted of all 1994 and 1995 samples atHorseshoe Bay dominated by the polychaeteMediomastus spp. There were no obviousdifferences between the 1994 and 1995 samplesexcept for the large influx of C. acherusicum inthe Central Bay.

Central Bay, Coarse SedimentAssemblage

All samples from Red Rock (BC60) wereclassified as a distinct assemblage. That site isa mid-channel location composed of over 85%sand. It was inhabited by a unique assemblageof organisms, dominated by the polychaeteHeteropodarke heteromorpha and the amphipodGrandifoxus grandis, and characterized by lownumbers of species and abundances typical ofsandy locations.

Diversity and Biomass

337 benthic species have been identified inthe 1994 and 1995 surveys. In general, num-bers of species were highest in the Central Bayfine sediment assemblage. The lowest numbersof species occurred at the sandy sedimentstations at Red Rock (BC60), near the CCCSDoutfall, and at the Sacramento River (D4C). Agradient of increasing numbers of species andindividuals exists between the South Bay andCentral Bay. Then, beginning at Red Rock (asandy site) numbers of species remained lowthrough the Northern Estuary to the Sacra-mento River, and then increased slightly intothe Delta (Figure 19). Contrary to the 1994results, numbers of species in 1995 were higherat Yerba Buena Island (BC11) than at theCCSF and EBMUD outfalls. There was noobvious seasonal or annual trend in numbers ofspecies, as numbers of species were similar tothose sampled in 1994.

Average abundances (number of individu-als) were highest (~ 375,000 per square meter)at the EBMUD outfall stations in the Augustsamples. These very high abundances were dueto the occurrence of the amphipod Corophiumacherusicum. This species was absent or rare inprevious years and in February 1995. Theyimmigrated or recruited at most South andCentral Bay sites (Redwood Creek to YerbaBuena Island and EBMUD) in August 1995possibly in response to the very wet winter of1995. The lowest abundances were at the sandystations.

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Number of Species

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Figure 19. Mean numbers of species, number of individuals, and biomass per samplecollected in February (wet) and August (dry) sampling periods in 1995. Biomass was notmeasured at the DWR stations.

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121

Benthic biomass was highest at YerbaBuena Island (BC11) and EBMUD outfallstations due to the presence of very largenumbers of amphipods described above. Biom-ass was also elevated at Redwood Creek (BA41)and Davis Point (BD41) due to the presence ofthe clam Potamocorbula amurensis. Biomasswas elevated at Alameda (BB70) in August1995 due to presence of the tunicate Molgula.Biomass was not measured by DWR.

Discussion and Conclusions

Indicators of reference conditions (Table 5)were observed at all stations except for RedRock (BC60) where they may not occur due tosandy conditions. Instead, it may be necessaryto recognize the species there as “normal” forthose conditions. Sandy sediments also havenaturally reduced numbers of species andabundances because of the dynamic nature ofthat environment. Therefore, reduced diversityand/or abundances cannot be used as anindicator of contamination at such sites. Ophi-uroids and amphipods occurred in the CentralBay assemblage and amphipods occurred in theEstuarine and the Delta and Rivers assem-blages; amphipods often dominated thoseassemblages.

Indicators of contamination occurred atsome sites. In the Delta and Rivers assemblage,the oligochaete Limnodrilus sp. and the midgeChironomus sp. occurred suggesting somedegree of impact. Further, the reduced diversityat the Grizzly Bay (D7) site may indicate somedegree of impact. Alternatively, it may repre-sent a natural response to life in the entrap-ment zone. If the fresh/brackish water assem-blage is impacted, the question then becomeswhat does a “normal” assemblage look like?Further study is warranted. In Castro Cove,the polychaetes Capitella “capitata”, Polydoraligni, and Streblospio benedicti were collected;diversity and abundances generally decreasedalong a gradient into the Cove. Amphipods wereamong the most abundant species at all CastroCove stations, although abundances ofAmpelisca abdita decreased in the Cove(Carney et al., 1994). These observations

suggest that Castro Cove is a moderatelycontaminated area forming a sub-assemblage ofthe estuarine assemblage.

In the Central Bay, the EBMUD and CCSFoutfall stations were inhabited by severalindicators of contamination and several indica-tors of reference conditions, suggesting thatbenthos there are only slightly impacted by theoutfalls. Average abundances of C. “capitata”were higher at those sites in both 1994 and1995 than at the adjacent non-outfall sites.Additionally, the outfall sites had numbers ofspecies and abundances among the highest inthe Estuary, which generally suggest enrich-ment and/or moderate levels of contamination(Pearson and Rosenberg, 1978; Swartz, et al.,1986). However, indicators of reference condi-tions also inhabited those sites.

Based on the 1994 and 1995 Benthic Pilotdata, four major assemblages have been identi-fied for the San Francisco Estuary which aregenerally consistent with benthic patterns inother estuaries (Boesch, 1977). Each assem-blage is characteristic of a range of salinity and/or sediment types. In general, each assemblageis believed to represent the “normal” benthiccondition for their respective salinity andsediment type regime. However, as discussedabove, there is still some uncertainty as towhether the presence of indicators of contami-nation in the Delta and Rivers assemblage infact indicate an impact. Further, within eachassemblage, sub-assemblages or sites containsome indications of contamination. However, inno case were differences strong enough to formdistinct assemblages with completely differentspecies composition, suggesting only slighteffects of contamination. Thus, it is a questionof the degree of effects and just how differentfrom a “reference” condition a site must beconsidered impacted.

In general, no large changes in speciescomposition were observed in any of the assem-blages between 1994 and 1995 data. The mostobvious change was the large influx ofCorophium acherusicum in the Central Bay. Itwas anticipated that some sites would switchfrom one assemblage type to another over time

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in response to seasonal changes in salinities assuggested by Nichols and Pamatmat (1988) andHymanson et al., (1993). It was rather surpris-ing to observe little seasonal or annual changein assemblage composition at DWR’s NorthernEstuary sites. Because of the very wet year in1995, Grizzly Bay was expected to be more likethe fresh/brackish water stations in the wetseason samples. However, that was not ob-served. Instead, the changes at that stationwere more subtle with minor shifts in domi-nance and composition. With only two years ofdata, how the assemblages described hereinmay change over time is still uncertain. Most ofthese assemblages include the Asian clamPotamocorbula amurensis. Although it is not anative species, it is now an established residentand must be included in our definition of“normal” for this Estuary.

Yet to be determined is how non-contami-nant factors influence the abundances of theindicators on Table 5. We need to evaluate howother water year types change the assemblagespresented. Questions about how to interpretimpacts in the Delta and Rivers assemblageneed further investigation. Relationshipsbetween benthic parameters and the range ofenvironmental parameters (contaminants,sediments, salinity, etc.) need to be evaluated.

This analysis is scheduled for the 1996 AnnualReport using three years of Pilot Data. Andfinally, we need to develop an objective way todetermine what is “reference”. The BPTCP hasdeveloped a benthic index that partitionsreference and impacted benthos in southernCalifornia estuaries, and a reference envelopefor marine benthos was developed in southernCalifornia (EPA, 1993a).

Acknowledgments

The authors thank Mr. Harlan Proctor(Environmental Services, DWR), and Ms.Arleen Navarret (Biology Laboratory, City andCounty of San Francisco) who coordinated theirrespective agency’s participation in this study.Samples were sorted under direction of Dr.Donald Weston, University of California,Berkeley. The taxonomists who identified thespecimens were Mr. Wayne Fields(Hydrozoology, Sacramento) for the DWRmaterial, and Michael Kellogg, Kathy Langan-Cranford, Patricia McGregor, and Brian Sak(City and County of San Francisco) for theremaining samples. Ms. Laura Riege(EcoAnalysis, Inc., Ojai) conducted the classifi-cation and ordination analysis. Ms. Sarah Loweand Mr. Ted Daum (SFEI) assisted with dataand reporting.

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Bay Protection and Toxic Cleanup Program:Evaluation of Sediment Reference Sites and Toxicity

Tests in San Francisco BayKaren Taberski, San Francisco Bay Regional Water Quality Control Board

John Hunt, Institute of Marine Sciences, University of California, Santa Cruz

Introduction

In previous studies (Long et al., 1990a;Flegal et al., 1994), attempts have been made toidentify sediment reference sites in San Fran-cisco Bay and other coastal embayments inorder to compare reference site conditions withthose at test sites. In these studies, toxicitytests at reference sites not only exhibitedtoxicity but also a great deal of variability. Oneof the main purposes of the Bay Protection andToxic Cleanup Program (BPTCP) is to identify“toxic hot spots”. In order to identify sites thatmay need remediation, it is important to beable to distinguish between these sites andthose that exhibit optimal ambient conditionsas characterized by reference sites.

The BPTCP recently conducted a studywith the following objectives:

1. To identify and characterize sedimentreference sites in San Francisco Bay,

2. To evaluate appropriate sediment toxicitytest methods for use in San Francisco Bay,

3. To evaluate a statistical method, thereference envelope approach, to distinguishtoxic samples from those characteristic ofambient conditions, and

4. To investigate the use of toxicity identifica-

tion evaluations (TIEs) in determining thecauses of toxicity at sites with both highand low concentrations of anthropogenicchemicals.

Methods

Five sites were selected as potential refer-ence sites to be used in future toxicity assess-ments in San Francisco Bay. These sites aredescribed in Table 7. Sites were selected basedon criteria established in previous studies(EPA, 1986; PTI, 1991; Long et al., 1990b).These criteria were: low concentrations ofanthropogenic chemicals, distance from knownmajor sources of pollution, and natural featuressuch as grain size and total organic carbon thatare similar to test sediments. Sites with finegrain sediment were selected because mostheavily contaminated sites are found in deposi-tional areas with fine grain sediment.

As part of the evaluation of toxicity testsand the reference envelope statistical approach,sites in Tomales Bay and Bolinas Lagoon werealso investigated because they had been previ-ously considered as reference sites and found toexhibit toxicity, although concentrations ofanthropogenic contaminants were low. Inaddition, one sample was collected from each of

Wate r Body Location Latitude Longitude Sampling Date s

San Pablo Bay Tubbs Island 38,06,87N 122,25,16W 4/94, 9/94, 3/95

San Pablo Bay Island #1 38,06,72N 122,19,71W 4/94, 9/94, 3/95

Central SF Bay Paradise Cove 37,53,95N 122,27,86W 4/94, 9/94, 3/95

South SF Bay North Site 37,34,23N 122,08,98W 3/95

South SF Bay South Site 37,32,18N 122,07,16W 3/95

Table 7. Reference sites.

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Figure 20. Overview map of study sites in and near San Francisco Bay. Circles indicatecandidate reference sites; stars indicate contaminated sites or uncontaminated sites that haveexhibited toxicity and were used for comparison.

three sites (Islais Creek, Castro Cove, andClipper Cove) where previous studies hadshown either high toxicity or high levels of toxicchemicals (Long et al., 1988, Flegal et al., 1994,Anderson et al., 1995). Data from these siteswere compared against reference sites. All sitesare shown in Figure 20.

Reference sites in San Pablo Bay and theCentral Bay were sampled during three differ-ent hydrologic conditions. Sites in the SouthBay were sampled only once. Three fieldreplicates were collected at each potentialreference site during each sampling period.Chemical analyses, total organic carbon, and

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125

Figure 21. Schematic illustration of the method for determining the lowertolerance interval bound (edge of the reference envelope) to determinesample toxicity relative to a percentile of the reference site distribution.

grain size analyses were conducted at allpotential reference sites. Benthic communityanalyses were conducted at potential referencesites in San Pablo Bay and the Central Bay. Upto nine toxicity tests were conducted on eachsample from all sites. These tests included thesolid phase amphipod survival test usingEohaustorius and Ampelisca, survival ofEohaustorius in intact cores and in pore water(for TIEs), the larval development test in porewater using the mussel Mytilus and the urchinStrongylocentrotus, the urchin development testat the sediment/water interface, the Neanthesgrowth and survival test and a survival testwith Nebalia, a Leptostracan crustacean. Testswere evaluated for control response acceptabil-ity, laboratory replicate variability, and sensi-tivity.

As mentioned above, one of the primaryobjectives of the BPTCP is the identification ofspecific areas of water or sediment qualityconcern, “toxic hot spots”, where adversebiological impacts are observed in areas with

localized concentrations of pollutants. While itis possible that all of the sediment in SanFrancisco Bay is degraded to some extent,logistical constraints require that efforts befocused on localized areas that are significantlymore toxic than optimal ambient conditionsthat exist at reference sites. In this study weare using a “reference envelope” statisticalapproach to make that distinction. Tolerancelimits can serve as a relative standard againstwhich to compare results from tests at sites ofconcern. One of the major advantages of thisapproach is that it accounts for major variancecomponents, such as variability in time, spaceand among field and laboratory replicates.

Figure 21 illustrates the reference envelopemethod for calculating tolerance limits. In thereference envelope approach, explicit decisionsmust be made regarding the choice of twostatistical parameters, values for “p” and“alpha”. The values chosen will depend on thedegree of certainty necessary in a particularregulatory setting. In Figure 21 a “p” or lower

126


percentile value of 10 was chosen. Tolerancelimits were calculated for all test protocols,with manipulation of “p” and “alpha” values toevaluate the use of the reference envelopetechnique with sediment toxicity data.

In order to investigate the causes of toxicity,TIE protocols were developed for Eohaustorius,and the mussel and urchin larval developmenttests in sediment pore water. TIEs were con-ducted on four sediment samples that exhibitedtoxicity. These samples were from Tomales Bay(Marconi Cove), Islais Creek, China Basin(Mission Creek), and Guadalupe Slough.

Results

Sediment samples from five candidatereference sites in San Francisco Bay were foundto have low concentrations of measured chemi-cals, and to exhibit low toxicity and low vari-ability in space and time. Toxicity tests withAmpelisca and Eohaustorius in homogenizedsediment had acceptable control survival, lowbetween replicate variability, and were capableof resolving differences between sediments fromreference sites and suspected contaminatedsites. Pore water and sediment/water interfacetests with sea urchin embryos met controlacceptability requirements in all tests, had verylow variability, and were sensitive to toxicantsat suspected contaminated sites. However, thesensitivity of the urchin and mussel develop-ment tests to ammonia may limit the use ofthese tests in pore water. The sediment/waterinterface exposure seems to minimize thisproblem and also provides a more environmen-tally relevant test. Tests with Eohaustorius inpore water and in intact cores provided highlyvariable results. Tests with Neanthes andNebalia appeared to be insensitive to sedimentcontaminants at test sites and also did not meetother acceptability criteria.

Data from candidate reference sites havebeen used to calculate reference envelopetolerance limits for each toxicity test. However,the potential effect of temporal and spatial

variability on reference envelope results is stillbeing investigated. Tolerance limits for specifictoxicity tests may need to be recalculated oncethis analysis is complete. Additional data fromscreening surveys is being added to the database to make the calculation of tolerance limitsmore robust.

TIE results indicate that in the samplesfrom Islais Creek and China Basin ammoniaand hydrogen sulfide were partially responsiblefor toxicity in the sea urchin development test.Toxicity remained, however, even after ammoniaand hydrogen sulfide were removed. In theTomales Bay sample, ammonia was partiallyresponsible for toxicity with the same test.However, ammonia seemed to increase signifi-cantly in stored samples between the timeinitial toxicity screening of the samples wasperformed and the time the TIEs were per-formed (about 1 week). For samples from IslaisCreek, Tomales Bay and Guadalupe Slough,significant toxicity remained even after all ofthe TIE procedures were conducted to removeammonia, hydrogen sulfide, metals and non-polar organics. The remaining toxicity at ChinaBasin degraded after ammonia and hydrogensulfide were removed. Therefore, TIE proce-dures to remove metals and non-polar organicswere not be performed.

The BPTCP is currently screening 95 sitesthroughout the Bay for toxicity. The toxicitytests being conducted are the sea urchin devel-opment test in pore water and at the sediment/water interface and the solid phase amphipodtest using Eohaustorius. Reference sites evalu-ated in the reference site study are beingsampled along with test sites. The referenceenvelope approach, along with others, is beingused to determine if a sample should be consid-ered toxic. Full chemical analysis is beingperformed on samples that exhibit significanttoxicity. PCB and mercury analyses are beingperformed on all samples to identify sedimentsthat may contribute to bioaccumulation of thesechemicals of concern.

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Sediment Monitoring Discussion

Patterns in SedimentContamination in 1995

Despite the very wet year of 1995, thedistributions and concentrations of sedimentcontaminants in the Estuary remained similarto those in previous years. For trace elementsin 1995, there were two patterns: 1) averageconcentrations of As, Cr, Cu, Ni, and Zn werehighest in the Northern Estuary (specifically,Cr, Cu, and Ni were highest at Pinole Point(BD31) in February; 2) average concentrationsof Ag, Cd, Pb, Hg, and Se were highest in theSouth Bay and Southern Sloughs (specifically,Cd, Pb, Ag, and Zn were highest at San Jose (C-3-0) in August). Concentrations of most metals(except As and Cr) were lowest at the coarsesediment stations, usually at Red Rock (BC60);reflecting the influence of sediment type onsediment metals concentrations.

The only consistent seasonal pattern in1995 was that nearly all metal concentrationswere higher in August than in February at bothSouthern Slough stations. These results areprobably related to the very wet winter. How-ever, except for Pb and As, similar trends weregenerally not observed at the Sacramento, SanJoaquin, Napa, or Petaluma River stations.

For trace organics, sediment concentrationswere always higher south of the Golden Gatethan in other parts of the Estuary. Concentra-tions of PCBs and DDTs were lowest at thecoarse sediment stations, but PAH concentra-tions were lowest at the Rivers confluencestations.

Seasonally, PAHs were generally highest inFebruary in the South and Central Bays. PCBswere generally highest in August in the SouthBay, but DDTs were always higher in Augustthan February throughout the Estuary.

Long Term Trends in SedimentContamination 1991–1995

Combining RMP sediment monitoring data1993–1995 allows for examination of trends insediment contaminant concentrations over the

first three years of the RMP. Average concentra-tions were calculated for each Estuary reach foreach of six sampling periods (Figures 22–35).

Trace metals concentrations have remainedrather constant in all reaches and through allthree years with no increasing or decreasingtrends observed (Figures 22–31). In general,differences in means and ranges of concentra-tions were small. Mean As concentrationsappeared to increase slightly in the Rivers. Hgin the Rivers was more variable during thewettest sampling periods (February 1993, 1995)than in the dry sampling periods; concentra-tions in the San Joaquin River increasedconsiderably during high flows. Pb was el-evated in the Rivers in August 1994, and Sewas elevated in the Northern Estuary inAugust 1993. There were no obvious differencesin concentrations related to wet or dry seasonsor years.

For trace organic contaminants, data fromthe State’s Bay Protection and Toxic CleanupProgram (BPTCP) Pilot Monitoring Studies inSan Francisco Estuary, 1991–1992 (Flegal et al.1994), and the RMP data, 1993–1995, werecombined (Figures 32–35). In general, differ-ences in means and ranges of concentrationswere small. There were no observable increas-ing or decreasing trends in PAHs. However,PAH concentrations were elevated in theNorthern Estuary, Central, and South Bays inFebruary 1994. These increases caused manystations to have numerous Effects Range Low(ERL) exceedances (up to 19) that included anumber of individual PAH compounds. Thecause of the elevated PAHs is not known. Thatincrease did not occur at the River stationswhich showed a different pattern of variationwith larger differences between samplingperiods. Average PCB concentrations appear tohave decreased in the River, Northern Estuary,and Central Bay, but the ranges of valuesnearly overlap. This observation corresponds tothe information presented by Risebrough (thisreport). Average DDTs appear to have de-

128


creased in the Rivers, but ranges nearly over-lap. There were no observable differences inother reaches. Average chlordanes have alsodecreased in most Estuary reaches, althoughranges of values in the Northern Estuarygenerally overlap. Beginning in 1994, concen-trations were greatly reduced in the Rivers andCentral Bay, but concentrations remainedvariable in the Northern Estuary and SouthBay.

The trends discussed above should beinterpreted cautiously. Rigorous statisticaltime-series analysis generally requires morethan 6 to 8 samplings. Each year the RMP addstwo more data points which will graduallyimprove our understanding of sediment con-tamination.

Comparisons to SedimentQuality Guidelines

Although the RMP has used ERL and ERMguidelines (Long and Morgan, 1990a; Long, etal., 1995) since 1993, those are not the onlysediment quality guidelines available. The ERLand ERM guidelines are currently the mostwidely used sediment guidelines world-wide.Although not specifically developed for the SanFrancisco Estuary, they do include data fromthe Estuary. One of the recommendations froma recent NOAA sediment quality workshop wasto use information from any and all availableguidelines in sediment assessments (Chapmanet al., in press). Table 8 lists several othernational and west coast guidelines for compari-son. The USGS background values from sedi-ment coring are not actually sediment qualityguidelines per se, but provide valuable contextof historic concentrations in the Estuary. Othersediment guidelines commonly used includethose for Florida (MacDonald, 1993) andfreshwater guidelines from Ontario (Persaud etal., 1992). The San Francisco Bay RegionalWater Quality Control Board is currentlydeveloping Apparent Effects Threshold (AET)values for the Estuary.

A listing of the contaminants above theERL and ERM guidelines at each RMP stationin 1995 is shown on Table 9. As in past years,

nearly all samples had Ni concentrations abovethe ERM. Ni is a natural component of serpen-tine soils abundant in the region, and Niconcentrations in the USGS sediment coreshave been generally constant for centuries.Similar to past years, concentrations of As, Cr,Cu, Hg, Ni, and total DDTs were usually abovethe ERL (Table 9). In 1995, several PAH com-pounds had concentrations above ERLs atAlameda (BB70).

Stations with the most exceedances of ERLsincluded Alameda (BB70) where eight contami-nants exceeded ERL concentrations in Febru-ary and Honker Bay (BF40) with six stationswith the fewest ERL exceedances were thestations with coarse sediments (more sand orgravel): Davis Point (BD41), Pacheco Creek(BF10), Red Rock (BC60), and Sunnyvale (C-1-3) had only one or two ERL exceedances.

Effects of SedimentContamination

The RMP currently uses sediment bioas-says as an indicator of the potential for ecologi-cal effects from contaminated sediments. Otherecological indicators of contamination are beingdeveloped through RMP Pilot and SpecialStudies (summarized below), as well as byother programs (e.g., USGS, BASMAA, BPTCP,and US EPA). It is clear that the RMP needs toinclude a broader range of sediment indicators.Identification of potential new sediment indica-tors was included in the RMP Ecological Indica-tors Workshop held in October 1995 (Thompsonet al., this report). The need for, and selectionof, additional sediment indicators will beconsidered during the RMP five-year programreview in 1997.

The RMP sediment bioassays continued toindicate toxicity at most stations throughoutthe Estuary. Analyses of the first three years ofsediment bioassays (Thompson et al., thisreport) showed that when more than sevencontaminants exceed ERLs at a station, amphi-pod toxicity usually occurs. This suggests thatthe additive effects of low levels of severalcontaminants may be causing the observedtoxicity. However, toxicity to bivalve larvae was

Sediment Monitoring

129

Tab

le 8

. Com

mon

ly u

sed

sed

imen

t q

ual

ity

guid

elin

es.

Par

amet

er

un

itE

PA

*1E

RL

2E

RM

2P

uget

S

ound

A

mph

ipod

A

ET

3P

uget

S

ound

B

ival

ve

AE

T3

Bac

kgro

und

Con

cent

ratio

ns

(Bay

wid

e ra

nges

)4

To

tal

Ars

enic

mg/

kg8

.27

0.

..

Cad

miu

mm

g/kg

1.2

9.6

6.7

9.6

.C

hrom

ium

mg/

kg8

13

70

27

0.

11

0–

17

0C

op

pe

rm

g/k

g3

42

70

13

00

39

02

0–

55

Mer

cury

mg/

kg0

.15

0.7

12

.10

.59

.N

icke

lm

g/kg

20

.95

1.6

..

70

–1

00

Le

ad

mg

/kg

46

.72

18

66

06

60

20

–4

0S

ilver

mg/

kg1

3.7

5.9

0.5

60

.1–

0.1

Zin

cm

g/kg

15

04

10

96

01

60

06

0–

70

high

mol

wt P

AH

sµg

/kg

17

00

96

00

69

00

01

70

00

Flu

oran

then

eµg

/kg

30

06

00

51

00

30

00

02

50

0P

yre

ne

µg/k

g6

65

26

00

16

00

03

30

0B

enzo

(a)a

nthr

acen

eµg

/kg

26

11

60

05

10

01

60

0C

hrys

ene

µg/k

g3

84

28

00

92

00

28

00

Ben

zo(b

,k)f

luor

anth

ene

µg/k

g.

.7

80

03

60

0B

enzo

(a)p

yren

eµg

/kg

43

01

60

03

00

01

60

0D

iben

z(a,

h)an

thra

cene

µg/k

g6

3.4

26

05

40

23

0B

enzo

(g,h

,i)pe

ryle

neµg

/kg

..

14

00

72

0In

deno

(1,2

,3-c

,d)p

yren

eµg

/kg

..

18

00

69

0

low

mol

. wt.

PA

Hs

µg/k

g5

52

31

60

24

00

05

20

02-

Met

hyln

apht

hale

ne7

06

70

..

Nap

htha

lene

µg/k

g1

60

21

00

24

00

21

00

Ace

na

ph

thyl

en

eµg

/kg

44

64

01

30

0.

Ace

na

ph

the

ne

µg/k

g2

30

16

50

02

00

05

00

Flu

ore

ne

µg/k

g1

95

40

36

00

54

0P

he

na

nth

ren

eµg

/kg

24

02

40

15

00

69

00

15

00

Ant

hrac

ene

µg/k

g8

5.3

11

00

13

00

09

60

TO

TA

L P

AH

s4

02

24

47

92

..

DD

Eµg

/kg

..

15

.D

DD

µg/k

g.

.4

3.

DD

Tµg

/kg

..

..

TO

TA

L D

DT

s1

.58

46

.1.

.D

ield

rinµg

/kg

20

..

..

En

dri

nµg

/kg

0.7

6.

..

.T

OT

AL

PC

Bs

µg/k

g2

2.7

18

03

00

01

10

0

* E

xpre

ssed

as

µg/g

org

anic

car

bon.

1

E

PA

—F

eder

al

Sed

imen

t G

uide

lines

F

rom

: EP

A, 1

991

2

ER

L &

ER

M—

Eff

ects

Ran

ge L

ow (

ER

L) a

nd E

ffec

ts R

ange

Med

ian

(ER

M)

F

rom

: Lon

g et

al.,

1

99

5.

3

A

ET

—P

uget

S

ound

A

ppar

ent

Eff

ects

T

hres

hhol

d (A

ET

) va

lues

Fro

m: B

arric

k, R

. et a

l., 1

988.

A

ET

s ar

e va

lues

abo

ve w

hich

sta

tistic

ally

sig

nific

ant (

p<=

0.05

) bi

olog

ical

effe

cts

ar

e al

way

s ob

serv

ed in

dat

a us

ed to

gen

erat

e th

e A

ET

.4

Bac

kgro

und

sedi

men

t co

ncen

trat

ions

for

sel

ecte

d tr

ace

elem

ents

in

US

GS

SF

Bay

sed

imen

t co

res.

F

rom

: Hor

nber

ger

et a

l. (u

npub

lishe

d)

130


Tab

le 9

. Su

mm

ary

of c

onta

min

ants

in

sed

imen

ts t

hat

wer

e ab

ove

sed

imen

t E

ffec

ts R

ange

Low

(E

RL

) an

d E

ffec

ts R

ange

Med

ian

(E

RM

) gu

idel

ines

at

each

199

5 R

MP

sed

imen

t sa

mp

lin

g st

atio

n. W

= W

et s

easo

n (

Feb

ruar

y), D

= D

ry s

easo

n (

Au

gust

), -

= n

otab

ove

guid

elin

e.

ME

TA

LS

ER

LE

RM

Arsenic

Chromium

Copper

Mercury

Nickel

Lead

Nickel

Gu

ide

lin

e8

.28

13

40

.15

20

.94

6.7

51

.6S

tatio

n

Na

me

Co

de

mg

/Kg

mg

/Kg

mg

/Kg

mg

/Kg

mg

/Kg

mg

/Kg

mg

/Kg

Sun

nyva

leC

-1-3

-,--,-

-,--,

DW

,D-,-

W,D

San

Jos

eC

-3-0

-,--,

D-,

D-,

DW

,D-,

DW

,DC

oyot

e C

reek

BA

10

-,D

-,D

-,D

W,D

W,D

-,-W

,DS

outh

Bay

BA

21

-,D

W,D

W,D

W,D

W,D

-,-W

,DD

umba

rton

Brid

geB

A3

0W

,DW

,-W

,DW

,DW

,D-,-

W,D

Red

woo

d C

reek

BA

41

W,D

-,D

W,D

W,D

W,D

-,-W

,DS

an B

runo

Sho

alB

B1

5W

,DW

,-W

,-W

,DW

,D-,-

W,D

Oys

ter

Poi

ntB

B3

0-,

D-,-

W,D

W,D

W,D

-,-W

,DA

lam

eda

BB

70

W,D

W,-

W,D

W,D

W,D

-,-W

,DY

erba

Bue

na Is

land

BC

11

W,D

-,D

-,D

W,D

W,D

-,--,

DH

orse

shoe

Bay

BC

21

W,-

-,--,-

W,-

W,D

-,-W

,DR

icha

rdso

n B

ayB

C3

2W

,D-,-

-,-W

,DW

,D-,-

W,D

Poi

nt Is

abel

BC

41

W,D

W,D

W,D

W,D

W,D

-,-W

,D

Red

Roc

kB

C6

0-,

D-,-

-,--,-

W,D

-,-W

,D

Pet

alum

a R

iver

BD

15

W,D

W,D

W,D

W,D

W,D

-,-W

,D

San

Pab

lo B

ayB

D2

2W

,D-,-

W,D

W,D

W,D

-,-W

,D

Pin

ole

Poi

ntB

D3

1W

,DW

,-W

,DW

,DW

,D-,-

W,D

Dav

is P

oint

BD

41

-,D

-,--,-

-,-W

,D-,-

W,D

Nap

a R

iver

BD

50

W,D

W,D

W,D

W,D

W,D

-,-W

,DP

ache

co C

reek

BF

10

-,D

-,--,-

-,-W

,D-,-

W,D

Griz

zly

Bay

BF

21

W,D

W,-

W,D

W,D

W,D

-,-W

,DH

onke

r B

ayB

F4

0W

,DW

,DW

,DW

,DW

,D-,-

W,D

Sac

ram

ento

Riv

erB

G20

W,D

-,D

-,--,-

W,D

-,-W

,DS

an J

oaqu

in R

iver

BG

30W

,D-,-

W,D

W,D

W,D

-,-W

,D

OR

GA

NIC

SE

RL

Anthracene

Fluorene

Phenanthrene

Sum of DDTs

p,p'-DDE

85

.31

92

40

1.5

82

.2µ

g/K

gµ

g/K

gµ

g/K

gµ

g/K

gµ

g/K

g-,-

-,--,-

-,--,-

-,--,-

-,--,-

-,--,-

-,--,-

-,D

-,D

-,--,-

-,--,

D-,-

-,--,-

-,--,

D-,-

-,--,-

-,--,

D-,-

-,--,-

-,--,

D-,-

-,--,-

-,--,

D-,-

W,-

W,D

W,-

-,D

-,--,-

-,--,-

W,D

-,--,-

-,--,-

W,D

-,--,-

-,--,-

-,D

-,--,-

-,--,-

-,D

-,-

-,--,-

-,--,-

-,--,-

-,--,-

-,--,-

-,--,-

-,--,

D-,-

-,--,-

-,--,

D-,-

-,--,-

-,--,-

-,--,-

-,--,-

-,D

-,--,-

-,--,-

-,--,-

-,--,-

-,--,

D-,-

-,--,-

-,-W

,D-,-

-,--,-

-,--,-

-,--,-

-,--,-

-,--,-

Sediment Monitoring

131

not related to the ERLs which are based onbulk chemistry measurements. The bivalvebioassay provides different information aboutsediment toxicity than the amphipod test, andthe RMP needs to find better ways to interpretthat information.

The RMP Special Studies on the develop-ment of bioassays using the resident amphipodAmpelisca abdita showed that it is equally ormore sensitive to contamination than otheramphipods commonly used in bioassays(Weston, this report). Results of the compari-sons of sensitivity between sublethal growthendpoints and acute mortality depended onwhich toxicant was used in the exposure. SinceA. abdita is numerically dominant at manyRMP benthic stations and can be used incontrolled sediment bioassays, they could be apowerful indicator for the RMP in the quest forunderstanding sediment contaminant effects.

The RMP Benthic Pilot Study (Thompson,et al., this report) showed that it may be pos-sible to identify normal, or “reference” benthicassemblages for specific Estuary salinity andsediment types. This knowledge will be usefulfor comparisons to sites where the benthos maybe degraded due to contamination or other

factors. Only minor benthic impacts wereobserved near some outfalls in Central Bay.Indicators of contamination were also observedin Castro Cove and possibly in the brackishwater benthos of the Northern Estuary. Withonly two years of Pilot data, these conclusionsshould be considered preliminary.

The State’s BPTCP has also worked on theidentification of sediment reference sites in theEstuary for comparisons to toxic “hot spots”.(Taberski and Hunt, this report). Their ap-proach is based on comparisons of impacted and“reference” sediments using information aboutsediment chemistry, toxicity, and benthos (thesediment quality triad). Together with RMPdata, a detailed understanding of Estuarysediments is being developed.

In summary, the RMP and other studies areincreasing our understanding of contaminatedsediments and their possible ecological effects.Based on the number of stations with sedimentconcentrations above the ERLs or ERMs,sediment bioassays, and benthic studies pre-sented in this report, contaminants in sedi-ments at some of the RMP stations are toxic,but in general, benthic assemblages appearmostly unimpacted.

132


Arsenic, mg/kg Cadmium, mg/kg

Figures 22–23. Plots of average arsenic and cadmium concentrations (parts per million,ppm) in sediments in each Estuary reach in 1993–1995. The vertical bars represent ranges ofvalues. Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4, Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2,1994–1995 n=3; Rivers 1993–1995 n=2.

3/93

9/93

2/94

8/94

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05

1015202530

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0.00.20.40.60.81.0

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1015202530

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3/93

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05

1015202530

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Sediment Monitoring

133

Copper, mg/kg3/

93

9/93

2/94

8/94

2/95

8/95

0306090

120150

Rivers

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0

20

40

60

80Rivers

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120150

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80Central Bay

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120150


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20

40

60

80Coarse Sediment Stations

Figures 24–25. Plots of average chromium and copper concentrations (parts per million,ppm) in sediments in each Estuary reach in 1993–1995. The vertical bars represent ranges ofvalues. Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4, Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2,1994–1995 n=3; Rivers 1993–1995 n=2.

Chromium, mg/kg

134


Lead, mg/kg Mercury, mg/kg3/

93

9/93

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01020304050

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01020304050


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Figures 26–27. Plots of average lead and mercury concentrations (parts per million, ppm)in sediments in each Estuary reach in 1993–1995. The vertical bars represent ranges of values.Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4,Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2, 1994–1995n=3; Rivers 1993–1995 n=2.

Sediment Monitoring

135

Selenium, mg/kg3/

93

9/93

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1.0

1.5

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1.0

1.5

2.0Northern Estuary

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1.0

1.5

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8/95

0.0

0.5

1.0

1.5

2.0Coarse Sediment Stations

Figures 28–29. Plots of average nickel and selenium concentrations (parts per million,ppm) in sediments in each Estuary reach in 1993–1995. The vertical bars represent ranges ofvalues. Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4, Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2,1994–1995 n=3; Rivers 1993–1995 n=2.

Nickel, mg/kg

136


Silver, mg/kg3/

93

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04080

120160200


Figures 30–31. Plots of average silver and zinc concentrations (parts per million, ppm) insediments in each Estuary reach in 1993–1995. The vertical bars represent ranges of values.Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4,Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2, 1994–1995n=3; Rivers 1993–1995 n=2.

Zinc, mg/kg

Sediment Monitoring

137

PAHs, µg/kg PCBs, µg/kg

Figure 32–33. Plots of average PAH and PCB concentrations (parts per billion, ppb) insediments in each Estuary reach in 1993-1995. The vertical bars represent ranges of values.Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4,Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2, 1994–1995n=3; Rivers 1993-1995 n=2. * indicates different scale

3/93

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200

400

600

800Rivers *

3/93

9/93

2/94

8/94

2/95

8/95

0123456

Rivers *

3/93

9/93

2/94

8/94

2/95

8/95

0

2000

4000

6000

8000Northern Estuary

3/93

9/93

2/94

8/94

2/95

8/95

0

15

30

45

60Northern Estuary

3/93

9/93

2/94

8/94

2/95

8/95

0

2000

4000

6000

8000Central Bay

3/93

9/93

2/94

8/94

2/95

8/95

0

15

30

45

60Central Bay

3/93

9/93

2/94

8/94

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0

2000

4000

6000

8000South Bay

3/93

9/93

2/94

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8/95

0

15

30

45

60South Bay

3/93

9/93

2/94

8/94

2/95

8/95

0

200

400

600

800Coarse Sediment Stations *

3/93

9/93

2/94

8/94

2/95

8/95

0123456

Coarse Sediment Stations *

138


DDTs, µg/kg Chlordanes, µg/kg3/

93

9/93

2/94

8/94

2/95

8/95

02468

10Rivers

3/93

9/93

2/94

8/94

2/95

8/95

0.0

0.5

1.0

1.5

2.0Rivers

3/93

9/93

2/94

8/94

2/95

8/95

02468

10Northern Estuary

3/93

9/93

2/94

8/94

2/95

8/95

0.0

0.5

1.0

1.5

2.0Northern Estuary

3/93

9/93

2/94

8/94

2/95

8/95

0

10

20

30Central Bay *

3/93

9/93

2/94

8/94

2/95

8/95

0.0

0.5

1.0

1.5

2.0Central Bay

3/93

9/93

2/94

8/94

2/95

8/95

02468

10South Bay

3/93

9/93

2/94

8/94

2/95

8/95

0.0

1.0

2.0

3.0

4.0South Bay *

3/93

9/93

2/94

8/94

2/95

8/95

02468

10Coarse Sediment Stations

3/93

9/93

2/94

8/94

2/95

8/95

0.0

0.5

1.0

1.5

2.0Coarse Sediment Stations

Figure 34–35. Plots of average DDT and chlordane concentrations (parts per billion, ppb)in sediments in each Estuary reach in 1993-1995. The vertical bars represent ranges of values.Sample sizes are as follows: South Bay, 1993 n=4, 1994 n=6, 1995 n=7; Central Bay, 1993–1995 n=4,Northern Estuary, 1993 n=4, 1994 n=5, 1995 n=6; coarse sediment stations,1993 n=2, 1994–1995n=3; Rivers 1993-1995 n=2. * indicates different scale

Bivalve Monitoring

139

CHAPTER FOUR

Bivalve Monitoring

140


Background

It has long been known that bivalves willaccumulate contaminants in concentrationsmuch greater than those found in ambientwater (Vinogradov, 1959). This phenomenonresults from the difference between the con-taminant-specific kinetics of uptake and depu-ration associated with the limited ability ofbivalves to regulate the concentrations of mostcontaminants in their tissues. This method ofactive bio-monitoring has been widely appliedby the California State Mussel Watch Program(Phillips, 1988; Rasmussen, 1994) and others(Young et al., 1976; Wu and Levings, 1980;Hummel et al., 1990; Martincic et al., 1992).Bioaccumulation of contaminants, however,does not necessarily imply that toxic effectsexist. The combined measurements of tracecontaminants in Estuary water, sediment, andtissue allow for investigation of quantitativerelationships between contaminants in the SanFrancisco Estuary and contaminant uptake byorganisms living in the Estuary.

Bivalves were collected from sites thoughtto be uncontaminated and transplanted to 15stations in the Estuary during the wet season(February through May) and the dry season(June through September) (Figure 1 in ChapterOne: Introduction). Sampling dates are listed inTable 1 in Chapter One: Introduction. Contami-nant concentrations in tissues, survival, andbiological condition were measured beforedeployment (referred to as time zero (T-0) orbackground) and at the end of the 90–100 daydeployment period. Composites of tissue weremade from T-0 organisms and from survivingorganisms from each deployment site (up to 45individuals) for analyses of trace contaminants.The condition of animals at control sites atLake Isabella (Corbicula fluminea), BodegaHead (Mytilus californianus), Tomales Bay, andDabob Bay, Washington (Crassostrea gigas) wasalso determined at the end of each deploymentperiod in order to sort out Estuary effects fromnatural factors affecting bivalve condition.

The effects of high short-term flows offreshwater on the transplanted bivalves west of

Carquinez Strait were minimized by deployingthe bivalves near the bottom where densitygradients tend to maintain higher salinities. Allbivalves were kept on ice after collection anddeployed within 72 hours. Multiple specieswere deployed at several stations due to uncer-tain salinity regimes and tolerances. Detailedmethods are included in Appendix A. Data aretabulated in Appendix C.

Guidelines: Maximum TissueResidue Levels (MTRLs)

In the following figures, tissue concentra-tions of various trace contaminants are com-pared to Maximum Tissue Residue Levels(MTRLs), as used to evaluate data from theCalifornia State Mussel Watch Program(Rasmussen, 1994). MTRLs were developed bythe State Water Resources Control Board andare used as alert levels indicating water bodieswith potential human health concerns. MTRLsare only an assessment tool and not used ascompliance or enforcement criteria. Since noregulatory tissue standards for trace metal andorganic contaminants exist in the UnitedStates, comparisons to these guidelines serveonly as a relative yard stick.

Tissue guidelines are expressed in ppm wetweight, while the RMP tissue data are pre-sented as ppm dry weight. A wet-to-dry weightconversion factor of 7, based on an average of85% moisture content in bivalves, was appliedfor comparisons.

Accumulation Factors

In addition to using the absolute tissueconcentrations at the end of each deploymentperiod and comparing them to initial tissueconcentrations prior to transplanting thebivalves to the Estuary (T-0), this report usesaccumulation factors (AFs) to indicate thedegree of accumulation or depuration (loss ofconstituents from bivalve tissue) during the 90–100 day deployment period. The AF is calcu-lated by dividing the contaminant concentra-tion in transplants by the initial bivalveconcentration at T-0. For example, an AF of 1.0indicates that the concentration of a specific

Bivalve Monitoring

141

contaminant remained the same during thedeployment period compared to the initialcontaminant level. An AF of 0.5 indicates thatthe bivalve sample lost 50% of the contaminantconcentration during the deployment period,while an AF above 1 indicates accumulation.

Biological Condition andSurvival

The biological condition (expressed as theratio of dry tissue weight to shell cavity vol-

ume) and survival rates of transplanted bi-valves following exposure to Estuary water isevidence that the animals were capable ofbioaccumulation at most sites.

Overall, the goal of obtaining enough tissuefor contaminant and condition determinationwas achieved in 1995, with complete retrievalof all deployed bags at the 15 sites after thewet-season deployment. During the dry season,one of the moorings with bivalves was lost atthe San Pablo Bay site (BD20).

142


05

10

15

20

25

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

012

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

1. A

rsen

ic c

once

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

Pst

atio

ns

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. T

-0 (

tim

e ze

ro)

indi

cate

s th

e in

itia

lco

nce

ntr

atio

ns

of a

rsen

ic m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

e E

stu

ary.

Acc

um

ula

tion

fac

tors

at

all s

tati

ons

wer

e be

low

2. A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.55,

indi

cati

ng

depu

rati

on, t

o 1.

80, a

nd

aver

aged

hig

hes

t in

the

Riv

ers.

Tis

sue

con

cen

trat

ion

s th

rou

ghou

t th

e E

stu

ary

wer

e ge

ner

ally

hig

her

du

rin

g th

e dr

y se

ason

th

an t

he

wet

sea

son

. Cla

ms c

onsi

sten

tly

accu

mu

late

d h

igh

er a

rsen

ic c

once

ntr

atio

ns

than

mu

ssel

s or

oys

ters

. All

sta

tion

s, in

clu

din

g th

e re

fere

nce

sit

e (T

-0),

for

wh

ich

MT

RL

s ar

eap

plic

able

, wer

e h

igh

er t

han

th

e gu

idel

ine

of 1

.4 m

g/kg

. Du

e to

a lo

st m

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(BD

20).

Du

e to

0%

su

rviv

al, M

. cal

ifor

nia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

e P

oin

t (B

D30

).

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Ars

enic

in T

rans

plan

ted

Biv

alve

s 19

95Arsenic, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Bivalve Monitoring

143

0123456

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

05

10

15

20

25

30

35

40

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

2. C

adm

ium

con

cen

trat

ion

s in

par

ts p

er m

illi

on d

ry w

eigh

t (p

pm

) in

th

ree

spec

ies

of t

ran

spla

nte

d b

ival

ves

at 1

5 R

MP

stat

ion

s d

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial c

once

ntr

atio

ns

of c

adm

ium

mea

sure

d on

a s

ubs

ampl

e of

eac

h s

peci

es t

aken

fro

m t

he

refe

ren

ce lo

cati

ons

at t

he

tim

e of

dep

loym

ent

in t

he

Est

uar

y. A

ccu

mu

lati

onfa

ctor

s w

ere

> 2

at

the

Nor

ther

n E

stu

ary

stat

ion

s w

her

e C

. gig

as w

ere

depl

oyed

du

rin

g th

e w

et s

easo

n a

nd

at t

he

C. g

igas

sta

tion

in t

he

Sou

thB

ay d

uri

ng

the

dry

seas

on. A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.25,

indi

cati

ng

depu

rati

on, t

o 5.

48. D

uri

ng

the

wet

sea

son

, bot

h M

ytil

us

and

Cor

bicu

la d

epu

rate

cad

miu

m a

nd

duri

ng

the

dry

seas

on t

hey

acc

um

ula

te c

adm

ium

. Oys

ters

acc

um

ula

ted

hig

her

con

cen

trat

ion

s an

d h

ad h

igh

erac

cum

ula

tion

fac

tors

th

an m

uss

els

and

clam

s. T

he

hig

hes

t co

nce

ntr

atio

n in

oys

ters

occ

urr

ed a

t N

apa

Riv

er (

BD

50).

All

fre

shw

ater

sta

tion

s h

adti

ssu

e co

nce

ntr

atio

ns

mu

ch lo

wer

th

an t

he

appl

icab

le t

issu

e re

sidu

e le

vel o

f 4.

48 m

g/kg

. Du

e to

a lo

st m

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

ew

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

% s

urv

ival

, M. c

alif

orn

ian

us

was

not

an

alyz

ed in

th

e dr

y se

ason

at

Pin

ole

Poi

nt

(BD

30).

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Cad

miu

m in

Tra

nspl

ante

d B

ival

ves

1995

Cadmium, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

144


02468

10

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

0

10

20

30

40

50

60

70

80

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

3. C

hro

miu

m c

once

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

Pst

atio

ns

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. T

-0 (

tim

e ze

ro)

indi

cate

s th

e in

itia

lco

nce

ntr

atio

ns

of c

hro

miu

m m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

eE

stu

ary.

Con

trol

mu

ssel

s in

th

e w

et s

easo

n h

ad u

nu

sual

ly h

igh

con

cen

trat

ion

s. T

her

e ar

e n

o M

TR

L g

uid

elin

es f

or t

his

com

pou

nd.

Du

e to

a lo

stm

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

% s

urv

ival

, M. c

alif

orn

ian

us

was

not

an

alyz

ed in

th

e dr

yse

ason

at

Pin

ole

Poi

nt

(BD

30).S

outh

Bay

Cen

tral

Bay

Nor

ther

n E

stua

ryR

iver

s

Chr

omiu

m in

Tra

nspl

ante

d B

ival

ves

1995

Chromium, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Bivalve Monitoring

145

02468

10

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

0

10

0

20

0

30

0

40

0

50

0

60

0

70

0

80

0

90

0

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

4. C

opp

er c

once

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

Pst

atio

ns

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. T

-0 (

tim

e ze

ro)

indi

cate

s th

e in

itia

lco

nce

ntr

atio

ns

of c

oppe

r m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

e E

stu

ary.

Acc

um

ula

tion

fac

tors

wer

e >

2 a

t al

l sta

tion

s w

her

e C

. gig

as w

ere

depl

oyed

du

rin

g th

e dr

y se

ason

. Acc

um

ula

tion

fac

tors

ran

ged

from

0.3

8,in

dica

tin

g de

pura

tion

, to

8.21

. Oys

ters

had

su

bsta

nti

ally

hig

her

acc

um

ula

tion

fac

tors

an

d co

nce

ntr

atio

ns

than

cla

ms

and

mu

ssel

s.C

once

ntr

atio

ns

in o

yste

rs w

ere

con

sist

entl

y h

igh

in t

he

dry

seas

on. T

her

e ar

e n

o M

TR

L g

uid

elin

es f

or t

his

com

pou

nd.

Du

e to

a lo

st m

oori

ng,

C.

giga

s w

as n

ot a

nal

yzed

in t

he

wet

sea

son

at

San

Pab

lo B

ay (

BD

20).

Du

e to

0%

su

rviv

al, M

. cal

ifor

nia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

tP

inol

e P

oin

t (B

D30

).

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Cop

per

in T

rans

plan

ted

Biv

alve

s 19

95Copper, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

146


012345678

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

5. L

ead

con

cen

trat

ion

s in

par

ts p

er m

illi

on d

ry w

eigh

t (p

pm

) in

th

ree

spec

ies

of t

ran

spla

nte

d b

ival

ves

at 1

5 R

MP

sta

tion

sd

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial c

once

ntr

atio

ns

of le

adm

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

e E

stu

ary.

Acc

um

ula

tion

fac

tors

wer

e>

2 a

t al

l sta

tion

s w

her

e C

. gig

as w

ere

depl

oyed

du

rin

g th

e dr

y se

ason

. Acc

um

ula

tion

fac

tors

ran

ged

from

0.3

0, in

dica

tin

g de

pura

tion

, to

7.76

.M

uss

els

exh

ibit

ed h

igh

er c

once

ntr

atio

ns

than

oys

ters

an

d cl

ams,

esp

ecia

lly

in t

he

dry

seas

on. O

yste

rs, h

owev

er, g

ener

ally

had

the

hig

hes

tac

cum

ula

tion

fac

tors

. Th

ere

are

no

MT

RL

gu

idel

ines

for

th

is c

ompo

un

d. D

ue

to a

lost

moo

rin

g, C

. gig

as w

as n

ot a

nal

yzed

in t

he

wet

sea

son

at

San

Pab

lo B

ay (

BD

20).

Du

e to

0%

su

rviv

al, M

. cal

ifor

nia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

e P

oin

t (B

D30

).

0.0

0.5

1.0

1.5

2.0

2.5

3.0

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Lead

in T

rans

plan

ted

Biv

alve

s 19

95Lead, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Bivalve Monitoring

147

0.0

0.5

1.0

1.5

2.0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

6. M

ercu

ry c

once

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

Pst

atio

ns

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. T

-0 (

tim

e ze

ro)

indi

cate

s th

e in

itia

lco

nce

ntr

atio

ns

of m

ercu

ry m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

e E

stu

ary.

Acc

um

ula

tion

fac

tors

at

all s

tati

ons

wer

e be

low

2 w

ith

th

e h

igh

est

valu

es f

oun

d in

C. f

lum

inea

at

the

Riv

er s

tati

ons

and

at G

rizz

ly B

ay (

BF

20)

duri

ng

the

dry

seas

on. A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.57,

indi

cati

ng

depu

rati

on, t

o 1.

81. C

lam

s h

ad t

he

hig

hes

t av

erag

e ac

cum

ula

tion

fact

ors,

fol

low

ed b

y oy

ster

s an

d m

uss

els.

Con

cen

trat

ion

s in

th

e th

ree

spec

ies

wer

e si

mil

ar. D

ry s

easo

n c

once

ntr

atio

ns

wer

e h

ighe

r th

an w

etse

ason

con

cen

trat

ion

s at

mos

t st

atio

ns.

All

sta

tion

s h

ad t

issu

e co

nce

ntr

atio

ns

mu

ch lo

wer

th

an t

he

Max

imu

m T

issu

e R

esid

ue

Lev

el of

7 p

pm d

ryw

eigh

t du

rin

g bo

th s

easo

ns.

Du

e to

a lo

st m

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

% s

urv

ival

, M.

cali

forn

ian

us

was

not

an

alyz

ed in

th

e dr

y se

ason

at

Pin

ole

Poi

nt

(BD

30).

0.0

0

0.0

5

0.1

0

0.1

5

0.2

0

0.2

5

0.3

0

0.3

5

0.4

0

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Mer

cury

in T

rans

plan

ted

Biv

alve

s 19

95Mercury, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

148


0123456789

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

0

10

20

30

40

50

60

70

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Nic

kel i

n Tr

ansp

lant

ed B

ival

ves

1995

Nickel, mg/kg dry weight Accumulation factor

Fig

ure

7. N

ick

el c

once

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

Pst

atio

ns

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. T

-0 (

tim

e ze

ro)

indi

cate

s th

e in

itia

lco

nce

ntr

atio

ns

of n

icke

l mea

sure

d on

a s

ubs

ampl

e of

eac

h s

peci

es t

aken

fro

m t

he

refe

ren

ce lo

cati

ons

at t

he

tim

e of

dep

loym

ent

in t

he

Est

uar

y.A

ccu

mu

lati

on f

acto

rs w

ere

> 2

du

rin

g th

e dr

y se

ason

at

man

y st

atio

ns

in t

he

Nor

ther

n E

stu

ary

and

in t

he

Sou

th B

ay. T

he

Nap

a R

iver

sta

tion

(BD

50)

show

ed a

ccu

mu

lati

on f

acto

rs >

2 d

uri

ng

both

sea

son

s. A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.30,

indi

cati

ng

depu

rati

on, t

o 8.

54. A

lth

ough

the

hig

hes

t co

nce

ntr

atio

n o

ccu

rred

in o

yste

rs a

t th

e N

apa

Riv

er in

th

e w

et s

easo

n, m

uss

els

had

th

e h

igh

est

aver

age

con

cen

trat

ions

amon

g th

eth

ree

spec

ies.

Con

trol

mu

ssel

s in

th

e w

et s

easo

n h

ad u

nu

sual

ly h

igh

con

cen

trat

ion

s. A

ll s

tati

ons,

incl

udi

ng

the

refe

ren

ce s

tatio

ns,

sh

owed

tis

sue

con

cen

trat

ion

s m

uch

low

er t

han

th

e M

axim

um

Tis

sue

Res

idu

e L

evel

(M

TR

L)

of 1

,540

ppm

dry

wei

ght

in s

altw

ater

an

d 19

6 pp

m in

fre

shw

ater

duri

ng

both

sea

son

s. D

ue

to a

lost

moo

rin

g, C

. gig

as w

as n

ot a

nal

yzed

in t

he

wet

sea

son

at

San

Pab

lo B

ay (

BD

20).

Du

e to

0%

su

rviv

al, M

.ca

lifo

rnia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

e P

oin

t (B

D30

).

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Bivalve Monitoring

149

012345

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

02468

10

12

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

8. S

elen

ium

con

cen

trat

ion

s in

par

ts p

er m

illi

on d

ry w

eigh

t (p

pm

) in

th

ree

spec

ies

of t

ran

spla

nte

d b

ival

ves

at 1

5 R

MP

stat

ion

s d

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial

con

cen

trat

ion

s of

sel

eniu

m m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

e E

stu

ary.

Acc

um

ula

tion

fac

tors

wer

e >

2 a

t al

l sta

tion

s w

her

e C

. gig

as w

ere

depl

oyed

du

rin

g th

e w

et s

easo

n a

nd

at C

oyot

e C

reek

(B

A10

) an

d P

etal

um

aR

iver

(B

D15

), b

oth

C. g

igas

sta

tion

s, d

uri

ng

the

dry

seas

on. A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.53,

indi

cati

ng

depu

rati

on, t

o 4.

11. O

yste

rs h

adpo

siti

ve a

ccu

mu

lati

on f

acto

rs a

nd

the

hig

hes

t co

nce

ntr

atio

ns

amon

g th

e th

ree

spec

ies.

Mu

ssel

s h

ad in

term

edia

te c

once

ntr

atio

ns

but

on a

vera

gesh

owed

dep

ura

tion

in t

he

Est

uar

y. C

lam

s h

ad lo

w c

once

ntr

atio

ns

and

slig

htl

y po

siti

ve a

ccu

mu

lati

on f

acto

rs. T

her

e ar

e n

o M

TR

L g

uide

lin

es f

orse

len

ium

. Du

e to

a lo

st m

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

% s

urv

ival

, M. c

alif

orn

ian

us

was

not

an

alyz

ed in

th

e dr

y se

ason

at

Pin

ole

Poi

nt

(BD

30).

Sou

th B

ayC

entr

al B

ayR

iver

s

Sel

eniu

m in

Tra

nspl

ante

d B

ival

ves

1995

Selenium, mg/kg dry weight Accumulation factor

Nor

ther

n E

stua

ry

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

150


01234567

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

012345

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

9. S

ilve

r co

nce

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

P s

tati

ons

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. T

-0 (

tim

e ze

ro)

indi

cate

s th

e in

itia

l con

cen

trat

ion

s of

sil

ver

mea

sure

d on

a s

ubs

ampl

e of

eac

h s

peci

es t

aken

fro

m t

he

refe

ren

ce lo

cati

ons

at t

he

tim

e of

dep

loym

ent

in t

he

Est

uar

y. A

ccu

mu

latio

n f

acto

rs w

ere

> 2

du

rin

g th

e dr

y se

ason

at

all s

tati

ons

wit

h t

he

exce

ptio

n o

f on

e st

atio

n f

or e

ach

dep

loye

d sp

ecie

s: M

. cal

ifor

nia

nu

s at

Red

Roc

k (B

C60

), C

.gi

gas

at C

oyot

e C

reek

(B

A10

), a

nd

C. f

lum

inea

at

Gri

zzly

Bay

(B

F20

). A

ccu

mu

lati

on f

acto

rs w

ere

belo

w 2

du

rin

g th

e w

et s

easo

n e

xcep

t fo

r th

eP

etal

um

a R

iver

sta

tion

(B

D15

). A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.66,

indi

cati

ng

depu

rati

on, t

o 4.

89. S

ilve

r co

nce

ntr

atio

ns

in oy

ster

s w

ere

con

side

rabl

y h

igh

er t

han

in m

uss

els

or c

lam

s, b

ut

not

mu

ch g

reat

er t

han

th

e T-

0 co

ntr

ols.

Mu

ssel

s h

ad t

he

hig

hes

t av

erag

e ac

cum

ula

tion

fac

tors

,bu

t di

d n

ot a

ccu

mu

late

hig

h c

once

ntr

atio

ns

rela

tive

to

oyst

ers.

Th

ere

are

no

MT

RL

gu

idel

ines

for

th

is c

ompo

un

d. D

ue

to a

lost

moo

rin

g, C

. gig

asw

as n

ot a

nal

yzed

in t

he

wet

sea

son

at

San

Pab

lo B

ay (

BD

20).

Du

e to

0%

su

rviv

al, M

. cal

ifor

nia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

eP

oin

t (B

D30

).

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Silver, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Silv

er in

Tra

nspl

ante

d B

ival

ves

1995

Bivalve Monitoring

151

051

01

52

02

53

03

54

04

55

0

BA10

BA30

BA40

BB71

BC10

BC21

BC61

BD15

BD20

BD30

BD40

BD50

0.0

0

0.0

2

0.0

4

0.0

6

0.0

8

0.1

0

0.1

2

0.1

4

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC61

BD15

BD20

BD30

BD40

BD50

Fig

ure

10.

Tri

bu

tylt

in (

TB

T)

con

cen

trat

ion

s, e

xpre

ssed

in

ter

ms

of t

otal

tin

(S

n)

(pp

m d

ry w

eigh

t), i

n t

hre

e sp

ecie

s of

tran

spla

nte

d b

ival

ves

at 1

5 R

MP

sta

tion

s d

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

★ in

dica

tes

not

det

ecte

d. W

her

e th

e T-

0 co

nce

ntr

atio

n w

as n

ot d

etec

ted,

th

e M

DL

was

use

d to

cal

cula

ted

the

accu

mu

lati

on f

acto

r. T

-0 (

tim

e ze

ro)

indi

cate

sth

e in

itia

l con

cen

trat

ion

s of

tri

buty

ltin

mea

sure

d on

a s

ubs

ampl

e of

eac

h s

peci

es t

aken

fro

m t

he

refe

ren

ce lo

cati

ons

at t

he

tim

e of

dep

loym

ent

inth

e E

stu

ary.

Th

ere

are

no

MT

RL

gu

idel

ines

for

th

is c

ompo

un

d. D

ue

to a

lost

moo

rin

g, C

. gig

as w

as n

ot a

nal

yzed

in t

he

wet

sea

son

at

San

Pab

loB

ay (

BD

20).

Du

e to

0%

su

rviv

al, M

. cal

ifor

nia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

e P

oin

t (B

D30

). A

ccu

mu

lati

on f

acto

rs a

re c

alcu

late

dfo

r C

. flu

min

ea d

uri

ng

the

dry

seas

on a

nd

M. c

alif

orn

ian

us

duri

ng

the

wet

sea

son

usi

ng

the

met

hod

det

ecti

on li

mit

(0.

031

and

0.00

2 pp

bre

spec

tive

ly),

as

the

init

ial T

-0 c

oncn

etra

tion

s w

ere

belo

w t

he

dete

ctio

n li

mit

.

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

TB

T in

Tra

nspl

ante

d B

ival

ves

1995

TBT, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

★★

152


012345

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

11.

Zin

c co

nce

ntr

atio

ns

in p

arts

per

mil

lion

dry

wei

ght

(pp

m)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

Pst

atio

ns

du

rin

g th

e w

et (

Jan

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial

con

cen

trat

ion

s of

zin

c m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

the

Est

uar

y.A

ccu

mu

lati

on f

acto

rs w

ere

> 2

at

all s

tati

ons

wh

ere

C. g

igas

wer

e de

ploy

ed d

uri

ng

the

dry

seas

on. A

ccu

mu

lati

on f

acto

rs r

ange

d fr

om 0

.35,

indi

cati

ng

depu

rati

on, t

o 4.

52. O

yste

rs h

ad b

y fa

r th

e h

igh

est

accu

mu

lati

on f

acto

rs a

nd

abso

lute

con

cen

trat

ion

s am

ong

the

thre

e spe

cies

. Th

eh

igh

est

con

cen

trat

ion

was

obs

erve

d at

Coy

ote

Cre

ek (

BA

10)

in t

he

dry

seas

on. T

her

e ar

e n

o M

TR

L g

uid

elin

es f

or t

his

com

pou

nd.

Due

to

a lo

stm

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

% s

urv

ival

, M. c

alif

orn

ian

us

was

not

an

alyz

ed in

th

edr

y se

ason

at

Pin

ole

Poi

nt

(BD

30).

0

50

0

10

00

15

00

20

00

25

00

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Zin

c in

Tra

nspl

ante

d B

ival

ves

1995

Zinc, mg/kg dry weight Accumulation factor

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Bivalve Monitoring

153

02468

10

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Fig

ure

12.

Tot

al P

AH

con

cen

trat

ion

s in

par

ts p

er b

illi

on d

ry w

eigh

t (p

pb

) in

th

ree

spec

ies

of t

ran

spla

nte

d b

ival

ves

at 1

5 R

MP

stat

ion

s d

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial

con

cen

trat

ion

s of

tot

al P

AH

s m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

eE

stu

ary.

Oys

ters

acc

um

ula

ted

the

hig

hes

t m

edia

n c

once

ntr

atio

ns,

cla

ms

wer

e in

term

edia

te, a

nd

mu

ssel

s w

ere

low

est.

Th

e h

igh

est

con

cen

trat

ion

was

mea

sure

d in

oys

ters

at

Pet

alu

ma

Riv

er (

BD

15)

in t

he

wet

sea

son

. Acc

um

ula

tion

fac

tors

wer

e >

2 d

uri

ng

the

dry

seas

on f

or a

ll de

ploy

edsp

ecie

s, a

nd

at a

ll s

tati

ons

wh

ere

C. g

igas

wer

e de

ploy

ed d

uri

ng

the

wet

sea

son

. Acc

um

ula

tion

fac

tors

ran

ged

from

0.8

4, in

dica

tin

g de

pura

tion

,to

8.5

0. A

ll s

tati

ons,

incl

udi

ng

the

refe

ren

ce s

tati

ons,

had

tot

al P

AH

con

cen

trat

ion

s th

at w

ere

hig

her

th

an t

he

MT

RL

of

6.51

ppb

dry

wei

ght

duri

ng

both

sea

son

s. D

ue

to a

lost

moo

rin

g, C

. gig

as w

as n

ot a

nal

yzed

in t

he

wet

sea

son

at

San

Pab

lo B

ay (

BD

20).

Du

e to

0%

su

rviv

al, M

.ca

lifo

rnia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

e P

oin

t (B

D30

).

0

20

0

40

0

60

0

80

0

10

00

12

00

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Tota

l PA

Hs

in T

rans

plan

ted

Biv

alve

s 19

95Total PAHs, µg/kg dry weight Accumulation factor

Riv

ers

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

154


110

100

1000

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

0

50

10

0

15

0

20

0

25

0

30

0

35

0

40

0

45

0

50

0

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Tota

l PC

Bs

in T

rans

plan

ted

Biv

alve

s 19

95

Total PCBs, µg/kg dry weight Accumulation factor

Fig

ure

13.

Tot

al P

CB

con

cen

trat

ion

s in

par

ts p

er b

illi

on d

ry w

eigh

t (p

pb

) in

th

ree

spec

ies

of t

ran

spla

nte

d b

ival

ves

at 1

5 R

MP

stat

ion

s d

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial

con

cen

trat

ion

s of

tot

al P

CB

s m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

eE

stu

ary.

Cla

ms

accu

mu

late

d th

e h

igh

est

med

ian

tot

al P

CB

con

cen

trat

ion

s, o

yste

rs w

ere

inte

rmed

iate

, an

d m

uss

els

wer

e lo

wes

t. T

he h

igh

est

con

cen

trat

ion

was

mea

sure

d in

oys

ters

at

Coy

ote

Cre

ek (

BA

10)

in t

he

wet

sea

son

. Acc

um

ula

tion

fac

tors

wer

e >

2 f

or a

ll d

eplo

yed

spec

ies

duri

ng

both

sea

son

s. A

ll s

tati

ons,

exc

ept

for

the

foll

owin

g re

fere

nce

sta

tion

s (C

. gig

as d

uri

ng

the

wet

sea

son

, C. f

lum

inea

an

d M

. cal

ifor

nia

nu

s du

rin

gth

e dr

y se

ason

) h

ad t

otal

PC

B c

once

ntr

atio

ns

that

wer

e h

igh

er t

han

th

e M

TR

L o

f 15

.4 p

pb d

ry w

eigh

t du

rin

g bo

th s

easo

ns.

Du

e to

a lo

stm

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

% s

urv

ival

, M. c

alif

orn

ian

us

was

not

an

alyz

ed in

th

e dr

yse

ason

at

Pin

ole

Poi

nt

(BD

30).

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Bivalve Monitoring

155

01

02

03

04

05

06

07

0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

0

50

10

0

15

0

20

0

25

0

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Tota

l DD

Ts in

Tra

nspl

ante

d B

ival

ves

1995

Total DDTs, µg/kg dry weight Accumulation factor

Fig

ure

14.

Tot

al D

DT

con

cen

trat

ion

s in

par

ts p

er b

illi

on d

ry w

eigh

t (p

pb

) in

th

ree

spec

ies

of t

ran

spla

nte

d b

ival

ves

at 1

5 R

MP

stat

ion

s d

uri

ng

the

wet

(J

anu

ary–

May

) an

d d

ry (

Ju

ne–

Sep

tem

ber

) sa

mp

lin

g p

erio

ds.

T-0

(ti

me

zero

) in

dica

tes

the

init

ial

con

cen

trat

ion

s of

tot

al D

DT

s m

easu

red

on a

su

bsam

ple

of e

ach

spe

cies

tak

en f

rom

th

e re

fere

nce

loca

tion

s at

th

e ti

me

of d

eplo

ymen

t in

th

eE

stu

ary.

Cla

ms

accu

mu

late

d th

e h

igh

est

med

ian

con

cen

trat

ion

s, o

yste

rs w

ere

inte

rmed

iate

, an

d m

uss

els

wer

e lo

wes

t. C

once

ntr

atio

ns w

ere

rela

tive

ly c

onst

ant

at t

he

stat

ion

s w

her

e cl

ams

wer

e de

ploy

ed. A

ccu

mu

lati

on f

acto

rs w

ere

> 2

at

all s

tati

ons

wh

ere C

. gig

as w

ere

depl

oyed

du

rin

gth

e w

et s

easo

n. A

ccu

mu

lati

on f

acto

rs w

ere

hig

hly

var

iabl

e fo

r oy

ster

s du

e to

th

e u

se o

f tw

o di

ffer

ent

con

trol

sit

es w

ith

ver

y di

ffer

ent

leve

ls o

fco

nta

min

atio

n, a

nd

for

clam

s du

e to

sea

son

al v

aria

tion

in c

once

ntr

atio

ns

at t

he

con

trol

sit

e. T

hre

e st

atio

ns

had

tot

al D

DT

con

cen

trat

ion

s th

atw

ere

hig

her

th

an t

he

MT

RL

for

DD

Ts

of 2

24 p

pb d

ry w

eigh

t du

rin

g th

e w

et s

easo

n.

On

ly o

ne

stat

ion

had

a t

otal

DD

T c

once

ntr

atio

n h

igh

er t

han

the

MT

RL

du

rin

g th

e dr

y se

ason

. Du

e to

a lo

st m

oori

ng,

C. g

igas

was

not

an

alyz

ed in

th

e w

et s

easo

n a

t S

an P

ablo

Bay

(B

D20

). D

ue

to 0

%su

rviv

al, M

. cal

ifor

nia

nu

s w

as n

ot a

nal

yzed

in t

he

dry

seas

on a

t P

inol

e P

oin

t (B

D30

).

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

156


0

20

40

60

80

10

0

12

0

14

0

16

0

T-0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

01234567891

0

BA10

BA30

BA40

BB71

BC10

BC21

BC60

BD15

BD20

BD30

BD40

BD50

40

.4

Sou

th B

ayC

entr

al B

ayN

orth

ern

Est

uary

Riv

ers

Tota

l Chl

orda

nes

in T

rans

plan

ted

Biv

alve

s 19

95

Total Chlordanes, µg/kg dry weight Accumulation factor

★

Cra

ssos

trea

gig

as, w

et s

easo

nC

rass

ostr

ea g

igas

, dry

sea

son

Cor

bicu

la fl

umin

ea, w

et s

easo

n

Cor

bicu

la fl

umin

ea, d

ry s

easo

nM

ytilu

s ca

lifor

nian

us, w

et s

easo

nM

ytilu

s ca

lifor

nian

us, d

ry s

easo

n

Fig

ure

15.

Tot

al c

hlo

rdan

e co

nce

ntr

atio

ns

in p

arts

per

bil

lion

dry

wei

ght

(pp

b)

in t

hre

e sp

ecie

s of

tra

nsp

lan

ted

biv

alve

s at

15

RM

P s

tati

ons

du

rin

g th

e w

et (

Jan

uar

y–M

ay)

and

dry

(J

un

e–S

epte

mb

er)

sam

pli

ng

per

iod

s. ★

in

dica

tes

not

det

ecte

d. T

-0 (t

ime

zero

)in

dica

tes

the

init

ial c

once

ntr

atio

ns

of t

otal

ch

lord

anes

mea

sure

d on

a s

ubs

ampl

e of

eac

h s

peci

es t

aken

fro

m t

he

refe

ren

ce lo

catio

ns

at t

he

tim

e of

depl

oym

ent

in t

he

Est

uar

y. W

her

e th

e T-

0 co

nce

ntr

atio

n w

as n

ot d

etec

ted,

th

e M

DL

was

use

d to

cal

cula

te t

he

accu

mu

lati

on f

acto

r. A

ccu

mu

lati

on f

acto

rsw

ere

> 2

du

rin

g th

e w

et s

easo

n a

t al

l sta

tion

s w

her

e C

. flu

min

ea a

nd

C. g

igas

wer

e de

ploy

ed a

nd

at o

nly

on

e M

. cal

ifor

nia

nu

s st

atio

n (

Du

mba

rton

Bri

dge-

BA

30).

Du

rin

g th

e dr

y se

ason

, acc

um

ula

tion

fac

tors

wer

e >

2 a

t al

l th

e st

atio

ns

wh

ere

C. f

lum

inea

wer

e de

ploy

ed a

nd

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, all

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dry

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Bivalve Monitoring

157

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01

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BA30

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BC60

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BD30

BD40

BD50

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20

25

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35

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16.

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(BD

30).

★★

158


0

10

20

30

40

50

60

70

80

90

100

BA

10

BA

30

BA

40

BB

71

BC

10

BC

21

BC

60

BD

15

BD

20

BD

30

BD

40

BD

50

BF

20

BG

20

BG

30

Crassostrea gigas, wet season Crassostrea gigas, dry seasonCorbicula fluminea, wet season Corbicula fluminea, dry seasonMytilus californianus, wet season Mytilus californianus, dry seasonOstrea lurida, wet season Ostrea lurida, dry season

Figure 17. Percent survival in four species of transplanted bivalves following exposure toEstuary water during the wet (January–May) and dry season (June–September)deployment periods. ★ indicates 0% survival. There were reduced rates of survival during wetseason versus dry season deployments for M. californianus at Dumbarton Bridge (BA30), RedwoodCreek (BA40), Red Rock (BC60) and Pinole Point (BD30). C. fluminea had reduced survival at theSacramento River (BG20) during the wet-season. 1995 was an unusually wet year, which mayexplain the significant differences in survival between the wet and dry season deployments of M.californianus, a species less tolerant of low salinities. The survival of C. gigas,which appears to betolerant of lower salinities than M. californianus, in the South Bay during the wet season is perhapsfurther evidence pointing to low salinities as an explanation for the low wet-season survival of M.californianus.

Bivalve % Survival

★ ★ ★★

% S

urvi

val


★ ★

Crassostrea gigas, wet seasonCorbicula fluminea, wet seasonMytilus californianus, wet seasonOstrea lurida, wet season

Crassostrea gigas, dry seasonCorbicula fluminea, dry seasonMytilus californianus, dry seasonOstrea lurida, dry season

Bivalve Monitoring

159

0.000.020.040.060.080.100.120.140.160.18

T-0

T-1

BA

30

BA

40

BB

70

BC

10

BC

21

BC

60

BD

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0.000.020.040.060.080.100.120.140.160.18

T-0

T-1

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30

BA

40

BB

70

BC

10

BC

21

BC

60

BD

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0.000.020.040.060.080.100.120.140.160.18

T-0

T-1

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BF

20

BG

20

BG

30

0.000.020.040.060.080.100.120.140.160.18

T-0

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BF

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BG

20

BG

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0.000.02

0.040.060.08

0.100.12

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T-0

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10

BD

15

BD

40

BD

50

0.000.02

0.040.060.08

0.100.12

0.140.16

T-0

T-1

BA

10

BD

15

BD

20

BD

40

BD

50

BF

20

Figure 18. Condition indices of three species of bivalves at reference locations prior todeployment (T0), at the end of the deployment period (T1), and at their deploymentlocations after exposure to Estuary water during the wet (January–May) and dry season(June–September) deployment periods. Stations with incomplete data show no histogram barsor no error bars. The reference sites were Bodega Head (M. californianus), Tomales Bay (C. gigas),and Lake Isabella (C. fluminea). Error bars represent 95% confidence interval.

C. gigasWet Season

C. gigasDry Season

C. flumineaWet Season

C. flumineaDry Season

M. californianusWet Season

M. californianusDry Season

Con

ditio

n In

dex

Con

ditio

n In

dex

Con

ditio

n In

dex

Con

ditio

n In

dex

Con

ditio

n In

dex

Con

ditio

n In

dex

160


A Comparison of Selenium and MercuryConcentrations in Transplanted and Resident Bivalves

from North San Francisco BaySamuel N. Luoma and Regina Linville

United States Geological Survey, Menlo Park

Monitoring With BioindicatorSpecies

Many of the methodologies for effective useof organisms to monitor and study contamina-tion in estuaries are well established (Phillips,1980; Phillips and Rainbow, 1993). Understand-ing the processes that determine bioaccumula-tion and determining concentrations of contami-nants in biological tissues are best employed inconjunction with analysis of other environmentalmedia (e.g., water, suspended particulate mate-rial, or sediment). Together these providecomplementary lines of field evidence indicativeof complexities that affect the exposures oforganisms to contaminants. While tissue analy-sis is not universally suitable as a measure ofexposure for all contaminants in all organisms orall circumstances, it does have important advan-tages when properly used:

1. Concentrations in tissues may be moreresponsive to environmental contaminationthan concentrations in water and/or sedi-ments in some circumstances, providing aunique perspective on understandingexposures.

2. Measurements of contaminant concentra-tions in organisms provide a time-averagedassessment. Temporal variability can be aproblem in understanding contamination.However, temporal variability is moderatedby biological processes in animal tissuescompared to other environmental media;thus organisms are described as “integra-tors” of contamination.

3. Understanding bioaccumulated concentra-tions can provide a more direct measure ofbioavailability than determination of con-centrations in water or sediments. One ofthe important difficulties in understanding

the effects of pollutants in nature lies inunderstanding how biological andgeochemical factors influence the dose thatan organism experiences. Tissue concentra-tions of contaminants can be a directmeasure of dose, and thus help reduceambiguities in interpreting environmentalexposures.

Results of tissue analyses are most sensi-tive to environmental contamination when thebioindicator species chosen for study is highlyresponsive to changes in contaminant exposure.Appropriate sample size (number of individu-als; number of replicate analyses) and samplemass are crucial for interpretable resultsbecause variability can be large among indi-vidual organisms of the same species, especiallyin contaminated environments. Tissue, lifestage, reproductive condition, size, sex, and gutcontent can be sources of variability and atleast need to be considered. Probably mostimportantly, contaminant concentrations aredirectly comparable only within the samespecies, unless proven otherwise.Bioaccumulation of trace element contaminantscan differ among even closely related species;although trends in time and space are oftensimilar among species.

Residents Versus TransplantedOrganisms

Either resident populations or individualstransplanted from one environment to anothercan be employed to monitor and assess con-taminant exposures, fate, distribution, orbioavailability. The California State MusselWatch Program, the Regional MonitoringProgram (RMP) and numerous specific studies(Smith et al., 1986; Phillips, 1988; Rasmussen,

Bivalve Monitoring

161

1994) have employed the transplant approach.In the RMP, bivalves are collected from sitesthought to be uncontaminated and transplantedto San Francisco Bay. Tissue concentrations aredetermined at the beginning of the deploymentand after a 90–100 day deployment period.Detailed methodologies for employing mussels(Mytilus edulis; Mytilus californianus) in trans-plant experiments are well developed (Phillips,1988) and are described in the Backgroundsection of this chapter and in Appendix A.

An extensive literature is also available onthe use of resident species as bioindicators(Phillips, 1980; Phillips and Rainbow, 1993; seealso The RMP Workshop on Ecological Indica-tors of Contaminant Effects, this report). Asuitable resident indicator species should be (1)widely distributed and abundant in theecosystem(s) of interest; (2) feasible to collect innumbers suitable for statistical validity (>15–20per collection); (3) sufficient in tissue mass thatanalysis is practical; (4) sufficiently tolerant tocontaminants that the species will be present(i.e. survive) in at least moderately contami-nated situations; and (5) sufficiently restrictedin movement that values are representative ofthe location or region of interest.

The most important advantage of employingtransplanted species is that the same speciesmay be placed at any station whether or not thespecies is present naturally. A second advantageis that transplanted populations may provide acommon baseline from which to evaluate con-tamination. The deployed organisms shouldhave a common history of exposure to only lowlevels of contamination. Thus, tissue concentra-tions in transplanted organisms should reflectonly changes in concentration that have oc-curred during the deployment period.

Some practical disadvantages can hinder thetransplant approach. Changes in behavior of thetransplanted organisms because of the deploy-ment is always a consideration, although in thehistory of California Mussel Watch this does notseem to prevent evaluations of trends in spaceand time (Phillips, 1988; Rasmussen, 1994).Nevertheless it is difficult to determine ifbehavioral attributes important to bioaccumula-tion are similar in transplanted and native

organisms (i.e., if stress from deployment hasaffected results; Cain and Luoma, 1985). Inestuaries the advantage of deploying a singlespecies to all sites is partly countered by wideranging and variable salinities. The RMPtransplant approach does not solely use mus-sels in San Francisco Bay because the range ofsalinities is broad. The RMP employs mussels(Mytilus californianus), oysters (Crassostreagigas), and freshwater/brackish water clams(Corbicula fluminea), respectively, in reaches ofthe Estuary with progressively lower salinities.The use of different species will affect directcomparability of data, at least for some con-taminants. Contaminant concentrations intransplanted organisms also represent a kineticview of contamination. In the RMP they reflectuptake after 90–100 days, which may or maynot reflect steady state with concentrations inthe environment. Finally, the spatial andtemporal intensity of sampling transplantedorganisms may be limited by the expense andcumbersome nature of the methods, trans-planted individuals may not survive, or somelocations may be unsuitable in terms of access,proper habitat, or interference from shipping orvandalism.

The most important concerns about the useof resident species as bioindicators include theavailability of animals in critical locations or atcritical times and the variability (or effects oninterpretation) caused by differences in lifecycle, size, or genetic and physiological changes.Resident bioindicator species can be absentfrom a location because the distribution ispatchy or because of natural or anthropogenicstresses. The history of contaminant exposureis not known for resident species unlesssamples are collected intensively over time.Differences in contaminant history might affectinterpretation of recent contamination or addvariability to the responses of residents.

The use of resident species also has advan-tages. The organisms are living in the habitatof interest, and effects of caging or moving theanimals is not a consideration in interpreta-tions. Concentrations in tissues should alsoreflect natural steady state concentrations; orin highly variable environments temporal

162


variability and the history of changes in con-centrations can be assessed directly by frequentsampling. While resident species may indeed beabsent or difficult to collect in some circum-stances, in other circumstances they may bemore practical to collect frequently than wouldtransplants or they may be present in areasotherwise unsuitable for deploying trans-planted animals.

Uncertainties in employing residentbioindicators can be reduced by careful deter-mination of the responsiveness of the species aswell as the environmental accuracy and preci-sion of responses to contamination (Brown andLuoma, 1995). Brown and Luoma (1995)studied use of the bivalve Potamocorbulaamurensis as a resident bioindicator of metalexposures in North San Francisco Bay. Theystudied responses to metal exposures in thisspecies in laboratory studies and in nearmonthly collections from six sites betweenJanuary 1991 and March 1992. The mostimportant advantage of employing this opportu-nistic species was its very broad distribution inthe North Bay, where it has been abundantsince 1987. P. amurensis is highly euryhaline(i.e., it tolerates wide salinity ranges andfluctuations) and available from a wide range ofconditions in the North Bay. Breeding popula-tions were found throughout the study periodat a site toward the mouth of the SacramentoRiver (see Figure 1 in Chapter One: Introduc-tion), where salinities ranged from 0.5 ‰ to12.0 ‰. They were also found throughout mostof Suisun and San Pablo Bays and in the SouthBay, where salinities ranged from 25.2 ‰ to31.8 ‰. Populations were found in a variety oftypes of sediment and intertidally as well assubtidally. Because P. amurensis was presentthroughout a contamination gradient in SuisunBay, it was inferred that the species was atleast moderately pollution-tolerant. Variabilityin metal concentrations was reduced to man-ageable levels with careful methodologies. Todetermine the effect of animal size, the shelllength versus concentration regression wasassessed for each metal at each site. Wherecorrelation occurred, methods were presented

to counter such biases. Undigested gut contentmaterial did not cause a detectable bias intissue concentrations where concentrations inparticulate materials were substantially lowerthan concentrations in tissues (see Quantifica-tion of Trace Element Measurement Errors inBioaccumulation Studies Associated withSediment in the Digestive Tract, this report).For trace elements that occur in high concen-trations in particles, a 24 hour depurationremoved sufficient gut content to eliminateeffects on tissue concentrations. Brown andLuoma (1995) also addressed the question oflocal variability in bioaccumulated metal thatmight result from the combination of biologicaland geochemical uncertainties (i.e., within asite, between adjacent sites, between adjacenttimes). The variability of replicates collected atone time and one place was similar to thevariability among adjacent locations or times, ifinputs did not change. Methodologies thatemployed relatively large numbers of organ-isms per sample (see Methods) had the statisti-cal power to detect 20% differences in meanconcentrations along regional gradients, at thehigher range of the standard deviation (25%),and the sensitivity to detect 10% differences atthe lower range of a typical standard deviation(12%). Although less detailed, earlier studiesalso showed the usefulness of employing theclams Macoma balthica (Luoma et al., 1985)and Corbicula sp. (Luoma et al., 1990) asresident bioindicators in North and South SanFrancisco Bay. However, neither of thesespecies were distributed as widely in the Bay asP. amurensis.

The comparability of results betweenresident and transplant approaches has notbeen fully studied. In some circumstancestransplanted organisms rapidly reach the samecontaminant concentrations as native species(Bryan and Gibbs, 1983; Nelson et al., 1995).However in other circumstances (especiallycontaminated environments), large differencesbetween transplanted and resident speciesremained after months of exposure (Bryan andHummerstone, 1978; Cain and Luoma, 1985;Widdows et al., 1984).

Bivalve Monitoring

163

Selenium Trends in the NorthBay

Bioindicators are especially effective inmonitoring selenium (Se) contamination, one ofthe most important contaminants in the NorthBay. The bivalves Corbicula sp., Macomabalthica and Mytilus edulis were all responsiveto changes in Se exposure in San Francisco Bayin past studies, either as resident or trans-planted species (Risebrough, 1977; Johns et al.,1988). A distinct gradient in Se contamination,with maximum concentrations near CarquinezStraits, was a feature of North Bay in 1976 inMytilus edulis (Risebrough, 1977) and 1985–1986 in Corbicula fluminea (Johns et al., 1988).Se concentrations in suspended particulatematerials were also highest near CarquinezStraits after the flood of 1986 (Cutter, 1989) butwere more widespread later in the year, whenriver inflows were reduced and residence timeswere longer in San Pablo Bay and Suisun Bay.

Bivalves were effective bioindicators of Sedistributions because of the pathway of Sebioaccumulation in the North Bay (Luoma etal., 1992). The most important species ofdissolved Se in the North Bay was selenite,which, when taken up by phytoplankton, wasbiotransformed to organo-selenium. Organo-selenium was efficiently transferred to bivalves(clams) that ingested phytoplankton withsuspended particulate material (Luoma et al.,1992). Direct exposure to dissolved Se was aninsignificant source of exposure for the clams.The clams were a logical vector for Se exposurefor diving ducks that contained high concentra-tions of Se (White and Hofman, 1988; Chadwicket al., 1991). Selenium bioaccumulation in P.amurensis was not studied previously, eventhough it is now the predominant residentbivalve in the North Bay.

Study Design

The goal of the present study was to com-pare selenium and mercury (Hg) concentrationsin resident bivalves (principally P. amurensis)in the North Bay with concentrations deter-mined in transplanted bivalves in the 1995RMP studies. These elements were chosen

because they are two of the pollutants ofgreatest concern in San Francisco Bay. Thedata reported here are from May 1995 throughJune 1996. A period of drought in the water-shed of San Francisco Bay ended in 1993 andespecially in 1995; the latter was a year ofexceptionally high and long-lasting riverineinflows into the system due to high precipita-tion and snowpack in the watershed (Cloern,this report). Hydrologic inputs to San FranciscoBay in 1996 were similar to the long-termaverage for the ecosystem. In contrast to thetwo relatively stable hydrologic years for metalbioaccumulation reported for P. amurensis byBrown and Luoma (1995), the temporal envi-ronmental influences that might affect theresponses of a biosentinel species to contamina-tion in the Estuary were probably accentuatedin 1995 and 1996.

The comparison of transplanted and nativespecies had four parts. The first goal was tocompare bioaccumulated Se concentrations indifferent species. Assuming such concentrationsmight differ among species, the sampling wasalso designed to compare spatial trends in Sebioaccumulation indicated by the resident andtransplanted bivalves. Resident clams werecollected from three locations near RMP baggedbivalve sites in May 1996: Grizzly Bay (BF20),Davis Point at the mouth of Carquinez Strait(BD40), and San Pablo Bay near Pinole Point(BD30) (seeFigure 1 in Chapter One: Introduc-tion). Resident animals were also collected atUSGS Station 8.1 in the Carquinez Strait,across the channel from the Napa River baggedbivalve site (BD50). P. amurensis were presentat three of the four sites (they were absent atDavis Point). Macoma balthica were collectedat Davis Point and, for comparison with P.amurensis at a site on the west side of PinolePoint. In the RMP, Corbicula fluminea wasdeployed in Grizzly Bay, and Crassostrea gigasat the other stations.

The third goal was to compare temporalvariability in concentrations. In October 1995,P. amurensis were collected from five locationsin the Napa River (including near baggedbivalve site BD50); and from United States

164


Geological Survey (USGS) sites in Suisun Bay(6.1), Carquinez Strait (repeat sampling at 8.1)and San Pablo Bay (subtidal site 12.5, compa-rable to BD30). Thus the May and Octobersampling of residents was comparable to thewet season, dry season sampling of the RMP.

The fourth goal was to repeatedly sampleresident bivalves at one station to verify anytemporal trends. P. amurensis were collected forSe analysis monthly, between December 1995and June 1996 from Carquinez Strait (USGS8.1). USGS 12.5 in San Pablo Bay was re-sampled in June 1996.

Methods

Resident clams (P. amurensis or Corbiculasp.) were collected from the subtidal zone witha Van Veen grab and 1 or 2 mm sieves. Channeldepths ranged from 8–20 m. The subtidal sitesadjacent to marshes in Honker Bay and theNapa River (Figure 1 in Chapter One: Introduc-tion) were located in the shallows at an averagedepth of 1–3 m. Clams (P. amurensis andMacoma balthica) were also collected intertid-ally at three sites, at low tide with a shovel,sieve and bucket. Between 60–120 clams of allsizes were collected at each time and each siteand placed into containers of water collected atthe site. The clams were kept in this ambientwater in a constant temperature room at 10 oCto depurate for 48 hours, as previous studies

Table 1. Determination of selenium and mercury in standard reference materials at thetime of analyses of tissue samples by USGS Se-Hg laboratory. * July 19, 1995 run; **August1996 run. Reference materials were chosen to represent both sediments and tissues and to cover arange of Se and Hg concentrations. Laboratory results also were comparable with other laboratoriesin intercalibration exercises with NOAA-NRC Canada DORM reference materials.

Re fe re nce Sample Obse rve d Se(mg/g)

Ce rtifie d Se(mg/g)

Obse rve d Hg(mg/g)

Ce rtifie d Hg(mg/g)

NIST SJS-sed 1.6, 1.6* 1.6 ± 0.1 1.3, 1.4* 1.4 ± 0.08NRC-Can DORM-1-

sediment1.6, 1.9*1.8, 1.8**

1.6 ± 0.1 0.76, 0.81*0.78**

0.8 ± 0.07

NIST Oyster 1.9, 1.9* 2.2 ± 0.2 0.08* 0.06 ± 0.01IAEA MA-B-3 -

Fish1.2*1.4, 1.5**

1.4–1.7 0.45, 0.50** 0.47–0.61

NRC-Can. TORT-1 6.5* 6.9 ± 0.5 0.30*, 0.29** 0.33 ± 0.06NRC-Can. TORT-2 5.5, 5.7** 5.6 ± 0.7 0.27, 0.25** 0.27 ± 0.06NRC-Can. DOLT-2 5.6, 6.2** 6.1 ± 0.5 2.11, 2.12** 1.99 ± 0.10

showed a residence time of material in the gutof P. amurensis approximately 24 hours in thisspecies (Decho and Luoma, 1991). Clams fromeach site were separated into size classes of 1mm difference and composite samples weremade of similar sized individuals. Samples oflarger numbers of individuals were necessaryfor smaller size classes in order to obtainenough mass for analysis. Mean concentrationscharacteristic of a site and at a particular timewere thus determined from analyses of usually3 replicate composite samples each containing20–60 clams (each composite was contained atleast 250 mg dry weight soft tissue). Mercuryand selenium were determined by HydrideAtomic Absorption Spectrophotometry. Aseparate subsample was decomposed formercury as well as one for selenium. Mercurysubsamples were digested at 100o C in aquaregia, re-digested in 10 percent nitric acid pluspotassium dichromate and then reduced at thetime of the hydride analysis. Seleniumsubsamples were digested in concentratednitric and perchloric acids at 200oC and recon-stituted in hydrochloric acid.

All glassware and field collection apparatuswere acid-washed, thoroughly rinsed in ultra-clean deionized water, dried in a dust-freepositive-pressure environment, sealed andstored in a dust free cabinet. Quality controlwas maintained by frequent analysis of blanks,

Bivalve Monitoring

165

Spatial distributions observed in the residentspecies were generally similar to those indicatedby the transplanted bivalves in May 1995,although some details differed. If all bivalve datawere compared, the RMP data indicated that Seconcentrations were lower in Grizzly Bay in May1995 than in San Pablo Bay, the Napa River, andat Davis Point. This was due to the difference inbioaccumulation between C. fluminea and C.gigas. Bioaccumulated Se concentrations weresimilar in Grizzly Bay and San Pablo Bay in P.amurensis. If it is assumed that concentrations

analysis of National Institute of Standards andTechnology standard reference materials(tissues and sediments) with each analyticalrun, and internal comparisons with preparedquality control standards. A full QA/QC plan isavailable upon request. Analyses of NationalInstitute of Technical Standards (NITS) refer-ence materials (oyster tissue, San Joaquinsoils) were within an acceptable range ofcertified values reported by NITS or wereconsistent where the nitric acid digest did notcompletely decompose the sediment samples(see Brown and Luoma, 1995 and Luoma et al.,1995 for metals; see Table 1 for Hg and Se).

Spatial Trends: May 1995

Concentrations of Se observed in residentand bagged bivalves are compared in Table 2and Figure 19. Bioaccumulation of Se differedamong some, but not all species, when com-pared at the same location. P. amurensisappeared to accumulate Se more efficientlythan C. fluminea. In Grizzly Bay, concentra-tions of Se in C. fluminea were 1.35 mg/gcompared to 3.90 ± 0.8 mg/g in P. amurensis.At comparable locations, concentrations in C.gigas were slightly greater than concentrationsin P. amurensis (5.43 mg/g compared to 3.70 ±0.7 mg/g, respectively, in San Pablo Bay) andM. balthica (6.52 mg/g compared to 3.60 ± 1.1mg/g at Davis Point) in May. M. balthica and P.amurensis did not differ significantly in Seconcentrations at Pinole Point (p>0.1).

Site Location Spe cie s:Transplant

Se(mg/g dry)

Spe cie s:Re side nt

Se(mg/g dry)

Location

Grizzly Bay 18 km C. fluminea 1.35 P. amurensis 3.90(0.8)

18 km

Napa River(Carquinez)

39 km C. gigas 6.22 P. amurensis 7.10(0.3)

30 km

Davis Point 40 km C. gigas 6.52 M. balthica 4.10(0.4)

42 km

San Pablo Bay 55 km C. gigas 5.43 P. amurensis 3.70(0.7)

50 km

San Pablo Bay M. balthica 3.60(1.1)

50 km

Table 2. Comparison of selenium concentrations in transplant and resident species inthe North Bay in May 1995. Locations are km from the mouth of the San Joaquin/SacramentoRivers confluence.

Figure 19. Spatial trends inconcentrations of Se in soft tissues oftransplanted Crassostrea gigas (Cg) andCorbicula fluminea (Cf) compared totrends in concentrations in residentPotamocorbula amurensis (Pa) andMacoma balthica (Mb) in May 1995, as afunction of distance from the SanJoaquin/Sacramento River confluence.

Tissue Residue Selenium LevelsTransplanted vs. Resident Species 5/95

Transplanted Resident

Sel

eniu

m (

ppm

)

km from the San Joaquin/Sacramento River confluence

166


in M. balthica are comparable to P. amurensis,Grizzly Bay was similar to Davis Point.

Probably the most important differencebetween the resident species survey and theRMP bagged bivalves was the elevated concen-trations of Se observed in Carquinez Straits inP. amurensis. This aspect of Se distributionswas slightly ambiguous in the RMP, becausebivalves were not deployed in this waterway.This was an instance where the widespreadnature of the resident species and relative easeof collection offered an advantage compared tothe transplant approach. Because Se enrich-ment in Carquinez Strait was also indicated inearlier studies; this location might be consid-ered a critical site for biomonitoring in thefuture.

The spatial distribution and concentrationsof Se observed in transplanted and residentspecies in May, 1995, may have been influencedby the hydrologic regime at the time. The RMPdeployment and the May resident samplingsoccurred in the middle of a prolonged period ofhigh river inflow. During low flow periods(summer and fall) the total outflow index atChipps Island, calculated by the US Bureau ofReclamation, is typically less than 7,000 cubicfeet per second (cfs). In the 1995 water year(October 1994 to October 1995) outflow firstexceeded 10,000 cfs during 15 days in Decem-ber 1994. Between January and the end of Juneaverage daily outflow for each month was44,000–80,000 cfs (United States Bureau ofReclamation Delta Outflow ComputationTables, unpublished); outflows greater than10,000 cfs continued into September.

Temporal Trends

Significant differences in Se trends wereobserved between resident P. amurensis andbagged bivalves in October 1995. Concentra-tions in P. amurensis indicated a substantialincrease in Se contamination in Suisun Bay,San Pablo Bay, and the Napa River in theresident food web by October 1995. An unam-biguous increase was not indicated in thedeployed bivalves.

In the RMP, Se concentrations in C.fluminea transplanted to Grizzly Bay were 1.35mg/g deployment (Figure 8). The latter are notexceptionally high concentrations for C.fluminea; they are below the higher valuesobserved by Johns et al. (1988) near GrizzlyBay in this species in 1985–1986. Concentra-tions of Se in C. gigas transplanted to the NapaRiver were only slightly higher (statisticalsignificance could not be determined) in Octo-ber compared to May. Concentrations of Sewere substantially lower in October than Mayin C. gigas transplanted to Davis Point. Con-centrations of Se in mussels at Pinole Pointwere not high in October, compared to thoseobserved by Risebrough et al. (1977); and Sewas not determined in bagged bivalves fromSan Pablo Bay in October. Thus, the RMP dataalone did not indicate any great change in therelatively low levels of Se in the food web of theSuisun/San Pablo Bay region between May andOctober 1995.

In contrast to the RMP results, substantial,statistically significant increases in Se concen-

Figure 20. Concentrations of Se in soft tissuesof resident Potamocorbula amurensiscollected subtidally from Carquinez Straits(USGS 8.1) and average monthly river inflowin thousands of cubic feet per second, ascomputed by the US Bureau of Reclamationfor the time period May 1995 through June1996. Data from June 1994 are also shown asreported by Linville, R. and Kegley, S. E. Seleniumenrichment surrounding oil refineries: Analysis ofPotamocorbula amurensis and sediment. 1994Biology Fellows Undergraduate ResearchSymposium, Berkeley, CA.

Se Concentrations in P. amurensisFrom Carquinez Strait

Se (ppm) Flow

Se

conc

entr

atio

n (p

pm)

Flo

w fr

om d

elta

(tho

usan

ds)

Sample Date* 6/94 data from Linvillville 94, unpublished

Bivalve Monitoring

167

studied at the station nearest Carquinez Strait.Elevated Se concentrations have been observedin all studies since 1976. However, meanconcentrations in the dominant bivalve in thesystem (C. fluminea in 1985 compared to P.amurensis in 1996) have almost tripled inrecent years, suggesting the possibility of alarge increase in Se dose to upper trophic levelorganisms feeding on bivalves. Oysters trans-planted in a study in 1985 achieved a concen-tration very similar to oysters transplanted in1996. On the other hand, the ambiguities of theoyster results between May and October in theRMP raise questions about whether baggedoysters would be sensitive to increases inenvironmental concentrations. It cannot bediscounted that Se concentrations in CarquinezStrait increased after October 1995. But it isalso possible that the higher Se in 1995–1996compared to 1985–1986 might be the result ofthe replacement of C. fluminea by the invasionof a species that bioaccumulates Se moreefficiently, the opportunist P. amurensis.Dissolved Se concentrations were not deter-mined in October, and in 1995 elevated river

trations in P. amurensis were observed betweenMay and October 1995. Concentrations at alllocations in October were the highest everreported for bivalves in North Bay, rangingfrom a maximum of 15.4 ± 1.0 mg/g at USGS8.1 in Carquinez Strait to a minimum of 11.6 ±1.1 mg/g at USGS 12.5 in San Pablo Bay(Figures 20 and 21; Table 3). Concentrationswere also elevated throughout the Napa River(ranging from 12.5 ± 1.0 mg/g to 15.3 ± 1.0 mg/gat the six sites) in October. All concentrations inP. amurensis were substantially higher thanobserved in C. gigas at comparable locations, incontrast to the May results. All values exceededthe concentrations of Se that cause adverseeffects in fish and birds when ingested in food(i.e.>10 mg/g) .

Highly elevated Se concentrations wereobserved repeatedly in Carquinez Strait be-tween October 1995 and June 1996. Concentra-tions of Se in P. amurensis ranging from 15.4 ±1.0 mg/g to 18.9 ± 0.4 mg/g were observedbetween October 1995 through February 1996at station 8.1. Concentrations declined slightly,to a range of 10.0 ± 0.7 µg/g to 12.8 ± 0.4 µg/g,between March 1996 and June 1996. Thedecline in concentrations coincided with theannual increase mean monthly river inflow toNorth Bay (Figure 20).

Figure 22 summarizes results from paststudies with bivalves in the North Bay, showingmean concentrations of Se for each species

Figure 22. Selenium concentrations intissues of mussels (transplanted Mytiluscalifornianus, as reported by Risebrough,1977), Corbicula fluminea (resident species,as reported by Johns et al., 1988),transplanted oysters (Crassostrea gigas)and Potamocorbula amurensis. All values aregrand means of all analyses conducted at thestation nearest Carquinez Strait in each study.

Figure 21. Spatial trends of Seconcentrations in tissues of Potamocorbulaamurensis in May 1995 and October 1995.

Se Concentration Gradient in North BayMay and October 1995

10/95 5/95S

e (m

g/g

dry

wei

ght)

Sampling Locations

Selenium in BenthosSan Pablo Bay and Carquinez Strait

Se

in ti

ssue

(m

g/g

dry

wei

ght)

168


Site

10

/95

12

/95

1/9

62

/96

3/9

64

/96

5/9

66

/96

6.1

14

.5±1

.4 (3

)8

.1(C

arq

. Str

aits

)1

5.4

±1.0

(3)

16

.9 (1

)1

5.4

±1.6

(3)

18

.9±0

.4 (3

)1

1.3

±0.2

(2)

12

.8±0

.4 (3

)1

1.1

±0.4

(3)

11

.6±1

.1 (3

)

12

.5(S

an P

ablo

)1

1.6

±1.1

(5)

10

.0±0

.7 (4

)

Nap

a 1

12

.5±1

.0 (3

)N

apa

21

5.3

(1)

Nap

a 3

14

.1±0

.5 (3

)N

apa

41

4.0

±0.9

(3)

Nap

a 5

12

.7±0

.6 (2

)N

apa

61

2.6

±0.8

(5)

Tab

le 3

. Sel

eniu

m c

once

ntr

atio

ns

in m

g/g

dry

wei

ght

in P

ota

moc

orbu

la a

mu

ren

sis

at n

ine

loca

tion

s in

Nor

th S

anF

ran

cisc

o B

ay (

Fig

ure

1 i

n t

he

Intr

odu

ctio

n)

in O

ctob

er 1

995,

an

d b

etw

een

Oct

ober

199

5 an

d J

un

e 19

96 a

t S

tati

on8.

1 in

Car

qu

inez

Str

ait.

Val

ues

are

mea

ns

± on

e st

anda

rd d

evia

tion

. (#)

is t

he

nu

mbe

r of

com

posi

tes

anal

yzed

. Eac

hco

mpo

site

incl

ude

d ap

prox

imat

ely

20–6

0 in

divi

dual

P. a

mu

ren

sis,

an

d >

250

mg

dry

wei

ght

soft

tis

sue.

Nap

a R

iver

sta

tion

s ar

en

um

bere

d N

orth

-to-

Sou

th a

scen

din

g.

Bivalve Monitoring

169

inflows were present when the August samplingof Se was conducted.

Accumulation factors in C. gigas exceeded 1in the wet season in the RMP transplant. Thisindicates that Se was taken up when animalswere deployed from uncontaminated environ-ments to the North Bay. However, accumulationfactors in the dry season (October) in both C.gigas and M. edulis were low, indicating little Seuptake after deployment. It is possible thatdeployed animals either were feeding littleduring the dry season, or were feeding on a foodsource of lower Se bioavailability than thatexperienced by the resident species. The reducedcondition indices of both C. gigas and M.californianus in October support the formercontention (Figure 18). Detrital freshwater algaecould be an important food source for filterfeeders in North Bay, especially during periodsof high river inflows. Such sources are lessavailable during low flow periods. Behavioralchanges as a result of the deployment or as aresult of high Se concentrations on particulatematerials are possible. But it seems more likelythat the low standing stock of phytoplanktonand algal detritus in North Bay affected thefeeding or availability of food to C. gigas and M.californianus in October. If so, differences infood sources between deployed and residentspecies must be a consideration in interpretingtransplant data, especially with regard toelements like Se that are bioaccumulated fromfood. One possible explanation may be thechange in phytoplankton standing stock in thewater column of the North Bay in recent years.Transplanted mussels or oysters may not befeeding the way they have in the past, affectingtheir exposures to Se.

Summary of SeleniumComparison

The differences between trends in residentspecies and those in transplanted bivalves weresmall in May 1995. The most important differ-ence may have been the lack of an RMP stationin the region most influenced by Se inputs:Carquinez Strait. However, it is of concern thatthe substantial change in the Se contamination

of the benthos in the North Bay that occurred inOctober 1995, was not indicated by data fromdeployed bivalves, especially C. gigas and M.edulis. It becomes important to better under-stand the food source(s) exploited during periodsof low river inflows by the highly successful P.amurensis, because that appears to carry Se in aform that is highly bioavailable during a timewhen vulnerable migratory species (e.g., divingducks) are arriving in San Francisco Bay. Alter-natively, deployed bivalves may obtain food in amanner different from how resident animalsobtain food.

The temporal trends in Se concentrations inP. amurensis in the North Bay point out theinteractions among the important issues affect-ing San Francisco Bay. River inflow appeared toinfluence bioavailable Se concentrations in NorthBay in 1995 and 1996, presumably by affectingresidence times and dilution of local Se inputs byfreshwater. Concentrations of Se were lowest inP. amurensis during a prolonged period of highinflows (May 1995) and increased greatly afterinflows subsided in October 1995. Similarly, theconcentrations of Se in the transplanted C.fluminea were lower than any concentrationsobserved in resident C. fluminea by Johns et al.(1988) during 1985–1986. The latter studyincluded no period of high river flow as pro-longed as occurred in May 1995. A smallerdecrease in Se bioaccumulation also occurredcoincident with the pulse of high inflows inJanuary–March 1996. Further investigation iswarranted of the potentially important linkagebetween these issues.

The susceptibility of the Bay to invasions byexotic species also appeared to affect Se contami-nation of the food web. After the invasion of theEstuary by P. amurensis in 1986, Se concentra-tions in dominant resident bivalve in 1996increased to levels three times greater than thecontamination of the dominant bivalves in themid-1980. Whatever the cause, it is clear thatpredators of bivalves in the food web of theNorth Bay could have been exposed to muchmore Se in 1996 than they were in the late 1980,when most studies of upper trophic levels wereconducted.

170


Mercury Concentrations inBagged and Resident Bivalves

Mercury concentrations were low in P.amurensis (0.08–0.24 mg/g) at all locationsstudied in the North Bay and at all times(Table 4). No spatial trends were evident in thedata. Concentrations doubled between May1995 and October 1995 to June 1996; but theincrease in absolute terms was small. Mercuryconcentrations in the two resident bivalvesincluded in this study were not comparable.Concentrations in M. balthica were higher thanconcentrations in P. amurensis at Pinole Point.Comparing mercury concentrations in M.balthica between Pinole Point and Davis Pointsuggested greater contamination in residentspecies at the former site in May 1995.

Mercury concentrations in bagged bivalvesranged from 0.14–0.39 mg/g in May and Octo-ber 1995 at the North Bay sites, approximatelythe same range as the resident species. Thebagged bivalve data indicated that greatercontamination occurred during the dry seasonthan during the wet season, as observed in P.amurensis. The highest mercury concentrationsin the RMP data and in the resident speciesdata was observed at Pinole Point (~ 3.9 mg/gin M. californianus in October 1995; Figure 6),although it was unclear if the different specieswere directly comparable.

Bagged bivalves and resident species thusshowed generally the same trends in mercurycontamination in the North Bay. Most impor-tant, both indicated that substantial mercurycontamination was not found in the benthos ofthe North Bay, either during high flows orduring wet flows. Johns et al. (1988) drewsimilar conclusions from mercury analyses of C.fluminea at six sites in the North Bay inSeptember 1986. They observed a range ofconcentration of 0.08–0.18 mg/g Hg dry weightamong sites, similar to the concentrationobserved in bagged C. fluminea in May, 1995,but less than the 0.30 mg/g observed in RMPcollections in October 1995.

Mercury contamination has been found inlonger-lived higher trophic level species in theNorth Bay. That contamination may not betransferred via the benthic food web. Interac-tions between mercury and selenium have alsobeen reported in the literature. If such interac-tions occur in North San Francisco Bay, theyhave only a minor influence on concentrations.Mussels and M. balthica may be the bestbioindicators for mercury contamination in thebenthos of San Francisco Bay.

Acknowledgements

This study was conducted in partnershipwith the San Francisco Bay Region, CaliforniaRegional Water Quality Control Board.

Site 5 /9 5 1 0 /9 5 1 2 /9 5 1 /9 6 2 /9 6 6 /9 6P. amurensis.CarquinezStraits

0.10±0.00 (2) 0.18±.01 (3) 0.2 (1) 0.21±.02 (3) 0.24±.01 (3) 0.19±.02 (3)

San Pablo Bay 0.08±.01 (3)Napa 1 0.21±.01 (3)Napa 3 0.20±.02 (3)Napa 5 0.23±.01 (2)MacomaDavis Point 0.24±.04 (3)San Pablo Bay 0.37±.04 (4)

Table 4. Mercury concentrations in mg/g dry weight in Potamocorbula amurensis andMacoma balthica at five locations in North San Francisco Bay (Figure 1 in Chapter One:Introduction) in October, 1995; between October 1995 and June 1996 at Station 8.1 inCarquinez Strait and at station 12.5 in San Pablo Bay in June 1996. Mercury concentrationsin Macoma balthica also shown for May 1995. Values are means ± one standard deviation. (#) is thenumber of composites analyzed. Each composite included approximately 50 individual P. amurensis, and>250 mg dry weight soft tissue. Napa River stations are numbered North-to-South ascending.

Bivalve Monitoring

171

Bioaccumulation of Contaminants by TransplantedBivalves in the San Francisco Estuary:

A Summary of Status and Trends with Emphasis onLocal Effects Monitoring Programs 1

Rainer Hoenicke, Jay Davis, Bruce Thompson, and John HaskinsSan Francisco Estuary Institute

Introduction

San Francisco Bay Area dischargers, throughthe Bay Area Dischargers Association (BADA)and the South Bay Dischargers, have analyzedbioaccumulation in transplanted bivalves fortheir Local Effects Monitoring Program (LEMP)since 1989. Five separate surveys have beenconducted. Except for the first survey, the sur-veys have been termed “Rounds”. The objectivesof this summary were to:

1. provide information on the bioaccumulationof contaminats in bivalves sampled in LEMPRounds 3 and 4;

2. evaluate the similarities and differences inbioaccumulation among sampling locations(outfalls of the City and County of SanFrancisco, East Bay Municipal UtilityDistrict, and Contra Costa Central SanitaryDistrict);

3. evaluate similarities and differences betweenreference sites and sites along outfall gradi-ents wherever possible;

4. evaluate trends in bioaccumulation over timebetween sites located along transects alongthree outfall areas and their respectivereference sites;

5. compare the trends in bioaccumulationbetween outfall sites, Regional MonitoringProgram reference sites, and State MusselWatch sites in the Bay; and

6. compare bioaccumulation patterns whenbivalves are transplanted in the wet seasonversus the dry season.

The reader is referred to the full report for adetailed description of the reference envelope

approach (see also Taberski, this report), datatables, and figures.

Beginning with the BADA surveys (Rounds1–4), samples were located along gradientsfrom three major Estuary sewage outfallsbelonging to the City and County of San Fran-cisco (SFSE), the East Bay Municipal UtilitiesDistrict (EBMUD), and the Contra CostaCentral Sanitary District (CCCSD). Sites“near”, “mid”, “far” (from the outfall) and “out”(reference sites presumably outside outfallinfluences) were sampled. Bivalve deploymentswere made below the water surface and/orabove the bottom in the cases of SFSE andEBMUD, and just below the surface forCCCSD, and for 30 and/or 90 days. One to threereplicate samples for analysis of trace metalsand organics were collected at each station.Oysters, Crassostrea gigas, were used atCCCSD, and mussels, Mytilus californianus,were used at EBMUD and at SFSE. Thesesurveys collected samples during successive dryand wet season in the Estuary.

General Patterns

Differences between the 30- and 90-daydeployments and between the shallow and deepdeployments during Round 1 and 2 weredescribed in previous reports (O’Connor et al.,1992; Davis and Daum, 1993). Those reportsmade several conclusions that are important inconsidering the results of Rounds 3 and 4presented in this document. In general, the 90-day deployments had higher concentrationsthan the 30-day deployments except for polycy-clic aromatic hydrocarbons (PAHs) which were

1 This is a summary of Bioaccumulation of Contaminants by Transplanted Bivalves in the San Francisco Estuary: Status andTrends, available through SFEI.

172


more often higher in the 30-day deployments.There was no clear pattern of greater accumu-lation at the surface or bottom (deep) deploy-ments except for pesticides which had higherconcentrations in the deep deployments inRound 1. Bioaccumulation of contaminants bytransplanted bagged bivalves during LEMPRounds 3 and 4 showed three general patterns;

1. There was no evidence of bioaccumulationof arsenic, cadmium, and chromium inmussels. However, cadmium did accumu-late in some of the CCCSD samples.

2. Only copper accumulated in all musselsamples and the majority of oystersamples. Most other metals accumulated insome samples, but not in others, evenwithin individual study areas. Only copperat SFSE indicated a possible outfall-relatedeffect (Round 4).

3. All of the trace organic contaminantsaccumulated at all locations and sites. AtEBMUD polychlorinated biphenyls (PCBs)showed a pattern of accumulation thatsuggested a “near-outfall” source. At SFSEonly PAHs showed such a pattern, and atCCCSD none of the trace organic contami-nants exhibited this pattern.

Spatial Patterns of Accumulation

If outfalls were sources of biologicallyavailable contaminants, concentrations inbivalves might be expected to decrease withdistance from the outfalls. For most contami-nants, this expectation did not hold true. It ispossible that depending on the tidal or riverflow (in the case of CCCSD), or the feedingregime of the bivalves, one could find greatertissue contamination farther away from theoutfall as compared to the end of the pipe. OnlyPAHs and copper levels at SFSE and PCBs atEBMUD were elevated at “near-outfall” sta-tions relative to more distant ones. Othercontaminants did not show any spatial gradi-ents that could be attributed to the outfalls.When comparing sites nearest the outfalls withmultiple reference locations throughout theEstuary using a “reference envelope” approach

(SFEI, 1996) that included, silver, selenium,and PAHs exhibited higher concentrationsnearest the outfalls, while other constituentscould not be differentiated from Estuary“background”. Other contaminants were fre-quently elevated at the “near-outfall” locations,but in an inconsistent or indistinct manner;these included nickel at CCCSD, pesticides andPCBs at EBMUD, and copper at SFSE. Noother contaminants were distinctly elevated atthe “near-outfall” locations.

One non-outfall location, the “far” stationfor EBMUD, consistently had very high concen-trations of PAHs (up to 7000 ng/g dry-weight inRound 3).

Temporal Patterns ofAccumulation

In general, there was little evidence oftemporal trends over the four LEMP Rounds,i.e., no consistent increases or decreases overtime could be discerned for most contaminants.Only copper and zinc increased over the fourRounds at EBMUD, while PCBs exhibited adecreasing trend over the four Rounds at theCCCSD locations. It should be noted, however,that all of these observations are qualitativeonly.

Comparisons with Other Data

A relatively large database exists forcontaminant concentrations in transplantedmussels in the Estuary due to the long-termmonitoring of the State Mussel Watch Program(SMW), the database of the Bay Protection andToxic Cleanup Program, and the more recentinception of the RMP. This extensive data set isvery suitable for comparison to the bioaccumu-lation data from the various Rounds of theLEMP, the Western States Petroleum Associa-tion (WSPA) LEM from 1993, and the SouthBay LEM from 1989–1990. For transplantedoysters, the Bay Protection and Toxic CleanupProgram and the RMP provide a frame ofreference. Table 5 summarizes comparisons ofdata distributions from the Local EffectsMonitoring Programs, the RMP, and the SMW.

Bivalve Monitoring

173

Co

nta

min

an

tM

uss

els

Oys

ters

Silv

er

So

me

val

ue

s at

EB

MU

D a

nd

SF

SE

exc

ee

d th

e R

MP

dis

trib

utio

n a

nd

are

in th

e u

pp

er e

nd

of t

he

dis

trib

utio

n o

f SM

W m

eas

ure

me

nts

in th

e B

ay.

So

uth

Bay

co

nce

ntr

atio

ns

ove

rlap

RM

P a

nd

SM

W d

istr

ibu

tion

s.

All

valu

es

at C

CC

SD

exc

ee

d th

e R

MP

dis

trib

utio

n.

Ars

en

icL

EM

P d

ata

ove

rlap

tho

se fr

om

the

oth

er p

rog

ram

s, w

ith th

e e

xce

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me

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ry lo

w (a

nd

pro

bab

ly s

pu

riou

s) v

alu

es

fro

m th

e S

ou

th B

ay.

Ge

ne

ral o

verla

p b

etw

ee

n C

CC

SD

an

d R

MP

dis

trib

utio

ns,

bu

t gre

ate

rra

ng

e fo

r CC

CS

D.

Cad

miu

mL

EM

P d

ata

are

ne

ar th

e c

en

ter o

f th

e S

MW

dis

trib

utio

n. R

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dis

trib

utio

nis

un

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174


Two contaminants, silver in mussels andoysters and selenium in mussels, reacheddistinctly elevated concentrations at the “near-outfall” locations, accumulating to concentra-tions that were high relative to both the RMPand State Mussel Watch (SMW) data. Silver inmussels and oysters and selenium in mussels in1994 also were shown to exceed the upperboundary of the “reference envelope” based on1994 RMP data (SFEI 1996).

The sum of all measured PAH compounds(ΣPAH) at SFSE was clearly and consistentlyelevated relative to RMP data and exceeded theupper boundary of the “reference envelope”based on 1994 RMP data (SFEI 1996). Relativeto the SMW data, however, SFSE ΣPAH concen-trations were not exceptionally high. SFSEΣPAH concentrations were in the upper half ofthe SMW distribution, but the highest SFSEconcentration approximated the 75th percentileof the SMW distribution. While a PAH signalhas clearly been detected near the SFSEoutfall, the concentrations measured are notexceptionally high relative to data for the Bayas a whole.

For two contaminants, cadmium andcopper, LEMP concentrations were high rela-tive to RMP data, but RMP data were generallylower than SMW data. Even SMW stations thatshould have been comparable to RMP stationshad higher concentrations. These results raisethe possibility that methodological differencesmight be a factor contributing to the patternsobserved among these data sets, particularly incases where the RMP and SMW distributionsare clearly offset from each other.

The South Bay data were generally withinthe range of the LEMP data, with some notableexceptions: arsenic and selenium concentra-tions were much lower than concentrations inany of the other datasets, suggesting method-ological artifacts. The South Bay data as awhole were slightly lower than the “near-outfall” data points at SSFE and EBMUD forsilver, copper, and cadmium. Compared to the1993/94 RMP data, copper and cadmiumconcentrations in the South Bay were relativelyhigh.

Seasonal Differences inBioaccumulation

None of the data revealed any consistentdifferences in bivalve tissue concentrationsbetween wet and dry seasons, although PCBconcentrations at EBMUD and copper atCCCSD at the stations nearest their respectiveoutfalls suggested higher concentrations duringthe dry season than during the wet season.

Efficacy of Bivalve Monitoring

One of the goals of the Local Effects Moni-toring Program was to evaluate potentialbioaccumulation differences between near-outfall sites and those presumably less influ-enced by treated waste water. Bivalves are aneffective tool for providing time-averagedconcentrations for contaminants thatbioaccumulate. Therefore, the LEMP data,together with those generated by the RMP andthe State Mussel Watch Program, are useful indetermining water quality trends that snap-shot water-column sampling may not be able toreflect accurately (see Schoellhamer, thisreport). The LEMP data show that areas nearoutfalls are, with exceptions of a few contami-nants, comparable to the Estuary as a whole.However, the lack of, or comparable levels of,bioaccumulation near outfalls compared toreference sites does not necessarily indicate alack of contaminant effects due either to directtoxicity or loadings to the Estuary over time.Additional indicators are needed to obtain amore complete picture of the success of pollu-tion prevention programs.

Some difficulties exist with regard tointerpretation of transplanted bivalve data.Some of the difficulty is due to sampling designproblems, such as the loss of bivalves fromsome transect stations, inability to differentiatespatial variability at outfall locations, and useof several species that preclude spatial com-parisons. Another difficulty is a low degree ofaccumulation of some contaminants in trans-plants relative to initial concentrations atpresumably clean sites. The meaning of bioac-cumulation of contaminants in an ecological

Bivalve Monitoring

175

context is also difficult to determine, althoughbioaccumulation data have great potential inecological risk assessment when used to evalu-ate impacts to bivalve predators, such as fish,birds, and mammals. Regional site-specificexposure information can add greatly to thecertainty of ecological risk assessments.

Monitoring with transplanted bivalves doesindicate that contaminants are capable ofentering the food web. Evaluation ofbioaccumulation along a waste dischargegradient, as has been done by the LEMP, alsoprovides an indication of whether or not theoutfalls may be directly contributing contami-nants beyond Estuary background levels thatare available for bioaccumulation. Only thepatterns observed for PAHs at SFSE , PCBs atEBMUD, and copper at SFSE suggest thatoutfalls may be direct contributors. Silver (alloutfalls) and selenium (SFSE and EBMUD) didnot show a gradient with distance from theoutfall, but concentrations measured near theoutfalls were high relative to both RMP andSMW data, suggesting that concentrations inthe areas surrounding the outfalls are elevated.The lack of a contaminant gradient away from

the outfalls seems to indicate that many contami-nants in treated waste water may not be appre-ciably different from the receiving water, al-though contaminant levels for the Estuary as awhole are (in some cases considerably) elevatedin bivalve tissue compared to non-urbanizedreference areas along the Pacific coast.

Another question to consider is whether otherspecies or methods of sampling could be used. C.gigas no longer lives in the Estuary (although itonce did). Transplanting organisms into bagsplaced on the bottom of the Estuary, which is nottheir natural habitat, may cause unnaturalbioaccumulation patterns. Perhaps resident/native bivalves, such as Ostrea lurida, should beused, since they would have integrated theirlifetime exposure and do not exhibit the largeseasonal fluctuation in body burdens due to theirdifferent reproductive strategy as brooders.Another candidate resident species that has beenused by USGS is Potamocorbula amurensis (seeLuoma and Linville, this report).

Resolving these questions will no doubtrequire some pilot studies to determine the bestdesign.

176


Quantification of Trace Element Measurement Errorsin Bioaccumulation Studies Associated with Sediment

in the Digestive TractRainer Hoenicke and Sarah Lowe, San Francisco Estuary Institute

Khalil Abu-Saba and Jonathan Crick, University of California, Santa CruzDane Hardin, Applied Marine Sciences

Introduction

As far back as the late 1960s, researchindicated that contamination of biologicalsamples by ingestion of sediment may causesignificant measurement errors (Martin, 1969;Bertine and Goldberg, 1972; Martin and Knaur,1973; Flegal and Martin, 1977). Despite thisrecognition, however, many individual studiesand even large-scale monitoring programs havefailed to include analysis of elements character-istic of lithogenic material to account forpotential artifacts. Particularly those programsthat are concerned with quantifying thebioavailable portion of various trace elementsfor purposes of water pollution trend evalua-tions may be impacted by this oversight.

Lobel et al. (1991a) determined that theamount of sediment in the intestinal tracts ofcaplin (Mallotus villosus) was highly correlatedwith the concentrations of a number of metals,especially aluminum, manganese, and iron.They concluded that metals bound to sedimentin the intestinal tracts of marine organisms caninterfere with the determination of the truelevel of metals incorporated into the organism’stissue and may result in an overestimation oftrue tissue concentrations. Moreover, in caseswhere bivalves are used to integrate contami-nant levels in the water column over time andto assess the “bioavailable” portion of thecontaminant spectrum the organism is exposedto, sediment artifacts may cause problems ininterpreting bioaccumulation results.

Although references to measurementartifacts are numerous, we have found nopublished reports that attempted to estimatethe magnitude of error for a variety of trace

elements, particularly those that are toxic toaquatic life or humans and of interest to envi-ronmental managers. Quantifying the exactcontribution of intestinal sediment to theproportion of toxic trace elements found in theorganism as a whole would require separateanalyses of sediment-free organisms andintestinal sediment. Obviously, this exercisewould prove logistically difficult and tedious atbest. Another approach, taken by Stephenson(1992), would be to compare tissue concentra-tions of depurated bivalves with those ofundepurated ones, but as Flegal and Martin(1977) point out, even purged animals stillcontain significant amounts of lithogenicmaterial in their digestive tracts. In this study,we used a third approach, suggested by Lobel etal. (1989, 1991), whereby aluminum, as anelement known to be of lithogenic origin andshown not to be incorporated into bivalvetissue, was used as surrogate for sediment inthe intestinal tract of bivalves. An importantconsideration in this approach is that either thesurrogate trace element concentration in theparticulate fraction of the water column isknown or, at a minimum, the concentration insediment near the bivalve deployment site. TheSan Francisco Estuary Regional MonitoringProgram for Trace Substances (RMP) hascollected data since 1994 that enabled us in thispresent study to estimate the magnitude ofbioaccumulation measurement error associatedwith intestinal sediment for ten trace elementsof concern.

Sediment and bivalve bioaccumulationsampling and analyses were conducted by theRMP using methods described in Appendix A.

Bivalve Monitoring

177

The following formula was applied to adjusttissue concentrations in bivalves based on theiraluminum concentrations:

TEbiv - Albiv/(Alsed/TEsed) = TEtis

1 - (Albiv)(1/Alsed)

whereTEbiv is the trace element concentration in thebivalve (tissue and ingested sediment)Albiv is the aluminum concentration in thebivalve (assumed to be in ingested sedimentonly)Alsed is the aluminum concentration in sedi-mentTEsed is the trace element concentration insediment, andTEtis is the trace element concentration intissue only, without the portion associatedwith sediment in the digestive tract.

Current measurements assume that traceelement concentrations in undepuratedbivalves are equal to “real” tissue concentra-tions that factor out the contribution of traceelements associated with ingested sediment(TEbiv is equal to TEtis). This hypothesis is easilytested with this fairly large data set involvingthree species of bivalves at six stations in theEstuary for four different deployment periods(wet and dry seasons of 1994 and 1995).

Results

After applying the correction equationlisted above, results of uncorrected and cor-rected tissue concentrations are depicted inFigure 23.

The most striking differences occurred inthe case of lead (Figure 23). Interestingly, atthree stations in 1995, the corrected valueswere negative, indicating that the contributionof lead contained in ingested sediment ac-counted for all of the lead measured in theanimals. Ingested sediment appears to contrib-ute heavily to the total lead concentrationsmeasured in all three species of bivalves. Twometals known to be strongly associated withsuspended solids—chromium and nickel—alsoshowed some indication of a positive bias inuncorrected bivalve concentrations, but much

less consistently than lead. After poolingresults from all species, chromium and nickelshow significant differences between correctedand uncorrected values. When species datawere pooled, arsenic, cadmium, and seleniumalso showed significant differences betweencorrected and uncorrected bivalve concentra-tions. However, these differences were muchless pronounced and less consistent betweenyears and species than for the other elementslisted above. Also, unlike lead, chromium, andnickel, corrected concentrations for arsenic,cadmium, and selenium were slightly higherthan uncorrected concentrations, suggestingthat sediment in the intestinal tract “dilutes”the tissue signal to some extent. Somewhatsurprisingly, mercury, which also is stronglyassociated with sediment particles, showeddifferences between corrected and uncorrectedbivalve concentrations only in 1994, afterconcentration results from all three specieswere pooled. Corrected and uncorrected mer-cury concentrations of individual species, whenexamined separately, were not significantlydifferent. Bivalve mercury concentrationsclosely resemble those in nearby sediment,indicating that total mercury is notbiomagnified by bivalves.

Silver was the only trace element thatshowed no significant difference betweencorrected and uncorrected values for all fourdeployment periods and all species. Correctedcopper concentrations were only statisticallydifferent from uncorrected values in mussels,and after pooling results from all three species,no differences were apparent. The same resultsapplied to zinc.

Discussion

At first glance, measurement artifacts seemto be pervasive for a majority of RMP traceelements. Differences in the trace elementuptake characteristics between species andamount of ingested sediment at differentstations seem to influence the magnitude ofmeasurement errors. Although statisticallysignificant differences were found betweencorrected and uncorrected bivalve concentra-

178


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Bivalve Monitoring

179

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180


tions, they do not appear to be of a magnitudethat would impair data interpretation, with theexception of lead and possibly chromium andnickel. For lead, differences were substantialand have implications with respect to howmuch lead is actually bioavailable. Apparentbioaccumulation factors for lead, calculated bydividing bivalve concentrations after the 90-daydeployment periods by the initial bivalveconcentrations at reference sites, seem to beheavily influenced by sediment in the intestinaltract (see Figure 5). This is consistent withfindings by Stephenson (1992) who comparedmussels depurated in clean Granite Canyonseawater with undepurated ones and foundstatistically significant differences for lead.

The somewhat surprising finding thatcertain trace elements show statistically highertissue concentrations after factoring out thelithogenic material in the gut may be spurious.However, the fact that those elements that arenot affiliated with suspended sediments (nota-bly arsenic, cadmium, and selenium) exhibithigher corrected values, may indicate that“true” tissue concentrations are disproportion-ately higher than those contained in the gutsediments. For these elements, the bioavailableportion may actually be underestimated ifcorrection factors are not applied.

Bivalve Monitoring

181

Bivalve Monitoring Discussion

The primary purpose of the bivalve bioac-cumulation component of the Regional Moni-toring Program is to measure the bioavailableportion of contaminants in the water columnand thus the potential for entry into the foodweb. Unlike the “snapshot” picture of watercolumn contamination obtained from watersampling during three periods each year, thebioaccumulation component provides anintegrative measure of water contamination,since bivalves are exposed to varying concen-trations during the three-month deploymentperiod that are reflected in their tissues.Together with bioaccumulation studies con-ducted by dischargers near waste wateroutfalls, this type of monitoring is also usefulin determining potential differences betweenreference sites and those close to a dischargepoint (see Arnold and Haskins, this report) andhelps in evaluating general pollution sourcecategories or pinpointing pollution hot spots.

Time series of bivalve concentrationsstarting in 1993 are depicted in Figures 24–36.As is the case with water and sediment con-centration “trends”, exogenous variablesprobably exert strong influences on bivalveconcentrations as well. The raw data essen-tially show no trends for any of the contami-nants, and quantitative relationships ofbivalve concentrations with key environmentalfactors should be established so that theinfluence of non-contaminant factors can beremoved statistically.

Trace Elements

As a whole, tissue trace element concentra-tions in the Estuary were generally compa-rable between the three years investigated sofar. Table 6 shows average trace elementconcentrations statewide (State Mussel Watch)and in the Estuary (RMP) from 1991 to 1995.Because of the varying seasonal and annualsalinity levels in the Estuary, and resultinguse of three different species of bivalves thathave different contaminant uptake character-

istics, it is difficult under the current design tocompare individual stations over time. Espe-cially in the Northern Estuary, and to a lesserdegree in the South Bay, freshwater inflowsand hydrologic conditions determine whichbivalve species survives and can be used forbioaccumulation measurements. The extremelywet year of 1995 limited the number of stationswhere mussels survived to those located prima-rily in the Central Bay and South Bay, thuslimiting the ability to interpret any spatialgradients.

Species differences in bioaccumulationpotential seem to be consistent from year toyear, independent of the location. Oyster tissuecontains similar levels of most contaminantscompared to mussels and clams prior to deploy-ment in the Estuary, with the exception ofsilver and zinc, which are higher than in theother two species, and lead, which is higher inmussels. However, the three-year RMP data-base suggests that the bioaccumulation poten-tial for oysters is considerably higher than forthe other two species in the case of copper,silver, selenium, and zinc, while musselsaccumulate lead to a greater extent than theother two species. This is consistent withprevious findings by O’Connor (1992) andStephenson (1992).

Unlike in previous years, lead and nickelwere the only trace metals that accumulatedsubstantially above background concentrations(between two and thirty-three times) in allthree species during their deployment in theEstuary (see Figures 5 and 7). Leadbioaccumulated at all Estuary stations, andnickel at all but one. Arsenic and mercuryshowed no appreciable differences in pre-andpost-deployment tissue concentrations. Cad-mium, chromium, copper, selenium, silver, andzinc increased over reference concentrationsbetween two and nine times at one or morestations, but primarily in the South Bay andthe Northern Estuary. Arsenic is the only traceelement that has not shown bioaccumulation in

182


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42

.82

7.8

58

.14

3.7

17

.16

0.1

78

.02

7.5

25

0.0

Hg

0.3

0.2

0.4

0.2

0.2

0.3

0.2

0.2

0.3

0.2

0.1

0.3

0.3

0.1

1.8

Ni

68

.54

1.0

96

.05

.22

.37

.85

.21

.31

1.1

6.0

3.2

9.2

8.7

1.4

26

.0P

b1

.50

.72

.40

.70

.41

.10

.70

.21

.20

.30

.10

.51

.20

.17

.1S

e3

.13

.03

.13

.01

.74

.22

.21

.43

.02

.01

.42

.94

.32

.19

.6Z

n1

60

.01

20

.02

00

.01

01

.26

2.0

12

6.6

84

.65

7.0

11

4.6

70

.32

9.1

96

.01

60

.07

4.0

47

0.0

RM

P

Pilo

t 19

91R

MP

1

99

3R

MP

19

94

RM

P

1995

C

rass

ostr

ea

giga

sC

rass

ostr

ea

giga

sC

rass

ostr

ea

giga

sC

rass

ostr

ea

giga

sM

eta

lA

vera

ge

Min

.M

ax.

Ave

rag

eM

in.

Ma

x.A

vera

ge

Min

.M

ax.

Ave

rag

eM

in.

Ma

x.n

=2

4n

=7

n=

11

n=

8A

g6

.84

.38

.31

.80

.73

.05

.10

.79

.14

.02

.26

.3A

l6

35

.03

90

.09

50

.02

59

.29

0.0

48

4.0

44

2.2

26

2.0

87

0.8

As

6.8

5.5

9.0

8.1

6.2

10

.78

.95

.01

3.0

9.8

5.6

16

.4C

d8

.06

.19

.81

3.7

5.1

25

.31

3.0

7.9

20

.51

8.3

10

.63

6.5

Cr

3.6

1.1

6.0

3.5

1.2

6.4

21

.91

.71

54

.88

.85

.31

3.9

Cu

28

6.6

18

0.0

42

0.0

33

4.6

15

4.9

63

4.2

40

6.0

18

8.0

68

3.6

43

1.2

21

8.0

86

7.1

Hg

0.2

0.1

0.3

0.3

0.2

0.3

0.3

0.1

0.6

0.2

0.1

0.3

Ni

71

.44

9.0

95

.02

.70

.84

.51

5.7

1.3

11

3.0

15

.54

.36

2.2

Pb

0.8

0.5

1.6

0.7

0.2

1.5

0.6

0.2

1.0

0.5

0.2

1.3

Se

3.5

2.7

4.3

5.0

2.0

8.3

3.4

1.9

5.2

6.8

4.0

11

.0Z

n3

68

7.8

90

0.0

21

00

2.0

12

44

.45

54

.62

64

6.5

14

28

.97

64

.03

26

8.0

14

22

.61

20

7.0

20

50

.0

RM

P

Pilo

t 19

91R

MP

1

99

3R

MP

19

94

RM

P

1995

S

tate

M

usse

l W

atch

(8

7–93

)M

ytilu

s ca

lifor

nian

usM

ytilu

s ca

lifor

nian

usM

ytilu

s ca

lifor

nian

usM

ytilu

s ca

lifor

nian

usM

ytilu

s ca

lifor

nian

usM

eta

lA

vera

ge

Min

.M

ax.

Ave

rag

eM

in.

Ma

x.A

vera

ge

Min

.M

ax.

Ave

rag

eM

in.

Ma

x.A

vera

ge

Min

Ma

xn

=3

0n

=1

2n

=6

n=

13

n=

43

2A

g0

.20

.10

.50

.50

.01

.10

.40

.20

.70

.20

.10

.40

.30

.02

.9A

l1

53

0.6

64

0.0

20

00

.04

33

.11

03

.01

19

9.1

53

8.7

25

0.0

10

42

.36

11

.21

5.0

32

00

.0A

s8

.57

.71

0.0

11

.67

.21

8.6

12

.17

.91

5.2

13

.29

.11

8.3

9.5

4.3

14

.0C

d9

.17

.01

2.0

8.6

1.4

19

.55

.91

.81

0.0

5.5

2.1

7.9

7.6

1.3

24

.0C

r8

.02

.21

9.0

11

.12

.64

0.9

14

.72

.18

0.9

17

.24

.84

2.2

4.3

0.5

17

0.0

Cu

10

.77

.01

3.0

5.9

2.7

8.6

7.5

3.4

22

.08

.76

.51

2.2

26

.14

.43

03

.7H

g0

.30

.20

.30

.30

.20

.50

.40

.21

.90

.30

.20

.40

.20

.01

.5N

i2

9.7

20

.05

4.0

9.3

3.0

28

.91

1.4

1.3

64

.42

0.4

4.5

50

.72

.40

.76

.2P

b2

.61

.83

.92

.20

.04

.21

.80

.63

.31

.50

.32

.95

.00

.14

7.5

Tab

le 6

. Ave

rage

tra

ce e

lem

ent

con

cen

trat

ion

s in

biv

alve

tis

sue

stat

ewid

e an

d i

n t

he

Est

uar

y, 1

991–

1995

. Sta

te M

uss

el W

atch

dat

aar

e th

e av

erag

e of

all

sam

ples

, sta

tew

ide.

Un

its

are

ppm

(µg/

g) d

ry w

eigh

t. n

= n

um

ber

of s

ampl

es.

Bivalve Monitoring

183

Figures 24 and 25. Arsenic and cadmium accumulation or depuration in parts per million,dry weight (ppm) in three species of transplanted bivalves for six sampling periods from1993–1995. Initial (T-0) concentrations are subtracted from tissue concentrations after retrieval togive concentrations accumulated or depurated (negative value) during deployment in the Estuary.Bars indicate the range of values of all stations where species were deployed. Note different scales (*).

Arsenic, mg/kg, dry weight Cadmium, mg/kg, dry weightJu

n-19

93

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-20

-15

-10

-5

0

5

10

15Oysters

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-20

-15

-10

-5

0

5

10

15Clams

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-0.6-0.4-0.20.00.20.40.60.81.01.21.4

Clams*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-20

-15

-10

-5

0

5

10

15Mussels

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-8-6-4-202468

1012

Mussels*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-50-40-30-20-10

010203040

Oysters*

184


Figures 26 and 27. Chromium and copper accumulation or depuration in parts permillion, dry weight (ppm) in three species of transplanted bivalves for six samplingperiods from 1993–1995. Initial (T-0) concentrations are subtracted from tissue concentrationsafter retrieval to give concentrations accumulated or depurated (negative value) during deploymentin the Estuary. Bars indicate the range of values of all stations where species were deployed. Notedifferent scales (*).

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-200

20406080

100120140160

Oysters*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-4

-2

0

2

4

6

8

10Clams*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-30

-20

-10

0

10

20

30Clams

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-60

-40

-20

0

20

40

60

80Mussels*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-30

-20

-10

0

10

20

30Mussels

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0

100

200

300

400

500

600

700

800Oysters*

Chromium, mg/kg, dry weight Copper, mg/kg, dry weight

Bivalve Monitoring

185

Figures 28 and 29. Lead and mercury accumulation or depuration in parts per million, dryweight (ppm) in three species of transplanted bivalves for six sampling periods from 1993–1995. Initial (T-0) concentrations are subtracted from tissue concentrations after retrieval to giveconcentrations accumulated or depurated (negative value) during deployment in the Estuary. Barsindicate the range of values of all stations where species were deployed. Note different scales (*).

Lead, mg/kg, dry weight Mercury, mg/kg, dry weightJu

n-19

93

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5Oysters

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5Clams

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14Clams*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5Mussels

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-0.20.00.20.40.60.81.01.21.41.61.8

Mussels*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2Oysters*

186


Figures 30 and 31. Nickel and selenium accumulation or depuration in parts per million,dry weight (ppm) in three species of transplanted bivalves for six sampling periods from1993–1995. Initial (T-0) concentrations are subtracted from tissue concentrations after retrieval togive concentrations accumulated or depurated (negative value) during deployment in the Estuary.Bars indicate the range of values of all stations where species were deployed. Note different scale (*).

Nickel, mg/kg, dry weight Selenium, mg/kg, dry weightJu

n-19

93

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-40

-20

0

20

40

60

80

100

120Oysters

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-2

0

2

4

6

8

10Clams*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-3

-1

1

2

4

5

7

8Clams

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-40

-20

0

20

40

60

80

100

120Mussels

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-3

-1

2

4

6

8Mussels

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-3

-1

2

4

6

8Oysters

Bivalve Monitoring

187

Figures 32 and 33. Silver and zinc accumulation or depuration in parts per million, dryweight (ppm) in three species of transplanted bivalves for six sampling periods from1993–1995. Initial (T-0) concentrations are subtracted from tissue concentrations after retrieval togive concentrations accumulated or depurated (negative value) during deployment in the Estuary.Bars indicate the range of values of all stations where species were deployed. Note different scales (*).

Silver, mg/kg, dry weight Zinc, mg/kg, dry weightJu

n-19

93

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-5-4-3-2-101234

Oysters*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-0.3-0.2-0.10.00.10.20.30.40.50.60.70.8

Clams

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-40

-30

-20

-10

0

10

20

30

40Clams*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-0.3-0.2-0.10.00.10.20.30.40.50.60.70.8

Mussels

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-150-100

-500

50100150200250300350

Mussels*

Jun-

1993

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-500

0

500

1000

1500

2000

2500Oysters*

188


any of the three species at any station since theinception of the RMP. Chromium, copper, lead,nickel, and zinc, the same metals as in theprevious two years, showed much higher tissueconcentrations in the Estuary than at thereference locations. Silver was accumulated to alesser degree, with remarkably similar spatialpatterns as in the previous two years.

It is interesting to note that no signal fromthe high mercury loads suspected to have beentransported into the Estuary via the GuadalupeRiver, possibly from mobilization of minetailings (see Arnold and Haskins, this report),was observable in bivalve tissue at any of theSouth Bay stations (see Figure 6), despite theunusually high sediment concentrations of 1.1ppm and 2.9 ppm seen at the San Jose/Sunny-vale Local Effects Monitoring station (C-1-7) inFebruary and June, respectively. Clamsdeployed in Grizzly Bay (BF20) and the RiverStations (BG20, BG30) also did not reflect thelarge mercury loads that were transported viathe Yolo Bypass into the Estuary during periodsof high runoff in 1995 (Chris Foe, CVRWQCB,personal communication).

Trace Organic Contaminants

Bivalves accumulate many trace organiccontaminants to a much larger degree thantrace elements, particularly the lipophiliccompounds. For some compounds, accumula-tion can be on the order of hundreds of timesabove initial tissue concentrations measured atcontrol sites. Thus, contaminants that occur inminute quantities in the water column or insediments are quite easily detected and quanti-fied. Especially for the chlorinated compounds,but also for PAHs, the observed bioaccumula-tion left no doubt that these contaminants weretaken up in the Estuary.

Total PCBs were uniformly lower in 1995compared to the year before, although this wasmuch less pronounced at the River stations(Figures 13 and 35). Seasonal differences inPCBs were less pronounced than in 1994,although many of the chlorinated pesticidesshowed distinct seasonal differences at moststations. Particularly elevated wet-season

concentrations were observed at the CoyoteCreek station for DDTs, chlordanes, and dield-rin, possibly implicating runoff as a source,despite the fact that these chlorinated pesti-cides have long been banned. In 1996, the RMPlaunched a Watershed Pilot Study to test thishypothesis, and preliminary data show that,indeed, sediment samples taken at the upperend of the tidal prism of Coyote Creek propercontain much higher chlorinated pesticideconcentrations than adjacent Bay sediments.These data will be discussed in detail in the1996 Annual Report. PAH concentrations in theEstuary were much more variable betweenseasons, without any consistent patterns.

Broad spatial patterns, such as thoseobserved in 1994 for PCBs, did not hold in1995. In 1994, the South Bay had uniformlyhigher concentrations of many PCB congenersthan the other reaches, while in 1995, only theCoyote Creek station, but none of the otherSouth Bay stations, showed consistently highertissue levels than all others. As in 1994, thePetaluma River station exhibited elevatedconcentrations of most trace organic contami-nants, but here too, the signal was more mutedcompared to the previous year. The mixture ofPAHs, although not individual concentrations,was again fairly uniform throughout theEstuary, suggesting multiple inputs via urbanrunoff or direct aerial deposition.

Comparison with Guidelines

For this report, a more comprehensivesummary of applicable tissue concentrationguidelines was tabulated than last year, so thereader can evaluate a variety of “yardsticks”that indicate how some of the Estuary datacompare to what is considered “acceptable” or“undesirable” by public health and regulatoryagencies (Table 7). This table summarizesthreshold contaminant concentrations forhuman consumption of fish and shellfish. Noneof these guidelines are ideal for comparisons forreasons outlined below. It should be kept inmind that these guidelines were developed for avariety of purposes and do not have any regula-tory implications.

Bivalve Monitoring

189

Un

itM

TR

L1

Gre

at L

akes

2S

FR

WQ

CB

3

Pilo

t S

tudy

NA

S4

FD

A5

MIS

6

(fis

h, s

hellf

ish

&

drin

king

w

ater

)(f

ish

)(f

ish

)R

eco

mm

en

de

d

Gui

delin

e (f

resh

w

ater

sh

ellfi

sh)

(fre

sh &

mar

ine

she

llfis

h)

(sh

ellf

ish

)

Dry

w

eigh

tD

ry

wei

ght

Dry

w

eigh

tD

ry

wei

ght

Dry

w

eigh

tD

ry

wei

ght

Ars

enic

mg/

kg1

.4*

..

9.8

Cad

miu

mm

g/kg

4.4

8*

2.3

..

7.0

Chr

omiu

mm

g/kg

..

.7

Cop

per

mg/

kg.

..

14

0Le

adm

g/kg

..

.1

4M

ercu

rym

g/kg

70

.14

.7

3.5

Nic

kel

mg/

kg15

40 /

196

*.

..

Sel

eniu

mm

g/kg

.1

1.6

7.

.2

.1Z

inc

mg/

kg.

..

49

0

Ald

rinµg

/kg

2.31

/ 0

.35*

.2

10

0.

Alp

ha-H

CH

µg/k

g11

.9 /

3.5

*.

..

Bet

a-H

CH

µg/k

g42

/ 1

2.6*

..

.D

ield

rinµg

/kg

4.9

/ 4.

55*

10

.5.

21

00

.E

ndri

nµg

/kg

2240

0 /

2100

0*4

90

0.

21

00

.G

amm

a-H

CH

µg/k

g56

.7 /

17.

5*.

..

Hep

tach

lor

µg/k

g13

.3 /

12.

6*.

21

00

.H

epta

chlo

r E

poxi

deµg

/kg

5.6

18

.2.

21

00

.H

exac

hlor

oben

zene

µg/k

g4

21

02

.2.

..

Sum

Chl

orda

nes

µg/k

g8.

4 /

7.7*

12

5.3

..

.S

um D

DT

sµg

/kg

22

44

80

.27

00

0.

.T

otal

End

osul

fan

µg/k

g35

00 /

175

0*2

45

00

..

.T

otal

PA

Hs

µg/k

g6.

51 /

0.5

6*.

..

Tot

al P

CB

s (A

rocl

ors)

µg/k

g1

5.4

14

70

–7

00

02

13

50

01

40

00

.

* V

alue

s ar

e M

TR

Ls fo

r inl

and

surfa

ce w

ater

s (fr

esh

wat

er).

1 M

TR

L fro

m: S

tate

Mus

sel W

atch

Pro

gram

198

7–93

Dat

a R

epor

t, M

axim

um T

issu

e R

esid

ue L

evel

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tate

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sel W

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gram

198

7–93

Dat

a R

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AS

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nd F

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198

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a R

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from

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(edi

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le 7

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190


The San Francisco Regional Water QualityControl Board conducted a pilot study entitled“Contaminant Levels in Fish Tissue from SanFrancisco Bay” (SFRWQCB, 1995) in whichthey developed Pilot Study Screening Valueswhich have received extensive public andscientific review. Although fish tissue guide-lines are not necessarily applicable to shellfish,they are included, because they identify poten-tial chemicals of concern and are based onfairly recent toxicological and exposure infor-mation. Similarly, the Great Lakes Draft SportFish Consumption Advisory of 1993, does notapply to shellfish, but is based on recent scien-tific information. Since human exposure to toxicchemicals, and therefore the health risk,depends on the consumption rate and the bodyweight of the individual eating the contami-nated tissue, both of these threshold levels arecalculated using certain consumption rates anda standard weight of 70 kg (the weight of anaverage male adult). The Pilot Study ScreeningValues were calculated based on the EPAGuidance for Assessing Chemical ContaminantData for Use in Fish Advisories (US EPA, 1993)using a consumption rate of 30 g per day(rather than the EPA rate of 6.5 g/day), and theGreat Lakes guideline was based on a con-sumption rate of 7.4 g per day. Only in rarecases is the consumption rate of shellfishexpected to approach the same levels as thosefor fish.

Median International Standards (MIS),while applicable to shellfish, are based on fairlyoutdated information. MIS have a varyingdegree of toxicological and exposure informa-tion associated with them, and are generallyconsidered of low value to health risk manag-ers. MIS were compiled by the United Nationsbased on a survey of health protection criteriaused by member nations (Nauen, 1983). TheMIS do not apply within the United States butindicate what other nations consider to beelevated concentrations of trace elements inshellfish.

Maximum Tissue Residue Levels (MTRLs)were developed by staff at the State WaterResources Control Board from human health

water quality objectives that protect againstconsumption of fish, shellfish, and drinkingwater containing substances at levels whichcould result in significant human healthproblems. MTRLs are an assessment tool onlyand are extremely conservative. For example,even at clean background sites, MTRLs areexceeded for dieldrin and arsenic.

National Academy of Science (NAS) guide-lines were developed to protect both the organ-isms containing the toxic substance and anyanimals that prey on the contaminated species.As with the MIS, these guidelines are quiteoutdated (NAS, 1973) and are primarily appli-cable to marine fish. Only two guidelines applyto freshwater clams.

The United States Food and Drug Adminis-tration (USFDA) has set action levels at orabove which it will take legal action to removecontaminated food from the market. Thesevalues contain economic and other assumptionsthat are not based on health risk.

Because MTRLs are the most recent guide-lines applicable to seafood in general, the 1995report only uses these criteria for comparisonpurposes. Arsenic, cadmium, nickel (freshwateronly), and mercury are the only trace elementsfor which MTRLs apply, and, with the exceptionof arsenic, bivalve tissue concentrations werefar below the threshold level for each of theseelements. It should be noted, however, that theMTRL for arsenic is exceeded even at theuncontaminated control site at Lake Isabella.As in the previous years, most of the traceorganic compounds analyzed by the RMP forwhich MTRL guidelines exist were higher thantheir respective threshold levels. Table 8summarizes the exceedances of guidelines forthe three bivalve species. The same patterns asin the previous years occurred, with the CoyoteCreek station (BA10) during the wet seasonand the Rivers during both wet and dry seasonsshowing levels consistently above the MTRLsfor most pesticides. PCB and PAH tissue levelswere consistently far above MTRLs throughoutthe Estuary. Once the database is sufficientlylarge, bioaccumulation data may be compared

Bivalve Monitoring

191

Figures 34 and 35. Total PAHs and total PCBs accumulation or depuration in parts permillion, dry weight (ppm) in three species of transplanted bivalves for six samplingperiods from 1993–1995. Initial (T-0) concentrations are subtracted from tissue concentrationsafter retrieval to give concentrations accumulated or depurated (negative value) during deploymentin the Estuary. Bars indicate the range of values of all stations where species were deployed. Notedifferent scales (*).

Total PAHs, µg/kg Total PCBs, µg/kgO

ct-1

993

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0

1500

3000

4500

6000

7500

9000Oysters*

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-100

100

300

500

700

900

Clams

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0

100

200

300

400

500

600Clams

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-100

100

300

500

700

900

Mussels

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0

100

200

300

400

500

600Mussels

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0

500

1000

1500

2000

2500Oysters*

192


Figure 36. Total DDTs accumulation or depuration in parts per million, dry weight (ppm)in three species of transplanted bivalves for six sampling periods from 1993–1995. Initial(T-0) concentrations are subtracted from tissue concentrations after retrieval to give concentrationsaccumulated or depurated (negative value) during deployment in the Estuary. Bars indicate therange of values of all stations where species were deployed. Note different scales (*).

Total DDTs, µg/kg

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

-100100300500700900

110013001500

Oysters*

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

5

0

50

100

150

200

250

300Clams

Oct

-199

3

May

-199

4

Sep

-199

4

Apr

-199

5

Sep

-199

50

50

100

150

200

250

300Mussels

Bivalve Monitoring

193

Tab

le 8

. Su

mm

ary

of c

onta

min

ants

th

at w

ere

abov

e th

e M

TR

Ls

at e

ach

199

5 R

MP

bio

accu

mu

lati

onsa

mp

lin

g st

atio

n.

W =

Wet

sea

son

(F

ebru

ary

- Apr

il),

D =

Dry

sea

son

(Ju

ne

– A

ugu

st),

- =

not

abo

ve g

uid

elin

e,*

= n

ot a

vail

able

or

not

sam

pled

. Spe

cies

: CG

IG—

Cra

ssos

trea

gig

as, C

FL

U—

Cor

bicu

la f

lum

inea

,M

CA

L—

Myt

ilu

s ca

lifo

rnia

nu

s.

Aldrin

Dieldrin

Heptachlor Epoxide

Sum Chlordanes

Sum DDTs

Total PAHs

Total PCBs

MT

RL

G

uid

elin

e2

.31

4.9

5.6

8.4

22

46

.51

15

.4S

tatio

n

Na

me

Co

de

Sp

ec

ies

µg

/kg

µg

/kg

µg

/kg

µg

/kg

µg

/kg

µg

/kg

µg

/kg

Lake

Isab

ella

T-0

CF

LU-,-

-,--,-

W,-

-,-W

,DW

,-D

abob

Bay

, WA

(W

et),

T

omal

es B

ay (D

ry)

T-0

CG

IG-,-

-,--,-

-,D

-,-W

,D-,

D

Bod

ega

Hea

dT

-0M

CA

L-,-

W,-

-,-W

,--,-

W,D

W,-

Coy

ote

Cre

ekB

A1

0C

GIG

-,-W

,--,-

W,D

W,-

W,D

W,D

Dum

bart

on B

ridge

BA

30

MC

AL

-,-W

,D-,-

W,D

-,-W

,DW

,DR

edw

ood

Cre

ekB

A4

0M

CA

L-,-

W,D

W,-

W,D

-,-W

,DW

,DA

lam

eda

BB

71

MC

AL

-,-W

,D-,-

W,D

-,-W

,DW

,DY

erba

Bue

na Is

land

BC

10

MC

AL

-,-W

,D-,-

W,D

-,-W

,DW

,DH

orse

shoe

Bay

BC

21

MC

AL

-,-W

,D-,-

W,-

-,-W

,DW

,DR

ed R

ock

BC

60

MC

AL

-,-W

,D-,-

W,-

-,-W

,DW

,DP

etal

uma

Riv

erB

D1

5C

FLU

/CG

IG-,-

W,-

-,-W

,D-,-

W,D

W,D

San

Pab

lo B

ayB

D2

0C

GIG

-,*

W,*

-,*

W,*

-,*

W,*

W,*

Pin

ole

Poi

ntB

D3

0M

CA

L*,

-*,

D*,

-*,

D*,

-*,

D*,

DD

avis

Poi

ntB

D4

0C

GIG

-,-W

,D-,-

W,D

-,-W

,DW

,DN

apa

Riv

erB

D5

0C

GIG

-,-W

,--,-

W,D

-,-W

,DW

,DG

rizzl

y B

ayB

F2

0C

FLU

-,D

W,D

-,-W

,DW

,-W

,DW

,DS

acra

men

to R

iver

BG

20C

FLU

-,-W

,D-,-

W,D

-,D

W,D

W,D

San

Joa

quin

Riv

erB

G30

CF

LU-,-

W,D

-,-W

,DW

,-W

,DW

,D

194


to a running mean of concentrations at RMPstations, rather than to guidelines.


Survival and condition measurements aretaken primarily to account for confoundingfactors that could affect bioaccumulationmeasurements and to determine if animalswere capable of pollutant uptake. The causesfor poor bivalve condition and low survival canbe numerous, but are probably primarilyrelated to the varying seasonal and year-to-yearsalinity regimes. However, the data indicatelow survival at several sites (Figure 17) thatdoes not appear attributable to salinity stress.High survival and good condition are notnecessarily related, and different factors mayinfluence each to varying degrees.

Dry season condition indices were almostalways lower than wet season condition indicesfor all species that had high survival rates attheir respective stations (see Figure 18). Simi-lar to 1994, condition for each bivalve specieswas determined both at the beginning and theend of each deployment period in the Estuaryand the control sites, in recognition of the factthat the bivalves’ reproductive cycle noticeablyinfluences the ratio of dry weight to shellvolume, and without taking condition fluctua-tions into account at control sites, it is moredifficult, if not altogether impossible to inter-pret changes in condition at the Estuarydeployment sites. If condition decreases at the“clean” reference sites, i.e. decreases between T-0 and T-1 measurements, natural factors arepresumed to be the likely causes. As an im-provement to the 1994 program, the reference-site bivalves were treated the same as theEstuary transplants, i.e., they were bagged tocontrol for handling factors that might influ-ence the condition of the animals.

Oyster condition during the wet seasondeployment increased at the control sites(Bodega Marine Laboratory and Tomales Bay)between January and April, while oystercondition in the Estuary either significantlydecreased or increased to a much lesser degreethan controls. During the dry-season deploy-

ment, oyster condition remained essentially thesame at the control sites, while oyster conditionin the Estuary showed dramatic decreases,especially at the Coyote Creek and PetalumaRiver sites. Although causal relationshipscannot be established without special follow-upstudies, it is interesting to note that for thesecond year in a row, the two sites with themost elevated contaminant concentrations intissue also showed pronounced condition indexdecreases.

Clam condition increased slightly at theLake Isabella control site during the wet-season deployment, but decreased at all sta-tions where they survived. Dry-season condi-tion decreased at the control site, butdramatically more so in the Estuary.

Compared to controls, mussels improvedtheir condition at all stations during the wetseason, except at Red Rock (BC60), but showedapproximately 20–45% reductions in conditionduring the dry season.

Any correspondence between contaminantconcentrations in the water column or tissueand condition and survival may be spurious.However, because both survival and conditionmeasurements are relatively straightforward,their usefulness as indicators of contaminationshould be explored with controlled laboratoryexperiments.

As a special study not funded by the RMP,Applied Marine Science began deploying thenative oyster Ostrea lurida with the RMPbivalves during the wet-season cruise of 1995.The purpose of these deployments was toinvestigate the potential value of this residentnative bivalve species for bioaccumulationstudies in the Estuary and its possibly highersensitivity to contaminants indicated by lowersurvival and decreased condition. At this point,not enough data have been accumulated toevaluate condition and survival response tocontamination. However, it is clear that itsurvives well in salinities as low as 15 ppt, itslow reproductive effort as a brooder, as opposedto broadcast spawners like M. californianusand C. gigas, reduces variability in contami-

Bivalve Monitoring

195

nant body burdens and condition, and its smallsize facilitates deployment.

Condition and survival are not indicators ofpopulation-level effects, especially since bi-valves are known to tolerate and survivecontaminant levels far in excess of thoseobserved in the water column of the Estuary.However, bivalve condition indices of the lastthree years are remarkably similar not onlywith respect to spatial patterns but also whencomparing wet and dry seasons and the abso-lute index values. During the wet season, theCentral Bay stations where mussels weredeployed appear to promote healthy animalswhose condition index actually increasedrelative to the reference site. Oyster condition

was roughly comparable to reference sitesduring the wet season, and clam condition wasalways slightly lower than at the reference site.With the exception of Horseshoe Bay (BC21)and Yerba Buena Island (BC10), the conditionindex at all other stations decreased for allspecies during the dry season in 1995, and in1994, condition decreased everywhere for allspecies. Natural environmental and physiologi-cal factors may play an important role in thesehighly consistent patterns, but year-to-yearvariation in condition indices has been muchlower than for ancillary water quality param-eters, such as salinity or total suspendedsediments, and possible contaminant influenceson condition should be investigated.

196


CHAPTER FIVE

Pilot and Special Studies


197

Background

In addition to the primary monitoringactivities, the Regional Monitoring Program(RMP) also supports two other types of relatedactivities: pilot studies and special studies.

Pilot studies employ methods that are underevaluation for potential incorporation into theRMP monitoring program. In 1995, two pilotstudies were conducted: a Benthic Pilot Studystarted in 1994 and a Tidal Wetlands Pilot Studystarted in 1995. The Benthic Pilot results arereported in Chapter 3: Sediment Monitoring.

Special studies help improve interpretation orcollection of RMP data. The results of a specialstudy on analysis of trends in water trace ele-ments is reported in Chapter 2: Water Monitoring.Continued studies on improved sediment bioas-says using the amphipod Ampelisca abdita arereported in Chapter 3: Sediment Monitoring. Areport of the workshop on ecological indicators ofcontaminant effects and the intercomparisonexercise are included below.

Contamination in Tidal WetlandsJoshua N. Collins and Michael May

San Francisco Estuary Institute

Introduction

Wetlands have enormous popularity world-wide as centers for a broad range of ecologicalservices, from the support of endangeredspecies and the filtration of local pollutants tothe stabilization of coasts and the regulation ofair quality (e.g., Sather and Smith, 1984;Mitsch and Gosselink, 1986; Bay Institute,1987; ABAG, 1991). In the United States,wetlands are notorious as arenas for testing therelations between environmental science andregulatory policy (Kusler, 1983), and there is awealth of methodologies for conducting naturalresource inventories that are based on wetlandsstudies (e.g., Cowardin et al., 1979; FWS, 1989;Brinson, 1993; Ferren et al., 1996).

The Bay Area public is concerned aboutwetlands. This concern has grown for decadesinto larger and more integrated plans forwetlands protection, with the expectation for acoordinated regional wetlands monitoringprogram (SF NERR, 1992; SFEP, 1993; RMG,1995; SF Bay Habitat Joint Venture, 1995;CALFED, 1996).

Given all this interest in wetlands, the risk ofhaving uncoordinated approaches to wetlandsmonitoring and assessment seems slight. Theassumption is, of course, false. Coordinationamong wetlands investigations that are based indifferent disciplines is an ongoing challenge, evenwhen the investigators agree to be coordinated.

The challenge for coordination is well illus-trated by the different approaches that have beenused to study tidal marsh contamination andother aspects of marsh condition in the Bay Area.The few previous studies of tidal marsh contami-nation have adopted a very general definition ofstudy sites, disregarding the variations in physiog-raphy and geomorphic controls within a marsh. Incontrast, local and regional studies of tidal marshhydro-geomorphology and ecology regard thenatural physiographic structure of tidal marsh-land as a detailed sampling template. The tidalchannels of different order (i.e., natural size class),the levees, pannes, and vegetated plains arecommonly regarded as major strata for samplingthe tides, sedimentation, and living resources ofall kinds.

198


Because past studies of tidal marsh con-taminants and ecological resources differ insampling approach, there is poor spatial ortemporal correspondence between data forcontaminant concentrations and other descrip-tors of tidal marshland. For example, assess-ments of wildlife hazards and restorationsuccess are less likely to use contaminant databecause they are not related to specific habi-tats. In some cases, the problem relates toinexact records of sample site locations forcontaminants, but more commonly the problemis due to inadequate spatial resolution of thecontaminant sampling design. Use of similarsampling designs (e.g., having a standardstratification scheme) would help link togetherstudies of tidal marsh contamination, hydro-geomorphology, and ecological function.

Now is the time to begin laying a founda-tion for coordinated investigations of tidalmarsh condition, including contamination. Weare in an early stage in the study of tidal marsh

contamination in the Bay Area. Datasets are not large and the samplingrecord is short. This means that anapproach to contaminant studies intidal marshland can be developed incoordination with related samplingefforts. Recent reviews of local andregional pollutant studies (e.g., Chanet al., 1981; CBE, 1983; Phillips,1987; SFEI, 1991; 1992; ACURCWP,1994; CH2M HILL, 1994), indicatethat the amount of data about thecontaminants of our open bays, majorrivers, local streams, and constructedwetlands far exceeds what is avail-able for our tidal marshes. There isscant information about tidal marshcontamination compared to theinformation about hydrology (e.g.,Leopold et al., 1993), geomorphology(e.g., Collins et al., 1987; Haltiner andWilliams, 1987; Siegel, 1993;Grossinger, 1995), plants (e.g.,Atwater and Hedel, 1976; Balling andResh, 1983; Wayne, 1995; Larsson,1996), or animals (e.g., Collins andResh, 1985; Barnby et al., 1985;

Foerester et al., 1990; Evens et al., 1991;Lonzarich et al., 1992; Garcia, 1995). Theexisting regional description of tidal marshcontamination (e.g., Anderson et al., 1990;Flegal et al., 1994; Hoffman et al., 1994) is anexcellent start, but is very general and lackslinkage to tidal marsh form or ecologicalfunction.

Objectives

The following objectives were set to helpassure that the wetlands pilot can lead to amonitoring program for trace substances thatyields comparable data for bays, wetlands, andwatersheds, and that the wetlands data con-tribute to the local and regional expressions ofwetlands condition.

• Develop equipment and train personnelto sample tidal marsh sediments forcontaminant analysis. The methodology

China CampState Park

Petaluma Marsh

Richmond

San Francisco

N

5 mi

Vallejo

Figure 1. Location of RMP wetland sampling sites.


199

should yield results that are comparableto other results of the Regional Monitor-ing Program for Trace Substances (RMP),and that are consistent with otherscientific efforts to understand tidalmarshes.

• Gain insight about the usefulness ofnatural tidal marsh physiography as aspatial template for sampling sedimentcontaminants within and among tidalmarshes.

Sampling PlanField Locations

The RMP wetlands pilot was conducted intidal marshlands at China Camp State Park inMarin County, andPetaluma Marsh inSonoma County (Figure1). These marshlandswere selected for thefollowing reasons: (1)they are among the bestunderstood tidal marsh-lands in the region, basedupon past and continuingecological and geomor-phic studies; (2) they aresites of the proposed SanFrancisco Bay NationalEstuarine ResearchReserve (NERR), andtherefore future sam-pling in these marsh-lands may be supportedthrough funding or in-kind services and coordi-nation through the NERR; (3) they are publicwith easy access, such that this new samplingeffort is not complicated by logistical problems;(4) they contain areas that do not receive anydirect fluvial inputs of sediment or water, andthat are, therefore, indicative of the pattern ofsediment contamination affected by the tides;and (5) they are located adjacent to existingRMP stations for San Pablo Bay and theentrance to the Petaluma River, and therefore

they are logical geographic extensions of theexisting RMP for bays.

Spatial Design

The sampling effort was designed to deter-mine whether the natural physiography of tidalmarshlands is a useful spatial template tosample sediments for contaminant analysis.

The most obvious elements of the physiog-raphy are the channel network, vegetatedplain, and natural pannes (Collins et al., 1987).The channel network is dendritic in plan view.The pattern of branching upstream of the tidalsource, or entrance into the channel network, isremarkably regular, and can be described bythe Strahler system of stream classification

(Strahler, 1957). That is, channels with notributaries are termed first-order; two or morefirst-order channels coming together form asecond-order channel; two or more second-orderchannels coming together form a third-orderchannel, and so forth (Figure 2). Channels ofdifferent order have distinct profiles in crosssection or longitudinal view. Depth, width, andarea of cross section can be predicted basedupon upstream tidal prism or marsh surfacearea (Leopold et al., 1993). The vegetated plain

4

4

3

3

2

2

2

11

1

1

1

1 1

1

21

1

2

3

1

3

11

3

22

1

1

1

22

1

2

2

1

1

11

1

1

1 1

23

BAY OR RIVER SHORELINE

Figure 2. Wetland channel order classification.

200


is defined as the area of marshland surroundedby channels or bordered in part by adjacentuplands. The natural levees, tension cracks tothe side of channel banks, and the naturalpannes are not considered part of the vegetatedplain. The pannes tend to form on the vegetatedplain at places equidistant from any channels.

The orders of the tidal channels of ChinaCamp and Petaluma Marsh were determinedfrom recent low-elevation aerial photographyand ground-truthing. At these locations, themost common drainage networks with indepen-dent tidal sources are third-order. Two typicalthird-order drainage networks were selected ateach location, China Camp and Petaluma.

Three sampling stations were establishedin each of the four selected networks as follows:one station near a panne on the drainage divideof the vegetated plain, one station at thedownstream reach of a second-order channel,and one station at the downstream reach of thethird-order channel. Each drainage dividestation involved an area of about 200 m2, atleast 10 meters from any channel or ditch, andat least 5 meters from the upland edge of thetidal marsh. The stations were thereforeoutside of the drawdown curves of nearbychannels (Howland, 1976; Balling and Resh,1983). Each channel station was a reach ofchannel about 20 m long. Based upon this arrayof stations, the variability within and betweenchannels large and small and whole drainagenetworks could be investigated.

A sample was defined as 10 sub-samplestaken at random from one station during onesample period. A sub-sample was defined asabout 100 cm3 of sediment collected from thesediment surface to a depth of 5 cm. Thevolume of a sample was therefore about 500cm3, which is comparable to the volume of anRMP subaqeuous in-bay sediment sample.

To further assure that data for the bays andtidal marsh channels were comparable, themarsh channel stations were stratified intosubstrate types, and only sediments similar tothe nearby bay stations of the RMP weresampled. The chosen substrate stratum wasunconsolidated fine-grain sediments of recent

deposition. The stratum lacked a diatom feltand was very easily penetrated. This is commonon the surface of recent slump blocks and thesurface of actively accreting point bars on theinside of meander bends. The maximum sampledepth of 5 cm did not extend into the blackobvious anoxic sediments below the zone ofrecent deposition. For drainage divide stationsthe maximum sample depth of 5 cm is wellwithin the active root zone and therefore doesnot extend into the anoxic sediments.

Temporal Design

During 1995, samples were taken from thetwo replicate drainage divides and third-orderchannel networks at China Camp during theregular fall and winter RMP sampling periods.These early results suggested that, for mostchemical species analyzed, the stations forsecond- and third-order channels were the samewithin and among the replicate channel net-works, and the replicate drainage divides werealso the same. Therefore, during the fall andwinter periods of 1996, the sampling effort atChina Camp was decreased to one second-orderchannel station and one adjacent drainagedivide station. This decrease in sampling effortat China Camp provided resources to extendthe pilot project into the two replicate networksand drainage divides selected at PetalumaMarsh. Winter results for Petaluma Marshsuggest that the replicate drainage networksand drainage divides are similar in mostregards, which prompted a decrease in sam-pling effort to one drainage divide station andone second-order channel station at PetalumaMarsh during the fall 1996 RMP samplingperiod.

Sampling Gear and Procedure

The following procedure was followed for allsamples of tidal marsh sediment:

1. One week prior to sampling, all equipmentwas thoroughly cleaned with Alconox®

detergent. The Teflon®-coated samplingscoops were soaked in the detergent fortwo days, then rinsed three times withdeionized water, soaked three days with


201

10% HCL, and finally rinsed with petro-leum ether. The cleaned scoops werestored in sealed Ziploc® bags until used inthe field. Following the detergent wash,the glass coring tubes and Teflon®-coatedbucket were rinsed with tap water, fol-lowed by three rinses with deionizedwater, a rinse with 10% HCL, and a finalrinse with petroleum ether. The ends ofthe glass coring tubes and the top of thebucket were sealed with plastic wrap.

2. All samples were taken with a thick-walled, 2 m long glass tube, having aninside diameter of 5 cm.

3. For channel stations, sub-samples wererandomly selected in unconsolidated fine-grain sediment below the exposed rootzone of the bank vegetation and above thebed of the channel. For drainage dividestations, sub-samples were randomlyselected at least 10 m from any channel orditch, and at least 5 m from the uplandedge of the tidal marsh.

4. The tube was inserted to a depth of firmresistance from stiff, consolidated sedi-ments. If the depth to resistance was lessthan 5 cm, then another place for sub-sampling was randomly selected withinthe station. As the glass tube was in-serted, its top end was kept uncovered, toprevent back pressure that could inhibitthe sediment from entering the bottom ofthe tube.

5. The tube was extracted from the substrateby turning the tube in a twisting motion tobreak the connection between the sub-strate and the sediment in the core. Beforethe tube was pulled from the substrate,some of the air within the tube wasremoved by inhalation. As the tube wasbeing extracted, its top end was firmlycapped with one hand. The plug of stiffsediment at the base of tube and thepartial vacuum in the tube helped thetube hold the core.

6. The total length of the core in the tubewas measured to the nearest 0.5 cm. The

outside of the tube was wiped clean with adry cloth to clearly view the core.

7. The core was slowly extruded from the tubeby blowing on the top end of the tube untilonly the top 5 cm of the core remain inside.The clean scoop was used to cut the ex-truded portion of the core flush with thebottom of the tube. The extruded portion(representing conditions below the fivecentimeter depth) was discarded.

8. The remaining portion of the core wasextruded into the Teflon© -coated bucket.This procedure required one person to blowinto the top end of the tube and a secondperson to measure, cut, and otherwisedirect extrusion of the core.

9. After all ten subsamples from a station hadbeen combined in the bucket, then theclean scoop was used to thoroughly stir thecombined sediment into one homogenousmixture.

10. Using the same clean scoop, about one literof the homogenous mixture was placed intoa clean glass jar, sealed and labeled, andthe jar was placed on ice for short-termstorage. Space was left at the top of thesample jar to allow for expansion of thesediment due to freezing.

11. To avoid cross-contamination betweenstations, all utensils, buckets, and the glasscore tubes were rinsed between stationswith tide water, then scrubbed thoroughlywith Alconox®, followed successively by onerinse with deionized water, one rinse with10% HCL, and one rinse with methanol.Spent chemicals were bottled separatelyand disposed of properly.

Results

The data are available for trace metals andtrace organics from samples taken at ChinaCamp during the fall and winter 1995 RMPsampling periods and the winter 1996 samplingperiod, and at Petaluma Marsh for the winter1996 sampling period. The data have beenreduced for the comparable stations for second-order channels and drainage divides.

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Silver at China Camp and Petaluma

0

0.1

0.2

0.3

0.4

0.5

0.6

pp

m

Feb 1995Sept 1995Feb 1996

China Camp Petaluma

DrainageDivide

2nd Order DrainageDivide

2nd Order

ERL=1ppm

BD22

ERL

Arsenic at China Camp and Petaluma

0

5

10

15

20

25

30

35

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

BD22

RMP WetlandsTrace Elements 1995-1996

Figures 3 and 4. RMP wetlands trace element results. Data pooled among drainagesystems. Only one drainage system measured at China Camp in February of 1996. Verticalbars indicate range between drainage systems. Grey band indicates range of bay sedimentstation BD22. ERL = effects range low; ERM = effects range median (see Chapter 3:Sediment Monitoring for an explanation).


203

ERL=1.2ppm

Cadmium at China Camp and Petaluma

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

BD22

Chromium at China Camp and Petaluma

0

20

40

60

80

100

120

140

160

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

ERLBD22



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Copper at China Camp and Petaluma

0

10

20

30

40

50

60

70

80

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

ERL

BD22

Iron at China Camp and Petaluma

0

10000

20000

30000

40000

50000

60000

70000

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

No ERL

BD22




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Mercury at China Camp and Petaluma

0

100

200

300

400

500

600

pp

b


China Camp Petaluma

DrainageDivide


2nd Order

ERL

BD22

Manganese at China Camp and Petaluma

0

500

1000

1500

2000

2500

3000

3500

4000

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

No ERL

BD22



206


Nickel at China Camp and Petaluma

0

20

40

60

80

100

120

140

160

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

ERM

ERL

BD22

Lead at China Camp and Petaluma

0

20

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pp

m


China Camp Petaluma

DrainageDivide


2nd Order

ERL

BD22




207

Selenium at China Camp and Petaluma

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

No ERL

BD22

Zinc at China Camp and Petaluma

020406080

100120140160180200

pp

m


China Camp Petaluma

DrainageDivide


2nd Order

ERL

BD22



208


RMP WetlandsOrganics 1995-1996

Figures 15 and 16. RMP wetlands organics results. Data pooled among drainagesystems. Only one drainage system measured at China Camp in February of 1996. Verticalbars indicate range between drainage systems. Grey band indicates range of bay sedimentstation BD22. ERL = effects range low; ERM = effects range median (see Chapter 3:Sediment Monitoring for an explanation).

No ERL

Total HCHs at China Camp and Petaluma

0

0.2

0.4

0.6

0.8

1

1.2

pp

b


China Camp Petaluma

DrainageDivide


2nd Order

BD22

Total PAHs at China Camp and Petaluma

0

200

400

600

800

1000

1200

1400

1600

pp

b


China Camp Petaluma

DrainageDivide


2nd Order

ERL=4022 ppbBD22 = 1934 to 3523 ppb


209


Figures 17 and 18. RMP wetlands organics results. Data pooled among drainagesystems. Only one drainage system measured at China Camp in February of 1996. Verticalbars indicate range between drainage systems. Grey band indicates range of bay sedimentstation BD22. ERL = effects range low; ERM = effects range median (see Chapter 3:Sediment Monitoring for an explanation).

Total PCBs at China Camp and Petaluma

0

5

10

15

20

25

pp

b


China Camp Petaluma

DrainageDivide


2nd Order

ERL

BD22

Total Chlordanes at China Camp and Petaluma

0

5

10

15

20

25

30

35

40

45

pp

b


China Camp Petaluma

DrainageDivide


2nd Order

No ERL

BD22

210


Figures 3–19 show the concentrations oftrace metals and trace organics, respectively,for drainage divides and second-order channelsin China Camp and Petaluma Marsh for winter(February) and fall (September) 1995, andwinter (February) 1996. In each graph, concen-trations at the marsh stations are compared tothe appropriate Effects Range Low (ERL) and/or Effects Range Medium (ERM), and to therange of concentrations observed at the nearestRMP bay station (BD22) for the 12 monthperiod between the 1995 and 1996 wintersample periods.

Only non-validated data for trace organicsare available for 1996. All results shown herepertain only to total concentrations, and shouldbe regarded as preliminary. A full report on thewetlands pilot will be prepared after all the

data, including the outstanding data for fall1996, have been validated.

DiscussionSample Analysis

All samples were processed according toestablished RMP protocols through the samelaboratories that process all other RMP data forconcentrations of trace substances. Conse-quently, data for the RMP bay stations and forthe wetlands pilot should be comparable,differences in data collection technique notwith-standing. However, the wetlands data have notbeen subject to some of the conventional treat-ments, such as standardization for total organiccontent, and not all the data for trace organicshave been validated. Therefore, the wetlands


Figure 19. RMP wetlands DDT results. Data pooled among replicate drainage systems. Onlyone drainage system sampled at China Camp in February of 1996. Vertical bars indicate rangebetween drainage systems. Grey band indicates range of bay sediment station BD22.ERL = effects range low; ERM = effects range median (see Chapter 3: Sediment Monitoring foran explanation).

ERL

Total DDTs at China Camp and Petaluma

0

5

10

15

20

25

30

35

pp

b


China Camp Petaluma

DrainageDivide


2nd Order

BD22


211

pilot data must be regarded as preliminary atthis time.

Sample Plan

In general, the preliminary results suggestthat concentrations of trace substances weresimilar among replicate stations within alocation and sampling period (absolute value ofrange was less than 25% of median value). Forexample, within any sample period, concentra-tions tended to be similar for the two drainagedivide stations at China Camp for all tracemetals except cadmium and chromium. Concen-trations were also similar for the replicatestations among second-order channels. Theseresults support the decision to reduce thenumber of replicate drainage networks, basedupon the use of drainage divides and second-order channels as sampling strata.

The stratification scheme used in thisproject is unusually specific for contaminantstudies, but may yet be too general tocharaterize tidal marshlands. Drainage dividestations as defined in this pilot project may notbe adequate to characterize the sedimentchemistry of mature, high-elevation tidalmarsh plains. Each sample represents 10 sub-samples taken randomly within a station that

included perhaps 200 m2 of tidal marshland.While this may seem like a large station, two orthree stations of this size together representless than 1% of the area served by a typicalthird-order channel network. Given that thesurface elevation of mature marshland corre-sponds to the upper limits of the tide, thenslight topographic relief of the marsh surfacecan have substantial influence on the frequencyand duration of tidal inundation. Given alsothat the tidal regime may be a controllingfactor for contaminant concentration, eitherthrough delivery or removal, then having smallsampling stations relative to the area of themarsh plain could produce a false picture ofuniformity. The stratification used to selectstations on drainage divides may have yieldeddata that only pertain to these highest parts ofthe marsh plain. A more representative sampleof the plain might have been produced bysampling within a number of elevational strata.Since the sub-samples were pooled, there wasno opportunity to collect covariate data on tidalelevation.

The bottoms and lower banks of the tidalmarsh channels are both low in the intertidalzone. Differences in elevation between thebottom and midbanks of the channels, there-

Table 1. Spatial and temporal patterns in trace element concentrations.

Ag As Cd Cr Cu Fe Hg Mn Ni Pb Se

MOST SAMPLES EXCEEDMAXIMA FOR BD2 2

• • • • • • • • •

MOST SAMPLES EXCEED

ERL• • • na • na • na

CONSISTENTLY HIGHERWINTER MAXIMA

• •

CONSISTENTLY HIGHER FALLMAXIMA

CONSISTENTLY HIGHERMAXIMA IN CHANNELS

• • • • • • • • •

CONSISTENTLY HIGHERMAXIMA ON DRAINAGE DIVIDES

•

HIGHER MAXIMA INP ETALUMA MARSH

• • • • • • • •

HIGHER MAXIMA IN CHINACAMP

•

na = not applicable

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fore, correspond to relatively slight differences intidal regime. The data for channel stations asdefined in this pilot project are therefore likely togenerally characterize channel exposure to tracesubstances.

Trace Metal Patterns

No consistent seasonal pattern was observedfor any trace metals except silver and copper,which tended to be higher in winter (Table 1). Itis not obvious, however, what period of depositionis represented by the samples, given that neitherthe residence time of the sediment within thechannel network, nor the rate of vertical fluctua-tions of trace metals on the drainage divides isknown.

For all metals except silver and cadmium,maximum concentrations tended to be higher inthe marshlands than at the nearby RMP baystation in San Pablo Bay. The obvious suggestionis that the tidal marsh sediments are morecontaminated than the bay sediments. Thissuggestion alone may be reason enough to extentthe wetlands sampling program to other marshesin the region. Concentrations also exceeded theERL for more than half of the trace metals forwhich an ERL has been established.

Concentrations tended to be higher in thechannel stations than on the drainage divides for

TotalHCHs

TotalPAHs

TotalPCBs

TotalChlordanes

TotalDDTs

MOST SAMPLES EXCEEDMAXIMA FOR BD2 2 • • • •

MOST SAMPLES EXCEED

ERLna na •

CONSISTENTLY HIGHERWINTER MAXIMA • •

CONSISTENTLY HIGHER FALLMAXIMA

CONSISTENTLY HIGHERMAXIMA IN CHANNELS

CONSISTENTLY HIGHERMAXIMA ON DRAINAGE DIVIDES • • • •

HIGHER MAXIMA INP ETALUMA MARSH •

HIGHER MAXIMA IN CHINACAMP • •

na = not applicable

Table 2. Spatial and temporal patterns in trace organics concentrations.

all trace metals except lead and selenium. Thisis a striking pattern that deserves to be ex-plored further. A possible explanation for thepattern is that most of the metals are stronglyassociated with inorganic sediments, such asclays and silts, which dominate the sedimentsof the channels, whereas the sediments of thedrainage divides are mostly peat, with a smallinorganic faction.

Concentrations were consistently higher inPetaluma Marsh than at China Camp. It is notknown if the higher concentrations upstreamalong the Petaluma River represent runoff fromthe Petaluma watershed, increased residencetime of tidal water upstream from the Bay (andhence more opportunity for filtration by theupstream marshlands), or differences in localsources. Sewage treatment outfalls existupstream of both of these locations, but Peta-luma Marsh also borders an active sanitarylandfill.

Trace Organic Patterns

No consistent seasonal pattern was ob-served for any trace organics except PAH’s andchlordanes, which tended to be higher in winter(Table 2). As with the trace metal data, it is notobvious what period of time is represented bythe trace organic samples, given that neither


213

the residence time of the sediment within thechannel network nor the rate of vertical fluctua-tions of trace metals on the drainage divides isknown.

For all compounds except PAH’s, maximumconcentrations tended to be higher in the marsh-lands than at the nearby RMP bay station inSan Pablo Bay. Again, the obvious suggestion isthat the tidal marsh sediments are more con-taminated than the bay sediments. Concentra-tions also exceeded the ERL for DDT’s.

Concentrations of trace organics tended to bemuch higher on the drainage divides than in themarsh channels. This pattern is essentially thereverse of what was suggested by the data fortrace metals. Atmospheric deposition andabsorption by peaty sediments may be part ofthe explanation for the high concentrations ofthe trace organics on the drainage divides. Apreliminary examination of the raw data sugges-tions an abundance of DDT degradation prod-ucts, and the spikes in HCH’s and PAH’s appar-ently relate to combustion products rather thanpetroleum.

No overall difference was apparent betweentrace organics concentration at China Camp andPetaluma Marsh, although the concentration oftotal PCB’s tended to be much higher at ChinaCamp. The data for trace organics was generallymore variable than the data for trace metals.

Conclusions

The RMP wetlands pilot project, although ofshort duration and limited scope, produced apractical methodology for sampling tidal marshsediments yielding data on contaminants thatare comparable to other RMP data. The projecthas demonstrated that novice field personnelcan be trained to test and conduct technicalsampling procedures for sediment samplingconsistent with existing RMP protocols.

The wetlands pilot clearly demonstrated thatthe natural physiography of the tidal marsh is auseful template for a stratified sediment sam-pling plan. Using channels large and small and

drainage divides as major strata, and substratetypes as minor strata, new patterns of contami-nant concentration were revealed that relatewell to the assessment of plant and animalhabitats. Although the data are rather scant, thepatterns of higher concentrations of traceorganic compounds on drainage divides, andhigher concentrations of trace metals in chan-nels seem especially persistent within andamong locations and sample periods. The sug-gestion of an upstream increase in contamina-tion along the Petaluma River also deservesfurther examination.

The evidence that tidal marshland sedi-ments are more contaminated than the sedi-ments of the open bay is not surprising, giventhat the marshlands are retentive filters washedtwice daily by the tides. This does not precludethe rather obvious need, however, to assess theeffect of these high concentrations upon theecological functions of the tidal marshes.

A more focused monitoring program shouldproceed. Based upon this pilot project, a monitor-ing program could be designed to focus on highlevels of trace organics on drainage divides, highlevels of trace metals in channels, or exceptionsto the general patterns observed. The questionis, what should the focus be? When the data setis complete, we will outline a variety of optionsthat follow directly from the considerations ofdifferent monitoring objectives, including thesupport of endangered species, the filtration oflocal pollutants, and the assessment of inputsfrom local watersheds.

Acknowledgments

We wish to thank the following people fortheir assistance in the field: John Haskins, TedDaum, Jung Yoon, Scott Featherston, A.J.Glauber, Dane Hardin, and Andy Peri. We wishto especially thank John Haskins for his expertcoordination of the field work and Dane Hardinfor his technical guidance. This was the firstfield study of contamination for the other people,and their performance was commendable.

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The RMP Workshop onEcological Indicators of Contaminant Effects

Bruce Thompson, Rainer Hoenicke, Jay Davis, SFEI.Bob Spies, Applied Marine Sciences, Livermore, CA

Lynn Suer, San Francisco Bay Regional Water Quality Control Board

Background

This report summarizes a workshop spon-sored by the Regional Monitoring Program(RMP) on Ecological Indicators of ContaminantEffects held on October 11, 1995 at the UnitedStates Environmental Protection Agency’s(USEPA) Regional Laboratory on the RichmondField Station. The goal of the workshop was toproduce recommendations for ecological indica-tors of contaminant effects that the RMP couldconsider using.

Determination of which indicators shouldbe used in monitoring programs requires thatthe goals and objectives of the program areclearly stated. Monitoring variables should betied directly to the specific questions to beanswered and the resources at risk. Changes inthe status of the selected variables mustunambiguously reflect changes in the resourcesat risk (National Research Council, 1990).

Another use of indicators was stated by theComprehensive Conservation and ManagementPlan (CCMP) which called for Regional Moni-toring to “provide information to assess theeffectiveness of management actions that havebeen taken to improve conditions in the Estu-ary and to protect its resources” (SFEP, 1993).Such use of indicators underscores the impor-tance that monitoring measurements arerelated to, and appropriate to the achievementof program goals and objectives.

The RMP currently operates using a set ofprogram objectives adopted at its inception in1993 (see Chapter One: Introduction). Theseobjectives address monitoring the status andtrends of contaminants in water, sediment, andtransplanted bivalve tissues, and evaluatingcompliance with water quality guidelines.Although the Basin Plan specifically contains

references to the evaluation of ecological effectsof contaminants, at this time there are nospecific RMP objectives to conduct such assess-ments.

The CCMP’s goals for Regional Monitoring(SFEP, 1993) mandated that biological effectsare monitored to “evaluate the ecological‘health’ of the Estuary and enhance scientificunderstanding of the ecosystem.” Ecologicalhealth is an important concept that implies theknowledge of conditions or effects of contamina-tion, in addition to indicators of many othertypes.

Currently, the RMP measures aquatictoxicity (two tests), sediment toxicity (twotests), bioaccumulation and condition of trans-planted bivalves, and, as pilot studies, mac-robenthic and phytoplankton communitycomposition and abundances. Although there iscurrently no monitoring of fish, birds, or mam-mals, a fish contamination pilot study orientedtowards human health began in 1996.

As the RMP enters its fifth year, the pro-gram objectives are being reevaluated, includ-ing the need to monitor for effects. The resultsof this workshop provide a beginning forconsiderations of which indicators will be usefulonce those revised objectives are in place. Thefocus on ecological indicators reflects the needfor the RMP to provide direct, easily inter-preted measurements of contaminant effects onthe habitats and biota of the Estuary.

The RMP indicators will be used, in con-junction with indicators provided by othermajor monitoring programs, in the evaluationof overall Estuary health as envisioned by theCCMP. Any individual indicator is but onecomponent of a comprehensive ecological healthassessment.


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What is an Ecological Indicator?

Webster’s New Collegiate Dictionarydefines an indicator as “an organism or ecologi-cal community so strictly associated withparticular environmental conditions that itspresence is indicative of the existence of theseconditions.”

The US EPA’s Environmental Monitoringand Assessment Program (EMAP) defines anindicator as “an environmental characteristicthat can be measured to assess the status andtrends of environmental quality, i.e., the abilityto support a desired human or ecologicalcondition” (Hunsaker and Carpenter, 1990).

Ecological indicators should be sensitivewithin the range of conditions encounteredwithin the system to be monitored, i.e., theyshould respond in the “worst case conditions” inthe system, and show little or no response whendisturbance/contamination is minimal. If not(and there are usually exceptions), then theother sources of variability should be known,measured, and/or controlled.

Since indicators work best for the level ofbiological organization at which they aremeasured, no single indicator can provide acomprehensive assessment of condition. Theyshould provide an early indication of a poten-tially worsening situation at a higher level ofbiological organization (e.g., communities andecosystems).

Indicators of exposure should be indicativeof classes of chemical compounds (e.g., divalentcations, PAHs, coplanar PCBs, etc.) Linksbetween exposure and effect, and betweenmarkers of effects on different levels of organi-zation can provide deeper insight into the totaleffects of contaminants/alterations in theecosystem.

Indicator Concepts

One of the best developed indicator con-cepts is used by EMAP. This national programhas developed a formal indicator strategy(Hunsaker and Carpenter, 1990) which issummarized below. It has been widely adoptedthroughout the country for environmental

assessments, and has received wide scientificreview and discussion. The EMAP framework issummarized here as an example. The RMP mayconsider adopting a similar framework, orcomponents of the EMAP framework, in thefuture.

The EMAP framework begins by identifyingwhat are important as environmental valuesand then proceeds hierarchically throughassessment endpoints to indicators. The maincomponents of the EMAP indicator strategy aredefined below.

Environmental value: A characteristic thatcontributes to the quality of life provided to anarea’s inhabitants, i.e., the ability of the area toprovide desired functions such as food, cleanwater and air, aesthetic experience, recreation,and desired animal and plant species. Forexample, productivity, sustainability, biodiver-sity, fishability, biological integrity.

Assessment endpoint: An explicit expressionof the environmental value that is to be pro-tected. For example, population abundance ormortality, contaminant concentrations in apopulation, susceptibility to invasions of exoticspecies.

Measurement endpoint: A measurableecological characteristic that is related to thevalued characteristic chosen as the assessmentendpoint. Measurement endpoints are oftenexpressed as the statistical or arithmeticsummaries of the observations that comprisethe measurement. For example, individualgrowth, mortality, fecundity, toxicity, overtsymptomology, biomarkers, population agestructure, pollutant concentrations, speciesdiversity.

Indicator: An environmental characteristicthat can be measured to assess the status andtrends of environmental quality, i.e., the abilityto support a desired human or ecologicalcondition. EMAP uses several different types ofindicators:

• Response Indicators represent character-istics of the environment measured toprovide evidence of the ecological condi-

216


tion of a resource at the organismal,population, community, ecosystem, orlandscape level of organization.

• Exposure Indicators are characteristics ofthe environment measured to provideevidence of the occurrence or magnitudeof a response indicator’s contact with aphysical, chemical, or biological stressor.

• Habitat Indicators are physical, chemi-cal, or biological attributes measured tocharacterize conditions necessary tosupport an organism, population, commu-nity, or ecosystem in the absence ofpollutants (e.g., substrate of streambottom; vegetation type, extent, andspatial pattern).

• Stressor Indicators are characteristicsmeasured to quantify natural processes,environmental hazards, or managementactions that can effect changes in expo-sure and habitat (e.g., climate fluctua-tions, pollutant releases, species intro-ductions). Information on stressors willoften be measured and monitored byprograms other than EMAP.

Previous work on indicators for use in theSan Francisco Estuary include the NationalOceanic and Atmospheric Administration’s(NOAA) Status and Trends Program SanFrancisco Bay Study. NOAA proposed a set ofcriteria for selection of biological effects mea-sures and evaluated 16 endpoints from sevenecological indicators including sediment bioas-says, benthos, and fish. Most of NOAA’s indica-tors performed well and could qualify as candi-date indicators for the Status and TrendsProgram (NOAA, 1989).

The State Board’s Bay Protection and ToxicCleanup Program (BPTCP) proposed criteriafor selection of biological effects measures. TheBPTCP does not have a formal definition ofindicators, but uses measurements to guidetheir identification and designation of “hotspots.” Their documentation states that “themost appropriate and scientifically defensibleapproach currently available appears to bechoosing not one, but an array of tests thatdetermine multiple endpoints using a number

of individual species or ecological assemblages,and that can also assess various routes of expo-sure” (BPTCP, 1993). Their measurements mayinclude toxicity testing, histopathology, biomark-ers, and benthic community analysis.

Many other reports and papers have beenwritten about biological indicators. Criteria forbioaccumulation indicators were considered byPhillips and Segar (1986), criteria for biomarkerindicators were discussed by Mayer et al. (1992),and criteria for indicator species were discussedby Young and Young (1982).

Workshop Results

In preparation for the workshop, backgroundmaterial on the RMP and ecological indicatorswere produced. A listing of indicators commonlyused in aquatic and sediment bioassays, bioaccu-mulation, and biomarker measurement was alsoproduced (Suer, 1995). Copies of the workshoppreparatory materials are available from the SanFrancisco Estuary Institute (SFEI).

Approximately 50 scientists attended theone-day workshop representing a wide range ofagencies or companies and expertise (Table 3).The workshop began with presentations on theRMP, the need for additional ecological indica-tors, and background on ecological indicatorsincluding a review of indicators and their appli-cation. Most of that information is presented inthis summary.

For use in the RMP it was suggested that asuite of ecological indicators should be identifiedthat could reflect effects including those from:

• several “important” habitat types,• several levels of organization, e.g., molecu-

lar to ecosystem,• several trophic levels or ecological com-

partments,• a variety of contaminant types, and• reflect results of management actions.

It was also suggested that habitat andexposure indicators (similar to EMAP) should beidentified and measured synoptically withresponse indicators in order to develop under-standing of the relationships between them.

Workshop participants were provided with aset of draft criteria for RMP indicators (Table 4)


217

Rob Aldenhuysen California State University—BiologyBrian Anderson Marine Pollution Studies LaboratoryJack Anderson Columbia Analytical Services, Inc.John Andrew US Environmental Protection AgencyAndree Breaux SFB RWQCBGeoff Brosseau BASMAACindy Brown US Geological SurveyJay Davis San Francisco Estuary InstituteDebra Denton US Environmental Protection AgencyJody Edmunds US Geological SurveyChris Foe Central Valley RWQCBMichael Fry University of CaliforniaWill Gala Chevron Products CompanyTom Gandesbery SFB RWQCBM.H. Garcia California State University—BiologyJordan Gold Applied Marine SciencesSteve Hansen SR Hansen & AssociatesSusan Hatfield US Environmental Protection AgencyBruce Herbold US Environmental Protection AgencyRainer Hoenicke San Francisco Estuary InstituteErika Hoffman US Environmental Protection AgencyFrances Hostettler US Geological SurveyJohn Hunt University of California, Santa CruzMichael Kellogg City & County of San FranciscoChris Kitting California State University—BiologyDianne Kopec Earth Island InstituteOscar Mace US Geological SurveyJeff Miller AQUA-ScienceTrish Mulvey Clean South BayFrancis Parchaso US Geological SurveyWilfred Pereira US Geological SurveyHarlan Proctor California Department of Water ResourcesBob Risebrough Bodega Bay InstituteJim Salerno City and County of San FranciscoSteven Schwarzbach US Fish & Wildlife ServiceRobert Spies Applied Marine SciencesMark Stephenson California Department of Fish & GameLynn Suer SFB RWQCBKaren Taberski SFB RWQCBPatti TenBrook EBMUDBruce Thompson San Francisco Estuary InstituteJanet Thompson US Geological SurveyAmy Wagner US Environmental Protection AgencyDon Weston University of California—EEHSLDave Young US Environmental Protection Agency

Table 3. Ecological indicators workshop participants.

218


to help in the evaluation of various proposedcandidate indicators. Some of the work groupsmodified these criteria (Table 8).

The workshop participants broke into threegroups:

1. water column indicators,

2. sediment indicators, and

3. upper trophic level indicators.

Each group was given the tasks of:1. ratifying or modifying proposed criteria in

Table 5,

2. focusing on response indicators, and

3. discussing and rating currently used RMPand new candidate indicators using acommon format.

The types of indicators to be consideredmay include those in Table 4. Workshop partici-pants suggested candidate indicators, thenrated them based on the criteria in Table 5 oras modified. The ratings are not included inthis summary because the lists of indicators arenot comprehensive.

Water Column Indicators

The water column indicator work groupreviewed the proposed list of criteria for theusefulness of ecological response indicators to“pressure” or “stressors” in the Estuary’s open-water habitat. The group agreed that theproposed criteria were useful and modified afew. Changes in the originally proposed word-ing listed in Table 5 are in italics:

1. The measurement endpoint is ecologicallyrelevant.

2. Use (historically) resident species or acritical life stage in the Estuary.

3. The measurement endpoint can be easilyand unambiguously interpreted. It mea-sures a consistent response (accounting fornatural variation, such as seasonality),and it has a high signal-to-noise ratio.

4. Adequately and quickly reflects temporaland spatial changes in contaminantconcentrations in water or sediment.

5. Can be used throughout the region, e.g.,over a wide salinity range and seasonally.

6. Is cost-effective, easily measured, and haswell developed protocols.

The work group developed a list of candi-date response indicators of “stressors” or“pressures” affecting them and subsequentlyranked each based on each of the six rankingcriteria. The matrix, including commentspertaining to each candidate indicator, is shownin Table 6.

The candidate indicators discussed by thework group can be placed into four generalcategories:

1. bioassays with various endpoints (growth,mortality, condition),

2. population densities of key species,

3. biomarkers (fish histopathology, enzymeinduction, reporter genes), and

4. contaminant body burdens.

Several comments were made in relation tothese indicator categories: bioassays need toexplicitly state measurement endpoints and lifestages, and laboratory experiments need to becombined with field measurements to addressthe “ecological relevance” criterion.

Population density measurements of keyspecies need to be related to some kind ofbenchmark or baseline. Few are capable ofsorting out natural from human-induced“pressures”.

The ecological relevance of biomarkersdepends on how they are used, and the workgroup deferred discussion on this subject. Theenzyme inductors can be used as screeningtools and for prioritization. Histopathologyevaluation is a useful tool if tied to othermeasurements and bioassays. These kinds ofevaluations are very species- and life stage-specific.

Contaminant body burdens are not aresponse indicator per se, but they serve as arelative measurement of improvement in“pressures”.

Sediment Indicators

The sediment indicators work group dis-cussed both laboratory and field sedimentindicators. The group only had time to discuss


219

and evaluate ten of the indicators in Table 7, butconsidered bioassays, fish, benthos, wetlands, eelgrass, and exposure indicators. Evaluations forthe remaining entries were returned after theworkshop. Obviously, many other indicatorscould be considered and rated for use in the RMP(e.g., those listed in Suer, 1995).

The sediment group adopted the generalcriteria in Table 5 per se. First they discussed the

currently used RMP sediment indicators—theEohaustorius 10-day bioassay and the larvalbivalve elutriate bioassay. Those indicatorsreceived moderate ratings. Among the laboratoryindicators, the larval bivalve bioassay usingundisturbed sediment water interface samplesreceived the highest average rating, but thecurrently used Eohaustorius and larval bivalveelutriate bioassays were rated nearly as high.

Ecosystem Indicatorsprimary productionfisheries productiondiversity and abundance of top predatorshealth of top predators (re: chlorinated

hydrocarbons)characteristics of special features (size and

position of the null zone)balance of habitat typesspecies extinctionsintroduced species

Communityspecies richnessdiversitydominancebacterial activityshort lived opportunists vs. longer lived

“climax” speciesnematode/copepodpresence of indicator speciesbacterial abundance/activity: ATPbenthic metabolismnuisance species

Populationdensity (BACI)productionaltered allelic frequency—toxicological/adaptiveparasite load

Individual and organ systemgrowthhormone levelreproductive successimmune function (macrophage phagocytosis)diseasebioassaysgenetic alterationteratogenicity

Tissuehistopathology (hyperplasia, necrosis, melanin

macrophage centers, etc.)

Cellularmetallothioneinsmixed-function oxidaseschromosomal aberrationsactivated oncogenessister chromatid exchangelysosomal latencyheat stress proteins

Table 4. Examples of ecological indicators for several levels of biological organization.

1. Endpoint is ecologically relevant (may be linked).2. Use resident species.3. Endpoint can be easily and unambiguously interpreted. It measures a consistent

response (accounting for natural variation such as seasonality), it has a highsignal-to-noise ratio.

4. Adequately reflects changes in contaminant concentration in water or sediment.5. Can be used throughout the region. e.g., over a wide salinity range, seasonally.6. Cost effective, easily measured, well developed protocols.

Table 5. General criteria for ecological indicators.

220


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19

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22

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. Can

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ksh

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221

Ca

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Ind

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All

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(elu

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gro

wth

All

Cag

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ph

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Po

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All

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Po

pu

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le 7

. Can

did

ate

sed

imen

t in

dic

ator

s d

iscu

ssed

at

the

wor

ksh

op.

222


Discussions highlighted the importance ofspecifying the exact test or sampling protocol,whether the test used bulk sediment or spikedsediments, which bivalve species to use, theexposure medium (water or sediment), and theeffectiveness of the indicator.

Among the field indicators, the use of anexposure biomarker, P450, in fish was rated thehighest. There was considerable support fromthe sediment work group that field indicatorswere more important than laboratory indicatorsin overall ecological assessments.

Many of the indicators discussed could bespecified better. For example, separate ratingscould be produced for a number of different fishcommunity indicators (abundances, diversity,biomass, production, catch statistics, etc.)Similarly, wetland indicators could be greatlyspecified to include what wetland types (sea-sonal, diked, etc.), which plant or animal speciesto focus on, etc.

Upper Trophic Level Indicators

Much of the discussion in the upper trophiclevel work group centered on the criteria to beused in the evaluation of indicators. The draftlist of criteria provided to the work groups (Table5) was modified and expanded to a list of tencriteria (Table 8).

Since many indicators are available forevaluation of contaminant effects in high trophic

level species, several different indicators foreach species were discussed (Table 9). The groupevaluated two species: double-crested cormo-rants and harbor seals. Black-crowned nightherons and avocets/stilts were mentioned asspecies that may also be useful indicators, butthe group did not have time to evaluate specificmarkers for these species.

The types of indicators considered includedthose for molecular, tissue, individual, andpopulation levels. The molecular and tissuebiomarkers have the advantage of being relatedto specific contaminants or contaminant classes,but are less closely linked to population leveleffects. The population level indicators, on theother hand, are closely linked to population leveleffects, but are difficult to relate to contami-nants in general, much less particular contami-nants. Combinations of markers from both highand low levels of organization can provideinformation that is both ecologically relevantand attributable to specific contaminants.

Discussion and Conclusions

The workshop provided the beginning ofdiscussion and consideration of which indicatorsthe RMP should be using. Based on this sum-mary, it is obvious that many indicators areavailable for consideration to expand the list ofindicator candidates. Before any list of indicatorcandidates will be useful to the RMP, much

1. Ecological relevance1. Indicator of exposure 2: Adverse effect on individual 3: Direct effects on population

2. Uses resident species. Indicator response measured is a result of contaminants accumulatedfrom the Estuary

3. Endpoint can be easily and accurately measured. It measures a consistent response (account-ing for natural variation such as seasonality) and has a high signal-noise ratio.

4. Adequately reflects changes in contaminant concentration in water or sediment. Responsive tovariation in contaminant concentrations within the Estuary and from year to year.

5. Can be used throughout the region (over a wide salinity range), seasonally6. Cost effective, easily measured, well developed protocol7. Helps to identify sources of contamination8. Linked to human health. Consumes prey that are part of human food chain or is directly con-

sumed by humans.9. Indicators of regional patterns in contamination

10. Suitable reference populations available.

Table 8. Revised criteria for evaluation of upper trophic level indicators.


223

more specific RMP objectives and assessmentquestions need to be stated that specifically linkobjectives to indicators. In that regard, the EMAPframework provides a useful model.

The RMP steering committee is currentlyconsidering new objectives and assessmentquestions that may provide the cornerstones for arevised RMP indicator framework. The revisedobjectives and assessment questions will beconsidered in the 1997 Program Review. At thattime, the results of this workshop and futureefforts to determine indicators will become useful.It is envisioned that the RMP will eventuallyutilize a suite of indicators that, together, willprovide an assessment of the condition of theEstuary in terms of contamination.

There are several other efforts to determineuseful ecological indicators in the region. TheEcotoxicology Unit of the Office of Environmental

Health Hazard Assessment (OEHHA) has beendeveloping guidance and methodologies foridentifying ecological endpoints to evaluatepotential adverse effects to ecosystems fromchemical stressor exposure. However, theirwork does not focus on open water estuarinehabitat, but does include wetlands. Their reportwill be available in late 1996.

In support of the CALFED process, a seriesof workshops were held in late 1995/early 1996to determine ecosystem indicators. Their reportis in preparation.

Working with these programs, as well asevolving programs in wetlands and watershedsat SFEI, will eventually provide a battery ofecological indicators that may be used toevaluate the overall condition of the SanFrancisco Estuary.

Table 9. Evaluation of upper trophic level indicators in relation to criteria forecological indicators.

Candidate Indicator Indicator Type Contaminant Type sDouble-crested EROD Molecular marker Dioxin TEQs (PCBs, dioxins)cormorants Eggshell thickness Tissue DDE

Hatchability, deformities Individual AllReproductive success

(colony production)Population All

Retinol/retinol palmitate Molecular marker Dioxin TEQs (PCBs, dioxins)Harbor Seals Pup ratio (pup/non-pup) Population All

Population size Population AllRetinol/retinol palmitate Molecular marker Dioxin TEQs (PCBs, dioxins)

Black-crowned EROD Molecular marker Dioxin TEQs (PCBs, dioxins)night herons Eggshell thickness Tissue DDE

Hatchability, deformities Individual AllRetinol/retinol palmitate Molecular marker Dioxin TEQs (PCBs, dioxins)Reproductive success


American avocets/ Hatchability, deformities Individual Allblack-necked stilts Reproductive success


224


1995 Intercomparison ExerciseRainer Hoenicke and Sarah LoweSan Francisco Estuary Institute

An important function of the RegionalMonitoring Program (RMP) is to provide dataon background or ambient concentrations forcomparison to monitoring data collected bydischarge agencies or their contractors. In orderto accomplish this, it is necessary to demon-strate that samples taken near outfalls ornonpoint sources are collected and analyzed ina comparable manner to those collected as partof the RMP. Comparability is defined as “theconfidence with which one data set can becompared to another” (Stanley and Verner,1985). In addition, a number of Bay Area wastewater treatment plant laboratories are inter-ested in directly participating in the analyses ofsediment and bivalve tissue, and would like toevaluate their performance relative to eachother and the laboratories currently analyzingRMP samples. These laboratories are part ofthe Bay Area Dischargers Association and willbe referred to throughout this chapter as BADAlaboratories.

Although individual laboratories canevaluate the performance of their own analyti-cal operations against standard referencematerials, the most complete mechanisms forthe evaluation of analysis system variability isthrough the use of split samples. Comparabilityis then assessed through application of appro-priate statistical tests (e.g., t-tests, ANOVA),and results are considered comparable if thereare no significant differences, or if data meetpre-determined data quality objectives.

Objectives

The 1995 Intercomparison Exercise had thefollowing objectives:

1. To establish a measure of comparabilitybetween analytical operations among locallaboratories and for initial demonstrationsof capability using a non-certified SanFrancisco Bay sediment sample (SFERM-

S95) collected at an RMP site (BD50, NapaRiver).

2. To check relative performance amongparticipating laboratories through theintercomparison for trace metals andorganics in marine sediments and biologi-cal tissues sponsored by the NationalOceanic and Atmospheric Administration(NOAA).

3. To ascertain the overall performance of theparticipating laboratories with regard toanalytical capabilities, project manage-ment, data documentation, timeliness ofdata submission, and responsiveness toproblem solutions.

These exercises also provided a tool forcontinuous improvement of laboratory mea-surements by helping analysts identify andresolve problems in methodology and/or QA/QC,and by pointing out and subsequently rectifyingchallenges in data transfer and management.We chose not to mention individual laboratoriesby name in this chapter, but rather assignednumbers that are known only to the individuallaboratories.

Project Organization

SFEI provided overall project oversight anddeveloped the objectives, design, and implemen-tation plan. Initially, RMP Participating Agencyrepresentatives were contacted to determinethe level of interest in intercomparison and toagree on an intercomparison approach. For thefirst round of performance evaluations, threeseparate analyses were agreed on: the local,non-certified sediment reference sample(SFERM-S95), the sediment samples, andtissue samples distributed by the NationalResearch Council Canada (NRCC) and theNational Institute of Standards and Technology(NIST) as part of the NOAA-sponsored inter-comparison.


225

The CDFG laboratory completely digestedthe four sediment sub-samples using hydrofluo-ric acid, while all other laboratories used aquaregia for digestion (Flegal, 1981; Tetra Tech,1986). This represented a major differencebetween laboratories and biased the data forrefractory elements, particularly aluminum andchromium, toward the low end for those labora-tories using aqua regia extraction. The sameextraction procedure was used for sedimentsamples analyzed for the NOAA-sponsoredintercomparison exercise.

In order to determine laboratory perfor-mance, three criteria were used: ability to meettarget method detection limits, ability to meetprecision targets, and ability to meet accuracytargets as specified in the 1994 Quality Assur-ance Project Plan.

ResultsReference material (SFERM-S95)

Eleven trace elements of interest to theRMP were evaluated and compared among allparticipating laboratories (Figure 20). BADAlaboratories only quantified the agreed-uponPCB congeners and PAH isomers (Figures 21and 22). No data are available for chlorinatedpesticides from the BADA laboratories.

Laboratory results were compared usingBonferroni (Dunn) multiple comparison tests.The Bonferroni multiple comparisons are veryconservative, i.e., they are less likely to detectstatistically significant differences betweentreatments than other tests. For our purposes,the Bonferroni test is adequate, and results arepresented in Tables 11 and 12 as the meanvalue of three to five replicates for each labora-tory and a letter grouping for each laboratory.The Bonferroni letter group for each compoundmeans that laboratories with the same letterare not significant. It should be noted, however,that those laboratories with high precision (i.e.,low intra-laboratory variance) tend to be moreoften significantly different than laboratorieswith high variability among replicates, andtherefore, the multiple comparison tests onlyprovide a general screening of laboratorydifferences, without taking into account any

Four BADA laboratories, one contractlaboratory for a number of storm water man-agement agencies, and three RMP contractlaboratories participated in the intercompari-son exercise involving the local referencesample.

Several planning meetings were held toagree on the analyte list, extraction proceduresfor sediment, and data submittal procedures.The intercomparison plan was finalized prior tothe distribution of samples and served as areference document.

Two of three RMP contract laboratories andfive BADA laboratories (the same four thatparticipated in the SFERM-S95 analysis andone additional laboratory) participated in theNOAA exercise involving an unknown and areference sample for both sediment and tissue.The laboratories were requested to followinstructions received through the distributorsof the sample material (NRCC and NIST) andto submit data directly, rather than throughSFEI. Both exercises were logistically quitechallenging due to the number of participantsinvolved. Table 10 shows the different samplesanalyzed by the various laboratories.

Methods

A large sample of sediment from the NapaRiver station (BD50) was collected in February1995 with a dykon-coated van Veen grab usingstandard RMP sampling methods. The samplewas transferred to an independent laboratory(California Department of Fish and Game(CDFG) laboratory, Moss Landing) and homog-enized under clean conditions. “Mega-sample”homogeneity was determined by analyzing foursub-samples each for trace elements and traceorganics. Trace elements were analyzed byCDFG and trace organics at Long MarineLaboratory (UCSC Trace Organics Facility).Results from these initial determinations wereincluded in the overall evaluation of laboratoryperformance. No specific analysis methods wereprescribed, although data quality objectivesand target method detection limits were agreedupon prior to analysis.

226


Tab

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√

Tra

ce

Org

anic

s:T

issu

e, F

ish

Hom

ogen

ate

III (

QA

95F

SH

3)√

√√

√1

Tis

sue,

CR

M C

arp-

1√

√√

√ 1

Tra

ce

Org

anic

s:S

edim

ent,

Sed

imen

t V

√√

Sed

imen

t, S

RM

194

1a√

√

1 Onl

y P

CB

s w

ere

subm

itted

.


227

other factors that identify laboratory perfor-mance.

Cadmium, mercury, selenium, and silverexhibited high inter-laboratory variability.Chromium, copper, nickel, and zinc resultswere comparable among laboratories (excludingCDFG, having used a different extractionprocedure), while arsenic and lead were inter-mediate.

Contrary to expectations, PCB concentra-tions in SFERM-S95 were low and close to thedetection limit. Only four congeners for whichsemi-quantitative values were obtained couldbe compared among laboratories. Twenty-twoPAH isomers were analyzed by four laborato-ries, two of them BADA laboratories. For manyPAH isomers close to the detection limit, resultsof the participating laboratories varied widely.

Comparisons to RMP Data Quality Objectives

For the initial intercomparison exercise, thetarget method detection limit was met only forchromium, nickel, and zinc by all participatinglaboratories (Table 13). All BADA laboratorieswere able to meet the target for copper, butnone of them were able to meet MDL targets forcadmium and silver, and only one BADAlaboratory met the target for selenium. Of the

two BADA laboratories that measured PCBsand PAHs, one met MDL targets in all cases,while the other’s detection limits were almostfive times higher (Table 14).

The precision measurements for almost allthe trace element results were lower for the fiveBADA laboratories compared to the RMPlaboratories and the contract laboratory forstorm water agencies, although they werewithin precision target range for all elementsexcept aluminum, selenium, silver, and cad-mium which were exceeded by one or two of theBADA laboratories (Table 15).

NOAA-95

Five BADA laboratories and one RMPcontract laboratory participated in the NOAA/9Ninth Round Intercomparison for Trace Metalsin Sediments and Biological Tissue (Figures23–26).

One BADA laboratory and two RMP con-tract laboratories participated in the NIST/NOAA NS&T/EPA EMAP IntercomparisonExercise Program for Organic Contaminants inthe Marine Environment, 1995 (Figures 27–30).Two BADA laboratories analyzed 1994 NOAAsediment for organic contaminants, which willbe compared to the other 1994 participants.

Note: Laboratory 4 used the hydrofluoric acid extraction method.

Tetra Tech Method Ag Al As Cd Cr Cu FeLaboratory 2 . . . . 12.30 (CB) . . 130.00 (B) 66.57 (A) . .Laboratory 3 . . 94320.00 (A) 19.14 (A) 0.21 (C) 103.27 (C) 58.63 (A) 36541.00 (B)Laboratory 9 . . . . 15.53 (B) . . 124.67 (B) 71.10 (A) . .Laboratory 4 0.25 (B) 60000.00 (B) 9.33 (C) 0.30 (B) 200.00 (A) 68.75 (A) 55500.00 (A)Laboratory 5 0.35 (A) 29211.00 (C) 10.18 (C) 0.44 (A) 89.30 (C) 64.47 (A) 39737.00 (BA)Laboratory 11 0.36 (A) 32535.00 (C) 15.03 (B) 0.26 (CB) 106.33 (C) 60.33 (A) 43723.00 (BA)

Tetra Tech Method Hg Mn Ni Pb Se ZnLaboratory 2 0.35 (B) . . 94.70 (CB) 23.10 (C) . . 148.33 (CB)Laboratory 3 . . 853.90 (B) 84.15 (C) 32.27 (A) 3.16 (A) 151.28 (B)Laboratory 9 . . . . 100.30 (B) 26.23 (BC) 0.40 (B) 142.00 (CB)Laboratory 4 0.27 (C) 941.75 (A) 125.00 (A) 31.00 (BA) . . 175.00 (A)Laboratory 5 0.45 (A) 806.14 (B) 92.81 (CB) 32.37 (A) 0.34 (B) 132.63 (C)Laboratory 11 0.34 (CB) 784.08 (B) 106.69 (B) 28.88 (BA) 0.41 (B) 145.25 (CB)

Table 11. San Francisco Estuary Reference Material-Sediment 95 trace elementmultiple comparison results using the Bonferroni (Dunn) T test, where alpha = 0.05.Below are the mean values of three replicates and the Bonferroni assigned groupings. Missingvalues are a result of the values being below the MDL, not detected, or data were not reported.Laboratory results associated with the same letter are not significantly different.

228


SF

ER

M-S

95

P

CB

sP

CB

138

PC

B 1

53P

CB

180

PC

B 1

87La

bora

tory

2

1.0

4(B

)0

.82

(B)

0.5

3(A

)0

.41

(A)

La

bo

rato

ry

12

1.2

5(A

)1

.02

(A)

0.6

0(A

)0

.45

(A)

*

Unl

iste

d P

CB

com

poun

ds w

ere

eith

er b

elow

the

dete

ctio

n lim

it or

not

rep

orte

d fo

r al

l par

ticip

atin

g la

bora

torie

s.

SF

ER

M-S

95

P

est

icid

es

1-M

ethy

lnap

htha

lene

1-M

ethy

lphe

nant

hren

e2,

6-D

imet

hyln

apht

hale

ne2-

Met

hyln

apht

hale

neA

cena

naph

then

eA

cena

naph

thyl

ene

Labo

rato

ry

28

.14

(A)

10

.60

(A)

10

.10

(A)

30

.53

(A)

7.8

4(A

)5

.09

(A)

Labo

rato

ry

5La

bora

tory

6

6.5

3(A

)5

.18

(B)

5.9

8(B

)9

.60

(C)

4.4

3(B

)5

.22

(A)

La

bo

rato

ry

12

7.4

8(A

)9

.86

(A)

16

.58

(B)

5.2

3(B

)

SF

ER

M-S

95

P

est

icid

es

Ant

hrac

ene

Ben

z(a)

anth

race

neB

enzo

(a)p

yren

eB

enzo

(b)f

lour

anth

rene

Ben

zo(e

)pyr

ene

Ben

zo(g

hi)p

eryl

ene

Labo

rato

ry

21

4.2

7(A

)5

9.9

3(B

)1

16

.67

(B)

16

1.3

3(A

)7

6.7

0(A

)6

8.1

3(B

)La

bora

tory

5

78

.95

(A)

10

5.2

6(B

)1

05

.26

(B)

78

.95

(A)

12

2.8

1(A

)La

bora

tory

6

10

.59

(A)

38

.63

(C)

87

.55

(C)

92

.57

(B)

59

.53

(B)

10

9.6

6(A

)L

ab

ora

tory

1

21

3.7

8(A

)4

6.3

3(C

)1

46

.75

(A)

14

0.7

5(A

)8

1.3

8(A

)1

31

.50

(A)

SF

ER

M-S

95

P

est

icid

es

Ben

zo(k

)flo

uran

thre

neB

iphe

nyl

Chr

ysen

eD

iben

z(a,

h)an

thra

cene

Flo

uran

thre

neF

luo

ren

eLa

bora

tory

2

42

.07

(A)

14

.03

(A)

56

.20

(B)

10

.00

(B)

11

8.3

3(B

)1

4.2

0(A

)La

bora

tory

5

87

.72

(A)

13

1.5

8(B

A)

Labo

rato

ry

62

6.5

8(B

)6

.48

(C)

51

.31

(B)

10

.03

(B)

92

.72

(C)

7.1

7(B

)L

ab

ora

tory

1

24

2.7

3(A

)9

.32

(B)

47

.58

(B)

18

.30

(A)

14

1.5

0(A

)9

.87

(B)

SF

ER

M-S

95

P

est

icid

es

Ind

en

o(1

,2,3

-cd

)pyr

en

eP

ery

len

eP

he

na

nth

ren

eP

yre

ne

Labo

rato

ry

28

8.6

7(B

)9

9.8

7(C

B)

57

.83

(A)

16

0.3

3(A

)La

bora

tory

5

10

5.2

6(B

A)

35

0.8

8(A

)4

3.8

6(B

A)

78

.95

(C)

Labo

rato

ry

68

5.8

5(B

)3

9.3

2(C

)3

3.0

9(B

)1

09

.49

(B)

La

bo

rato

ry

12

12

9.0

0(A

)1

15

.50

(B)

54

.78

(BA

)1

59

.25

(A)

Tab

le 1

2. S

an F

ran

cisc

o E

stu

ary

Ref

eren

ce M

ater

ial-

Sed

imen

t 95

(S

FE

RM

-S95

) or

gan

ics

mu

ltip

le c

omp

aris

on r

esu

lts

usi

ng

the

Bon

ferr

oni

(Du

nn

) T

tes

t, w

her

e al

ph

a =

0.05

. Bel

ow a

re t

he

mea

n v

alu

es o

f th

ree

repl

icat

es a

nd

the

Bon

ferr

oni a

ssig

ned

gro

upi

ngs

.M

issi

ng

valu

es a

re a

res

ult

of

the

valu

es b

ein

g be

low

th

e M

DL

, not

det

ecte

d, o

r da

ta w

ere

not

rep

orte

d. L

abor

ator

y re

sult

s as

soci

ated

wit

h t

he

sam

e le

tter

are

not

sig

nif

ican

tly

diff

eren

t.


229

Trace RMP-Laboratories BADA- Laboratories OtherElement Tar g et 1 1 1 3 9 2 5 1 0 4A g

MDL 0.001 0.07 0.25 1.2 0.08 0.1 0.01>10X MDL? NO NO NO NO YESAl

MDL 70 5428 0.60 1>10X MDL? NO YES YESAs

MDL 1.6 0.01 2 1.2 0.01 0.1 0.2>10X MDL? YES NO YES YES YES YESC d

MDL 0.00002 0.01 0.2 0.37 0.06 0.1 0.01>10X MDL? YES NO NO NO NO YESCr

MDL 9.44 7 2.5 1.2 0.18 0.1 0.1>10X MDL? YES YES YES YES YES YESC u

MDL 4.57 6.8 2.5 1.2 0.06 0.1 1>10X MDL? NO YES YES YES YES YESH g

MDL 0.005 0.008 5 0.002 0.20 0.02 0.03>10X MDL? YES NO YES NO NO NONi

MDL 4.28 5.9 5 3 0.20 0.1 0.1>10X MDL? YES YES YES YES YES YESP b

MDL 0.1 1 5 2.5 0.60 0.1 0.1>10X MDL? YES NO NO YES YES YESS e

MDL 2.2 0.01 0.2 1.2 0.02 0.1 0.2>10X MDL? YES NO NO YES NO NOZ n

MDL 18.9 12 2.5 1.2 0.60 1 0.02>10X MDL? YES YES YES YES YES YES

Table 13. Comparison of the method detection limits for trace elements in sediment.Sediment reference material SFERM-S95. “>10X MDL?” = Is the sample value greater than tentimes the MDL?

NOAA/9 Trace Elements

In general, statistically significant differ-ences between laboratories could be discerned,with the exception of Hg for Sediment-W, As forthe Sediment SRM BCSS-1, chromium, copperand lead for Tissue-X and silver, lead, and zincfor the tissue standard reference material, SRM1566a (Table 18).

Not all laboratories analyzed the completelist of eleven trace elements of interest to theRMP. In comparing the participating laborato-

ries with the NRCC accepted and certifiedvalues for both sediment and tissue, the per-centage of results that were within the acceptedconfidence interval (95% confidence interval)are presented in Table 19.


The data summaries did not contain themethod detection limits that were achieved byparticipating laboratories and therefore couldnot be compared to RMP targets.

230


RMP-Lab BADA-LabsUnits are in µg/Kg Tar g et 6 2 5

1-Meth y lnaphthalene MDL 5 4 5>10 X MDL? NO NO

1-Meth y lphenanthrene MDL 5 2 5>10X MDL? NO NO

2,6-Dimeth y lnaphthalene MDL 5 2 5>10X MDL? NO NO

2-Meth y lnaphthalene MDL 5 4 5>10X MDL? NO NO

Acenaphthene MDL 5 2 5>10X MDL? NO NO

Acenaphth y lene MDL 5 2 5>10X MDL? NO NO

Anthracene MDL 5 2 5>10X MDL? NO NO

Benzo (a)anthracene MDL 5 1 5 24>10X MDL? YES YES NO

Benzo (a)p y rene MDL 5 1 5 24>10X MDL? YES YES NO

Benzo (b )f luoranthene MDL 5 1 5 24>10X MDL? YES YES NO

Benzo (e)p y rene MDL 5 1 5 79>10X MDL? YES YES NO

Benzo (g hi )per y lene MDL 5 1 5 24>10X MDL? YES YES NO

Benzo (k )fluoranthrene MDL 5 1 5>10X MDL? YES NO

Biphen y l MDL 5 1 5>10X MDL? NO NO

Chr y sene MDL 5 1 5 16>10X MDL? YES YES NO

Dibenz (a,h )anthracene MDL 5 1 5>10X MDL? NO NO

Fluoranthene MDL 5 1 5 24>10X MDL? YES YES NO

Fluorene MDL 5 2 5>10X MDL? NO NO

Indo (1,2,3-cd )p y rene MDL 5 1 5 55>10X MDL? YES YES NO

Per y lene MDL 5 10 5 79>10X MDL? NO YES NO

Phenanthrene MDL 5 2 5 24>10X MDL? YES YES NO

Py rene MDL 5 1 5 24>10X MDL? YES YES NO

P C B 0 2 8 MDL 1 0.1>10X MDL? NO

P C B 1 2 8 MDL 1 0.5>10X MDL? NO

P C B 1 3 8 MDL 1 0.6>10X MDL? NO

P C B 1 5 3 MDL 1 0.2>10X MDL? NO

P C B 1 8 0 MDL 1 0.4>10X MDL? NO

P C B 1 8 7 MDL 1 0.5>10X MDL? NO

P C B 2 8 MDL 1 0.5>10X MDL? NO

4,4 ' -DDT MDL 1 1.3>10X MDL? YES

4,4 'DDD MDL 1 0.2>10X MDL? NO

4 ,4 'DDE MDL 1 0.2>10X MDL? NO

Table 14. Comparison of the method detection limits for organics insediment. Sediment Reference Material SFERM-S95. “>10X MDL?” = Isthe sample value greater than ten times the MDL?


231

Labo

rato

ry

2La

bora

tory

3

Labo

rato

ry

4S

ED

-BC

SS

-1S

ED

-WS

FE

RM

-S95

SE

D-B

CS

S-1

SE

D-W

SF

ER

M-S

95S

ED

-BC

SS

-1S

ED

-WS

FE

RM

-S95

Ag

21

XN

DA

gN

DN

DN

DA

g3

As

11

9A

s5

41

0A

s6

Cd

3C

d3

3X

61

2C

d4

Cr

87

Cr

22

7C

r7

Cu

61

1C

u1

21

1C

u5

Fe

Fe

22

32

XF

e1

1H

g1

23

Hg

56

Hg

5N

i1

6X

3N

i1

41

Ni

10

Pb

81

Pb

42

15

Pb

6S

eN

DS

eN

DN

D7

1X

Se

Zn

21

Zn

14

2Z

n7

Labo

rato

ry

5La

bora

tory

8

Labo

rato

ry

9S

ED

-BC

SS

-1S

ED

-WS

FE

RM

-S95

SE

D-B

CS

S-1

SE

D-W

SF

ER

M-S

95S

ED

-BC

SS

-1S

ED

-WS

FE

RM

-S95

Ag

ND

17

7X

15

XA

g1

1A

g1

45

ND

As

52

1A

s7

As

29

59

Cd

22

X1

41

8X

Cd

2C

d3

1C

r1

21

Cr

2C

r2

23

Cu

46

2C

u1

0C

u3

65

Fe

22

1F

e2

Fe

Hg

31

91

5H

g3

Hg

11

10

Ni

38

2N

i7

Ni

35

2P

b4

34

Pb

12

Pb

55

3S

e2

37

8S

e5

Se

30

Zn

13

1Z

n2

Zn

33

5

La

bo

rato

ry

11

La

bo

rato

ry

13

La

bo

rato

ry

10

SE

D-B

CS

S-1

SE

D-W

SF

ER

M-S

95S

ED

-BC

SS

-1S

ED

-WS

FE

RM

-S95

SE

D-B

CS

S-1

SE

D-W

SF

ER

M-S

95A

g5

18

X4

Ag

41

1A

gA

s9

As

As

2C

d4

52

Cd

71

Cd

5C

r4

51

Cr

Cr

2C

u3

41

Cu

16

X6

Cu

1F

e4

83

Fe

Fe

Hg

4H

gH

g3

Ni

32

0N

i9

4N

i2

Pb

41

3P

b3

6P

b0

Se

3S

eS

e1

Zn

45

1Z

n1

5Z

n1

NO

DA

TA

NO

D

AT

A

NO

DA

TA

NO

D

AT

AN

O

DA

TA

NO

D

AT

A

NO

D

AT

A

Tab

le 1

5. P

reci

sion

eva

luat

ion

for

th

e 19

95 s

edim

ent

trac

e el

emen

t in

terc

omp

aris

on e

xerc

ises

of

par

tici

pat

ing

lab

orat

orie

s. P

reci

sion

is d

eter

min

ed b

y th

e re

lati

ve s

tan

dard

dev

iati

on (

RS

D, a

lso

know

n a

s th

e co

effi

cien

t of

var

iati

on)

ofre

plic

ate

sam

ple

anal

yses

. Th

e R

MP

tar

get

prec

isio

n g

uid

elin

e fo

r tr

ace

elem

ents

mea

sure

d in

sed

imen

t is

±15%

(±35

for

As,

Hg,

an

dS

e). C

ompo

un

ds t

hat

exc

eede

d th

e R

SD

are

indi

cate

d w

ith

an

X. N

D in

dica

tes

not

det

ecte

d, b

lan

ks in

dica

te n

ot a

nal

yzed

.

SE

D-B

CS

S-1

= N

OA

A/9

Sed

imen

t Sta

ndar

d R

efer

ence

Mat

eria

l; S

ED

-W =

NO

AA

/9 S

edim

ent U

nkno

wn;

SF

ER

M-S

95 =

RM

P S

edim

ent R

efer

ence

Mat

eria

l

232


Labo

rato

ry

2La

bora

tory

3

Labo

rato

ry

8T

ISS

-SR

M15

66T

ISS

-XT

ISS

-SR

M15

66T

ISS

-XT

ISS

-X (s

ampl

e 1)

TIS

S-X

(sam

ple

2)A

g1

8A

g1

43

6X

Ag

4A

s1

2A

s3

12

As

4C

d1

1C

d2

3C

d2

1C

r3

0X

Cr

41

4C

r5

14

Cu

14

Cu

14

Cu

91

Hg

2H

g1

56

Hg

10

2N

i1

3N

i1

71

1N

i8

Pb

42

XP

b4

4X

16

Pb

51

X3

9X

Se

12

Se

22

36

XS

e9

Zn

6Z

n3

8Z

n4

Labo

rato

ry

9La

bora

tory

13

TIS

S-S

RM

1566

TIS

S-X

TIS

S-S

RM

1566

TIS

S-X

Ag

14

Ag

15

As

As

Cd

13

Cd

26

Cr

34

Cr

Cu

12

Cu

15

Hg

13

8H

gN

i7

7N

i1

32

9X

Pb

88

Pb

19

9S

e5

6S

eZ

n1

3Z

n4

2

NO

DA

TA

Tab

le 1

6. P

reci

sion

eva

luat

ion

for

th

e 19

95 t

issu

e tr

ace

elem

ent

inte

rcom

par

ison

exe

rcis

es o

f p

arti

cip

atin

gla

bor

ator

ies.

Pre

cisi

on is

det

erm

ined

by

the

rela

tive

sta

nda

rd d

evia

tion

(R

SD

, als

o kn

own

as

the

coef

fici

ent

of v

aria

tion

) of

repl

icat

e sa

mpl

e an

alys

es. T

he

RM

P t

arge

t pr

ecis

ion

gu

idel

ine

for

trac

e el

emen

ts m

easu

red

in t

issu

e is

±15

% (±

35 f

or A

s, H

g,an

d S

e). C

ompo

un

ds t

hat

exc

eede

d th

e R

SD

are

indi

cate

d w

ith

an

X. B

lan

ks in

dica

te n

ot a

nal

yzed

.

TIS

S-S

RM

1566

= N

OA

A/9

Tis

sue

Sta

ndar

d R

efer

ence

Mat

eria

l; T

ISS

-X =

NO

AA

/9 T

issu

e U

nkno

wn.


233

Tis

sue

Inte

rcom

pari

son

Org

anic

s:

NIS

T/N

OA

A

95

(Fis

h ho

mog

enat

e II

I (Q

A95

fsh3

) an

d th

e S

tand

ard

Ref

eren

ce

Mat

eria

l C

AR

P-1

).

BA

DA

L

ab

ora

tory

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P

La

bo

rato

ryO

the

r L

ab

ora

tori

es

Labo

rato

ry

2La

bora

tory

6

Labo

rato

ry

7La

bora

tory

12

QA

95

FS

H3

SR

M C

AR

P-1

Q

A9

5F

SH

3S

RM

CA

RP

-1

QA

95

FS

H3

SR

M C

AR

P-1

Q

A9

5F

SH

3S

RM

CA

RP

-12

,4'-

DD

D2

43

41

7X

22

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DD

E1

12

4X

17

23

X8

2,4

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DT

39

54

11

15

X4

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D4

52

21

7X

34

,4'-

DD

E3

42

21

29

4,4

'-D

DT

11

32

46

X1

0a

lph

a-H

CH

86

3ci

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lord

an

e3

63

31

08

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r4

95

55

4d

ield

rin

99

42

13

13

ga

ma

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54

81

55

he

pta

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44

61

13

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69

17

X1

35

2P

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1

81

5X

11

10

62

91

7X

7P

CB

2

81

5X

15

11

94

37

6P

CB

4

41

28

56

22

11

9P

CB

5

22

8X

56

45

21

09

PC

B

10

55

72

32

61

27

PC

B

11

86

10

34

55

11

9P

CB

1

28

36

46

35

13

6P

CB

1

53

35

71

31

6X

31

01

0P

CB

1

80

35

55

23

12

8P

CB

1

95

17

X2

1X

85

39

2X

32

6P

CB

2

06

93

4X

13

84

54

5P

CB

2

09

14

73

63

71

6P

CB

1

01

/90

06

34

62

71

0P

CB

1

38

/16

3/1

64

51

03

62

51

18

PC

B

17

0/1

90

10

27

X1

34

33

34

PC

B

18

7/1

82

75

48

25

91

1P

CB

6

6/9

55

11

63

42

14

12

PE

ST

ICID

E D

AT

A

NO

T A

VA

ILA

BLE

Tab

le 1

7. P

reci

sion

eva

luat

ion

for

th

e 19

95 t

issu

e or

gan

ics

inte

rcom

par

ison

exe

rcis

es o

f p

arti

cip

atin

g la

bor

ator

ies.

Pre

cisi

on is

det

erm

ined

by

the

rela

tive

sta

nda

rd d

evia

tion

(R

SD

, als

o kn

own

as

the

coef

fici

ent

of v

aria

tion

) of

rep

lica

te s

ampl

ean

alys

es. T

he

RM

P t

arge

t pr

ecis

ion

gu

idel

ine

for

orga

nic

com

pou

nds

mea

sure

d in

tis

sue

is ±

15%

. Com

pou

nds

th

at e

xcee

ded

the

RS

Dar

e in

dica

ted

wit

h a

n X

.

234


Se

dim

en

t-W

Ag

Al

As

Cd

Cr

Cu

Fe

Hg

Mn

Ni

Pb

Se

Zn

Labo

rato

ry

20

.14

(C)

20

.62

(B)

2.1

5(B

A)

40

.74

(CD

)1

24

.80

(BA

)1

.50

(A)

23

.74

(C)

21

3.6

0(B

A)

0.2

6(D

)3

32

.60

(BA

)La

bora

tory

3

2.0

0(A

)1

.79

(B)

22

.38

(B)

1.9

4(B

DC

)3

5.9

0(E

D)

11

4.6

2(B

)2

.70

(B)

1.3

6(A

)3

38

.52

(B)

23

.48

(C)

18

3.8

8(C

)4

.00

(A)

29

4.1

2(C

)La

bora

tory

5

0.6

6(B

)2

6.9

0(A

)2

.32

(A)

46

.58

(B)

13

5.8

0(A

)2

.83

(BA

)1

.47

(A)

33

5.5

0(B

)2

8.4

0(B

A)

20

8.4

0(B

AC

)1

.30

(B)

35

3.4

0(A

)La

bora

tory

9

0.2

5(C

)1

6.9

2(C

)1

.69

(D)

46

.10

(CB

)1

26

.40

(BA

)1

.45

(A)

41

5.2

0(A

)2

4.2

2(B

C)

19

1.4

0(B

C)

0.7

3(C

)3

29

.40

(BA

)L

ab

ora

tory

1

10

.41

(CB

)1

.28

(C)

2.1

5(B

A)

34

.80

(E)

13

7.4

2(A

)2

.39

(C)

31

7.4

0(B

)2

5.7

6(B

AC

)3

5.1

4(D

)3

43

.80

(A)

La

bo

rato

ry

13

0.2

6(C

)2

.08

(BA

C)

13

1.8

0(A

)2

8.9

0(A

)2

06

.00

(BA

C)

33

8.0

0(B

A)

Labo

rato

ry

80

.33

(CB

)5

.21

(A)

20

.00

(B)

1.8

3(D

C)

60

.20

(A)

13

9.8

0(A

)3

.09

(A)

1.2

4(A

)4

62

.40

(A)

27

.48

(BA

C)

22

2.4

0(A

)1

.20

(B)

31

6.6

0(B

C)

Se

dim

en

t B

CS

S-1

Ag

Al

As

Cd

Cr

Cu

Fe

Hg

Mn

Ni

Pb

Se

Zn

Labo

rato

ry

2La

bora

tory

3

2(A

)2

.72

6(A

)1

2.4

4(A

)0

.28

(A)

57

.1(B

)1

5.7

2(B

A)

3.1

24

(A)

0.1

99

(A)

19

1.2

(B)

48

.44

(B)

20

.6(B

)4

(A)

10

7(B

A)

Labo

rato

ry

50

.34

(B)

1.4

24

(C)

9.0

8(A

)0

.24

(A)

51

.88

(B)

11

(D)

2.6

42

(C)

0.1

77

(B)

19

9(B

)5

1.5

(BA

)1

9.8

(BC

)0

.31

6(B

)9

9.3

6(C

)La

bora

tory

9

0.0

8(C

)1

0.7

2(A

)0

.19

2(A

)6

8.6

2(A

)1

7.4

(A)

0.1

6(B

)2

12

.8(A

)5

1.5

(BA

)1

8.1

2(C

)1

09

.8(A

)L

ab

ora

tory

1

10

.11

(C)

1.9

04

(B)

0.2

62

(A)

53

.6(B

)1

2.5

4(D

C)

2.9

14

(B)

17

8.8

(C)

52

.44

(BA

)2

1.4

6(B

A)

10

3.8

(BC

)L

ab

ora

tory

1

30

.08

(C)

0.2

76

(A)

14

.08

(BC

)5

4.6

6(A

)2

2.5

4(A

)1

01

.2(C

)La

bora

tory

8

Tis

sue

-XA

gA

lA

sC

dC

rC

uF

eH

gN

iP

bS

eZ

nLa

bora

tory

2

0.3

3(B

C)

3.3

0(B

)1

.27

(BC

)1

.85

(A)

10

.92

(A)

0.1

6(B

)0

.68

(BA

C)

16

.40

(A)

1.2

8(B

)1

13

.00

(A)

Labo

rato

ry

30

.32

(C)

15

9.6

0(B

)3

.68

(B)

1.1

3(C

)1

.49

(A)

9.9

6(A

)3

77

.60

(C)

0.1

8(A

)0

.48

(C)

11

.38

(A)

2.5

4(A

)1

03

.52

(BA

)La

bora

tory

9

0.5

9(A

)1

.35

(BA

)1

.65

(A)

9.8

5(A

)4

24

.40

(B)

0.1

8(A

)0

.89

(A)

9.6

5(A

)1

.76

(B)

10

4.4

0(B

A)

La

bo

rato

ry

13

0.5

0(B

A)

1.4

3(A

)1

1.1

2(A

)0

.87

(BA

)1

4.5

6(A

)1

01

.64

(B)

Labo

rato

ry

80

.58

(A)

47

0.8

0(A

)7

.08

(A)

1.3

0(B

A)

1.8

6(A

)1

0.5

0(A

)4

65

.20

(A)

0.1

5(B

)0

.65

(BC

)1

4.5

6(A

)1

.86

(BA

)9

5.6

0(B

)

Tis

sue

S

RM

-15

66

aA

gA

lA

sC

dC

rC

uF

eH

gN

iP

bS

eZ

nLa

bora

tory

2

Labo

rato

ry

31

.5(A

)1

00

(A)

4.0

3(B

)0

.87

6(B

)5

9.8

6(C

)4

63

.4(B

)0

.10

5(A

)2

.4(A

)0

.38

(A)

3.0

4(A

)8

24

.4(A

)La

bora

tory

9

1.5

6(A

)4

.21

6(A

)1

.32

8(A

)6

2.3

(B)

49

1.6

(A)

0.0

72

(B)

2.5

08

(A)

0.3

88

(A)

1.9

8(B

)8

31

(A)

La

bo

rato

ry

13

1.5

1(A

)4

.01

6(B

)6

5.7

(A)

1.7

8(B

)0

.40

6(A

)8

47

.6(A

)La

bora

tory

8

18

9(B

)

Tab

le 1

8. N

OA

A/9

tra

ce e

lem

ent

mu

ltip

le c

omp

aris

on r

esu

lts

usi

ng

the

Bon

ferr

oni

(Du

nn

) T

tes

t, w

her

e al

ph

a =

0.05

. Bel

ow a

re t

he

mea

n v

alu

es o

f th

ree

repl

icat

es a

nd

the

Bon

ferr

oni a

ssig

ned

gro

upi

ngs

. Mis

sin

g va

lues

are

a r

esu

lt o

f th

e va

lues

bei

ng

belo

w t

he M

DL

s, n

otde

tect

ed, o

r da

ta w

ere

not

rep

orte

d. L

abor

ator

y re

sult

s as

soci

ated

wit

h t

he

sam

e le

tter

are

not

sig

nif

ican

tly

diff

eren

t.


235

RMP -Laboratories BADA- Laboratories OtherTrace Elements 1 1 1 6 3 2 5 9 1 3 1 2 8

SedimentNOAA/9 (Sed-W & BCSS-1) 75 NA NA 64 70 82 79 92 NA 100

TissueNOAA/9 (TISS-X & SRM1566) NA NA NA 86 90 NA 100 100 NA 100

Organics 1 1 1 6 3 2 5 9 1 3 1 2 7Sediment

NIST SRM 1941A NA NA 27 NA 40 39 NA NA NA

TissueNIST/NOAA NA NA 61 NA 72 NA NA NA 79 88 (QA95FSH3 & CARP-1 )

Table 19. Percentage of the 1995 intercomparison studies performed by each laboratory thatwere within the 95% confidence interval or the RMP accuracy guidelines. Results were countedif one or more of the replicates fell within either limit.

The inter-laboratory precision evaluationfor both sediment and tissue is presented as therelative standard deviation (RSD) of threereplicate samples run by each laboratory.Results are presented in Tables 15 and 16. Itshould be noted that Laboratory 9 showedexcellent precision, for all samples analyzed, forboth sediment and tissue. In sediment, cad-mium and silver did not meet precision targetranges for some laboratories, while lead provedto be difficult to measure in tissue.

NOAA/NIST Organics

Of the participating laboratories, only oneBADA laboratory analyzed tissue organics forthe 1995 NOAA/NIST intercomparison exer-cise. Inter-laboratory results were found to besignificantly different with the exception ofPCBs 18, 153, and 170/190 for the certifiedreference material, Carp-1, and PCBs 18, 52,153, 195, and 170/190 for the unknown tissuesample QA95FSH3 (Tables 20 and 21).

It is interesting to note that between theunknown tissue samples and the StandardReference Material (SRM), a consistent patternoccurred, with PCBs 18, 153, and 170/190having no significant difference betweenlaboratories for both materials.


The inter-laboratory precision evaluationfor tissue organics is presented as the relativestandard deviation (RSD) of three replicatesamples run by each laboratory. Results arepresented in Table 17. In general, it seems thatit was easier to meet precision targets for PCBsthan for pesticides.

Accuracy was generally high for PCBs intissue for all laboratories that participated inthe comparison (Figures 29 and 30).

The 1995 intercomparison exercises re-vealed some unanticipated challenges withrespect to project management, data documen-tation, and data submission. After the firstround, it became obvious that a very specificproject management plan, outlining clearguidelines for communication and responsibili-ties, was needed to meet the expectations ofeveryone involved. Initially, only meetingminutes and various memos were distributedthat contained information critical to all par-ticipating laboratory staff. This proved to beinsufficient for effective guidance and has beencorrected.

Many lessons in data reporting and filetransfer were learned by all parties involved.The most important one was that data report-ing spreadsheets need to be intuitive to thebench chemist, rather than to the data man-

236


CR

M

Car

p-1

PE

ST

2,4

,-D

DE

2,4

-DD

D2

,4-D

DT

4,4

-DD

D4

,4-D

DE

4,4

-DD

TA

ldri

nA

lph

a-H

CH

Cis

-ch

lord

an

eC

is-n

on

ach

lor

Labo

rato

ry

72

.19

(B)

26

.67

(A)

7.7

2(A

)7

4.8

3(A

)1

28

.33

(B)

7.6

2(B

)6

.82

(A)

10

.53

(A)

6.5

0(A

)La

bora

tory

6

2.6

4(B

)8

.67

(B)

3.5

9(B

)5

8.8

7(B

)1

23

.67

(B)

0.6

3(C

)1

.43

(B)

6.1

8(B

)4

.49

(B)

La

bo

rato

ry

12

5.0

9(A

)2

4.7

7(A

)3

.83

(B)

74

.10

(A)

17

1.3

3(A

)2

7.8

3(A

)0

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(C)

4.8

5(B

)3

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(B)

CR

M

Car

p-1

PE

ST

Die

ldri

nG

am

a-H

CH

He

pta

chlo

rH

ep

tach

lore

po

xid

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exa

chlo

rob

en

zen

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ire

xO

xych

lord

an

eT

ran

s-ch

lord

an

eT

ran

s-n

on

ach

lor

Labo

rato

ry

74

.65

(A)

1.3

2(A

)1

.36

(B)

3.2

9(B

A)

2.3

2(B

)8

.17

(A)

11

.97

(A)

Labo

rato

ry

64

.68

(A)

0.6

5(B

)1

1.4

4(A

)3

.54

(A)

0.4

1(B

)5

.89

(A)

4.4

1(B

)7

.00

(C)

La

bo

rato

ry

12

5.4

0(A

)0

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(B)

1.5

8(B

)2

.65

(B)

1.0

1(A

)1

.27

(C)

4.1

3(B

)9

.40

(B)

QA

95

FS

H3

-PE

ST

2,4

,-D

DE

2,4

-DD

D2

,4-D

DT

4,4

-DD

D4

,4-D

DE

4,4

-DD

TA

ldri

nA

lph

a-H

CH

Cis

-ch

lord

an

eC

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on

ach

lor

Labo

rato

ry

73

.01

(B)

21

.83

(A)

8.4

7(A

)9

7.0

7(A

)1

47

.00

(B)

4.3

1(B

)5

.60

(A)

7.5

6(A

)5

.29

(A)

Labo

rato

ry

62

.79

(B)

9.1

7(B

)3

.49

(B)

59

.77

(B)

11

5.0

0(C

)0

.64

(B)

1.0

7(B

)6

.22

(B)

4.8

4(B

A)

La

bo

rato

ry

12

5.4

2(A

)2

7.2

7(A

)4

.29

(B)

86

.80

(A)

18

0.6

7(A

)3

0.8

0(A

)0

.66

(C)

4.8

6(C

)4

.46

(B)

QA

95

FS

H3

-PE

ST

Die

ldri

nG

am

a-H

CH

He

pta

chlo

rH

ep

tach

lore

po

xid

eH

exa

chlo

rob

en

zen

eM

ire

xO

xych

lord

an

eT

ran

s-ch

lord

an

eT

ran

s-n

on

ach

lor

Labo

rato

ry

78

.52

(A)

2.1

4(A

)4

.20

(A)

4.1

9(A

)1

0.7

7(A

)La

bora

tory

6

6.0

1(B

)1

.37

(B)

12

.66

(A)

4.4

0(A

)0

.33

(B)

6.2

4(A

)4

.44

(A)

8.0

7(B

)L

ab

ora

tory

1

26

.33

(B)

0.8

9(C

)1

.70

(B)

3.5

1(A

)1

.11

(A)

1.4

5(B

)4

.32

(A)

10

.93

(A)

Tab

le 2

0. N

IST

/NO

AA

pes

tici

de

mu

ltip

le c

omp

aris

on r

esu

lts

usi

ng

the

Bon

ferr

oni

(Du

nn

) T

tes

t, w

her

e al

ph

a =

0.05

. Bel

ow a

re t

he

mea

nva

lues

of

thre

e re

plic

ates

an

d th

e B

onfe

rron

i ass

ign

ed g

rou

pin

gs. M

issi

ng

valu

es a

re a

res

ult

of

the

valu

es b

ein

g be

low

th

e M

DL,

not

det

ecte

d, o

rda

ta w

ere

not

rep

orte

d. L

abor

ator

y re

sult

s as

soci

ated

wit

h t

he

sam

e le

tter

are

not

sig

nif

ican

tly

diff

eren

t.


237

CR

M

Car

p-1

PC

BP

CB

8P

CB

18

PC

B2

8P

CB

44

PC

B5

2P

CB

10

5P

CB

11

8P

CB

12

8P

CB

15

3L

ab

ora

tory

1

20

.95

(B)

20

.87

(A)

21

.83

(C)

84

.10

(B)

12

7.3

3(B

)4

8.7

7(A

)1

27

.00

(BC

)1

7.2

3(A

)8

9.4

3(A

)La

bora

tory

2

1.8

9(A

)2

2.8

3(A

)5

4.3

7(A

)9

8.0

0(A

)1

54

.33

(A)

47

.13

(A)

15

6.3

3(A

)1

6.4

7(A

)1

01

.67

(A)

Labo

rato

ry

61

.37

(BA

)2

1.6

7(A

)2

9.9

7(B

)8

3.1

3(B

)1

31

.67

(B)

34

.67

(B)

10

1.3

3(C

)1

2.6

7(B

)9

7.1

0(A

)La

bora

tory

7

25

.53

(A)

22

.90

(CB

)6

7.6

0(C

)1

17

.67

(B)

54

.80

(A)

13

5.6

7(B

A)

19

.00

(A)

91

.53

(A)

CR

M

Car

p-1

PC

BP

CB

18

0P

CB

19

5P

CB

20

6P

CB

20

9P

CB

10

1/9

0P

CB

13

8/1

63

/16

4P

CB

17

0/1

90

PC

B1

87

/18

2P

CB

66

/95

La

bo

rato

ry

12

51

.17

(A)

3.9

8(B

)4

.69

(A)

4.4

7(A

)1

34

.67

(BA

)9

7.3

3(B

A)

16

.50

(A)

32

.97

(A)

19

7.3

3(A

)La

bora

tory

2

44

.67

(A)

2.4

1(C

)2

.92

(A)

3.3

6(B

)1

45

.33

(A)

11

9.3

3(A

)1

6.5

3(A

)3

3.0

7(A

)1

65

.33

(BA

)La

bora

tory

6

33

.43

(B)

5.9

3(A

)4

.12

(A)

4.2

8(A

)1

16

.67

(B)

75

.67

(B)

18

.73

(A)

26

.40

(A)

14

1.3

3(B

)La

bora

tory

7

44

.87

(A)

4.1

5(B

)4

.23

(A)

3.4

3(B

)1

31

.33

(BA

)1

13

.67

(A)

16

.93

(A)

32

.77

(A)

15

5.0

0(B

)

QA

95

FS

H3

-PC

BP

CB

8P

CB

18

PC

B2

8P

CB

44

PC

B5

2P

CB

10

5P

CB

11

8P

CB

12

8P

CB

15

3L

ab

ora

tory

1

23

.87

(B)

29

.63

(A)

27

.50

(C)

92

.47

(BA

)1

41

.00

(A)

54

.03

(A)

13

3.3

3(B

)2

1.9

7(A

)9

7.4

3(A

)La

bora

tory

2

4.9

6(B

A)

29

.97

(A)

65

.50

(A)

11

2.3

3(A

)1

94

.33

(A)

48

.57

(A)

16

0.3

3(A

)1

6.0

0(B

)1

04

.33

(A)

Labo

rato

ry

65

.73

(A)

30

.70

(A)

38

.27

(B)

87

.80

(B)

13

8.0

0(A

)3

4.1

7(B

)9

6.3

3(C

)1

2.7

0(B

)9

6.2

3(A

)La

bora

tory

7

31

.00

(A)

31

.63

(CB

)7

9.1

7(B

)1

39

.00

(A)

58

.10

(A)

14

7.6

7(B

A)

20

.73

(A)

11

3.0

0(A

)

QA

95

FS

H3

-PC

BP

CB

18

0P

CB

19

5P

CB

20

6P

CB

20

9P

CB

10

1/9

0P

CB

13

8/1

63

/16

4P

CB

17

0/1

90

PC

B1

87

/18

2P

CB

66

/95

La

bo

rato

ry

12

54

.97

(A)

4.0

8(A

)4

.66

(A)

4.8

4(A

)1

41

.33

(A)

10

6.3

3(A

)1

7.9

0(A

)3

4.6

0(B

A)

21

8.6

7(A

)La

bora

tory

2

47

.20

(A)

2.1

6(A

)2

.50

(C)

2.8

2(C

)1

48

.33

(A)

11

6.6

7(A

)2

1.2

7(A

)3

1.5

0(B

)1

62

.33

(BC

)La

bora

tory

6

34

.10

(B)

6.1

0(A

)4

.16

(BA

)4

.63

(BA

)1

06

.00

(B)

75

.33

(B)

19

.17

(A)

25

.20

(C)

14

4.6

7(C

)La

bora

tory

7

51

.33

(A)

13

.33

(A)

3.4

2(B

C)

3.7

1(B

C)

14

1.6

7(A

)1

24

.00

(A)

20

.57

(A)

38

.43

(A)

19

8.0

0(B

A)

Tab

le 2

1. N

IST

/NO

AA

PC

B m

ult

iple

com

par

ison

res

ult

s u

sin

g th

e B

onfe

rron

i (D

un

n)

T t

est,

wh

ere

alp

ha

= 0.

05. B

elow

are

th

e m

ean

valu

es o

f th

ree

repl

icat

es a

nd

the

Bon

ferr

oni a

ssig

ned

gro

upi

ngs

. Mis

sin

g va

lues

are

a r

esu

lt o

f th

e va

lues

bei

ng

belo

w t

he

MD

L, n

ot d

etec

ted,

or

data

wer

e n

ot r

epor

ted.

Lab

orat

ory

resu

lts

asso

ciat

ed w

ith

th

e sa

me

lett

er a

re n

ot s

ign

ific

antl

y di

ffer

ent.

238


ager. After the first round of analyses, it be-came clear that complex instructions on filestructures served neither the data generatorsnor the recipients, and the data reporting wassubsequently simplified.

Conclusions

The first two intercomparison exercisesshowed that statistically significant differencesbetween laboratories exist. For most traceelements, however, values were comparablemost of the time when data quality criteriawere applied, with some notable exceptions,primarily silver, cadmium, selenium, andmercury. One laboratory seemed to have asystematic offset in trace element measure-ments and consistently had lower values thanall others. This difference needs to be takeninto consideration when comparing sedimentresults generated by this particular laboratorywith those of others. Trace organic contami-nants were comparable between laboratories,although in one case, detection limits were toohigh to evaluate results in any meaningful way.

An assessment of each individuallaboratory’s quality assurance programs would

be the first step in reducing the variation inlong-term data sets from laboratories involvedin analyzing Estuary water, sediment, or tissueparameters. Continued analysis of splitsamples and participation in large-scale inter-comparison exercises, such as the one organizedby NOAA, will help improve the quality andcomparability of results from participatingRMP laboratories as well as other local moni-toring efforts.

Based on the lessons learned, plans shouldbe made to include additional laboratories inintercomparisons. The United States GeologicalSurvey laboratories in Menlo Park and Sacra-mento, for example, generate a wealth of datathat should have a great degree of comparabil-ity with data generated by other monitoringprograms, so that data sets can be confidentlycombined for various assessments. The degreeof comparability, however, has not yet beenformally determined. The same applies to databeing collected in the Delta and the Sacramentoand San Joaquin Rivers. The annual NOAA-sponsored “round robin” may be an appropriateand cost-effective mechanism.


239

05

10152025

As 4 1 10 2 3 9 5

050

100150200250

Cr 4 11 10 2 3 9 5

020000400006000080000

100000120000

Al 4 11 10 2 3 9 5

0

10

20

30

40

Pb 4 11 10 2 3 9 5

0

50

100

150

Ni 4 11 10 2 3 9 5

00.10.20.30.40.5

Ag 4 11 10 2 3 9 5

00.10.20.30.40.5

Cd 4 11 10 2 3 9 5

0

20

40

60

80

Cu 4 11 10 2 3 9 5

00.10.20.30.40.5

Hg 4 1 10 2 3 9 5

0

1

2

3

4

Se 4 1 10 2 3 9 5

0

50

100

150

200

Zn 4 11 10 2 3 9 5

Lab Intercomparison ResultsTrace Metals in Sediment

Figure 20. Sediment reference materialSFERM-S95 trace metal results from partici-pating San Francisco Bay POTW laboratoriesand RMP contract laboratories. All units aremg/kg. X-axis is laboratory ID number. Meanvalue for each analyte is indicated by a solid line.The mean value is calculated from all participat-ing laboratories. The 95% confidence interval isindicated by the dashed lines. Please note that laboratory # 4 used the hydrofluoric acid extrac-tion method while the other laboratories used the aqua regia for sediment extraction.

Arsenic

Chromium

Aluminum

Lead

Nickel

Cadmium

Copper

Mercury

Selenium

Zinc

Silver

240


02468

10

µg/Kg 2 5 6 12

02468

1012

µg/Kg 2 5 6 12

02468

10

µg/Kg 2 5 6 12

0123456

µg/Kg 2 5 6 12

0

20

40

60

80

µg/Kg 2 5 6 12

0

50

100

150

200

µg/Kg 2 5 6 12

0

5

10

15

µg/Kg 2 5 6 12

0

10

20

30

40

µg/Kg 2 5 6 12

0

5

10

15

20

µg/Kg 2 5 6 12

0

50

100

150

200

µg/Kg 2 5 6 12

020406080

100

µg/Kg 2 5 6 12

Lab Intercomparison ResultsOrganics in Sediment

Figure 21. Sediment reference material-SFERM-S95 organics results from partici-pating San Francisco Bay POTW laborato-ries and RMP contract laboratories. X-axis islaboratory ID number. Mean value for eachanalyte is indicated by a solid line. The meanvalue is calculated from all participating labora-tories. The 95% confidence interval is indicatedby the dashed lines.

1-Methylphenanthrene

2-Methylnapthalene1-Methylnapthalene

Anthracene

Benzo(a)pyrene

2,6-Dimethylnapthalene

Acenapthene

Acenapthylene

Benzo(a)anthracene Benzo(e)pyrene

Benzo(a)fluoranthrene


241

0

50

100

150

µg/Kg 2 5 6 12

0

5

10

15

µg/Kg 2 5 6 12

0

5

10

15

20

µg/Kg 2 5 6 12

0

50

100

150

µg/Kg 2 5 6 12

0

50

100

150

µg/Kg 2 5 6 12

0

20

40

60

80

µg/Kg 2 5 6 12

01020304050

µg/Kg 2 5 6 12

020406080

100120

µg/Kg 2 5 6 12

0

5

10

15

20

µg/Kg 2 5 6 12

0

100

200

300

400

µg/Kg 2 5 6 12

0

50

100

150

200

µg/Kg 2 5 6 12


Figure 21 (continued). Sediment referencematerial-SFERM-S95 organics results fromparticipating San Francisco Bay POTWlaboratories and RMP contract laborato-ries. X-axis is laboratory ID number. Mean valuefor each analyte is indicated by a solid line. Themean value is calculated from all participatinglaboratories. The 95% confidence interval isindicated by the dashed lines.

Benzo(k)fluoranthrene

Chrysene

Benzo(ghi)perylene

Fluorene

Perylene

Biphenyl

Dibenz(a,h)anthracene

Fluoranthrene

Indeno(1,2,3-cd)pyrene Pyrene

Phenanthrene

242


0

0.5

1

1.5

µg/Kg 2 5 12

0

0.2

0.4

0.6

0.8

µg/Kg 2 5 12

00.20.40.60.8

11.2

µg/Kg 2 5 12

00.10.20.30.40.5

µg/Kg 2 5 12


Figure 22. Sediment reference material-SFERM-S95 organics results from participating SanFrancisco Bay POTW laboratories and RMP contract laboratories. X-axis is laboratory IDnumber. Mean value for each analyte is indicated by a solid line. The mean value is calculated from allparticipating laboratories. The 95% confidence interval is indicated by the dashed lines.

PCB 153

PCB 187

PCB 138

PCB 180


243

02468

Al%

8 11 2 3 5 9 13

05

1015202530

As 8 11 2 3 5 9 13

020406080

100

Cr 8 11 2 3 5 9 13

050

100150200250300

Pb 8 11 2 3 5 9 13

0

10

20

30

40

Ni 8 11 2 3 5 9 13

00.5

11.5

22.5

3

Cd 8 11 2 3 5 9 13

0

50

100

150

200

Cu 8 11 2 3 5 9 13

0

0.5

1

1.5

2

Hg 8 11 2 3 5 9 13

0

0.5

1

1.5

2

Se 8 11 2 3 5 9 13

<0.25 <4

0100200300400500

Zn 8 11 2 3 5 9 13

0

0.5

1

1.5

Ag 8 11 2 3 5 9 13

<2 <0.4

Lab Intercomparison ResultsTrace Metals in Sediment

Figure 23. NOAA/9 sediment-W results fromparticipating San Francisco Bay POTWlaboratories and an RMP contract labora-tory. All units mg/kg unless indicated. X-axis islaboratory ID number. The accepted value for eachanalyte is indicated by a solid line calculated fromthe mean of all NOAA/9 particiapting laboratories.The 95% confidence interval is indicated by thedotted lines. The RMP data quality objective (DQO) is indicated by the dashed lines. The RMP DQOfor trace elements is ±25% accuracy for As, Hg, and Se and ±30% for all others. Please refer to theNRC, NOAA/9 publication (November, 1995) for more information.

Arsenic

Chromium

Aluminum, % units

Lead

Nickel

Cadmium

Copper

Mercury

Selenium

Zinc

Silver

244


0

2

4

6

8

Al 8 11 2 3 5 9 130

5

10

15

20

As 8 11 2 3 5 9 13

0

50

100

150

200

Cr 8 11 2 3 5 9 13

05

1015202530

Pb 8 11 2 3 5 9 13

0

0.1

0.2

0.3

0.4

Cd 8 11 2 3 5 9 13

05

10152025

Cu 8 11 2 3 5 9 13

00.05

0.10.15

0.20.25

Hg 8 11 2 3 5 9 13

0

50

100

150

Zn 8 11 2 3 5 9 13

0

20

40

60

80

Ni 8 11 2 3 5 9 13

00.10.20.30.40.50.6

Se 8 11 2 3 5 9 13

<40

0.05

0.1

0.15

Ag 8 11 2 3 5 9 13

<2 <0.4

Lab Intercomparison ResultsTrace Metals in Sediments

Figure 24. NOAA/9 sediment referencematerial BCSS-1 results fromparticipating San Francisco Bay POTWlaboratories and an RMP contract labora-tory. All units mg/kg unless indicated. X-axis islaboratory ID number. The accepted value foreach analyte is indicated by a solid line calculatedfrom the mean of all NOAA/9 particiaptinglaboratories. The 95% confidence interval is indicated by the dotted lines. The RMP data qualityobjective (DQO) is indicated by the dashed lines. The RMP DQO for trace elements is ±25% accuracyfor As, Hg, and Se and ±30% for all others. Please refer to the NRC, NOAA/9 publication (November,1995) for more information.

Arsenic

Chromium

Aluminum, % units

Lead

Nickel

Cadmium

Copper

Mercury

Selenium Silver

Zinc


245

0100200300400500600

Al 8 8 3 2 9 13

02468

10

As 8 8 3 2 9 13

00.5

11.5

22.5

Cr 8 8 3 2 9 13

05

10152025

Pb 8 8 3 2 9 13

0

0.5

1

1.5

Ni 8 8 3 2 9 13

0

0.2

0.4

0.6

0.8

Ag 8 8 3 2 9 13

0

0.5

1

1.5

2

Cd 8 8 3 2 9 13

0

5

10

15

Cu 8 8 3 2 9 13

00.05

0.10.15

0.20.25

Hg 8 8 3 2 9 13

00.5

11.5

22.5

3

Se 8 8 3 2 9 13

0

50

100

150

Zn 8 8 3 2 9 13

Lab Intercomparison ResultsTrace Metals in Tissue

Figure 25. NOAA/9 tissue-X results fromparticipating San Francisco Bay POTWlaboratories and an RMP contract laboratory.All units mg/kg unless indicated. X-axis is labora-tory ID number. The accepted value for eachanalyte is indicated by a solid line calculated fromthe mean of all NOAA/9 particiapting laboratories.The 95% confidence interval is indicated by thedotted lines. The RMP data quality objective (DQO) is indicated by the dashed lines. The RMP DQOfor trace elements is ±25% accuracy for As, Hg, and Se and ±30% for all others, except Al which doesnot have a RMP DQO. Please refer to the NRC, NOAA/9 publication (November, 1995) for moreinformation.

Arsenic

Chromium

Aluminum, % units

Lead

Nickel

Cadmium

Copper

Mercury

Selenium

Zinc

Silver

Solid line indicates the consensus value of thenon HF method of digestion. Lab # 8 used theHF method and therefore had higher results.

246


0

5

10

15

20

As 3 2 9 13

0

0.5

1

1.5

2

Cr 3 2 9 13

050

100150200250300

Al 3 2 9 13

00.10.20.30.40.50.6

Pb 3 2 9 13

00.5

11.5

22.5

3

Ni 3 2 9 13

00.5

11.5

22.5

Ag 3 2 9 13

0123456

Cd 3 2 9 13

020406080

100

Cu 3 2 9 13

00.020.040.060.08

0.10.12

Hg 3 2 9 13

0

1

2

3

4

Se 3 2 9 13

0200400600800

10001200

Zn 3 2 9 13

Lab Intercomparison ResultsTrace Metals in Tissue

Figure 26. NOAA/9 tissue reference materialSRM-1566 results from participating SanFrancisco Bay POTW laboratories & an RMPcontract laboratory. All units mg/kg unlessindicated. X-axis is laboratory ID number. Theaccepted value for each analyte is indicated by asolid line calculated from the mean of all NOAA/9particiapting laboratories. The 95% confidenceinterval is indicated by the dotted lines. The RMP data quality objective (DQO) is indicated by thedashed lines. The RMP DQO for trace elements is ±25% accuracy for As, Hg, and Se and ±30% for allothers, except Al which does not have a RMP DQO. Please refer to the NRC, NOAA/9 publication (No-vember, 1995) for more information.

Arsenic

Chromium

Aluminum, % units

Lead

Nickel

Cadmium

Copper

Mercury

Selenium Silver

Zinc


247

0

10

20

30

40

µg/Kg 7 12 6

02468

10

µg/Kg 7 12 6

050

100150200250

µg/Kg 7 12 6

0

10

20

30

40

µg/Kg 7 12 6

0

2

4

6

8

µg/Kg 7 12 6

00.5

11.5

22.5

µg/Kg 7 12 6

0123456

µg/Kg 7 12 6

0

2

4

6

8

µg/Kg 7 12 6

020406080

100

µg/Kg 7 12 6

02468

10

µg/Kg 7 12 6

02468

10

µg/Kg 7 12 6

012345

µg/Kg 7 12 6

0

5

10

15

µg/Kg 7 12 6

Lab Intercomparison ResultsPesticides in Fish Tissue

Figure 27. NIST/NOAA-95 fish homogenate III(QA95FSH3) pesticide results from participat-ing RMP contract laboratories. X-axis is labora-tory ID number. The certified or “target” value foreach analyte is indicated by a solid line. The targetvalue is a noncertified concentration calculated byNIST. The 95% confidence interval is indicated bydotted lines. The RMP data quality objective of ±20% accuracy is indicated by the dashed lines.

2,4’-DDE

4,4’-DDD

2,4’-DDD

cis-chlordane

dieldrin

2,4’-DDT

trans-nonachlor

trans-chlordane

hexachlorobenzenecis-nonachlor

gamma-HCH

4,4’-DDE

4,4’-DDT

248


0

10

20

30

40

µg/Kg 7 12 6

02468

10

µg/Kg 7 12 6

0

50100

150

200

µg/Kg 7 12 6

05

1015202530

µg/Kg 7 12 6

02468

10

µg/Kg 7 12 6

0

0.5

1

1.5

2

µg/Kg 7 12 6

02468

1012

µg/Kg 7 12 6

0123456

µg/Kg 7 12 6

020406080

100

µg/Kg 7 12 6

0

5

10

15

µg/Kg 7 12 6

02468

10

µg/Kg 7 12 6

012345

µg/Kg 7 12 6

0

5

10

15

20

µg/Kg 7 12 6


Figure 28. NIST/NOAA-95 fish certified refer-ence material (Carp 1) persticide results fromparticipating RMP contract laboratories. Allunits mg/kg unless indicated. X-axis is laboratoryID number. The certified or “target” value for eachanalyte is indicated by a solid line. The target valueis a noncertified concentration calculated by NIST.The 95% confidence interval is indicated by dotted lines. The RMP data quality objective of ±20%accuracy is indicated by the dashed lines.

2, 4’-DDE

4,4’-DDD

2,4’-DDD

cis-chlordane

dieldrin

2,4’-DDT

trans-nonachlor

trans-chlordane

hexachlorobenzenecis-nonachlor

gamma-HCH

4,4’-DDE

4,4’-DDT


249

0

2

4

6

8

µg/Kg 7 12 6

012345

µg/Kg 7 12 6

012345

µg/Kg 7 12 6

0

2

4

6

8

µg/Kg 7 12 6-5

0

5

10

15

µg/Kg 7 12 6

012345

µg/Kg 7 12 6

012345

µg/Kg 7 12 6

0

0.5

1

1.5

2

µg/Kg 7 12 6


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Figure 29. NIST/NOAA-95 fish homogenateIII (QA95FSH3) PCB results from partici-pating RMP contract laboratories. X-axis islaboratory ID number. The certified or “target”value for each analyte is indicated by a solid line.The target value is a noncertified concentrationcalculated by NIST. The 95% confidence intervalis indicated by dotted lines. The RMP dataquality objective of ±20% accuracy is indicated by the dashed lines.

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CHAPTER SIX

Other Monitoring Activities


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February Sediment Quality 1995

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A Summary of the South BayLocal Effects Monitoring Program

Don Arnold, City of San JoseJohn Haskins, San Francisco Estuary Institute

This report is a compilation of data fromtwo sources: Near Field Receiving Water Moni-toring of Trace Metals in Clams (Macomabalthica) and Sediments Near the Palo Alto andSan Jose/Sunnyvale Water Quality ControlPlants in South San Francisco Bay: December1994 through December 1995 (Luoma et al.,1996), and Local Effects Monitoring datacollected through the Regional MonitoringProgram for Trace Substances (RMP).

The stations included in this report aredefined as follows:

1. San Jose (station code C-3-0) is located inCoyote Creek, midway between ArtesianSlough and Mud Slough; sampling andanalysis are conducted through the SanFrancisco Estuary Institute (SFEI).

2. Sunnyvale (station code C-1-3) is located inGuadalupe Slough approximately onekilometer downstream from the SunnyvaleWater Pollution Control Plant; samplingand analysis are conducted through SFEI.

3. SJ/SV(station code C-1-7) is located in themouth of Coyote Creek midway betweenAlviso Slough and Guadalupe Slough;

sampling and analysis are conductedthrough the United States GeologicalSurvey (USGS).

4. Palo Alto (with no station code) is locatedone kilometer downstream from the PaloAlto Regional Water Quality Control Plant;sampling and analysis are conductedthrough USGS.

Local Effects Monitoring Program (LEMP)data collection and analysis for stations C-3-0and C-1-3 was performed by methods andtechniques identical to the RMP. The USGSdata are generally comparable, with exceptionof grain size analysis. A copy of the LEMPreport has been filed with the Regional WaterQuality Control Board.

Samples from the San Jose (C-3-0) andSunnyvale (C-1-3) sites were collected using amodified Van Veen grab with a surface area of0.1 m2. The top 5 cm of sediment was scoopedfrom each of two replicate grabs and mixed in abucket to provide a single composite sample foreach station. The same collection method wasemployed by USGS at the SJ/SV (C-1-7) site.Sediments at the Palo Alto site were collected

Figure 1. Percent TOC and sand in sediment samples during the month of February .

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by hand and shovel and were scraped from thetop 1–2 cm of the mudflat. The sediments werethen sieved through 100 µm polyethylene meshwith distilled water to remove the largergrains. This was not done at the San Jose (C-3-0) and Sunnyvale (C-1-3) sites and thus maybias interpretation.

Clams and oysters were collected in asimilar manner but had some differences.USGS collected more than 40 individuals ofMacoma balthica and held them in ocean waterfor 48 hours to depurate undigested materialfrom their digestive tract. In contrast, RMPcollected individuals of Crassostrea gigas anddid not hold animals for depuration. Based onfindings by Stephenson (1992) during the 1992Pilot Program, bivalve guts were not depuratedbefore homogenization for tissue analyses,although gonads were removed from organismsfor trace metal analyses. Stephenson (1992)found that, with the exception of lead andselenium, there were no significant differencesfound in trace metal concentrations betweenmussels held for 48 hours in “clean” GraniteCanyon seawater before homogenization andundepurated mussels. Slightly different ana-lytical techniques were also used by USGS andRMP laboratories though these differences areunlikely to affect comparisons between stations.

The 1995 sediment analysis resulted in asimilar relationship between percent totalorganic carbon (TOC) and concentration oftrace metals as the 1994 sediment samples(Tables 1 and 2). In general, metal concentra-tions increased with an increase in percentTOC. Manganese, selenium, and cadmium werethe exceptions to this trend. Manganese concen-trations increased with percent TOC at allstations except San Jose (C-3-0) where concen-trations decreased as percent TOC increased.At the SJ/SV (C-1-7) station selenium concen-trations remained the same with a decrease inpercent TOC. At the Palo Alto site seleniumconcentrations increased slightly with decreas-ing percent TOC. Cadmium at the Sunnyvale(C-1-3) site and selenium at the SJ/SV (C-1-7)site remained the same as percent TOC in-creased and decreased respectively. All theother metals followed the trend without devia-tion.

The San Jose (C-3-0) and Sunnyvale (C-1-7)sites increased in percent TOC and decreasedin percent sand from the wet to dry season(Figures 1 and 2). The SJ/SV (C-1-7) and PaloAlto sites showed the opposite trend, decreas-ing in percent TOC and increasing in percentsand from the wet to dry season (Figures 1 and2). The San Jose (C-3-0) site demonstrated a

Figure 2. Percent TOC and sand in sediment samples during the August/September sampling.


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Sediment Analysis Sediment Analysis February 1994 February 1995

Parameter San Jose Sunn y vale S J / S V Palo Alto San Jose Sunn y vale S J / S V Palo Alto(C-3-0) (C-1-3) (C-1-7) (No ID) (C-3-0) (C-1-3) (C-1-7) (No ID)

A g 0.13 1.11 0.51 1.00 0.36 0.07 0.36 0.84Al 14,891.00 46,785.00 38,200.00 42,300.00 12,231.00 11,896.00 58,916.00 53,127.00As 6.97 7.89 N/A N/A 6.10 2.00 na naC d 0.18 0.48 0.20 0.19 0.26 0.17 0.35 0.25Cr 81.00 170.50 101.00 120.00 70.00 55.60 148.00 125.00C u 21.99 94.59 45.00 52.00 21.10 22.70 58.10 47.60F e 29,996.00 82,760.00 39,000.00 47,700.00 22,962.00 20,640.00 54,500.00 73,197.00H g 0.07 0.41 0.37 0.34 0.13 0.11 1.10 0.42M n 2,817.00 1,250.00 1,229.00 1,202.00 888.00 400.00 904.00 1,232.00Ni 68.56 130.82 92.00 107.00 78.20 57.90 140.00 97.30P b 10.64 45.40 38.00 49.00 16.30 16.50 61.50 40.90S e 0.30 0.87 0.30 0.30 0.24 0.22 0.50 0.40Z n 60.77 221.84 136.00 156.00 72.00 70.00 175.00 144.80% Sand 93.00 1.00 41.00 52.00 76.00 88.00 6.00 2.00% TOC 0.33 1.63 1.24 1.39 0.53 0.35 1.77 1.57

Table 1. Trace elements, TOC and sand in sediment samples. Trace element data in mg/kg dry weight.

Table 2. Trace elements, TOC and sand in sediment samples. Trace element data in mg/kg dry weight.

Sediment Analysis Sediment AnalysisAugust 1994 August/September 1995

Parameter San Jose Sunn y vale S J / S V Palo Alto San Jose Sunn y vale S J / S V Palo Alto(C-3-0) (C-1-3) (C-1-7) (No ID) (C-3-0) (C-1-3) (C-1-7) (No ID)

A g 0.98 0.28 0.58 0.67 0.96 0.22 0.22 0.22Al 27,009.00 18,749.00 45,100.00 31,200.00 21,185.00 20,510.00 na 34,850.00As 8.02 7.51 N/A N/A 8.20 6.00 na naC d 0.68 0.30 0.26 0.24 0.75 0.17 0.23 0.20Cr 107.70 75.10 112.00 85.00 97.70 69.10 109.00 95.30C u 57.81 34.79 47.00 33.00 49.80 24.90 42.00 35.70F e 38,405.00 26,248.00 44,000.00 33,800.00 34,018.00 28,103.00 na 37,425.00H g 0.54 0.24 0.41 0.33 0.40 0.31 0.60 0.30M n 559.00 467.00 542.00 863.00 595.00 728.00 na 888.70Ni 118.59 81.13 104.00 78.00 105.70 63.80 101.00 86.80P b 41.22 27.98 39.00 31.00 50.60 22.40 45.00 36.70S e 0.42 0.54 0.30 0.23 0.41 0.31 0.50 0.42Z n 162.92 112.49 140.00 106.00 148.00 78.00 137.00 116.80% Sand 4.00 38.00 10.00 40.00 28.00 53.00 13.00 44.00% TOC 1.39 1.06 1.33 0.98 1.22 0.71 1.35 1.14

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large increase in percent TOC whereas both theSJ/SV (C-1-7) and Palo Alto sites decreasedfrom February to August (Figure 3). The largestdecrease in percent sand was at the San Jose(C-3-0) site and the largest increase in percentsand was at the Palo Alto site (Figure 4).

A notable observation in 1995 was the highconcentrations of mercury seen in February atthe SJ/SV (C-1-7) station (1.1 µg/g), and aneven higher concentration of 2.9 µg/g in June(Near Field Receiving Water Monitoring,USGS). The concentration in August (0.6 µg/g)at this site was higher than any other RMPstation in either 1994 or 1995. These peakswere not seen at the Palo Alto, Sunnyvale (C-1-3), or San Jose (C-3-0) sites. Salinities at theSJ/SV (C-1-7) site were lowest in February,April, and June, increased slightly during lowflow in September and declined again in De-cember 1995. This USGS data suggests thatlocal runoff could be an important source ofsedimentary mercury during years of highprecipitation.

In general, all the trace elements had verysimilar seasonal trends within stations, thoughthese trends were not consistent betweenstations. For the majority of trace elements,concentrations at the San Jose (C-3-0) siteincreased from February to August for both1994 and 1995. At the Sunnyvale (C-1-3), siteconcentrations of all trace elements decreased

from February to August in 1994 and increased in1995. At the SJ/SV (C-1-7) the opposite case wasthe trend. Concentrations generally increased in1994 and decreased in 1995. Concentrations atthe Palo Alto site generally decreased fromFebruary to August during both years.

Silver, chromium, iron, and selenium hadmaximum and minimum concentrations thatwere observed at the same stations. The lowestconcentration for all of these metals were ob-served at the Sunnyvale (C-1-3) site in February1995. The highest concentrations were observedat this site in February of 1994. Average concen-trations were generally about the same for bothyears with the exception of Sunnyvale (C-1-3)which had higher average concentrations in 1994than 1995. The ranges of concentrations were asfollows; silver, from 0.07 to 1.11 ppm; chromium,from 55.6 to 170.5 ppm; iron, from 20640 to 83760ppm; and selenium, from 0.217 to 0.87 ppm.

The highest concentrations of copper and zincwere also observed at Sunnyvale (C-1-3), andtheir lowest concentrations were observed at theSan Jose (C-3-0) site in February of 1995 forcopper and February 1994 for zinc. Copperconcentrations ranged from 21.1 to 94.59 ppm,and zinc concentrations ranged from 60.77 to221.8 ppm. Average concentrations were generallyconsistent from 1994 to 1995 except for a notablyhigher concentration at the Sunnyvale (C-1-3) sitein 1994 for both of these metals.

Figure 3. Percent TOC in sediment samples during the wet and dry seasons.


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The highest concentrations of lead, mercury,aluminum, and nickel were observed at the SJ/SV (C-1-7) site in February of 1995. The lowestconcentrations of mercury and lead were ob-served at the San Jose (C-3-0) site in February of1995, but the lowest concentrations of nickel andaluminum were observed at the Sunnyvale (C-1-3) site in February 1995. In general, averageconcentrations for these metals were consistentat each station except for SJ/SV (C-1-7) whichhad higher average concentrations in 1995 thanin 1994. Nickel and aluminum also had higheraverage concentrations at the Sunnyvale (C-1-3)site in 1994 than in 1995. Concentrations ofthese metals exhibited the following ranges: lead,from 10.64 to 61.5 ppm; mercury, from 0.072 to1.1 ppm; aluminum, 11896 to 58916 ppm; andnickel, from 57.9 to 140.

The highest concentrations of magnesiumand cadmium were observed at San Jose (C-3-0)in February 1994 and August 1995 respectively.The lowest concentrations were both observed atSunnyvale (C-1-3) in February 1995. Averageconcentrations of cadmium were consistent, butthe average magnesium concentration was largerin San Jose (C-3-0) in February 1994.

To measure bioaccumulation of trace ele-ments in tissue, two different species of bivalveswere used. The RMP measured the oyster,Crassostrea gigas, while at the USGS sites the

clam Macoma balthica was analyzed.Bioaccumulation was not measured at the SanJose (C-3-0) or Sunnyvale (C-1-3) sites, thuscomparisons are made to the next closest RMPsite which is Coyote Creek (BA10).

At the Palo Alto site, concentrations intissues were analyzed once each month in 1995except for May and November. The San Jose/Sunnyvale (C-1-7) site was sampled six times in1995. The RMP Coyote Creek station (BA10)was sampled in April and September. Wet anddry season (April and September) concentra-tions at all three sites are shown in Tables 3Aand 3B.

At the Palo Alto site, the lowest concentra-tions observed were in April except for zincwhich had its lowest concentration in March.The highest concentrations were not as consis-tent, but generally were observed either inOctober or December. Thus, when comparingApril and September at this site, the concentra-tions of each metal increased respectively.

At the SJ/SV (C-1-7) site, cadmium, copper,lead, selenium, and silver exhibited a similartrend of highest concentrations found in De-cember. This was similar to concentrationsobserved in 1994. Other metals had variableconcentrations throughout the year. Mercuryconcentrations were slightly higher in early1995 compared to early 1994 but were essen-

Figure 4. Percent sand in sediment during the wet and dry seasons.

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tially the same in September of both years. Thisincrease in tissue was not comparable to theincrease observed in sediments. There was noconsistent trend for when the lowest concentra-tions were observed.

In Coyote Creek (BA10), concentrationswere higher in September compared to April forall metals except for silver which had a lowerconcentration in September, and chromiumwhich had no data in April. This was differentfrom last year at this site where there was no

consistent trend of increasing concentrationsfrom wet to dry season.

Comparisons between these four stationswere made possible by the efforts of personnelto coordinate sampling design, analyticalmethods, and collection techniques. The LEMdatabase is large enough to warrant a more in-depth analysis of sediment chemistry near theoutfalls compared to RMP reference sites. Thisprogram could benefit from sediment grain sizeintercalibration and quantification of method-ological differences in sediment chemistry.

Table 3B. Trace metal concentrations in the tissue of the filter-feeding bivalve, Crassostrea gigas,transplanted for 90 days, during the wet (April) and dry (September) season in 1995, at the RMPsite, Coyote Creek (BA10).

Table 3A. Mean trace metal concentrations in the deposit-feeding bivalve, Macoma balthica,collected during the wet (April) and dry (September) season in 1995, at the Local EffectsMonitoring sites, SJ/SV and Palo Alto. STD = standard deviation, SEM = standard error of the mean.

Trace Elements in Macoma balthicaA g C d Cr C u H g Ni P b S e Z n

SJ/SV April 1994Mean (ug/g) 1.80 0.10 5.90 30.50 ★ 7.80 4.10 4.60 231.00

S T D 0.30 * 2.00 3.90 1.90 1.00 1.50 21.00SJ/SV Sept.1994

Mean (ug/g) 1.60 0.30 4.80 33.80 0.43 7.60 4.40 3.90 163.00S T D 0.30 * 1.60 5.80 1.60 0.80 1.30 24.00

SJ/SV April 1995Mean (ug/g) 1.20 0.56 3.20 28.00 * 7.40 2.40 * 412.00

S E M 0.30 0.01 0.40 6.00 1.50 0.40 100.00

SJ/SV Sept. 1995

Mean (ug/g) 3.50 0.50 1.90 80.00 0.42 4.40 2.60 5.40 255.00

S E M 0.60 0.10 0.30 13.00 0.40 0.40 0.30 0.10 11.00

Palo Alto April 1995

Mean (ug/g) 2.50 0.31 1.60 23.00 0.33 3.40 1.20 4.00 305.00

S E M 0.40 0.03 0.20 2.00 0.02 0.30 0.10 0.30 35.00Palo Alto Sept. 1995

Mean (ug/g) 5.90 0.50 1.90 67.00 0.37 5.00 2.70 4.60 336.00S E M 0.30 0.08 0.10 4.00 0.04 0.20 0.30 0.50 18.00

* Not enough animals found to perform analysis. ★ Incomplete data sets.

A g C d Cr C u H g Ni P b S e Z nCoyote Creek–April

(ug/g) 6.25 10.60 * 218.00 0.17 5.00 0.52 4.00 1,443.00Coyote Creek.–Sept.

(ug/g) 2.16 16.20 9.10 867.00 0.35 8.00 1.32 11.00 2,050.00


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Sacramento Coordinated WaterQuality Monitoring Program

T.R. GrovhougLarry Walker Associates, Davis, California

Introduction

The Sacramento Coordinated Water QualityMonitoring Program (CMP) is a cooperativeprogram initiated and implemented by theSacramento Regional County SanitationDistrict (SRCSD), the City of Sacramento (City)and the County of Sacramento Water ResourcesDivision (County). These three public agenciesare responsible for the management of allmunicipal waste water and storm water in thevicinity of Sacramento within SacramentoCounty. The CMP was established in July 1991through a Memorandum of Understandingbetween these entities.

The purpose of the CMP is to develop ascientifically defensible database of waterquality information on the Sacramento andAmerican Rivers at selected locations in theSacramento metropolitan area. Key features ofthe CMP include:

1. The Ambient Water Quality MonitoringProgram (Ambient Program) for theSacramento American Rivers.

2. Coordination of ongoing surface waterquality monitoring programs within theSacramento area.

3. A water quality database managementsystem for water quality data produced bythe Ambient Program and other City andCounty programs.

4. Special studies to address specific monitor-ing needs and to address new regulatoryinitiatives.

5. An annual technical report summarizingthe data collected under the AmbientProgram, the results of special studies, andproposed changes in the CMP for theupcoming year.

The Ambient Program is the primary waterquality data collection element of the CMP.

Sampling under the Ambient Program began inDecember 1992. The 1996 Annual Report forthe Sacramento CMP assesses the results ofAmbient Program monitoring completedthrough July 1996.

Monitoring program features, monitoringresults from the first year and one half ofAmbient Program sampling (December 1992through July 1996 covering 77 samplingevents), and future direction of the program aresummarized below.

Ambient Monitoring Program

Five river sites are now monitored underthe Ambient Program: three on the SacramentoRiver (at Veteran’s Bridge near Alamar Marina,at Freeport Bridge, and at River Mile 44downstream of the Sacramento metropolitanarea) and two on the American River (at Nim-bus Dam and at Discovery Park near themouth; see Figure 5). Monitoring at the FolsomLake site upstream of Nimbus on the AmericanRiver was discontinued in October 1995. Themonitoring sites have been selected to providewater quality data upstream and downstreamof the influence of discharges from the Sacra-mento community.

Sampling is performed by a two-personsampling crew using peristaltic pumps. Meth-ods for sample collection include mid-depthshore samples at Nimbus and cross-sectionalspatial composite samples taken by boat at theother four sites.

Samples are taken monthly at each site.Additionally, two episodic storm events aresampled in coordination with the SacramentoStormwater Monitoring Program.

Parameters monitored include trace ele-ments (total and dissolved), cyanide, andconventional parameters (pH, TSS, TDS,

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Figure 5. Typical water quality in the CMP study area.These bar graphs represent a comparison of typical water qualityobserved by the Ambient Program for the period from December1992 through July 1996, and US EPA water quality criteria forthe protection of aquatic life and human health. In thiscomparison, median water quality is represented as a percentageof the appropriate water quality criterion.


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hardness, TOC, temperature). For the stormsampling, organophosphate pesticides are alsomonitored. The frequency of analysis varies byconstituent, ranging from monthly to quarterlyto annually.

Clean sampling and analytical methods areemployed to produce contaminant-free sampleswith low detection limits. Sample containers,equipment cleaning, field quality control, andlaboratory QA/QC procedures are describedbelow.

Sample Containers and Preservatives: Highdensity polyethylene containers are used forall samples except mercury. Teflon bottlesare used for mercury samples. Trace elementsamples are acidified with ultrapure reagentgrade nitric acid (ULTREX II). Cyanidesamples are preserved with NaOH. Totalorganic carbon and hardness samples arepreserved with sulfuric acid. Dissolvedsamples are filtered in the laboratory within72 hours of collection.

Figure 7. Ambient Program sample events and mean dailyriver flows: Sacramento River at Freeport.

Figure 6. Ambient Program sample events and mean daily riverflows: American River at Discovery Park.

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Figure 8. Compliance with US EPA water quality criteria:American River sites.

Figure 9. Compliance with US EPA water qualitycriteria: Sacramento River sites.


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Equipment Cleaning: All sample tubing andsample containers are acid rinsed andsoaked in concentrated nitric acid before use.After washing, tubing ends are covered andtubing is placed in acid rinsed plastic bagsfor transport to the field.Field Quality Control: Field quality controlincludes sampling procedures to avoidcontamination and use of field controlsamples. Field control samples include fieldblanks, bottle blanks, and Milli-Q waterblanks.Laboratory QA/QC Procedures: Both exter-nal and internal laboratory QA/QC proce-dures are employed. External laboratoryquality control samples include blind fieldduplicates, blind spike samples, and blindduplicate spikes. Internal laboratory qualitycontrol samples include laboratory dupli-cates, matrix spikes, matrix spike duplicates,method blanks, and filter blanks. One set ofinternal QC samples is run with each batchof field samples.

Monitoring Results

Data collected over the three plus years ofthe Ambient Program have indicated thefollowing:

1. The monitoring effort has taken place overa wide range of flow conditions in theSacramento and American Rivers (Figures6 and 7). The monitoring data collected todate demonstrates the dynamic waterquality conditions which exist in thesewater bodies.

2. Total recoverable levels of most tracemetals generally exhibit a seasonal patternin the Sacramento River, with higherconcentrations occurring during the wetseason (November through April) whenriver flows and suspended solids levels arehighest. The pattern of correlations be-tween river flows and total recoverablemetals concentrations is consistent with

the hypothesis that episodic high riverflows are a primary mechanism of bothsediment and trace element transport inthe Sacramento River system.

3. Levels of trace elements in the AmericanRiver generally do not exhibit significantcorrelation with river flow. Median valuesof suspended solids, temperature, hard-ness, organic carbon, and trace metals aretypically lower in the American River thanin the Sacramento River.

4. For compliance evaluation purposes, it isassumed that Environmental ProtectionAgency (EPA) criteria will be interpreted asdissolved (as recommended by EPA) for alltrace elements except mercury and sele-nium. A compliance problem exists withEPA human health criteria for total mer-cury in the Sacramento River. A complianceproblem would arise for arsenic in bothrivers if EPA’s controversial human healthcriterion (0.018 µg/L) is applied. For allother trace elements, no complianceproblems have been observed (Figures 8and 9).

5. An analysis of trace element concentrationchanges in the Sacramento River indicate aslight increase in the concentration of zincdownstream of the Sacramento metropoli-tan area. In the American River, smallconcentration increases have been observedfor copper, lead, and mercury.

Future Direction

The Ambient Program is producing data inaccordance with the monitoring objectives ofthe CMP. The CMP Steering Committee annu-ally reviews the program to reconfirm goals andmake appropriate adjustments. It is expectedthat the CMP monitoring effort will ultimatelybe incorporated into the Sacramento RiverWatershed Program monitoring plan which isnow being developed and is scheduled forimplementation in 1997.

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Sacramento River Watershed Program and theSacramento River Toxic Pollutant Control Program

Val Connor, Central Valley Regional Water Quality Control BoardSacramento, California

The Sacramento River Toxic PollutantControl Program (SRTPCP) was initiated inOctober of 1995. The long-term goal of theSRTPCP is to develop and implement a pro-gram that will bring the Sacramento River andits tributaries into compliance with waterquality standards for toxic pollutants andthereby protect beneficial uses. The SRTPCP isintended to be a long-term, multi-year program,and its success will require the active participa-tion of the various parties who have a “stake” inthe quality of the River and its tributaries (i.e.the “stakeholders”). For that reason, a secondgoal of the SRTPCP is to assist in the formationand maintenance of a viable organization ofwatershed stakeholders. It is intended that thestakeholder organization address not only thetoxic pollutant-related issues in the watershed,but the broader water quality issues necessaryto protect and enhance surface and groundwaters throughout the watershed. The broaderprogram being conducted by this stakeholderorganization has been named the SacramentoRiver Watershed Program (SRWP). TheSRTPCP is just one element of the SRWP.

The SRWP, although initiated by theSRTPCP, is much broader in scope. The SRWPis intended to address all water quality-relatedissues within the watershed, not just toxicpollutants. Potential additional issues include,but are not limited to, habitat, endangeredspecies, flow, temperature, sedimentation, andgroundwater. The goal of the SRWP is to ensurethat current and potential uses of thewatershed’s resources are sustained, restored,or, where possible, enhanced, while promotingthe long-term social and economic vitality of theregion. The SRWP consists of many individualprojects, programs, and specific tasks. Twocornerstones of the SRWP are comprehensive

monitoring and communication. Currently,information on existing monitoring programs isbeing compiled for two reasons: to summarizethe existing state of the watershed regardingtoxic pollutants and to identify overlap and“holes” in the existing watershed monitoringprograms. Participation in the SRWP does notrequire individual projects to assume a singlecommon goal. Instead, the SRWP relies oninformation exchange to connect existing andpotential projects.

In September 1997, the first State of theWatershed report will be released. This firstreport will focus on summarizing what isknown about toxic pollutants in the Sacra-mento Watershed. The report will includeinformation and data from all recent or ongoingmonitoring, research, demonstration andplanning programs and other activities relatedto the sources, effects, extent, and control oftoxic pollutants within the Watershed. Recom-mendations will be developed for future re-search, monitoring, and other activities thatwill facilitate the control of toxic pollutantswithin the Watershed.

A comprehensive monitoring program isbeing designed to augment and link the exist-ing programs. This comprehensive monitoringplan will build on the current monitoringprograms of the Department of Water Re-sources (DWR), the Department of PesticideRegulation (DPR), the Department of Fish andGame (DFG), the US Geological Survey,Sacramento’s Ambient Monitoring Program(AMP), the Regional Monitoring Program, andothers. The components of the monitoringprogram are being phased in as funding be-comes available. Toxicity testing with the EPA’sthree species (fathead minnow, Ceriodaphniadubia, and Selenastrum capricornutum) began


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in August 1996. Chemical monitoring is sched-uled to begin in January 1997. Biological andhabitat assessment of urban creeks and tribu-taries to the Sacramento River will begin inJune 1997; these assessments will be conductedby local community groups, high schools, andcolleges. All components of the monitoringprogram will have strong quality assuranceelements.

One of the major goals of the SRWP is topromote the exchange of information among theexisting programs and projects within thewatershed. This is being accomplished bymeetings and education workshops on topics ofinterest. Three workshops are planned for

1997, covering groundwater issues, drinkingwater issues, and mercury.

The SRWP has several subcommitteesfocusing on the following areas: monitoring,toxic pollutants, education, coordination,tributary watershed conservancies and pro-grams, funding, biological and habitat assess-ments, and the SRTPCP grants. To participatein any of these subcommittees, the SRWP, or tobe put on the SRWP mailing list, contact ShellyMorford at (916) 255–3100. For more informa-tion on either the SRWP or the SRTPCP,contact Val Connor at (916) 255–3111 or by e-mail at: [email protected]

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San Francisco Bay Area Storm Water RunoffMonitoring Data Analysis, 1988–1995

Summary and RecommendationsBay Area Stormwater Management Agencies Association

This brief summary represents an excerptof a report prepared for the Bay AreaStormwater Management Agencies Association(BASMAA) highlighting the findings of stormwater runoff monitoring programs from 1988 to1995.1 Runoff data have been collected by anumber of Bay Area agencies for a variety ofpurposes including characterization of pollut-ant concentrations from different land-useareas, assessment of compliance with receivingwater quality objectives, source identification ofpollutants and toxicity, and evaluation of BestManagement Practice (BMP) effectiveness. Thefocus of this data analysis project was tocompile all Bay Area runoff data into a cohesivedatabase and to perform analysis typicallyconducted by each agency. Combination of alldata provides a greater understanding of thequality of runoff and increases the confidence inthe conclusions drawn from statistical andregulatory comparisons.

Bay Area Monitoring Data:Findings

Review of existing storm water qualitymonitoring data collected in the San FranciscoBay Area have yielded the following findings:

• Concentrations of metals in runoff fromurban areas are generally lower than theEnvironmental Protection Agency’s (EPA)dissolved water quality criteria for theprotection of aquatic life.

• Concentrations of total cadmium, copper,lead, nickel, and zinc are sometimeshigher than the Basin Plan water qualityobjectives for the protection of aquaticlife. However, results from toxicityidentification evaluations indicate thatwhen toxicity is found in waterways it is

generally attributable to nonpolarorganics and not due to particulates ordissolved metal ions.

• Storm water runoff is often toxic to thelaboratory test organism Ceriodaphniadubia (water flea). For most waterways,the organisms die between 1 to 7 days ofexposure to runoff. The commonly usedorganophosphate insecticide diazinon hasbeen identified as the cause of the ob-served toxicity in some residentialwatersheds.

• Concentrations of total mercury aregenerally higher than the chronic EPAWater Quality Criteria (WQC) and BasinPlan Water Quality Objectives (WQOs).However, these standards are designed toprevent accumulation of mercury in fishtissues to levels that are hazardous toeat. It is unclear if the duration of stormflows in creeks is long enough to permitaccumulation to hazardous levels. Asimilar objective for the Bay is based on a30-day averaging period.

• Concentrations of metals in runoff fromdifferent types of urban land uses (resi-dential, commercial, industrial, transpor-tation) are generally not statisticallydifferent from one another. Within anyone monitoring station, variations instorm characteristics, timing, and specificurban activities cause the concentrationsto vary over a wide range, hampering ourability to observe differences betweenwatersheds caused by differing land use.

• Runoff from developed urban areasgenerally contains higher concentrationsof metals than runoff from undevelopedareas. However, total metal concentra-tions in runoff from open space can be

1 Copies of the full report are available through BASMAA (510) 286-0615.


269

higher than metals in runoff from heavyindustrial areas due to elevated concen-trations of suspended and settleablesolids associated with erosion.

Effectiveness of Monitoring

The two primary goals of the long-termstream monitoring are:

1. Determine trends in water quality andaugment the long-term database to includea range of hydrological and water qualityconditions for representative waterways inthe Bay Area.

2. Determine how receiving water qualityduring storm events compares with avail-able water quality and toxicity objectives.The ability to determine trends in water

quality due to implementation of BMPs in thefour to six monitored watersheds is limited byour understanding of the influence of variationsin hydrology on water quality. At selectedstations, enough monitoring data have beencollected to allow establishing relationshipsbetween event and antecedent conditions andwater quality. At one watershed such an analy-sis has been conducted and shown that much ofthe variability can be explained by changes inhydrologic factors (WCC, 1995; WCC, 1996).These observations indicate that if detection oftrends is a desired goal many (greater than 15)storm events need to be monitored over severalyears to encompass the range of hydrologicconditions. Therefore, at stations with fewstorms sampled, such as those in Contra CostaCounty, trend detection will be difficult until anadequate database has been established.

Existing monitoring results are adequate toprovide a general understanding of how waterquality compared with available water qualityobjectives and criteria and toxicity objectivesfor most trace metals. Data on organic com-pounds at detection levels that are adequate tocompare with federal criteria are more sparse.Specifically, low-level monitoring for PAHcompounds has been conducted for a few eventsat four waterway stations in Santa ClaraCounty and three waterway stations inAlameda County. Few waterway stations have

been monitored for low-level diazinon/chlorpyrifos and none have been monitored forlow-level PCBs. However, the utility of monitor-ing for PCBs is questionable as these com-pounds have been banned since the 1970s andfew, if any, active source control efforts could beenacted by storm water agencies. Additionally,diazinon/chlorpyrifos control is currently thefocus of an intensive BASMAA special studyand workgroup funded in part through an EPAgrant. Therefore, it is not clear that additionallong-term monitoring by BASMAA agencies isnecessary at this time.

PAH data are adequate to show certaincompounds exceed the federal water qualitycriteria designed to prevent food fish fromaccumulating hazardous levels of PAHs. How-ever, it is unclear if PAH concentrations inrunoff persist long enough to allow accumula-tion in fish. Also fish tissue quality in the Bayis currently the focus of an extensive RegionalMonitoring Program Special Study. It is recom-mended that the RMP study explore the possi-bility of sampling fish from streams withsignificant fisheries as well as the Bay.

Recommendations for Changesto Monitoring

Five changes to monitoring programs in theSan Francisco Bay Area are recommended:

1. Dissolved metal concentrations are rarelyfound to be higher than the EPA WQC.However, total metals often exceed theWQO in the San Francisco Bay Basin Plan.To determine if the particulate metals instorm water are causing a potential impactto sediment dwelling organisms, it isrecommended that a pilot sediment assess-ment program be initiated. This pilotprogram should use sediment toxicitytesting, and chemical characterization, aswell as biological assessment techniques toevaluate potential impacts. Because mostof these techniques are in the developmen-tal stage the program should be initiatedon a trial basis in one watershed to allowrefinement of these tools for urban water-ways.

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2. Duration and variability of dissolved metalconcentrations during and after stormevents has not been investigated for mosturban waterways. Because sediment/waterinteraction is complex, it is not known ifdissolved metal concentrations increase ordecrease following storm events. It isrecommended that a special study beconducted using in-field filtration todetermine how dissolved metal concentra-tions vary within and following stormevents.

3. Few reliable measurements of streamquality during dry weather have beenconducted. It is recommended that someeffort be spent to determine metal anddiazinon concentrations in waterways withsignificant dry weather flows.

4. Few reliable measurements of chromium(VI) have been performed. As chromium(VI) is the predicted form of chromium infresh water it is recommended that grab

samples be collected and analyzed fordissolved chromium (VI) using improvedlow-level methods appropriate to environ-mental surface water monitoring. Theseresults can be used to confirm previousresults which used older EPA methods.

5. Hydrologic factors are responsible for alarge portion of the observed variability inindividual watersheds. If the goal of themonitoring program is to detect changes inwater quality due to BMP implementation,the variability due to hydrology should beaccounted for in order to detect a trend. Itis recommended for those watershedswhere trend detection is desired that arange of storms should be sampled whichreflect the distribution of antecedent andevent-specific hydrologic parameters.Additionally, records should be kept ofrainfall and flow in the monitored water-shed to allow calculation of appropriatehydrologic statistics.

Conclusions

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CHAPTER SEVEN

Conclusions

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Temporal and Spatial Variations in Trace ElementContamination in the San Francisco Bay Estuary

Russ Flegal, Department of Environmental ToxicologyUniversity of California, Santa Cruz

Introduction

The San Francisco Estuary RegionalMonitoring Program (RMP) has established asystematic, and relatively comprehensive,survey of temporal and spatial distributions oftrace elements in the Estuary. The programhas replaced a hodgepodge of disparate sur-veys that used a variety of methods to measuredifferent trace element concentrations indifferent parts of the Estuary during differentperiods. With the new program, it is nowpossible to identify areas of anomalisticallyhigh trace element concentrations in theEstuary, determine the factors causing thatpollution, and develop means to control it. Assuch, the RMP now serves as the nationalmodel, promulgated by the United StatesEnvironmental Protection Agency’s Office ofWater, for monitoring trace element contami-nation in aquatic systems.

Establishing A SystematicProgram of Sampling andAnalyses

Previous programs to investigate traceelement contamination in San Francisco Baywere characterized by their limited scope andanalytical inconsistencies. Without a system-wide perspective, the studies were usuallylimited to a few measurements in a specificregion of the Estuary within a small timeperiod. The parochialism of those samplingdesigns precluded a comprehensive assess-ment of the state of the Estuary. Previousreports of trace element concentrations in theEstuary also varied by orders of magnitude,because of inconsistencies among the samplingand analytical techniques employed in differ-ent studies. Consequently, it was impossible toderive even a superficial perspective of thedistribution of trace elements in the Estuary

through a composite analysis of data collectedin those previous programs.

Those problems have been resolved withthe creation of a systematic sampling programfor the entire Estuary. Since samples arecollected from the freshwater confluence of theSacramento and San Joaquin Rivers at thenorthernmost reach of the Estuary down tosloughs in the southernmost reach of theEstuary, pronounced spatial differences in sometrace element concentrations are readilyapparent in plots of those data. Since three setsof samples are collected each year and theprogram has been in place for several years,seasonal and annual variations in the spatialgradients are also readily apparent. Finally,since rigorous sampling and analytical proto-cols have been utilized in the generation of allof those data, comparisons of spatial andtemporal variations in the trace element dataare not circumspect.

Identification of Areas ofConcern

The program has identified two principalproblems with trace element contamination inthe Estuary. Copper and nickel concentrationsexceed water quality criteria in the southernreaches of the Estuary during some periodswhen freshwater discharges to the Estuary arelowest. These seasonal increases have beenhighest during drought years when freshwaterdischarges to the Estuary have been minimal.

Consequently, trace element contaminationin the southern reach of the Estuary appears tobe caused by a combination of local and system-wide factors. These include:

1. Temporal reductions in freshwater dis-charges from the Sacramento and SanJoaquin Rivers,

Conclusions

273

2. Local inputs from waste water outfalls intothe South Bay,

3. Seasonal releases from contaminatedsediments within the South Bay, and

4. Surface runoff from areas surrounding theSouth Bay.

The impacts of each of those factors arebriefly summarized in the following sections.

Hydraulic Flushing

Many trace element concentrations in theSouth Bay vary inversely with the volume offreshwater discharges into the Sacramento andSan Joaquin Rivers. Notably, copper and nickelconcentrations often exceed water qualitycriteria in the South Bay during summerperiods when riverine flows to the Estuary arelowest, and trace element concentrations in theSouth Bay are often lowest during the winterand early spring when those riverine flows aregreatest. This pattern corresponds with thehydraulic flushing model proposed by theUnited States Geological Survey nearly threedecades ago to account for the similar temporalvariations of nutrient concentrations in theEstuary. Consequently, (1) elevated trace metalconcentrations in the South Bay may be con-trolled by freshwater discharges to the north-ern reach of the Estuary and (2) factors control-ling trace element concentrations in theEstuary may be partially resolved by analogieswith factors controlling nutrient concentrationsin the Estuary.

Waste Water Discharges

While a cursory analysis of the monitoringdata supports the common public perceptionthat waste water discharges are solely respon-sible for pollution in the San Francisco BayEstuary, more detailed analyses show thatother sources are also important. The season-ally high concentrations of copper and nickel inthe southern reach of the Estuary fit a simpledilution mixing line between the concentrationsof those elements in sea water and in wastewater discharges into the South Bay, but morerigorous mass balance calculations and

geochemical analyses demonstrate that inputsof trace elements (including copper and nickel)from other sources may be equal to, or in somecases exceed, inputs from waste water dis-charges into that area. Those analyses arecorroborated by similarities in trace elementexcesses in the northern reach of the Estuaryfor the past two decades, in spite of one to twoorders of magnitude reductions in trace ele-ment discharges into the Estuary during thatperiod. [The comparison of temporal variationsin the northern reach of the Estuary over thatextended period is possible because there is oneset of data for that period that was collectedand analyzed with comparable trace metalclean techniques, which have beenintercalibrated with the analyses utilized in thecurrent program.] Therefore, other internalsources must contribute to the seasonal ex-cesses of some trace elements within theEstuary.

Sedimentary Inputs

While sediments have historically beenconsidered a “sink” for trace elements inestuarine waters, they now appear to be one ofthe principal “sources” of trace elements in SanFrancisco Bay during some periods when thereis an intense decomposition of organic materialwithin those sediments. This sedimentary inputof trace metals to the overlaying water columnis based on parallels in seasonally elevatedconcentrations of trace elements and nutrientswithin the water column, which coincide withthe decomposition of organic matter in benthicsediments that solubilizes nutrients and traceelements. Preliminary mass balance calcula-tions indicate that benthic fluxes of some traceelements are much greater than their inputsfrom rivers draining into the Estuary; and, insome cases, the estimated benthic fluxes ofsome trace elements are comparable to theirinputs from waste water discharges into theEstuary. Consequently, the elevated traceelement concentrations in San Francisco Baywaters appear to be partially due to chronicinputs from historically contaminated sedi-ments within the Estuary.

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Urban Runoff

One of the limitations in the precedinganalyses of the total amounts and relativecontributions of different sources to traceelement concentrations in the Estuary is theabsence of comparable information on traceelement fluxes from non-point sources orsurface runoff. This includes runoff from bothurban and rural areas that drain into theEstuary. Based on analogies with nutrientfluxes in other estuaries (because there are alsoinsufficient data on surface runoff of traceelements in others estuaries), surface runoff isbelieved to be an important source of sometrace elements in San Francisco Bay. Thisincludes copper, which may be elevated in theSouth Bay by surface runoff containing rela-tively high concentrations of copper dustgenerated from the abrasion of automobilebrake pads.

Rural Runoff

While the program has not monitoredsurface runoff directly, analyses of temporalvariations in some of the program’s dataprovide evidence of the relative importance ofsurface runoff from rural runoff or agriculturaldrainage. This was first indicated by thecoincidence of anomalistically high chromiumconcentrations in the northern reach of theEstuary and episodic discharges of freshwaterfrom the Yolo Bypass. It is now being evaluatedwith more complex geochemical analyses andmass balance calculations. Although thoseinputs may be ephemeral, they may substan-tially impact the Estuary for a protractedperiod, because they may increase the recyclingof trace elements and nutrients from theestuarine sediments.

The potentially substantial impact offreshwater discharges from the Yolo Bypass ontrace element and nutrient distributions in theEstuary was only detected after several years ofdata had been collected. An extended samplingperiod was needed to identify those agriculturalinputs, because they are episodic and only occurduring periods of unusually large freshwater

discharges. Since there were no large dis-charges from the Yolo Bypass during thedrought years when the program was initiated,bypass releases of freshwater withanomalistically high chromium and silicateconcentrations were not detected during thatperiod. Moreover, those releases would not havebeen apparent until a sufficient amount of dataon the variability of trace element and nutrientconcentrations in freshwater discharges to theEstuary had been acquired.

Multiphase Approaches toRemediation

The suite of information on trace elementdistributions and cycles in the Estuary gener-ated by this program has been incorporated inmultiphased approaches to remediate problemsof trace element contamination within theEstuary. For example, problems of copper andnickel contamination in the South Bay may bediminished by actions that address each or allof the preceding factors that contribute to thoseelevated concentrations. This creates a series ofoptions that may be evaluated in terms of theirrelative efficacy and cost. For example, thefeasibility of reducing surface runoff of copperby controlling its use in brake pads is beingconsidered as an alternative means of decreas-ing copper concentrations in the South Bay,because waste water discharges of copper to theSouth Bay have already been decreased by 95%and additional reductions in waste watercopper loadings may not be cost-effective. Thatinnovative approach to control trace elementcontamination in San Francisco Bay has beenrecognized nationally as a model for collabora-tions among industry, municipalities, regula-tory agencies, and public interest groups.

Catalysis of ComplementaryStudies

By identifying areas of concern, the RMPhas catalyzed additional studies that specifi-cally address those concerns. Notable amongthese are studies to determine whether thewater quality criteria for copper in the SouthBay are appropriate. These include measure-

Conclusions

275

ments of the chemical speciation of copper,which show that a large fraction of the dis-solved copper in the South Bay is in forms thatare not readily available to the biota. Therehave also been studies with estimates of therelative importance of inputs of copper to theSouth Bay from waste water discharges andcontaminated sediments, which indicate thatboth contribute to the elevated levels observedduring the summer period. These, and similarstudies, have facilitated the development ofappropriate actions to address those areas ofconcern.

The complementary studies have benefitedfrom the RMP in three other ways. First, theprogram has provided an efficient means tocollect additional samples and conduct comple-mentary analyses. Second, the programssampling cruises have often been coordinatedwith those of other programs (e.g., the UnitedStates Geological Survey) to expand thebreadth and scope of the collections. Third, datafrom the program have been provided forevaluation and modeling by other groups (e.g.,Stanford, University of California, USGS)interested in the cycling of trace elements inthe Estuary. Consequently, the data base fortrace elements in the Estuary is now muchgreater than the one generated by the RMPalone, and numerous groups are involved inanalyses of that expanded data base.

The National Model forMonitoring Trace Elements inAquatic Systems

The success of the RMP has been recog-nized on a national level. The Office of Water ofthe US EPA has developed new protocols formeasuring trace elements in aquatic systemsthat are based, in large part, on the RMP.These include ten new methods for sampling,processing, measuring, and reporting traceelement concentrations using techniquesemployed in the RMP. That methodology hasbeen presented at two US EPA national meet-ings in Norfolk, Virginia, and five US EPATrace Metal Workshops around the UnitedStates (Boston, Massachusetts; Chicago,

Illinois; Denver, Colorado; San Antonio, Texas;Seattle, Washington). Presentations at each ofthose meetings have included both a video ofthe sampling program in San Francisco Bayand a discussion of the success of that program.As a result, the RMP is now serving as thenational model for monitoring trace elements inaquatic systems.

Judicial Confirmation of theMethodology in Civil Litigation

The judicial credibility of the methodologyincorporated in the monitoring program hasbeen substantiated in litigation. This occurredin a Proposition 65 class action suit in Califor-nia, which was based on analyses of elevatedlead concentrations in solutions in some leadcrystal glassware. Since the analyses used thesame protocols as the monitoring program,which had been approved by both the CaliforniaState Water Resources Control Board and USEPA, the judge ruled the analyses were valid. Asa consequence, the resulting settlement favoredthe complaints of the citizens of California.

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A Summary of Mercury Effects, Sources,and Control Measures 1

Alan B. Jones, Brooks Rand, Ltd. Seattle, WashingtonDarell G. Slotton, University of California, Davis

Introduction

Mercury is but one of the toxic heavymetals that contaminates much of the watersand sediments of the San Francisco Estuary. Ithas been found throughout the Estuary atelevated concentrations in water, sediment, andbiota. It accumulates in tissues and is magni-fied in higher orders of the food web. The formof mercury that typically bioaccumulates in fishis monomethyl mercury, which can constitute85% of the total tissue mercury. The balance isthe soluble, ionic form of mercury, Hg+2 which iscommonly found in the gut lining. However, inedible muscle tissue (fillet), the portion nor-mally consumed, virtually all of the incorpo-rated mercury is in the monomethyl form. Fishat the top of the food web can harbor mercuryconcentrations in their tissues over one milliontimes the mercury concentration in the water inwhich they swim.

Bivalves appear to accumulate mercury in amanner different from fish. Mercury in theseorganisms accumulates principally as Hg+2 andonly 15–20% of the total mercury is methylmercury. Consequently, a doubling of the mosttoxic form of mercury, monomethyl mercury,can occur in bivalves without producing astatistically significant change in concentrationof total tissue mercury.

Partly as a result of the tremendous in-crease in mercury production and use in thiscentury and partly as a result of the manysoluble species of mercury, mercury contamina-tion is now virtually worldwide in extent andwidespread in our environment. It travelseasily through different environmental media,including the atmosphere, in a variety ofchemical forms and is toxic to humans andbiota in extremely low concentrations. In water

environments, conjugation with particlesdominates the movement and fate of mercury(PTI, 1994; Schoellhamer, this report). Inaddition to experiencing the general, industri-ally-related, global increase in mercury distri-bution over the last century, California isunique in also being the site of massive bulkcontamination by the element. The CaliforniaCoast Range contains one of the world’s greatgeologic deposits of mercury. This mercury wasmined intensively during the late 1800s andearly 1900s, largely to supply Gold Rush eragold mining in the Sierra Nevada, where themercury was used in the gold extraction pro-cess. A legacy of leaking Coast Range mercurymines and lost Sierra Nevada quicksilver nowprovides a significant, additional, ongoingburden of mercury to the Delta and Bay fromboth sides of the state.

Mercury Sources

Mercury, which occurs as a result of bothnatural and anthropogenic sources in ourenvironment, continually cycles in the marineenvironment of the Estuary. The cycle involvesdifferent forms and species of mercury as aresult of both chemical and biological reactionsin aerobic and anoxic microenvironments. Untilseveral years ago, estimates of the naturalbackground level of mercury were unrealisti-cally high due to erroneous data, giving theimpression that anthropogenic contributions tothe global mercury flux were less than theytruly are (Fitzgerald and Clarkson, 1991). Thegeneration of erroneous data arose because of alack of appreciation for the ease of cross-contamination and the lack of sufficientlysensitive instrumentation to measure mercuryin soil, water, and air. A schematic of the cycleis shown in Figure 1.

1 This summary contains excerpts from a more extensive report available from SFEI.

Conclusions

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The bulk of the mercury is normallypresent as Hg+2 in the early stages of deposition,but over time it is probably converted byinorganic chemical reactions to the moreinsoluble cinnabar (HgS). In California, cinna-bar is the primary form of the Coast Rangemercury deposits. The mercury used in goldmining in the Sierra Nevada was refined liquidquicksilver (elemental mercury, Hg0), thoughthis elemental mercury likely experiencedvarious transformations once back in theenvironment. The concentration and rate offormation of HgCH3 (methyl mercury) inanaerobic sediment and water is thought to beproportionate to the amount of HgS, not theamount of total mercury. There are otherfactors which influence these reactions includ-ing pH, temperature, oxygen/redox level,salinity, toxicity, rate of sediment deposition,rate of pore water transvection, rate of mercurydeposition, species of mercury deposited (Hg0 orHg+2), and the rate of HgCH3 removal bybioaccumulation.

On a world-wide scale, volcanic depositsand mining sources are geographically localizedbut, in California, they are of great importance.Most additional mercury sources are part of awidespread, global cycle. The release, deposi-tion, and movement of mercury through these

global pools has been catalogued, as shown inTable 1.

Natural Sources

Mercury occurs naturally in the environ-ment and thus has a background concentrationindependent of man’s releases. Mercury canoccur naturally in a variety of valence statesand conjugations and as an organometal suchas methyl mercury (CH3Hg and (CH3) 2Hg).Moreover, through natural chemical andbiological reactions, mercury changes formamong these species, becoming alternatelymore or less soluble in water, more or less toxic,and more or less biologically available.

As with any site on the globe, there isnatural mercury contamination in San Fran-cisco Bay. The recent spate of forest fires inNorthern California alone undoubtedly contrib-uted some mercury to this environment.Clearly, in California there is an ongoing load ofsome magnitude associated with the generalexport of mercury from natural cinnabardeposits, in addition to mining-related pointsources. It is difficult to determine just whatproportion of mercury in the Bay Area is fromnatural sources because what is natural variesgreatly from one part of the world to the next.Because of airborne mercury pathways, there isno part of the globe today untouched by the

Sediment

Boundary

Bioaccumulation PELAGIC ECOSYSTEM

Hg +2

CH3

2 CH3CHOOHPore Water Transvection

HgCH3HgS ↔ S2- + Hg +2

Demethylating BacteriaHgCH3

Aerobic / Anaerobic Boundary, or

Redox Potent ia l Discont inuity (RPD)

2H2O + 2CH3COO-

SulfurReducing Bacteria

SO2

Hg0

BENTHIC ECOSYSTEM

+

Figure 1. Mercury cycling in a marine environment.

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world-wide increase in both use and release ofmercury by man in this century. Current andproposed research at the University of Califor-nia, Davis, seeks to differentiate and quantifythe generalized global atmospheric contributionof mercury in California, as compared toregional and point sources.

Volcanic

Mercury is initially released into thebiosphere through volcanic activity. Mercury ispresent in the earth’s crust at a concentrationof 0.5 ppm. Mercury typically forms the sulfide(HgS) because of the prevalence of sulfides involcanic gases. In this fashion it is foundnaturally in deposits as the red sulfide ore,cinnabar. It is commercially mined as this form.Volcanic sources emit an estimated global totalof 60,000 kg of mercury per year.

Forest fires

Biomass, particularly trees and brush,accumulate and harbor a substantial fraction ofthe biosphere’s mercury. When forest fires heatthese fuels to temperatures well above theboiling point of mercury (357°C), the mercurymay be released to the atmosphere as eitherHg+2 or the decomposed Hg0. The Hg0 releasedmay be oxidized in the atmosphere over time toHg+2 which is also quite soluble in water and so

dissolves in the moisture in the air whenreleased in this fashion.

Forest fires and rain are responsible for thetransport and deposition of mercury over muchof the world’s surface, regardless of its source.

Oceanic releases

Mercury is also a component of seawaterand is released naturally through the evapora-tion of elemental mercury from the ocean’ssurface. Both elemental and ionic mercury aresoluble in water, although elemental mercury toa much smaller degree. As less soluble elemen-tal mercury evaporates, the equilibrium reac-tion is pulled towards more elemental mercury,which then releases more elemental mercuryfrom the ocean’s surface. The equilibriumreaction between ionic and elemental mercuryis shown below in Equation 1:

Hg+2 Aq + 2e-- ↔Hg0 Atmos Equation 1

Ionic mercury can form from the oxidationof elemental mercury or from thedemethylation of monomethylmercury.

Anthropogenic Sources

Mercury is used in a broad array of morethan 2,000 manufacturing industries andproducts (Kurita, 1987). These include barom-eters, thermometers, hydrometers, pyrometers,

Table 1. Global atmospheric mercury (Fitzgerald and Clarkson, 1991)

Source s Hg Move me nt1 0 9 g/yr

Re fe re nce

Atmospheric Hg Deposition : 5–6 Fitzgerald, 19866 Slemr et. al., 1981

Atmospheric Hg Emissions : Anthropogenic 2 Watson, 1979Natural 3.6 Nriagu and Pacyna, 1988Volcanic 0.06 Fitzgerald, 1986

Other Continental Sources : 1–2Crustal DegassingForest FiresBiological Mobilization

Oceanic Sources : Equatorial Pacific 0.2 Kim and Fitzgerald, 1986World Ocean 2 Nriagu and Pacyna, 1988

Fluvial Hg Input : 0.2 Gill and Fitzgerald, 1987

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Name Form Source or UseMercury Metallic or Elemental (Hg0) Chlorine-alkali manufacturing

Dental fillingsGold miningElectrical equipment (batteries, switches)Instruments (thermometers, barometers)

Mercuric mercury Inorganic (Hg +2) Electrical equipment (batteries, lamps)Skin care productsMedicinal products

Mercurous mercury Inorganic (Hg1+) Electrical equipment (batteries)Medicinal products

Methyl mercury Organic (CH3 Hg1+) Diet (e.g., contaminated fish)Polluted sediment

Phenyl mercury Organic (C6H5 Hg1+) FungicidesPigments (paints)

mercury arc lamps, switches, fluorescent lamps,mercury boilers, mercury salts, mirrors, cata-lysts for the oxidation of organic compounds,gold and silver extraction from ores, rectifiers,cathodes in electrolysis/electroanalysis, and inthe generation of chlorine and caustic paperprocessing, batteries, dental amalgams, as alaboratory reagent, lubricants, caulks andcoatings, in pharmaceuticals as a slimicide, indyes, wood preservatives, floor wax, furniturepolish, fabric softeners, and chlorine bleach(Volland, 1991). Individual industries usedifferent forms of mercury as well, as shown inTable 2.

The United States produced about 3,435tons of mercury in 1986 and imported another6.5 tons. It is estimated that the US exportedabout 32.5 tons of mercury that year, yielding anet domestic annual use of about 3,409 tons ofmercury. Of this use, 50% to 56% was used inthe electrical industry, 12% to 25% was used inchloralkali plants to generate chlorine andcaustic soda, 10% to 12% was used in paintmanufacturing, and about 3% was used in thepreparation of dental amalgams (Sills, 1992).

Mining

In addition to the generalized global andlocal industrial sources of mercury describedabove, the watershed of the San FranciscoEstuary contains a tremendous amount of

mining-related, bulk mercury contamination.Historically, mercury was mined intensively inthe Coast range and transported across theCentral Valley for use in Sierra Nevada placergold mining operations. Virtually all of thequicksilver used in these operations wasultimately lost into Sierran watersheds. It hasbeen estimated that, in river drainages of theMother Lode region alone, approximately 7,600tons of refined quicksilver were inadvertentlydeposited in conjunction with Gold Rush eramining (CVRWQCB, 1987). Additional mercurywas used throughout the gold mining belt of thenorthwestern and central Sierra Nevada. Themajority of Coast Range mercury mines whichsupplied this practice have since been aban-doned and remain unreclaimed. As a result ofthese two activities, bulk mercury contamina-tion exists today on both sides of the Valley.

Larry Walker and Associates (1995) mea-sured mercury concentrations and loads atindex stations on the Sacramento, Feather andYuba Rivers. In related work, Slotton et al.(1995) have, since 1993, evaluated the localbioavailability of mercury in all major rivertributaries throughout the northwestern Sierra.The water quality data indicate that a signifi-cant amount of Gold Rush era mercury stillexists in sediment in the upper Yuba watershedand that this is being transported down intoEnglebright reservoir, where it is largely

Table 2. Sources and uses of mercury (USDHHS, 1992)

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trapped. Bioavailability studies confirm thatthe reservoir acts as an interceptor of not onlyinorganic, sediment-based mercury, but ofbioavailable methyl mercury as well. Despitethe fact that elevated levels of mercury arefound in the heavily mined upstream tributar-ies and, particularly, within EnglebrightReservoir itself, the aquatic biota below theimpoundment consistently demonstrate signifi-cantly reduced concentrations of mercury, ascompared to above the reservoir. However, as acautionary note, the United States GeologicalSurvey (USGS) observed high concentrations ofmercury associated with particulate matter inhigh flows downstream of Englebright Reser-voir last winter. The USGS believes the mer-cury was deposited in the streambed beforeconstruction of the dam and is only now beingeroded away (Joseph Domagalski, personalcommunication). Therefore, much, but clearlynot all, of the mercury remaining in the Sierrasfrom historic gold mining may be unavailablefor downstream transport and biomagnificationin the Estuary. In the few high mercury riverswithout dams, particularly the Consumnes,direct transport of historic gold mining mercuryinto the Estuary remains unimpeded.

Recent work suggests that the Coast Range,rather than the Sierra Nevada, may be adominant source of mercury to Central ValleyRivers and the Estuary.

Another mercury mass load export studywas undertaken by the Central Valley RegionalBoard in the southwestern part of the Sacra-mento River watershed during 1995. Thespring of 1995 was wet, and water from theSacramento Valley entered the Estuarythrough both the Sacramento River and YoloBypass. Highly elevated concentrations ofmercury were repeatedly observed in theBypass. The source of a significant portion ofthe mercury was traced to Cache Creek, whichdrains Clear Lake and which is estimated tohave exported about a thousand kilograms ofmercury to the Estuary in 1995. Follow-upstudies by the Central Valley Regional WaterQuality Control Board and Slotton et al. areunderway to determine (1) whether the

source(s) of the mercury are localized to minesand (2) to determine the spatial trends in insitu bioavailability of mercury throughout thewatershed.

Also in 1995, a comprehensive synopticstudy was undertaken in the small MarshCreek watershed of Contra Costa County(Slotton et al., 1996). This research was con-ducted during a period of steady high flow,immediately following a series of large storms,to identify and quantify mercury sources andlocal aquatic bioavailability. All significanttributaries were sampled. The small drainagewas found to export 10–20 grams of mercuryper day, with greater amounts during actualstorm events. Mass balance calculations indi-cate that about 95% of the entire watershed’smercury load originated from the Mount Diablomining area; about 93% of this was from arelatively small patch of exposed mine tailings.

Coal-Fired Power Plants

Coal is known to contain mercury as aresult of testing done upon the flue gas emittedfrom power plant stacks. The quantity releasedby burning coal is estimated to be on the orderof 3,000 tons per year globally, about the sameamount released through all industrial pro-cesses (Joensuu, 1971). The concentration ofmercury in coal varies form as low as 70 ng/gup to 22,800 ng/g (ppb). During the burning ofcoal, mercury is initially decomposed to elemen-tal mercury and then, as the flue gas cools andexits the plant, the majority of the mercury isquickly oxidized, probably catalytically due tothe presence of other metals in the gas, to itswater-soluble, ionic form, Hg+2.

Gasoline and Oil Combustion

Crude petroleum is known to contain smallbut measurable amounts of mercury. A studyperformed on the mass of metals in crude oilsfrom 32 different sources stored in the nation’sStrategic Petroleum Reserves (SPR) in saltdomes in Oklahoma has determined that theaverage of mercury in petroleum is 0.41 ppm(Shur and Stepp, 1993). The standard deviationfor this average was a rather large 0.90 with

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one crude oil (Arabian) containing 5.2 ppmmercury. Another study of metals performed onpetroleum found a range of mercury concentra-tion from 0.03 to 0.1 ppm (Speight, 1991). Bothof these studies were performed using oldermercury analysis methods with method detec-tion limits of approximately 0.11 ppm. However,these studies also indicate minimum mercuryconcentrations in crude oil.

Approximately 16 to 18 million barrels (672to 756 million gallons) of crude oil are con-sumed daily in the United States. At an aver-age concentration of 0.41 ppm mercury and anaverage density crude oil of 6.9 lbs per gallon,the minimum total amount of mercury vapor-ized daily is therefore 1,901 lbs. This valuerepresents an annual discharge of 347 tons ofmercury nationwide, assuming that all of theoil is combusted. Certainly, the greatest propor-tion of the petroleum used in the United Statesis burned in vehicles. It is unclear whether themercury present in crude oil is vaporizedduring the refining process or whether itremains in the refined petroleum. Because ofthe very large volumes of oil consumed, even asmall concentration of mercury clearly repre-sents a major source of atmospheric depositionof mercury. More work with the more sensitiveanalytical methods developed in the past fewyears should be performed to confirm thesenumbers.

Smelting

The smelting of ores to yield pure metals isthought to release some mercury into theatmosphere. Most metal ores are thought tohave higher concentrations of mercury thancoal, although the volumes of ore that aresmelted each year pale in comparison with thevolume of coal burned for power generation.

Chlor-Alkali Plants

Elemental mercury is employed as theelectrode in the electrochemical production ofchlorine gas and caustic soda (sodium hydrox-ide). Near most paper and pulp facilities whichemploy this technology to bleach the paper

product white, the sediment is contaminatedwith high concentrations of mercury.

Mildew Suppression, Laundry facilities

An infrequent and historical point source ofmercury contamination has been the use ofmercury compounds for mildew suppression bylaundry facilities, which have a chronic prob-lem with moisture and bacterial growth (Sills,1992). This contamination source type shouldno longer be a problem. The use of mercury as afungicide in interior latex paints has beensimilarly banned by the US EPA.

Sewage Treatment

Sewage treatment represents the focalpoint of today’s urban industrial, commercial,and domestic liquid waste streams. The second-ary treatment of sewage involves dewatering,which necessarily concentrates the solids andall non-volatile contaminants, but does little totreat or remove inorganic dissolved contami-nants. Mercury is commonly found in urbansewage through point source discharges fromdental offices and industrial manufacturingprocesses such as battery fabrication. As thesewage is dewatered and the solids concen-trated, mercury can be either sequestered bythe organic humus of sludge or, if the sludge iscaked and dried, can be released to the atmo-sphere in the drying process.

If the sludge has been dried, the fate of thesludge itself then dictates the extent of mercurycontamination. Commonly, the dried product isincinerated or spread upon tree farms as afertilizer and organic material. Sewage sludgeincineration probably accounts for no morethan 3,000 kg/yr in mercury emissions (USEPA, 1990). The distribution of sludge in thisfashion also spreads concentrated mercury overa large area where it is either taken up in thebiomass or contributes to surface water runoffand consequently downstream contamination.

Difficulties can arise when dissolvedinorganic contaminants are not removed fromtreated wastewater prior to its reintroductionto receiving sewage. In Michigan’s upperpeninsula, the sediments and fish of 900-acre

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Deer Lake near Ishpeming were found in 1981to be severely contaminated with mercury as aresult of releases from the Ishpeming wastewater treatment plant and combined stormsewer overflows (Sills, 1992). The upstreamdischarge that contaminated the sewagereleases was from the laboratories of an ironore mining company.

Mercury dumping from naval vessels

The US Navy has surfaced as a majorsource of near-shore marine mercury pollutionbecause of the use of mercury as ballast in itssubsurface vessel fleet. During inter-shipballast transfer operations, elemental mercuryis occasionally spilled into marine waters,resulting in contamination of both sedimentand water. This could be a significant pointsource of mercury directly within the Estuary.

Influences upon Mercury PollutionpH

The pH of inland surface waters has beenfound to dramatically affect the amount ofmercury taken up by biota (Gilmour and Henry,1991). Specifically, mercury in fish tissue ispresent predominantly as methyl mercury, sochanges in the biogeochemistry of this com-pound of mercury may account for any increasein bioaccumulation. It has been determinedthat inorganic mercury binds to organic mattermore strongly as the pH declines (Schindler etal., 1980), thus decreasing mercury’s solubility.Conversely, in sediments a lower pH mayincrease the solubility of HgS (Ramal et al.,1995).

Salinity

Salinity has been statistically linked todissolved mercury concentrations in an inverserelationship, suggesting that local runoff maybe an important source of dissolved mercury inthe South Bay. As runoff increases and salinitydecreases, the concentration of dissolvedmercury increased (SFEI, 1993). Increasingsalinity has also been associated with a declinein the rate of mercury methylation and in

equilibrium methyl mercury concentrations(Compeau and Bartha, 1984).

Sulfate concentration

The microbial methylation of mercury isthought to proceed through the metabolicaction of sulfur-reducing bacteria (SRB) inanoxic environments (Gilmour and Henry,1991). The concentration of sulfate in marinewaters is approximately 28 mM, which isconsiderably higher than freshwater sulfurconcentrations. In freshwater systems, it isclear that an increase in sulfur concentrationincreases sediment sulfate-reduction rates(Rudd et al., 1986). However, there appears tobe a window of sulfate concentration thatpromotes the highest mercury methylationrate. Optimum mercury methylation by SRB insediments is at 200–500 mM. Above this range,the formation of sulfide appears to inhibitmethylation. At the same time, the presence ofother sulfide-forming metals, such as iron, mayaffect the equilibrium between sulfate andsulfide in the pore water of the system.

Percent Fines

In aquatic sediments, mercury and otherheavy metal contamination is most stronglycorrelated with the proportion of fine particles.This is particularly the case when the heavymetal load entering the system is largely in avery diffuse, molecular form, such as in atmo-spheric deposition, mine leakage of dissolvedmetals, and direct introduction to the environ-ment of liquid or vaporized elemental mercury.In local research at a Sierra Nevada foothillreservoir, bottom sediment concentrations ofmercury, as well as copper, zinc, and cadmium,were found to increase exponentially at averagesediment grain sizes of less than 24 microme-ters (Slotton et al., 1994; Slotton and Reuter,1995). In addition to largely determining theconcentration of mercury in the sediments,sediment particle size also affects the diffusionof oxygen, minerals, and ions which thereforeaffects bacterial activity and the production ofmethyl mercury.

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Aerobic and Anaerobic Microenvironments

Each transformation of mercury from onevalence state or one species to another takesplace in specific microenvironmental compart-ments (Figure 1). At the aerobic/anaerobicboundary in sediment, which is the limitingdepth for oxygen penetration into the sediment,there is a redox potential discontinuity (RPD).In the oxygen-rich environment of the uppersediment, the electrochemical potential isoxidizing, thus favoring oxygen metabolism andthe ionized (soluble) states of metals (e.g.,Hg+2). Conversely, the oxygen-poor lowersediment exhibits a reducing electrochemicalpotential that favors sulfur metabolism bysulfur reducing bacteria (SRBs). Two productsof microbial sulfur metabolism are HgS (whichis highly insoluble) and CH3Hg (which is theform of mercury most commonly found intissue), when mercury is present in the sedi-ment.

Where the water itself becomes anaerobic,methyl mercury production can increasedramatically and transfer rapidly and effi-ciently into the aquatic food web (Slotton, 1991;Slotton et al., 1995a). Piscivorous largemouthbass in this system accumulated filet mercuryat concentrations up to 10 times the 0.5 ppmhealth guideline.

Both the proportions of total and dissolvedmercury concentrations in the water and theirabsolute values can change due to shifts in theelectrochemical potential of the sediment and/or water. Hydrological impacts such as thedeposition of abnormally high volumes of silt,scouring, growth of algae or other oxygen-scavenging flora can dramatically alter mer-cury biogeochemistry and, consequently, theproduction, transformation, and concentrationof the different mercury species.

Mercury’s Health Effects

As mercury cycles through various formsand media, its bioavailability and toxicitychange through both biological and chemicalreactions. Because mercury is found throughoutthe environment, everyone is exposed to low

levels of mercury. Dental amalgams are them-selves about half mercury and it is known thatmercury in the breath of persons with mercuryamalgam fillings is higher than those without.However, the health effects of dental amalgamsis unknown. Mercury emanating from amal-gams is, at least initially, entirely in inorganicforms, which are not readily accumulated by thebody as compared to methyl mercury. Otherprincipal means of human mercury exposureare through the use of skin care products and,particularly, through the consumption of methylmercury-contaminated fish. The three pathwaysof exposure are then inhalation, absorption, andingestion.

The principal target of long-term exposureto low levels of metallic and organic mercury isthe nervous system. The principal target oflong-term exposure to low levels of inorganicmercury appears to be the kidneys (USDHHS,1992). Short-term exposure to higher levels ofany form of mercury can result in damage to thebrain, kidneys, and to fetuses. Mercury has notbeen found to be carcinogenic. However, thereare significant differences in the toxicity of themajor forms of mercury. Mercury has beenfound to have a deleterious effect upon a widerange of systems including the respiratory,cardiovascular, hematologic, immune, andreproductive systems.

The bioaccumulation of mercury in variousforms contributes in large measure to itstoxicity. Concentrations that have been docu-mented in a typical freshwater lake food webare shown in Table 3.

The common markers for human mercuryexposure are blood, hair, and urine mercuryconcentrations. The mean total mercury levelsin whole blood and urine of the general humanpopulation are approximately 8 µg/L and 4 µg/L,respectively (WHO, 1990). This backgroundlevel of mercury can vary considerably, however,with the incidence of dental mercury amalgamsand the consumption of fish. Individuals whosediet consists of large amounts of fish can haveblood methyl mercury levels as high as 200 µg/Lwith a daily intake of 200 µg of mercury.

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Data Trends in the RegionalMonitoring Program

One of the apparently striking conclusionsthat can be drawn from the data is the lack ofbioaccumulation of mercury in the bivalvestransplanted for periods of 90 to 100 days tovarious locations in the Bay for any of the threeyears of the RMP. Bivalves generally do notaccumulate dramatically elevated mercuryconcentrations, and the mercury they docontain (primarily inorganic mercury) is trans-ferred to consumers far less efficiently than ismethyl mercury. The food chain pathway ofmethyl mercury through larger, piscivorous fishis typically of primary importance in consump-tion-related toxicity to higher order consumers,including humans. Mercury bioaccumulation inlarger piscivorous fish has resulted in tissueconcentrations 105 times higher than concentra-tions in adjacent water (PTI, 1994). No piscivo-rous fish or any organism at the higher end ofthe food chain has been studied for the RMP fortrace metal bioaccumulation. However, as partof the Bay Protection and Toxic Cleanup Pro-gram, a fish contamination study was con-ducted for the San Francisco Estuary (Taberskiet al., 1992), and findings revealed tissueconcentrations above levels of human healthconcern in several fish species analyzed.

There has been an appreciable correlationbetween sediment mercury concentrations andthe percentage of fines in the sediment for eachof the three years. The greatest proportion ofmost metals, including mercury (Reimers andKrenkel, 1974), in marine environments isassociated with particulates and specificallywith the small size fractions of sediment. (See

Times Series of Trace Element Concentrations inthis report). Local freshwater sediment re-search at Camanche Reservoir reported similarfindings (Slotton et al., 1994; Slotton andReuter, 1995).

Potential Control Measures

Control of anthropogenic sources of mer-cury pollution involves both point source andarea source control. Point source control is oftenwielded through mechanical or chemicalmeans, while area control is often executed byadministrative means. It is always true that itis easier to recover mercury at the source,where it is more concentrated, than it is torecover it after it has dispersed in differentforms and species throughout the environment.The continuous cycling of mercury through itsmany different forms also dramatically compli-cates the job of devising effective technologiesto remove mercury from the environment.

Source Control

Investigators of point sources of mercurypollution have been very effective in isolatingsources in the environment. Extremely sensi-tive analytical instrumentation is now availableto monitor total mercury emissions or to ana-lyze mercury’s different forms down to thepicogram level.

Remediation of Abandoned Mines

As a result of the Coast Range mercurydeposits, soils in several locations throughoutthe San Francisco Estuary watershed arenaturally high in mercury, and a great numberof abandoned mines exist that, to this day,release substantial amounts of mercury into

Planktivores 0.680 mg/kg wet Piscivores 1.130 mg/kg wet Zooplankton 0.260 mg/kg wet Benthivores 0.480 mg/kg wet Phytoplankton 0.032 mg/kg wet Benthic

Macroinvertebrates0.025 mg/kg wet

Lake Water 0.0000003 mg/L Pore Water 0.000002 mg/L(0.3 ng/L) (2 ng/L)

Table 3. Methyl mercury concentrations in the food web (PTI, 1994 )

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surface waters as rain falls onto mine tailings.When high sulfur ore is exposed to the combi-nation of water and oxygen, sulfuric acid isproduced. The resulting acidic drainage fromman-made tailings piles and mine workingsdissolves mercury and transports the dissolvedmetal, as well as mercury-bearing particles,into creek channels. Ongoing research in theMarsh Creek watershed has found the source ofdownstream mercury to be highly localized toupstream mine tailings, as opposed to a gener-alized, regional source (Slotton et al., 1996).This work has identified potentially effectivecontrol and remediation strategies, and hasdeveloped site-specific biological and chemicalmarkers which will be used to guide futureremediation efforts and quantify their effective-ness. On a larger areal scale, the Cache Creekproject is currently underway to evaluatepotential mercury control strategies in thatimportant drainage. Both of these projects mayserve as models for control and remediation ofabandoned mines throughout the San FranciscoEstuary watershed.

In contrast, the gold-mining mercury in theSierra Nevada has been found to be largelydispersed and unsuitable for point-sourcecleanup approaches (Slotton et al., 1995b).However, a considerable amount of mercury isextracted from Sierran rivers in the course ofongoing placer gold mining. A buy-back pro-gram is currently being developed by theCentral Valley Regional Water Quality ControlBoard to encourage the collection and removalof this mercury.

Waste Stream Capture

Dental offices contribute a fair portion ofmunicipal mercury waste. Mercury constitutesalmost 50% of the material in dental amalgamtooth fillings. When this material is removed orwhen a new amalgam is fitted, some particu-late-associated mercury is invariably releasedinto waste water. Entrapment of this particu-late mercury waste stream could appreciablyreduce the mass of mercury entering municipalwaste water. It is estimated that each dentist inthe US uses an average over 1 kg of amalgam

annually (Goering et al., 1992). It is not yetclear whether the highly bound, inorganicmercury of dental amalgams is appreciablyavailable for methylation and incorporationinto the food web. Indeed, a very importantfuture area of research involves the determina-tion of the short and long term dissolution andmethylation potential of all the major inorganicforms of mercury, including cinnabar, elementalmercury (quicksilver), and dental amalgams.

A good deal of the anthropogenic mercuryrelease world-wide is dissolved in waste waterstreams. In many industries that use largeamounts of mercury, dissolved mercury isroutinely captured from waste streams througha variety of technologies utilizing either theionic nature of most dissolved mercury or theunique and consistent size of dissolved mercuryions. The installation of such traps and filterscan be a very effective measure at preventingmercury releases from low volume emittersparticularly, because the capacity of suchsystems can be engineered to require regularbut infrequent changeouts.

Flue Gas Scrubbing

Scrubbers are added as air emission controldevices to a variety of incinerators to removetoxic or hazardous compounds, most commonlythe sulfates. Mercury is present in some con-centration in virtually all incineration pro-cesses. Commonly, the emitted gas is scrubbedby an aqueous counter-current to both cool thegas and to solubilize compounds in the gas.Other common scrubbing technologies arescrubber/fabric filters, lime injection directlyinto the combustion chamber, and electrostaticprecipitators. At the high temperatures used inmost incinerators (or in any process with atemperature greater than 900°C), all forms ofmercury are decomposed to reduced elementalmercury, Hg0. As the temperature of flue gasquickly drops, Hg0 is oxidized to soluble Hg+2

(probably in part due to the catalytic contribu-tions of other trace metals in the gas) and thusmost mercury scrubbed from incinerator gaswill dissolve in the cooling water and be trans-ported to the settling ponds.

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If flue gas is not scrubbed, mercury can beconveyed both far (as elemental mercury by thewind) and near (as Hg+2 dissolved in atmo-spheric moisture and deposited as rain). Inmunicipal waste incineration, most mercury isreleased as the volatile mercuric chloride,HgCl2 (Braun and Gerig, 1991).

Area Control

The mercury that evaporates from dentalamalgams and is inhaled can have a surpris-ingly large impact upon the human body’smercury burden, particularly for inorganicmercury (Goering et al., 1992). However, inmany parts of the US and the world, ingestionof fish and other seafood contaminated withmethyl mercury is an additional and oftendominant source of mercury exposure. Adminis-trative controls to limit the exposure of humansto mercury include warning limits on theamount of fish consumed in a given period.

When sediments are determined to becontaminated with mercury, capping is often auseful measure to limit exposure to the envi-ronment. Capping naturally produces an anoxicenvironment in the underlayment which, overtime, can promote the formation of insolubleHgS if sufficient amounts of sulfate are present.Capping also eliminates the potentially harm-ful effects associated with some forms of dredg-ing to remove contaminated sediments. Dredg-ing can mix sediments with relatively highconcentrations of mercury where it can disperseinto the water column, aerate sediments andthus promote transformation of mercury to

oxidized, soluble Hg+2, and result in the fre-quently more onerous issue of remediating ordisposing of highly contaminated dredge spoilson-land.

Some forms of dredging have been deliber-ately engineered to minimize the hazardsoutlined above. The watertight clamshell is one,and vacuum suction dredging is another. Thesetechnologies seek to recover only contaminatedsediment without mixing with the watercolumn and without further contaminatingclean, underlying sediment.

Finally, mercury-contaminated soil andsediment can be washed with any of a variety ofsurfactants, solvents, or redox reagents toconcentrate and/or chemically alter the mer-cury. The mercury can either be recovered asthe element or condensed as the vapor toprevent merely exchanging a problem in onemedium for one in another.

In the Estuary system, mercury contamina-tion is probably far too widespread for direct/physical areal control measures to be effectiveor economically feasible. However, significantopportunities may exist for effective pointsource remediation of important mercurydischarges, which would otherwise continue tobe transported into the Estuary.

Acknowledgements

Review contributions by Dr. ChristopherFoe, Central Valley Regional Water QualityControl Board, and Joeseph Domagalski,United States Geological Survey, are greatfullyacknowledged.

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Polychlorinated Biphenyls in the San Francisco BayEcosystem: A Preliminary Report on Changes Over

Three DecadesRobert W. Risebrough, The Bodega Bay Institute

In 1967, while attempting to identifyprominent peaks in a chromatogram of anextract of an unhatched egg of a PeregrineFalcon from Baja, California, peaks that werealso present in all chromatograms of fishextracts from San Francisco Bay, I came acrosscommercial brochures (Monsanto ChemicalCompany) that indicated the availability in theSan Francisco Bay area of polychlorinatedbiphenyls (PCBs) in railway car quantities. Ifsmaller amounts were needed, 520-lb steeldrums or 50-lb cans of the several Aroclorscould also be purchased. We were on to some-thing.

On March 3, 1969, shortly after the publica-tion of our paper on the global distribution ofthe polychlorinated biphenyls (PCBs;Risebrough et al., 1968), the Monsanto Chemi-cal Company, sole US manufacturer of thePCBs, issued a release that was highly skepti-cal of our results:

Polychlorinated biphenyls are stable chemi-cal compounds which are essentially in-soluble in water. Their use does not makethem easily released into the naturalenvironment ... It has also been implied thatpolychlorinated biphenyls are “highly toxic”chemicals. This is not true. The toxicity ofany material, whether it be chemicals,drugs, natural plants or even foods, isrelative.... PCBs are not hazardous whenproperly handled and used ... This raises thequestion ... whether they are compoundswhich, due to the metabolism of othermaterials in the marine environment,appear to be PCBs.

But a year later, three senior officials of theMonsanto Company, Dr. Robert Keller, Man-ager of Applied Sciences, Mr. WilliamPapageorge, Manager, Environmental Control,

and Mr. Elmer Wheeler, Manager, Environmen-tal Health, visited our laboratory in Berkeley.We poured over chromatograms of fish fromSan Francisco Bay, of seabirds from around theworld, and of mothers’ milk, and then went tolunch (seafood at Spengers’; how unlike ourrelationships with Montrose and the otherpesticide companies at that time). On June 30,1970, Mr. John Mason, the Assistant GeneralManager of Monsanto, wrote to CongressmanWilliam Ryan of New York, who had proposedlegislation to ban all further uses of PCBs, thatas of August 30 of that year, Monsanto wouldno longer sell PCBs for open-system applica-tions, of which there had been many: additivesto pesticides to reduce loss by vaporization,additives to paints, to fire-retardants, uses incarbon-less copy paper, etc.

Along the California coast in the late 1960s,species after species was showing symptoms ofcontaminant effects, usually eggshell thinning,but also there were local extinctions andpopulation declines. The fear was that moreand more species would be affected if contami-nant levels increased. To detect any suchchange, and to document point sources ofcontamination, David Young of the SouthernCalifornia Coastal Water Research Projectbegan one of the first ‘Mussel Watch’ programsto address these questions. The survey wasrepeated in 1974; many of these sites werepicked up later by the National Mussel Watchprogram which began in 1976 and the Califor-nia State Mussel Watch Program which beganin 1977. These programs indicated that PCBs,as well as the DDTs, declined by up to an orderof magnitude over this interval, with most ofthe decline occurring between 1971 and 1974after the Monsanto Company had restrictedopen-system applications (Risebrough et al.,

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1980b; de Lappe et al., 1980b; Goldberg et al.,1978). The principal uses of PCBs, however, asdielectric fluids in transformers and capacitors,which were considered to be “closed-system”applications, continued throughout the early1970s.

Passage of the Toxic Substances Control Actin 1976 ended any further new uses of PCBs inthe United States. Now, in 1996, 20 years later,PCBs are considered a major, and probably themajor, continuing pollution problem in SanFrancisco Bay. What happened?

This paper attempts to answer this ques-tion, but because of insufficient time, it has notbeen possible to construct a comprehensivereport. The extensive data base compiled by theState Mussel Watch program is not included.Also not included are extensive unpublisheddata from the National Mussel Watch program,and unpublished data from our laboratory onthe analysis of archived samples preserved infrozen storage since the 1960s. Rather, I havecompiled data from obscure grey-literaturereports and other obscure publications from ourlaboratory to make these available in one placeas a preliminary examination of the history ofPCB contamination in San Francisco Bay. Forlack of time, as noted above, the Mussel Watchdata in Table 4 include only a fraction of thepotentially available data from our own labora-tory, and do not include the extensive data baseof the California Mussel Watch Program. Theintent is to incorporate these data into a morecomprehensive report at a later time.

The oldest data set is of DDT and PCBlevels in several species of fish from San Fran-cisco Bay in 1965, including the shiner perch,Cymatogaster aggregata. DDTs and PCBs inthree of the 1965 collections (Risebrough, 1969)are compared with shiner perch data from 1994(SFBRWQCB et al., 1995) in Table 5.

The PCBs in the 1965 samples were quanti-fied by comparing the summed heights of thethree principal PCB peaks with the summedheights of those peaks in the most closelymatching Aroclor, Aroclor 1254. The 1994 dataare also reported as “Aroclor equivalents”. Thetwo methods, however, can not be assumed to

be equivalent, but the uncertainty is probablyno more than about 20–50%, not enough tomodify the conclusion that environmentallevels of PCBs have dropped by a factor ofabout 5 since the mid 1960s. This magnitude ofchange is comparable to the decline docu-mented along the coast in the Mussel Watchprograms during the early 1970s and mostlikely also occurred after the ending of thosePCB uses that resulted in immediate entry intothe environment.

While Mussel Watch data from the South-ern California Bight over the period 1971–1985indicate a sharp drop in PCB and DDE levelsbetween 1971 and 1974, with the declinecontinuing at a lower rate through 1977,thereafter levels appeared to stabilize through1985 (Risebrough, 1987). The Bodega Headdata suggest a similar pattern, with no pro-nounced changes in PCB and DDE valuesbetween 1976 and 1994. In San Francisco Bay,the data are consistent with a modest decline ofPCB levels since the mid 1970s, but a convinc-ing case cannot be made from this (incomplete)data set. Because of the uncertainty that thetransplanted mussels of the RMP haveachieved equilibrium, and because the trans-planted mussels are of a different species, arigorous comparison cannot be made betweendata from RMP transplanted mussels and theearlier data from native mussels. Also, therewere differences in analytical methodologies,and the analyses were done in different labora-tories at different times without appropriatequality control. Nevertheless, the geometricmean PCB concentration in the 1993 trans-plants (n=17) of 350 ng/g is of the same magni-tude of the geometric mean PCB concentrationsof 540 ng/g in mussels from 27 bay-wide sites in1976 (Risebrough et al., 1980a). Analysis ofadditional archived samples and systematiccollections in the future are necessary toconstruct the best picture of changes in PCBlevels in the San Francisco Bay ecosystem sincethe mid 1970s.

The water-column data (Table 6) suggestinitially that PCB levels might even haveincreased over the past twenty years. When

Conclusions

289

Sit

es

/A

na

lyti

cal

Pa

ck

ed

/Y

ear

Co

llect

ion

sL

oca

tio

nR

ep

lica

tes

PC

Bs

DD

EC

ap

illa

ryA

na

lyze

dR

efe

ren

ce

Co

mm

en

tsB

odeg

a H

ead

19

71

11

76

90

P1

97

1de

Lap

pe e

t al.,

1

98

016

Apr

73

11

49

44

C1

99

3R

iseb

roug

h, u

npub

lishe

d1

97

61

01

16

13

P1

97

6G

oldb

erg

et a

l., 1

978

24 M

ar 7

61

12

32

4C

19

93

Ris

ebro

ugh,

unp

ublis

hed

2 Ju

l 76

11

22

19

C1

99

3R

iseb

roug

h, u

npub

lishe

d1

97

71

21

15

16

P1

97

8F

arrin

gton

et a

l., 1

982

mon

thly

col

lect

ions

19

78

21

17

.59

P1

97

8R

iseb

roug

h et

al.,

198

0b25

Feb

93

11

18

22

C1

99

3R

MP

-BB

I25

Jun

93

11

37

2.7

C1

99

3R

MP

-GE

RG

Dat

a an

omal

ous

17 J

an 9

41

11

52

4C

19

93

RM

P-G

ER

G26

May

94

11

21

15

C1

99

3R

MP

-GE

RG

San

Fra

ncis

co B

ay

21 D

ec.

1974

1B

erke

ley

Pie

r1

64

7.3

P1

97

5A

nder

lini e

t al.,

197

6w

et w

eigh

t2

Feb

. 19

751

Ber

kele

y P

ier

17

04

.5P

19

75

And

erlin

i et a

l., 1

976

wet

wei

ght

8 F

eb.

1975

1B

erke

ley

Pie

r1

67

2.4

P1

97

5A

nder

lini e

t al.,

197

6w

et w

eigh

t1

97

62

7B

ayw

ide

15

40

33

P1

97

6R

iseb

roug

h et

al.,

198

0a1

97

71

Sou

th B

ay1

59

05

7P

19

76

Far

ringt

on e

t al.,

19

82,

1983

19

78

1A

ngel

Is1

79

05

6P

19

78

Ris

ebro

ugh

et a

l., 1

980b

20 M

ar. 7

81

Ber

kele

y P

ier

10

43

0---

P1

97

8R

iseb

roug

h et

al.,

198

0bG

eom

mea

n20

Mar

. 78

1B

erke

ley

Pie

r4

49

0---

C1

98

3R

iseb

roug

h, u

npub

lishe

dG

eom

mea

n3

Apr

. 92

1B

erke

ley

Pie

r1

15

01

8C

19

93

Ris

ebro

ugh,

unp

ublis

hed

2 Ju

l. 92

1B

ricky

ard

Jetty

14

10

36

C1

99

3R

iseb

roug

h, u

npub

lishe

d

RM

P T

rans

plan

ts, M

ytilu

s ca

lifor

nian

us

19

94

17

Bay

wid

e1

35

04

3C

19

94

RM

P 1

994

Geo

m m

ean

Tab

le 4

. Sel

ecte

d m

uss

el w

atch

dat

a fr

om B

odeg

a H

ead

an

d S

an F

ran

cisc

o B

ay 1

971–

1992

, wit

h R

MP

tra

nsp

lan

t d

ata,

199

3 an

d 1

994.

ng/

g dr

y w

eigh

t ex

cept

wh

ere

indi

cate

d.

290


Tab

le 5

. DD

Ts

and

PC

Bs,

Aro

clor

bas

is, i

n s

hin

er p

erch

fro

m S

an F

ran

cisc

o B

ay, 1

965

vs. 1

994.

ng/

g (p

pb)

wet

wei

ght

Lo

calit

yN

um

be

rD

ate

DD

Ts

PC

Bs

Re

fere

nc

eS

ize

or

Wei

ght

Cen

tral

San

Fra

ncis

co B

ay1

420

Oct

. 65

10

00

12

00

Ris

ebro

ugh,

196

95

.5gm

Cen

tral

San

Fra

ncis

co B

ay1

020

Oct

. 65

14

00

40

0R

iseb

roug

h, 1

969

26

.7gm

Cen

tral

San

Fra

ncis

co B

ay1

54

Nov

. 65

11

00

12

00

Ris

ebro

ugh,

196

91

5.3

gm

San

Mat

eo B

ridge

20

3 M

ay 9

42

71

20

SF

BR

WQ

CB

, 19

95

Dum

bart

on B

ridge

20

2 M

ay 9

41

81

00

SF

BR

WQ

CB

, 19

95

Ric

hmon

d H

arbo

r2

010

May

94

42

18

0S

FB

RW

QC

B,

1995

10

4m

m

Ric

hmon

d H

arbo

r2

010

May

94

37

15

0S

FB

RW

QC

B,

1995

91

mm

Ric

hmon

d H

arbo

r2

010

May

94

34

17

0S

FB

RW

QC

B,

1995

83

mm

Ber

kele

y P

ier

20

9 M

ay 9

42

11

40

SF

BR

WQ

CB

, 19

951

08

mm

Ber

kele

y P

ier

20

9 M

ay 9

41

59

1S

FB

RW

QC

B,

1995

92

mm

Ber

kele

y P

ier

20

9 M

ay 9

41

49

3S

FB

RW

QC

B,

1995

83

mm

Oak

land

Inne

r H

ar, F

ruitv

ale

20

6 M

ay 9

47

33

70

SF

BR

WQ

CB

, 19

951

04

mm

Oak

land

Inne

r H

ar, F

ruitv

ale

20

6 M

ay 9

42

72

50

SF

BR

WQ

CB

, 19

95

Oak

land

Inne

r H

ar, F

ruitv

ale

20

6 M

ay 9

43

02

40

SF

BR

WQ

CB

, 19

958

3m

m

Dou

ble

Roc

k (C

andl

estic

k)2

04

May

94

33

32

0S

FB

RW

QC

B,

1995

94

mm

Isla

is C

reek

20

4 M

ay 9

42

01

00

SF

BR

WQ

CB

, 19

958

5m

m

Oak

land

Mid

dle

Har

bor

Pie

r2

05

May

94

47

17

0S

FB

RW

QC

B,

1995

93

mm

Geo

met

ric m

eans

19

65

19

94

19

65

/19

94

DD

Ts

11

50

28

41

PC

Bs

83

21

61

5

Conclusions

291

only Central Bay stations, however, are in-cluded, this apparent upward trend disappears.The earliest measurements of PCBs in thewater column of San Francisco Bay wereundertaken in 1975, before and after an experi-mental dredge spoil operation designed toassess whether the disposal of dredge spoilswithin the Bay would increase the local con-taminant burden (Anderlini et al., 1976). Thegeometric mean concentrations measured atthat time, 880 and 950 pg/l, are of the sameorder as current measurements in the CentralBay. Occasional recent measurements in theSouth Bay and in the Petaluma River havebeen substantially higher.

Following a report by Holden (1970) thatwaste waters were significant sources of PCBsin coastal environments, we obtained wastewater samples from the principal treatmentplants of California in November–December1970 (Schmidt et al., 1971; Table 7). Input ofPCBs into Bay waters from the East BayMunicipal Utility District (EBMUD) wasestimated to be in the order of 2 kg/day. Assum-ing a mean concentration of 900 pg/liter in Baywaters, the PCB burden in the water column,from a volume of 6.66 x 109 m3 (Conomos, 1979),would have been about 6 kg in the early 1970s.This number is of the same order as the dailyinput from waste water treatment plants atthat time. Almost all of the input PCBs musttherefore have been deposited in the sedimentswith the particulate loads, which were muchhigher at that time than they are now. Acorollary to this conclusion is that most of thesePCBs deposited in the past are probably still inthe sediments of San Francisco Bay.

Samples of waste waters from EBMUD in1974–1975 had PCB concentrations almost anorder of magnitude lower than in 1970 (Table7). The samples from the San Francisco South-east Treatment Plant showed a five-fold dropbetween 1970 and 1979. Although the data arefew and scattered, they are consistent withother available data presented here thatindicate a significant decrease of PCB environ-mental inputs in the early 1970s.

The present water-column burden of PCBsis therefore approximately equivalent to what itwas 20 years ago, about 6 kg. Discarding lossthrough metabolism and redeposition in sedi-ments, the principal net losses must be to thePacific Ocean and to the atmosphere. Assum-ing: 1) the net water volume discharged intothe Pacific is equivalent to the sum of: a) anannual river input of 20.9 x 109 m3 (Conomos,1979); b) an estimated yearly input from wastewater treatment plants of 0.69 x 109 m3 on thebasis of a daily input of 500 mgd-1; and c)oceanic waters equivalent to an input per tidalcycle of 0.34 x 109 m3 new ocean water(Conomos, 1979) which mixes with Bay waters;and 2) the PCB concentration averages 800 pg/liter, allowing for dilution with incomingseawater, the yearly loss of PCBs from the Bayto the ocean would be about 216 kg, 36 timesthe water column burden at any one time. Thewater column burden must therefore renewitself every 10 days.

Modification of any of these assumptionswould result in corresponding changes in thispreliminary mass balance equation; the as-sumption about the volume of incoming oceanicwaters that become mixed with Bay waters isprobably the most susceptible to revision.

The magnitude of loss to the atmosphere isunknown. It can be assumed that the chemicalpotentials of PCB congeners in the offshoreoceanic atmosphere are equivalent to those insurface waters because of the long time avail-able for the attainment of equilibrium, and thatthese are much lower than those of congenersin the San Francisco Bay water column. Thenet flux is therefore from water to air in SanFrancisco Bay whenever the prevailing windsconsist predominantly of oceanic air.

From the estimates, subject to update, of adaily discharge into San Francisco Bay of 500million gallons of waste waters, with a PCBconcentration of 500 pg/liter, also subject toupdate upon the availability of current data,current input from treatment plants would beonly about 350 g/year, an insignificant portionof the estimated yearly loss to the ocean. The

292


Nu

mb

er

PC

Bs

Inte

rva

l,D

ate

Lo

calit

yS

am

ple

sp

g/l

ite

r1

std

So

urc

e

8–9

Jan.

75

E. o

f Ang

el Is

land

11

88

05

80

–1

,35

0A

nder

lini e

t al.,

197

6

3–4

Mar

. 75

E. o

f Ang

el Is

land

89

50

58

0–

1,5

60

And

erlin

i et a

l., 1

976

3–4

Aug

. 78

E. o

f Ang

el Is

land

16

60

de L

appe

et a

l., 1

983

Apr

. 92

Bay

wid

e1

01

,13

07

50

–1

,70

0S

edQ

ual I

II

Apr

. 92

Cen

tral

Bay

51

,00

06

60

–1

,60

0S

edQ

ual I

II, R

iseb

roug

h un

publ

ishe

d

Mar

. 93

Bay

wid

e7

42

02

60

–6

70

SF

EI,

1994

Mar

. 93

Cen

tral

Bay

43

10

23

0–

42

0S

FE

I, 19

94

Feb

. 94

Bay

wid

e1

11

,10

04

50

–2

,60

0S

FE

I, 19

95

Feb

. 94

Cen

tral

Bay

36

90

44

0–

1,1

00

SF

EI,

1995

Apr

. 94

Bay

wid

e1

12

,10

01

,10

0–

3,8

00

SF

EI,

1995

Apr

. 94

Cen

tral

Bay

31

,10

06

60

–1

,70

0S

FE

I, 19

95

Aug

. 94

Bay

wid

e1

01

,10

06

40

–1

,90

0S

FE

I, 19

95

Aug

. 94

Cen

tral

Bay

36

00

43

0–

82

0S

FE

I, 19

95

Gol

den

Gat

e, G

rizzl

y B

ay, S

acra

men

to R

iver

and

San

Joa

quin

Riv

er s

tatio

ns n

ot in

clud

ed

Tab

le 6

. PC

Bs

in t

he

wat

er c

olu

mn

of

San

Fra

nci

sco

Bay

, 197

6–19

94. G

eom

etri

c m

ean

s, p

icog

ram

s/li

ter

Conclusions

293

Co

nce

ntr

ati

on

Est

. D

aily

Da

teP

lan

tin

w

aste

wat

ers

Dis

cha

rge

Co

mm

en

tsS

ou

rce

pic

og

ram

s/lit

er

kg

16 D

ec.

1970

EB

MU

D3

,40

0,0

00

24

repl

icat

es, m

ostly

Aro

clor

126

0S

chm

idt e

t al.,

197

115

5 m

gd

16 D

ec.

1970

San

Fra

ncis

co4

,80

0,0

00

0.6

2 re

plic

ates

, mos

tly A

rocl

or 1

260

Sch

mid

t et a

l.,

1971

So

uth

ea

st31

.5 m

gd

5–13

Dec

. 19

74E

BM

UD

57

0,0

00

0.2

Mea

n of

thr

ee c

ompo

site

sA

nder

lini e

t al.,

197

680

mgd

Mos

tly A

rocl

or 1

254

10–2

0 F

eb.

1975

ED

MU

D3

40

,00

00

.1M

ean

of t

hree

com

posi

tes

And

erlin

i et a

l., 1

976

80 m

gdM

ostly

Aro

clor

125

4

16 F

eb.

1979

ED

MU

D6

1,0

00

0.0

2M

ixtu

re o

f 12

42 a

nd 1

254

Sis

tek

and

Ris

ebro

ugh,

197

9M

ean

of 2

gra

b sa

mpl

es

20 F

eb.

1979

ED

MU

D2

40

,00

00

.08

Mix

ture

of

1242

and

125

4S

iste

k an

d R

iseb

roug

h, 1

979

Mea

n of

2 g

rab

sam

ples

Mar

ch 1

979

San

Jos

e/1

30

,00

0C

ompo

site

ove

r 4–

22 M

arch

Sis

tek

and

Ris

ebro

ugh,

197

9S

anta

Cla

raM

ixtu

re o

f 12

42 a

nd 1

254

Apr

il 19

79S

an J

ose/

22

,00

0C

ompo

site

ove

r 1–

19 A

pril

Sis

tek

and

Ris

ebro

ugh,

197

9S

anta

Cla

raM

ixtu

re o

f 12

42 a

nd 1

254

11 M

arch

197

9S

an F

ranc

isco

1,3

00

,00

00

.16

Mix

ture

of

1242

and

125

4S

iste

k an

d R

iseb

roug

h, 1

979

So

uth

ea

stM

ean

of 2

gra

b sa

mpl

es

6–7

Mar

ch 1

979

Cen

tral

12

,00

0M

ixtu

re o

f 12

42 a

nd 1

254

Sis

tek

and

Ris

ebro

ugh,

197

9C

ontr

a C

osta

Mea

n of

2 g

rab

sam

ples

Tab

le 7

. Pas

t in

pu

ts o

f P

CB

s in

to w

ater

s of

San

Fra

nci

sco

Bay

fro

m w

aste

wat

er t

reat

men

t p

lan

ts.

294


daily input, in the order of a gram, is a smallfraction of the water column burden.

Two generalities emerge from this analysisthat are relevant to policy. The current inputfrom waste waters, if the estimate of 500 pg/liter is in the correct order of magnitude, couldcome entirely from human excretion. If so,elimination of pollution at the source is not, inthis case, a viable option. Furthermore, acriterion of 70 pg/liter of PCBs in waste waters,which has apparently been adopted by theRegional Board, would not contribute signifi-cantly to a reduction of water column concen-trations in the foreseeable future unless somewaste water concentrations substantiallyexceed 500 pg/liter.

Of the estimated daily input into the watercolumn of 600 g, a minor fraction enters theBay in rivers. In the absence of any knownother major input sources, the sediments arethe plausible source of the remainder.

Table 8 includes only a few measurementsof PCBs in sediments, from the dredging studymentioned above. The 1975 concentrations inTable 8 have been reduced by one third fromthe original packed-column values to eliminateany bias in comparing packed column withcapillary column results. Again, there is asuggestion of change since the mid 1970s, butPCBs in a 1993 sediment sample from YerbaBuena were comparable to those of the 1975samples (Table 8).

A mean concentration of 10 ng/g of PCBs indry sediments over an area of 1.24 x 109 m2,including mudflats (Conomos, 1979) to a depthequivalent to 5 gm dry sediment/cm2 wouldyield an estimate of 600 kg in the surfacesediments. This is not a sufficient quantity tomaintain water column levels over a period ofmany years. Available data are not sufficient toprovide a more accurate estimate of the totalPCB burden in San Francisco Bay sediments.Collection and analysis of dateable cores fromselected areas would significantly improve thedata base.

The currently accepted theory of equilib-rium partitioning (DiToro et al., 1991) providesa theoretical basis for predicting concentrations

of a nonpolar organic contaminant in the lipidpools of organisms from either its concentra-tions in water or in the organic carbon compo-nent of the sediments. Thus, the ratio of theconcentration of a PCB congener in fish lipid toits dissolved concentration in ambient water isexpected to be the same as its octanol-waterpartition coefficient (Kow). From a Kow of1,000,000 and a water concentration of 70 pg/liter, the current guideline for acceptable PCBconcentrations in the waters of San FranciscoBay, a concentration of about 3 ppb (60 ppb on alipid basis in a fish with 5 % lipid content) canbe predicted. This concentration of 3 ppb is thecurrently accepted guideline criterion (PilotStudy Screening Value, PS-SV) for PCBs in fishfrom San Francisco Bay (SFBRWQCB et al.,1995).

The equilibrium partition theory assumesthat the organic carbon matrices of sediments,biological lipids and octanol are equivalent.Real-world measurements in an intertidalmarsh of San Francisco Bay (Maruya et al.,1996, Maruya et al. in press) have shown thatthis assumption is not universally valid. If,however, allowances are made for the nature ofthe organic carbon matrix, the concept ofequilibrium partitioning is strengthened and itspredictive capability is enhanced. In generalterms, therefore, sediment quality criteria forPCBs on an organic carbon basis would beequivalent to those in fish lipid. All recentmeasurements of PCBs on an organic carbonbasis are substantially higher than a criterionof 60 ng/g. As long as the sediment concentra-tions exceed this level, water column concentra-tions will exceed 70 pg/liter.

The SedQual I and III programs(Risebrough, 1994a, 1994b), like the RMPwhich followed, have not detected any “hotspots” of PCB contamination. But several sitesin the SedQual programs had PCB concentra-tions on an organic carbon basis substantiallyhigher than the average. These includedCerrito Creek Mouth (21 ppm), Davis Point (17ppm), Richmond Inner Harbor (15 ppm),EBMUD Storm Drain (5.6 ppm) and SanLeandro Bay (3.7 ppm). All of these sites are

Conclusions

295

# of

Tot

al

PC

Bs

Inte

rval

of

Re

fere

nc

eC

om

me

nts

Lo

calit

yS

ite

sD

ate

Geo

m.

mea

ns1

std

dev

Cen

tral

San

Fra

ncis

co B

ay6

20 D

ec.

1974

–1

71

4.4

–2

0.4

And

erlin

i et a

l., 1

976

Geo

met

ric m

ean;

thre

e an

alyt

ical

rep

licat

es/s

ite E

ast o

f Ang

el Is

land

2 J

an. 1

975

Orig

inal

pac

ked

colu

mn

valu

es r

educ

ed b

y on

e th

irdA

rchi

ved

sam

ples

ava

ilabl

e fo

r re

anal

ysis

EB

MU

D O

utfa

ll8

Dec

. 19

743

92

4–

65

And

erlin

i et a

l.,

19

76

Geo

met

ric m

ean;

thre

e an

alyt

ical

rep

licat

es/s

iteE

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close to shore and could indicate the existenceof a “hot spot” where PCBs were discharged inthe past. Because of equilibrium partitioning,fluxes of PCBs from the sediments into thewater column in these areas are expected to behigher than elsewhere in the Bay, whether ornot even higher areas of contamination exist intheir vicinities. These areas of higher contami-nation are likely to be the principal currentsources of continuing PCB inputs into the watercolumn.

Recent political efforts to secure funding for“toxics cleanup” in the Bay have seriouslymislead both the public and the concernedenvironmental groups. Neither high-tempera-ture incineration of a substantial fraction of thesediments of San Francisco Bay which would berequired to attain an effective cleanup; nordredging the sediments (yes, all of the surfacesediments except those that are predominantlysand) and disposal at some upland site or at seaare feasible options. What then is the fundingto be used for?

Is the present concern about PCB contami-nation in the Bay justified? After all, levelswere higher in the 1960s (production peaked in1970) and the world did not collapse. Sufficienttime has elapsed to detect any pattern of newcancers among people who consumed fish fromthe Great Lakes that have had much higherlevels of PCB contamination than fish from SanFrancisco Bay. The very low PS-SV of 3 ppbwould make virtually every fish in California apotential cancer risk. Such is the range ofuncertainty, including the uncertainty thatPCBs are a human carcinogen, that the assign-ment of any PS-SV can not be justified inscientific terms; following the most conserva-tive approach in the protection of human healthagainst a potential threat is the justification.Specifically, the current criterion of 70 pg/literis based on a rationale that does not derivefrom empirical science.

Other considerations, however, argue for alow criterion, although not necessarily as low asthat for the perceived cancer risk. Childrenborn to mothers who had consumed fish fromLake Michigan had lower memory retention

and performed poorly in other tests of mentalcapability in infancy and at age 4 years (Fein etal., 1984; Jacobson et al., 1984, 1985, 1992).The latest report from this study, published in1996, reported that these differences havepersisted to eleven years of age, with thechildren exposed in utero to contaminants inLake Michigan fish performing more poorly inIQ tests (Jacobson and Jacobson, 1996). Afollow-up study of children born to mothers whoconsumed Lake Ontario fish has begun; theinitial results indicate poorer reflex responsesjust after birth for the more highly exposedgroup (Lonky et al., 1996). The assumption thatPCBs are the responsible contaminant issupported by animal studies, but the contribu-tion of other organochlorines such as toxaphenecannot be ruled out.

The no-adverse-effect level on visualrecognition memory is currently considered tobe about two orders of magnitude higher thanthe estimated one-in-a-million cancer risk overa lifetime (Swain, 1991). The most contami-nated fish of San Francisco Bay would thereforefall within the effects range, i.e. above approxi-mately 0.3 ppm, lowering the IQs of childrenborn to women who consume large amounts ofthese fish. Unlike the perceived cancer riskwhich has such a large interval of uncertainty,this conclusion derives support from empiricaldata.

In 1970 the means to accomplish the aim ofreducing environmental levels of PCBs wereobvious: end the uses of PCBs and reduce theirenvironmental inputs. In 1996–97 the means toaccomplish the aim of reducing further theenvironmental levels are not at all obvious.Given the small if any reduction in levels overthe past 20 years, more-of-the-same monitoringof sediments, water, shellfish and fish can notbe expected to produce any information usefulto this end. Two kinds of measurements might,however, produce information that could resultin effective action. Measurements of PCBs inwaste waters with a detection limit at least aslow as the receiving water criterion of 70 pg/liter would indicate whether there are stillsources discharging into the waste water

Conclusions

297

treatment systems beyond the PCBs that arebeing recycled through humans. In addition, asampling grid in those areas that showedhighest sediment PCB levels in the SedQualprograms might detect a “hot spot” about whichsomething could be done to slow the inevitableentry over time of PCBs into the water column.Mixing with cleaner sediments with a lowerPCB content on an organic carbon basis, ordisposal of cleaner dredged sediments in theseareas are options that would reduce the rate ofinput into the water column, and therebyreduce the water column burden.

Within a national perspective, PCB con-tamination in San Francisco Bay falls towardsthe “cleaner” end of 176 sites sampled inNational Oceanic and AtmosphericAdministration’s (NOAA) Status and TrendsProgram of the mid 1980s. The median valuewas 18.5 ng/g, substantially higher than thevalues recorded in the SedQual programs(NOAA, 1988; Table 8).

Are There “New PCBs” OutThere?

PCBs were detected by identifying un-known peaks on gas chromatograms. In theRMP prominent peaks have been identified byGC/MS as the herbicides trifluralin andoxadiazon; these compounds have since beenadded to the list of reported contaminants. Butchromatograms, particularly of the most polarfraction of the dissolved water phase, literallycontain hundreds of peaks that have not beenidentified. Do any of these compounds pose, likethe PCBs, a potential hazard to any species inthe ecosystem, including humans? Until theyare identified and investigated, no conclusionsare possible. The ‘surveillance’ component ofthe concept of monitoring is currently beingignored; the list of reported contaminants is avery imperfect description of the real world. Asurvey of potentially beneficial plants in arainforest using a guidebook that identifiesonly bananas, the coconut palm, and fivespecies of orchids would be equally incomplete.

298


Summary of Estuary Conditionin Terms of Contamination

The Discussions of the water, sediment, andbivalve monitoring sections in this report havesummarized the 1995 monitoring results. Thefollowing is a synthesis of those discussionsmade to generally assesses the condition of theEstuary in terms of contamination.

Contaminants of concern in the Estuarywere generally different depending on themedium sampled (water, sediment, tissue). Inwater, PCBs and nickel were most often aboveapplicable guidelines. PCBs were above EPAcriteria at nearly all stations sampled andnickel was above the Basin Plan Objective atabout half the stations. All other contaminantswere above guidelines at fewer than half thestations. In sediments, arsenic, chromium,copper, mercury, nickel, lead, and DDTs wereabove ERLs at most Estuary stations. Inbivalve tissues, dieldrin, chlordanes, PAHs andPCBs were usually above the MTRLs at allstations.

The total number of contaminants aboveconcentration guidelines at each RMP stationprovides some indication of where contami-nants may be the greatest problem and wherethey may be the least problem. For water,Coyote Creek (BA10) and Petaluma River(BD15) had the largest numbers of waterquality exceedances and the Central Baystations generally had the fewest partially dueto TSS effects. For sediments, Alameda (BB70)

and Honker Bay (BF40) had the most ERLexceedances, and the stations with the coarsestsediments at Red Rock (BC60) and Davis Point(BD41) had the fewest ERL exceedances. Forbivalve bioaccumulation, the number of MTRLexceedances were about the same (seven to ten)at most stations sampled. However, stations inSan Pablo Bay (BD20, BD30) had only fourexceedances.

Considering the number of “hits” to theRMP biological effects measurements (aquaticand sediment bioassays, bivalve condition andsurvival) shows that the Sacramento and SanJoaquin Rivers had the most indications ofpossible biological effects. As shown in a recentRMP Newsletter article (Summer 1996), thoseresults are similar to the trend in biologicaleffects seen in all RMP data (1993–1995) wherethe San Joaquin River station indicated biologi-cal effects in about 50% of the measurementsmade. Grizzly Bay and Napa River indicatedbiological effects about 47% of the time.

It is difficult to make comparisons amongstations because not all contaminants andeffects indicators are measured at each station.With that in mind, Coyote Creek, DumbartonBridge, Petaluma River, and Napa Riverindicated the most contaminant exceedancesand biological effects “hits”, while Red Rock andHorseshoe Bay in the Central Bay indicated thefewest.

Acknowledgments

321

Acknowledgements

322


This report is the product of the efforts of many people. The RMP was sponsored by 63 agencies inthe region (listed inside the front cover). Their contributions are gratefully acknowledged. MichaelCarlin, Kim Taylor, Karen Taberski, Tom Gandesbery, and Lynn Suer of the Regional Board wereinstrumental in planning and implementing the RMP. The support and guidance of MargaretJohnston, Executive Director of the San Francisco Estuary Institute, was greatly appreciated. Numer-ous comments and suggestions were received from many reviewers. We greatly appreciate their input.

Report Authors (Base Program and Discussions)Bruce Thompson, Ph.D., RMP Program Manager, SFEIRainer Hoenicke, Ph.D., RMP QA Officer, SFEITed Daum, SFEIJay Davis, SFEIJohn Haskins, SFEISarah Lowe, SFEI

Report ProductionAdrienne Yang, Editor and Layout, SFEIMichael May, Graphics and Layout, SFEIJung Yoon, RMP Data Manager, SFEILiz Hartman, Administrative Assistance, SFEIGabriele Marek, Administrative Assistance, SFEITodd Featherston, SFEICrimson, Oakland-California, Layout and Printing

PhotographsDavid Bell, Applied Marine Sciences, provided photographs on pages 254, 299, and 321.John Haskins, SFEI, provided photographs on pages 196 and 271.Michael May, SFEI, provided photographs on pages 1, 10, 94, 139, and A–1.

The RMP Steering CommitteeChuck Weir, East Bay Dischargers Authority, ChairmanLoretta Barsamian, SFBRWQCBTheresa DeBono, P.G.&E.Nancy Evans, Central Marin Sanitation AgencyScott Folwarkow, Western States Petroleum AssociationRobert Hale, Alameda Countywide Clean Water ProgramDouglas Humphrey, Sausalito/Marin City Sanitary DistrictEllen Johnck, Bay Planning CoalitionMaury Kallerud, USS POSCO

The RMP Technical Review CommitteeRay Arnold, EXXON, ChairmanJohn Amdur, Port of OaklandTheresa DeBono, P.G.&E.Chris Foe, Central Valley RWQCBTom Grovhoug, Larry Walker AssociatesEricka Hoffman, US Environmental Protection Agency

Acknowledgments

323

Maury Kallerud, USS POSCOJim Salerno, City and County of San FranciscoJim Scanlin, Alameda Countywide Clean Water ProgramKim Taylor, SFB RWQCBCraig Wilson, State Water Resources Control Board

Vessels, Captains, and CrewsCaptain Gordon Smith, R/V DAVID JOHNSTON, UCSCCaptains Brian Sak, Patrick Conroy, and Michael Kellogg, M/V RINCON

POINT, City and County of San FranciscoCaptain Byron Richards, R/V/ POLARIS, USGS Menlo Park.

In addition to the Principal Investigators listed on Table 1 in Chapter One:Introduction, their technical staffs are gratefully acknowledged.

Applied Marine Sciences, Livermore, CADavid Bell Sue Chase Dane HardinJordan Gold

Bodega Bay Institute, Berkeley, CARobert Ramer Jeffrey Stobaugh Jose Francisco Cid Montanes

S.R. Hansen and Associates, Concord, CARudy Mendibil Gary Wortham Mary Helen Garcia

University of California, Santa Cruz Trace Metals LaboratoryGenine Scelfo Ben Owen Jonathan CrickSharon Hibdon Punam Bansal Lise ThogersenKhalil Abu-Saba Ignacio Rivera-Duarte

University of California, Santa Cruz Trace Organics LaboratoryJocelyn Bedder Corinne Bacon Ben OwenMolly Jacobs John Newman

University of California, Santa Cruz Granite Canyon LaboratoryWitold Pickarski Michelle Hester Bryn PhillipsKelita Smith Matt Englund

Moss Landing Marine LaboratorySteve Fitzwater Gary Ichikawa

Brooks-Rand, LTD, Seattle, WAColin Davies Rick Manson Steven SenterPatrick Moore Becky Els Paul Swift

Texas A & M University, College Station GERG LaboratoryJennifer Wong Guy Denoux Jose SericanoTerry Wade Tom McDonald

324


REGIONAL MONITORING PROGRAM

Statement of Income and Expense for Twelve-MonthPeriod Ending December 31, 1995

Income:

Participant Fees: Municipal Dischargers $ 880,003.00 Industrial Dischargers $ 219,999.00 Cooling Water Dischargers $ 80,000.00 Stormwater Dischargers $ 470,000.00 Dredged Material Dischargers $ 100,200.00 Additional Sampling Assistance $ 41,325.00In-Kind Fees $ 249,800.00Interest $ 68,019.00

Total Income $ 2,109,346.00

Expense:

Program Management, Coordination and Public Information $ 168,223.00Quality Assurance/Quality Control $ 51,509.00Data Analysis $ 30,160.00Data Management $ 132,827.00Annual Report $ 196,916.00Monitoring Program $ 1,273,469.00Pilot Studies $ 119,910.00Special Studies $ 46,471.001993 RMP Deficit $ 12,543.00

Total Expense $ 2,032,028.00

Net Gain (Loss) $ 77,336.00

Notes: This statement is unaudited and approximate. SFEI’s audited financial

statement is available upon request. SFEI has a July 1–June 30 fiscal year, therefore,

amounts in the official audit will not correspond directly to the amounts shown here.

Much of the SFEI work on the Annual Report was done during calendar year 1996

and therefore the final cost of the Annual Report is not reflected in these figures.

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Appendices

A–1

Appendices

A–2


Table of Contents

Appendix A: Descriptions of Methods ............................................................... A–3

Appendix B: Quality Assurance .......................................................................... A–9Table 1. Quality assurance and control summary for laboratory analyses of water ......................... A–9Table 2. Quality assurance and control summary for laboratory analyses of water ....................... A–11Table 3. Quality assurance and control summary for laboratory analyses of sediment.................. A–12Table 4. Quality assurance and control summary for laboratory analyses of bivalve tissue .......... A–13Table 5. Reference toxicant and QA information for the aquatic bioassay. ...................................... A–14Table 6. Physical/chemical measurements of test solutions and QA information for the sediment

bioassays ........................................................................................................................................... A–14

Appendix C: Data Tables .................................................................................... A–15Table 1. Conventional water quality parameters, 1995 .................................................................... A–15Table 2. Dissolved concentrations of trace elements in water, 1995 ................................................. A–17Table 3. Total or near total concentrations of trace elements in water, 1995 .................................. A–19Table 4. Dissolved PAH and alkanes concentrations in water samples, 1995 ................................. A–21Table 5. Total PAH and alkanes concentrations in water samples, 1995 ......................................... A–23Table 6. Dissolved PCB concentrations in water samples, 1995. ...................................................... A–25Table 7. Total PCB concentrations in water samples, 1995 .............................................................. A–29Table 8. Dissolved pesticide concentrations in water samples, 1995 ............................................... A–33Table 9. Total pesticide concentrations in water samples, 1995 ....................................................... A–35Table 10. Water toxicity data for 1995 RMP Cruises ......................................................................... A–37Table 11. General characteristics of sediment samples, 1995 ........................................................... A–38Table 12. Concentration of trace elements for sediment samples, 1995 .......................................... A–39Table 13. PAH and alkanes concentration in sediment, 1995 ........................................................... A–41Table 14. PCB concentrations in sediment, 1995 .............................................................................. A–43Table 15. Pesticide concentrations in sediment samples, 1995 ........................................................ A–47Table 16. Sediment toxicity data for 1995 RMP cruises ................................................................... A–49Table 17. Bivalve condition index and survival, 1995 ....................................................................... A–50Table 18. Trace element concentrations in bivalve tissues, 1995 ..................................................... A–51Table 19. PAH concentrations in bivalve tissues, 1995 ..................................................................... A–53Table 20. PCB concentrations in bivalve tissues, 1995 ..................................................................... A–55Table 21. Pesticide concentrations in bivalve tissues, 1995 .............................................................. A–61

Appendices

A–3

Appendix ADescriptions of Methods

Water Sampling

One of the objectives of the RMP is toevaluate if water quality objectives at thestations sampled are met. Therefore, thesampling and analysis methods have to be ableto meet quantification levels below the waterquality objectives. In order to attain the lowdetection levels used in the RMP (see AppendixB), ultra-clean sampling methods were used inall sampling procedures (Flegal and Stukas,1987).

Water samples were collected approxi-mately one meter below the water surface usingpumps. The sampling ports for both the organicchemistry and trace element samplers wereattached to aluminum poles that were orientedup-current from the vessel and upwind fromequipment and personnel. The vessel wasanchored and the engines turned off.

Particulate and dissolved fractions ofEstuary water were collected. The evolution ofthe trace organic sampling system has beendescribed in a series of papers (Risebrough etal., 1976; de Lappe et al., 1980a; 1983). Waterwas pumped by a Teflon impeller pump with 3/4 inch Teflon tubing through a glass fiber filter(1 µm) providing a sample of particulate-associated contaminants. The water was thenpassed through four exhaustively cleanedpolyurethane foam plugs mounted in serieswhich adsorbed the dissolved material. Theentire sampling system was thoroughly rinsedwith methanol prior to sampling, and an all-Teflon-stainless steel system further minimizedpotential contamination. During sampling, thesystem was closed to outside sources of con-tamination, and extreme precaution was takenat other times to minimize, if not eliminate, theintroduction of contaminants. Total organicswere calculated by adding particulate anddissolved fractions.

For trace metals, water samples werecollected using a peristaltic pump system

equipped with C-Flex tubing in the pump head.Sample aliquoting was conducted on deck onthe windward side of the ship to minimizecontamination from shipboard sources. Theapplicability of this sampling procedure hasbeen demonstrated previously withintercalibrated analyses of water collected withthe California Institute of Technology DeepWater Sampler and General Oceanics, Inc.trace metal clean Go-Flos (Flegal and Stukas,1987). Filtered water was obtained by placingan acid-cleaned polypropylene filter cartridge(Micron Separations, Inc., 0.45 µm pore size) onthe outlet of the pumping system. Unfilteredwater was pumped directly into sample con-tainers. Prior to collecting water, several litersof water were pumped through the system, andbottles were rinsed three times before filling.Samples were acidified on board the vessel atthe end of each second day except for chro-mium, which was acidified and extractedwithin an hour of collection.

Samples for conventional water qualityparameters were collected using the sameapparatus as for trace metals. Water sampleswere collected for toxicity tests using the samepumping apparatus as for the collection of thetrace organics sample, but were not filtered.Five gallons of water were collected, and placedin ice chests for transfer at the end of eachcruise day to the testing laboratory. Two fieldblanks were collected each cruise consisting ofwater known to be non-toxic from the BodegaMarine Laboratory and then filtered (0.45 µm).

Sediment Sampling

Sediment sampling was conducted using amodified Van Veen grab with a surface area of0.1 m2. The grab is made of stainless steel, andthe jaws and doors are coated with Dykon®

(formerly known as Kynar) to achieve chemicalinertness. All scoops, buckets, and stirrers usedto collect and composite sediments were also

A–4


constructed of Teflon or stainless steel coatedwith Dykon®. Sediment sampling equipmentwas thoroughly cleaned prior to each samplingevent.

When the sampler was on deck, a sub-corewas removed for measurement of ammonia.Then, the top 5 cm of sediment were scoopedfrom each of two replicate grabs and mixed in abucket to provide a single composite sample foreach station. Aliquots were split on board foreach analytical laboratory and for sedimenttoxicity tests. Duplicate samples for archivingwere collected from a composite of two addi-tional grabs. The quality of grab samples wasensured by requiring each sample to satisfy aset of criteria concerning depth of penetrationand disturbance of the sediment within thegrab.

Benthos Sampling

Benthic invertebrates were collected with a0.05 m2 Ponar grab sampler, with assistancefrom staff of the City and County of San Fran-cisco. Samples were screened through 1.0 mmand 0.5 mm mesh screens and fixed in 10%borax-buffered formalin. In the laboratory, thesamples were transferred to 70% ethanol,sorted to major taxa, and identified to thelowest practical taxon, usually species.

Bivalve BioaccumulationSampling

Bivalves were collected from uncontami-nated sites and transplanted to 15 stations inthe Estuary during the wet season (Februarythrough May) and the dry season (Junethrough September). Contaminant concentra-tions in the animals’ tissues, and the animals’biological condition (expressed as the ratio ofdry weight and shell cavity volume) weremeasured before deployment (referred to astime zero or background) and at the end of the90–100 day deployment period. The condition ofanimals at control sites at Lake Isabella (Cor-bicula fluminea), Bodega Head (Mytiluscalifornianus) and Tomales and Dabob Bays(Crassostrea gigas) was also determined at theend of each deployment period in order to sort

out Estuary effects from natural factors affect-ing bivalve condition. Survival during deploy-ment was also measured. Composites of tissuewere made from 40–60 individual bivalves fromeach site before and after deployment foranalyses of trace contaminants.

Since the RMP sites encompass a range ofsalinities, three species of bivalves were used,according to the expected salinities in each areaand the known tolerances of the organisms. Themussel Mytilus californianus was collectedfrom Bodega Head and stored in runningseawater at the Bodega Marine Laboratoryuntil deployment at the stations expected tohave the highest salinities, west of CarquinezStrait. Mytilus californianus will surviveexposure to salinities as low as 5 ppt (Bayne1976). Oysters (Crassostrea gigas) were ob-tained from Tomales Bay Oyster Company(Marshall, California) or Dabob Bay, Washing-ton, and deployed at moderate-salinity sitesclosest to Carquinez Strait and in the extremeSouth Bay. Crassostrea gigas tolerates salini-ties as low as 2 ppt. The freshwater clamCorbicula fluminea was collected from LakeIsabella and deployed at sites with the lowestsalinities. Corbicula fluminea tolerates salini-ties from 0 ppt to perhaps 10 ppt (Foe andKnight, 1986). At several sites, more than onespecies was deployed in order to insure survivalof at least one set of bivalves in case of unan-ticipated salinity variations. The effects of highshort-term flows of freshwater on the trans-planted bivalves west of Carquinez Strait wereminimized by deploying the bivalves near thebottom where density gradients tend to main-tain higher salinities. All bivalves were kept onice after collection and deployed within 24–48hours.

Within each species, animals of approxi-mately the same size were used. Mussels werebetween 49–81 mm shell length, oysters werebetween 71–149 mm, and clams were 25–36mm. One-hundred-fifty oysters and 160 mus-sels and clams were randomly allocated fordeployment at the appropriate sites, with thesame number being used as a travel blank(time zero) sample for analysis of tissue and

Appendices

A–5

condition before deployment. At each site,oysters were divided among five nylon meshbags, and mussels and clams were dividedamong four nylon mesh bags.

Moorings were associated with pilings orother permanent structures. Mooring installa-tion, bivalve deployment, maintenance, andretrieval were all accomplished by SCUBAdivers. The deployed samples were checkedapproximately half-way through the 90-daydeployment period to ensure consistent expo-sure. Moorings and nylon bags were checked fordamage and repaired, and fouling organismswere removed.

Upon retrieval, the bags of bivalves wereplaced into polyethylene bags and taken to thesurface. On the vessel, the number of deadorganisms was noted, with 20 percent of thelive organisms being allocated for conditionmeasurement, and the remainder being equallysplit for analyses of trace metals and organiccompounds. Based on findings by Stephenson(1992) during the RMP Pilot Program, bivalveguts were not depurated before homogenizationfor tissues analyses, although gonads wereremoved from organisms for trace metal analy-ses. Stephenson (1992) found that, with theexception of lead and selenium, no significantdifferences were found in trace metal concen-trations between mussels held for 48 hours inclean Granite Canyon seawater before homog-enization and undepurated mussels. However,sediment in bivalve guts may contribute to thetotal tissue contaminant concentration andintroduce an unspecified amount of error intothe measurement process.

Analytical MethodsConventional Water Quality Parameters

Samples for dissolved phosphates, silicates,nitrate, nitrite, and ammonia were analyzedfollowing the procedures described by Parsonset al. (1984). Total chlorophyll was measuredusing a fluorometric technique with filteredmaterial from 200 ml samples (Parsons et al.,1984). Shipboard measurements for tempera-ture and salinity were obtained using a por-table conductivity/salinity meter (YSI model

33), pH was measured with a portable pHmeter (Orion SA250), and dissolved oxygencontent was measured using a portable dis-solved oxygen meter (YSI model 58). Dissolvedorganic carbon (DOC) was measured usinghigh-temperature catalytic oxidation with aplatinum catalyst (Fitzwater and Martin,1993). Total suspended solids (TSS) weredetermined using method 2540D in StandardMethods for the Examination of Water andWastewater (Greenberg et al., 1992)

A Sea-Bird SBE19 conductivity, tempera-ture and depth probe (CTD) was used to mea-sure water quality parameters at depthsthroughout the water column. CTD casts weretaken at each site during water and sedimentsampling. At each site, the CTD was lowered toapproximately one meter below the watersurface and allowed to equilibrate to ambienttemperature for 3 minutes. The CTD was thenlowered to the bottom at approximately 0.15meters per second, and raised. Only data fromthe down cast were kept. Data were down-loaded onboard the ship, and processed in thelab using software supplied by Sea-Bird.

The CTD measures temperature, conductiv-ity, pressure, dissolved oxygen, and backscatterat a sampling rate of two scans per second.These data were edited and averaged into 0.25m depth bins during processing. Also duringprocessing, salinity (based on conductivitymeasurements), oxygen, time, and depth (basedon pressure) were calculated. Later, SFEIcalculated density and total suspended solids(TSS), which were compared with measure-ments obtained using the standard methodsdescribed above. Although the CTD data arenot detailed in this report, SFEI maintains thedata.

Trace Elements

Total and dissolved (0.45 µm filtered)concentrations of arsenic, chromium, mercury,and selenium in water were measured, andnear-total and dissolved concentrations ofcadmium, copper, nickel, lead, silver, and zincin water were measured. Near-total concentra-tions were used in the RMP for consistency

A–6


with the Bay Protection and Toxic CleanupProgram (BPTCP) pilot studies results. Totalmetals in water are usually extracted withboiling aqua regia (a mixture of three partsconcentrated hydrochloric acid and one partconcentrated nitric acid) which extracts virtu-ally all metals from the sample. Near-totalmetals are extracted with a weak acid (pH < 2)for a minimum of one month, resulting inmeasurements that approximate bioavailabilityof some metals to Estuary organisms (Smithand Flegal, 1993). Near-total concentrationsunderestimate total metals concentrations byan unknown amount. Therefore, comparisons towater quality objectives tend to be ratherconservative.

To determine total chromium concentra-tions, the particulate matter in the sample wasextracted and analyzed, rather than analyzingunfiltered samples. Total mercury sampleswere photo-oxidized with the addition ofbromium chloride and quantified using a coldvapor atomic fluorescence technique. Tracemetals (except for arsenic, mercury, and sele-nium) in water were measured using graphitefurnace atomic absorption spectrometry pre-ceded by sample preconcentration using theAPDC/DDC organic extraction method(Bruland et al., 1985; Flegal et al., 1991).

Results for cadmium, copper, nickel, lead,silver, and zinc were reported by the laboratoryin units of µg/kg. For use in this report, thosevalues are reported as µg/L, without taking intoaccount the difference in density betweenEstuary water and distilled water. This differ-ence is much less than the precision of the data,which was on the order of 10%. In some in-stances, dissolved metals concentrations arereported as higher than total (dissolved +particulate) metals concentrations. This is dueto expected analytical variation in the methodsof analysis, particularly at concentrations nearthe detection limits. Such results should beinterpreted as no difference between dissolvedand total concentrations, or that all of metal isin the dissolved phase.

Metals in sediments were extracted withaqua regia and analyzed as described in the

standard methods developed for measuringtrace element concentrations in marine sedi-ments and waste water sludge for the Califor-nia State Water Resources Control Board(Flegal et al., 1981). This report comparesseveral extraction procedures. The methodchosen for RMP sediment analysis is compa-rable to standard EPA procedures (Tetra Tech,1986) but does not decompose the silicatematrix of the sediment. Because of this, anyelement tightly bound as a naturally occurringsilicate may not be fully recovered, as is thecase with hydrofluoric acid digestion. In orderto eliminate possible confusion between theterms near-total concentrations of metals inwater and sediment, the term near-totalextraction in sediment based on the aqua regiadigestion is avoided.

Bivalve tissue samples were analyzed withtechniques used in the California State MusselWatch (e.g., Flegal et al., 1981; Smith et al.,1986) and consistent with the Pilot Program(Stephenson, 1992). Hydride generationcoupled with atomic absorption spectroscopywas used to quantify arsenic. Mercury wasquantified using a cold-vapor atomic fluores-cence technique, and selenium was quantifiedusing the methods of Cutter (1986). Butyltinswere measured following NOAA Status andTrends Mussel Watch Project methods de-scribed in NOAA Technical Memorandum NOS/ORCA/CMBAD71 vol. IV. This techniqueinvolves extracting the sample with hexane andthe chelating agent tropolone and measuringthe butyltin residues by capillary gas chroma-tography. Concentrations are expressed in totaltin per gram of tissue dry weight.

Trace Organics

For water samples, plugs and filters wereextracted in custom-built soxhlet extractionunits. Extracts were reduced to 1–2 ml inhexane for cleanup with florisil-column chroma-tography. Chlorinated hydrocarbons (CH) ineach of the three analytical fractions (F1, F2,F3) were analyzed on a Hewlett Packard 5890Series II capillary gas chromatograph utilizingelectron capture detectors (GC/ECD). A single

Appendices

A–7

2 µL splitless injection was directed onto two 60m x 0.25 mm columns of different polarity (DB-17 and DB-5) using a y-splitter to provide two-dimensional confirmation of each analyte. Thequantitation internal standard utilized for theCH analysis was dibromooctafluorobiphenyl(DOB). Decachlorobiphenyl (PCB 209) wasintroduced to each sample prior to fraction-ation. This compound was treated as a surro-gate standard, and analyte concentrations werecorrected for PCB 209 losses prior to reporting.

PAHs were quantified in the F-2 fraction byanalysis on a Hewlett-Packard 5890 Series IIcapillary gas chromatograph equipped with a5971A mass spectral detector (GC/MS). A 2 µLsplitless injection was chromatographed on aDB-5 column and analyzed in a single ionmonitoring (SIM) mode. The quantitationinternal standard utilized for the PAH analysiswhen samples were at 100 µL was hexamethylbenzene (HMB). Samples quantitated at a finalvolume of 1mL utilized deuteratedfluoranthene. Deuterated phenanthrene anddeuterated chrysene were spiked into eachsample prior to fractionation. All PAH concen-trations were corrected for deuterated phenan-threne recoveries prior to reporting.

Sediment samples were freeze-dried, mixedwith kiln-fired sodium sulfate, and soxhlet-extracted with methylene chloride. The extractwas concentrated and purified using EPAMethod 3611 alumina column purification toremove matrix interferences.

Tissue samples were homogenized andmacerated, and the eluate was dried withsodium sulfate, concentrated, and purifiedusing a combination of EPA Method 3611alumina column purification and EPA Method3630 silica gel purification to remove matrixinterferences.

Aquatic Bioassays

Water column toxicity was evaluated usinga 48-hour mollusk embryo development testand a seven-day growth test using the estua-rine mysid Mysidopsis bahia. The bivalveembryo development test was performedaccording to ASTM standard method E 724-89

(ASTM, 1991). The mysid test was based onEPA test method 1007. Larval Mytilus eduliswere used in the February samples, and larvalCrassostrea gigas were used in the Augustsamples. Different species were used due toseasonal differences in larval availability. Themysid growth and survival test consisted of anexposure of 7-day old Mysidopsis bahia juve-niles to different concentrations of Estuarywater in a static system during the period ofegg development and was used during bothsampling periods. Appropriate salinity adjust-ments were made for Estuary water fromsampling stations with salinities below the testspecies’ optimal ranges. Reference toxicanttests with copper chloride and potassiumdichromate were performed for the bivalve andmysid tests, respectively. These tests were usedto determine if the responses of the test organ-isms were relatively consistent over time.

The salinities of the ambient samples andthe control/diluent (Evian spring water) wereadjusted to 5 ppt using artificial sea-salts(Tropic Marin). The test concentrations were100%, 50%, and control, each with four repli-cates, and with 20 larvae per replicate. Wastes,dead larvae, excess food, and 80% of the testwater were siphoned from the test chambersdaily, and general water chemistry parametersof dissolved oxygen, pH, and salinity wererecorded before and after each water change.

Sediment Quality Characteristics

Sediment size fractions were determinedwith a grain-size analyzer based on x-raytransmission (Sedigraph 5100). Total organiccarbon was analyzed according to the standardmethod for the Coulometrics CM 150 Analyzermade by UIC, Inc. This method involves mea-surements of transmitted light through a cell.The amount of transmitted light is related tothe amount of carbon dioxide evolved from acombusted sample. Spectrophotometric analy-ses of sulfides in sediment porewater wereperformed using a method adapted fromFonselius (1985) with variations from StandardMethods (APHA, 1985).

A–8


Sediment Bioassays

Two sediment bioassays were used: a ten-day acute mortality test using the estuarineamphipod Eohaustorius estuarius exposed towhole sediment using ASTM method E 1367(ASTM, 1992), and a sediment elutriate testwhere larval bivalves were exposed to thematerial dissolved from whole sediment in awater extract using ASTM method E 724-89(ASTM, 1991). Elutriate solutions were pre-pared by adding 100 g of sediment to 400 ml ofGranite Canyon sea water, shaking for 10seconds, allowing to settle for 24 hours, andcarefully decanting (EPA and COE, 1977; TetraTech, 1986). Larval mussels (Mytilus edulis)were used in both sampling periods, wherepercent normally developed larvae was theendpoint measured.


The condition of bivalves is a measure oftheir general health following exposure toEstuary water for 90–100 days. Measurementssuch as length, weight, volume, or ratios ofthose measurements have been used as indica-tors of integrated physiological response tocontaminants in water (Pridmore et al., 1990;KLI 1984). Measurements were made onsubsamples of specimens before deploymentand on the deployed specimens followingexposure. Condition was also determined onbagged controls at the clean reference sites atthe end of the deployment period. Dry weight(without the shell) and the volume of the shellcavity of each bivalve was measured. Bivalvetissue was removed from the specimens anddried at 60o C in an oven for 48 hours beforeweighing. Shell cavity volume was calculatedby subtracting shell volume of water displacedby a whole live bivalve less the volume of waterdisplaced by the shell alone. The conditionindex is calculated by taking the ratio of tissuedry weight and the shell cavity volume.

Appendices

A–9

Appendix BQuality Assurance

The following section contains summaries of quality assurance information for the 1995 RegionalMonitoring Program (RMP). A description of the RMP’s quality assurance program can be found inthe 1994 RMP Annual Report, Appendix 2 and the 1996 Quality Assurance Program Plan.

Table 1. Quality assurance and control summary for laboratory analyses of water.Cruise 7: February 95, Cruise 8: April 95, and Cruise 9: August 95

Analysis Type: Water Elements, Dissolved

Cruise # Parameter UnitsMDL

TargetMDL

MeasuredPrecision

TargetPrecision Measured

Accuracy Target

Accuracy Measured

No. Blanks/Batch

(+/- %) (rsd) 1 (+/- %) (+/- %)7 Ag µg/L 0.0003 0.0002 15 10 25 NA2 12/247 As µg/L 0.002 0.056 25 5 25 5 2/207 Cd µg/L 0.0003 0.0001 15 4 25 25 12/247 Cr µg/L 0.0250 0.0924 15 9 25 1 6/247 Cu µg/L 0.0058 0.0074 15 5 25 18 12/247 Hg µg/L 0.0001 0.0001 25 10 25 3 2/207 Ni µg/L 0.0054 0.0025 15 5 25 10 12/247 Pb µg/L 0.0028 0.0004 15 11 25 10 12/247 Se µg/L 0.005 0.019 35 12 35 5 2/207 Zn µg/L 0.0008 0.0039 15 3 25 8 12/248 Ag µg/L 0.0003 0.0002 15 20 25 NA2 12/248 As µg/L 0.002 0.043 25 7 25 5 2/208 Cd µg/L 0.0003 0.0001 15 1 25 12 12/248 Cr µg/L 0.0250 no data 15 no data 25 no data8 Cu µg/L 0.0058 0.0046 15 4 25 6 12/248 Hg µg/L 0.0001 0.0001 25 8 25 5 2/208 Ni µg/L 0.0000 0.0126 15 8 25 4 12/248 Pb µg/L 0.0028 0.0013 15 7 25 13 12/248 Se µg/L 0.005 0.019 35 14 35 5 2/208 Zn µg/L 0.0008 0.0045 15 2 25 9 12/249 Ag µg/L 0.0003 0.0001 15 6 25 NA2 15/249 As µg/L 0.002 0.100 25 7 25 9 2/209 Cd µg/L 0.0003 0.0000 15 2 25 10 15/249 Cr µg/L 0.0250 no data 15 no data 25 no data9 Cu µg/L 0.0058 0.0008 15 2 25 5 15/249 Hg µg/L 0.0001 0.0001 25 6 25 5 2/209 Ni µg/L 0.0054 0.0012 15 3 25 3 15/249 Pb µg/L 0.0028 0.0005 15 6 25 249 Se µg/L 0.005 0.019 35 14 35 6 2/209 Zn µg/L 0.0008 0.0008 15 8 25 2 15/24

A–10


Table 1. Quality assurance and control summary for laboratory analyses of water(continued). Cruise 7: February 95, Cruise 8: April 95, and Cruise 9: August 95

Analysis Type: Water Elements, Total

Cruise # Parameter UnitsMDL

TargetMDL

MeasuredPrecision


Accuracy Target

Accuracy Measured

No. Blanks/Batch

(+/- %) (rsd) 1 (+/- %) (+/- %)

7 Ag µg/L 0.0012 0.0009 15 11 25 NA2 12/24

7 As µg/L 0.0020 0.0560 25 5 25 5 2/20

7 Cd µg/L 0.0004 0.0010 15 4 25 18 12/24

7 Cr µg/L 0.3530 0.0733 15 4 40 29 6/24

7 Cu µg/L 0.0066 0.0098 15 5 25 14 12/24

7 Hg µg/L 0.0001 0.0001 25 10 25 3 2/20

7 Ni µg/L 0.0095 0.0221 15 6 25 6 12/24

7 Pb µg/L 0.0050 0.0032 15 5 25 18 12/24

7 Se µg/L 0.0050 0.0190 35 12 35 5 2/20

7 Zn µg/L 0.0074 0.0087 15 2 25 19 12/24

8 Ag µg/L 0.0012 0.0010 15 8 25 NA2 8/24

8 As µg/L 0.0020 0.0430 25 7 25 5 2/20

8 Cd µg/L 0.0004 0.0012 15 3 25 16 8/24

8 Cr µg/L 0.3530 0.4710 15 16 40 33 5/24

8 Cu µg/L 0.0066 0.0119 15 6 25 12 8/24

8 Hg µg/L 0.0001 0.0001 25 8 25 5 2/20

8 Ni µg/L 0.0095 0.0031 15 3 25 6 8/24

8 Pb µg/L 0.0050 0.0006 15 10 25 16 8/24

8 Se µg/L 0.0050 0.0190 35 14 35 5 2/20

8 Zn µg/L 0.0074 0.0164 15 5 25 3 8/24

9 Ag µg/L 0.0012 0.0003 15 20 25 NA2 12/24

9 As µg/L 0.0020 0.1000 25 7 25 9 2/20

9 Cd µg/L 0.0004 0.0001 15 4 25 4 12/24

9 Cr µg/L 0.3530 0.0001 15 16 40 30

9 Cu µg/L 0.0066 0.0049 15 3 25 10 12/24

9 Hg µg/L 0.0001 0.0001 25 6 25 5 2/20

9 Ni µg/L 0.0095 0.0046 15 6 25 22

9 Pb µg/L 0.0050 0.0051 15 8 25 3

9 Se µg/L 0.0050 0.0190 35 14 35 6 2/20

9 Zn µg/L 0.0074 0.0039 15 4 25 11 11/24

1 relative standard deviation2 There are no SRM certified values for silver.

Appendices

A–11

Table 2. Quality Assurance and Control Summary for Laboratory Analysesof Water. Cruise 7: February 95, Cruise 8: April 95, and Cruise 9: August 95

Analysis Type: Water Organics, Dissolved & Particulate * (Total values are calculated as the sum of dissolved and particulate data.)

Cruise #

Parameter

UnitsMDL

Target MDL MeasuredPrecision


Accuracy Measured 2

Dissolved and Particulate

(+/- %) (rsd) 1 (% rpd)

7 Aliphatics pg/L 50 11 20 < 20 < 20

7 PAHs pg/L 50 50 20 < 20 < 20

7 PCBs pg/L 50 0.5 20 < 20 < 20

7 Pesticides pg/L 50 not available 20 < 20 < 20

8 Aliphatics pg/L 50 11 20 < 30 < 30

8 PAHs pg/L 50 50 20 < 30 < 30

8 PCBs pg/L 50 0.5 20 < 30 < 30

8 Pesticides pg/L 50 not available 20 < 30 < 30

9 Aliphatics pg/L 50 24 20 < 30 < 30

9 PAHs pg/L 50 50 20 < 30 < 30

9 PCBs pg/L 50 0.5 20 < 30 < 30

9 Pesticides pg/L 50 not available 20 < 30 < 301 relative standard deviation2 Based on NIST standard solutions and calibration standards.

* Note: Certified reference Materials for trace organic contaminants in water are not available.

Accuracy was measured using continuing calibration check solutions.

Recoveries of these solutions were consistently 95 +/- 15%.

A–12

Regional Monitoring Program 1995 Annual ReportT

able

3. Q

ual

ity

Ass

ura

nce

an

d C

ontr

ol S

um

mar

y fo

r L

abor

ator

y A

nal

yses

of

Sed

imen

t. C

ruis

e 7:

Feb

ruar

y 95

, an

dC

ruis

e 9:

Au

gust

95

Ana

lysi

s Ty

pe: S

edim

ent M

etal

sC

ruis

e #

Par

amet

erU

nits

MD

L T

arge

tM

DL

Mea

sure

dP

reci

sion

T

arge

tP

reci

sion

M

easu

red

Acc

urac

y T

arge

tA

ccur

acy

Mea

sure

dN

o.

Bla

nks/

Bat

ch

(+/-

%)

(rsd

)*(+

/- %

)(+

/- %

)7

Agm

g/K

g0.

0012

0.00

0015

425

NA

23/

247

Al

mg/

Kg

7015

625

925

733/

247

As

mg/

Kg

1.6

0.3

258

258

2/20

7C

dm

g/K

g0.

0000

20.

0000

1514

2590

3/24

7C

rm

g/K

g9.

443.

4215

560

623/

247

Cu

mg/

Kg

4.57

2.40

153

2524

3/24

7Fe

mg/

Kg

140

167

152

2517

3/24

7H

gm

g/K

g5

0.14

355

2513

2/20

7M

nm

g/K

g27

1725

425

83/

247

Ni

mg/

Kg

4.28

0.80

154

2578

3/24

7Pb

mg/

Kg

0.1

015

1125

73/

247

Sem

g/K

g2.

20

3516

3513

2/20

7Zn

mg/

Kg

18.8

.15

.25

.3/

249

Agm

g/K

g0.

0012

0.00

0425

625

NA

23/

249

Al

mg/

Kg

7013

525

825

763/

249

As

mg/

Kg

1.6

0.03

258

255

2/20

9C

dm

g/K

g0.

0000

20.

0003

253

252

3/24

9C

rm

g/K

g9.

43.

025

760

623/

249

Cu

mg/

Kg

4.57

0.70

255

257

3/24

9Fe

mg/

Kg

140

444

254

2515

3/24

9H

gm

g/K

g5

0.14

356

258

2/20

9M

nm

g/K

g27

3325

325

283/

249

Ni

mg/

Kg

4.26

2.00

255

259

3/24

9Pb

mg/

Kg

0.01

0.01

256

252

3/24

9Se

mg/

Kg

2.2

0.01

3515

3514

2/20

9Zn

mg/

Kg

18.9

19.0

255

2516

3/24

Ana

lysi

s Ty

pe: S

edim

ent O

rgan

ics

Cru

ise

#P

aram

eter

Uni

tsQ

AM

DL

Tar

get

MD

L M

easu

red

Pre

cisi

on

Tar

get

Pre

cisi

on

Mea

sure

dA

ccur

acy

Tar

get

Acc

urac

y M

easu

red

Bla

nk

Freq

uenc

y 1

batc

h#(+

/- %

)(r

sd)*

(+/-

%)

(+/-

%)

7A

lipha

tics

µg/K

gM

2257

50.

8 - 9

1.6

± 20

3±

209

5% m

in.

7A

lipha

tics

µg/K

gM

2258

50.

8 - 9

1.6

± 20

2±

2010

5% m

in.

7P

AH

sµg

/Kg

M22

575

0.4-

10.7

± 20

12±

207

5% m

in.

7P

AH

sµg

/Kg

M22

585

0.4-

10.7

± 20

12±

208

5% m

in.

7P

CB

sµg

/Kg

M22

571

0.2

± 20

3±

2013

5% m

in.

7P

CB

sµg

/Kg

M22

581

0.2

± 20

6±

203

5% m

in.

7P

estic

ides

µg/K

gM

2257

10.

1±

206

± 20

15%

min

.7

Pes

ticid

esµg

/Kg

M22

581

0.1

± 20

2±

207

5% m

in.

9A

lipha

tics

µg/K

gM

2403

51

- 95

± 20

5±

208

5% m

in.

9A

lipha

tics

µg/K

gM

2404

51

- 95

± 20

4±

201

5% m

in.

9P

AH

sµg

/Kg

M24

035

0.4-

13.7

± 20

5±

209

5% m

in.

9P

AH

sµg

/Kg

M24

045

0.4-

13.7

± 20

13±

2012

5% m

in.

9P

CB

sµg

/Kg

M24

031

0.2-

0.7

± 20

5±

2010

5% m

in.

9P

CB

sµg

/Kg

M24

041

0.2-

0.7

± 20

2±

2014

5% m

in.

9P

estic

ides

µg/K

gM

2403

10.

1-0.

3±

204

± 20

165%

min

.9

Pes

ticid

esµg

/Kg

M24

041

0.1-

0.3

± 20

3±

204

5% m

in.

* re

lativ

e st

anda

rd d

evia

tion

1 M

axim

um B

atch

siz

e is

20

sam

ples

.2

The

re a

re n

o S

RM

cer

tifie

d va

lues

for s

ilver

.

Appendices

A–13

Tab

le 4

. Qu

alit

y A

ssu

ran

ce a

nd

Con

trol

Su

mm

ary

for

Lab

orat

ory

An

alys

es o

f B

ival

ve T

issu

e. C

ruis

e 7:

Feb

ruar

y95

, an

d C

ruis

e 9:

Au

gust

95

Ana

lysi

s Ty

pe: T

issu

e M

etal

sC

ruis

e #

Par

amet

erU

nits

MD

L T

arge

tM

DL

Mea

sure

dP

reci

sion

T

arge

tP

reci

sion

M

easu

red

Acc

urac

y T

arge

tA

ccur

acy

Mea

sure

dN

o. B

lank

s/B

atch

(+/-

%)

(rsd

)*(+

/- %

)(+

/- %

)7

Agm

g/K

g0.

0012

0.02

330

735

13/

247

As

mg/

Kg

1.6

0.01

2512

253

2/20

7C

dm

g/K

g0.

0000

20.

064

3014

258

3/24

7C

rm

g/K

g9.

440.

048

3016

25N

A3/

247

Cu

mg/

Kg

4.57

2.41

3013

2511

3/24

7H

gµg

/Kg

10.

2735

425

42/

207

Ni

mg/

Kg

4.26

0.4

304

253

3/24

7Pb

mg/

Kg

0.1

0.03

3015

259

3/24

7Se

mg/

Kg

2.2

0.01

335

935

32/

207

Znm

g/K

g18

.94.

6830

625

223/

249

Agm

g/K

g0.

0012

025

530

03/

249

Al

mg/

Kg

.11

.6.

10.

833/

249

As

mg/

Kg

1.6

0.01

254

254

2/20

9C

dm

g/K

g0.

0000

20.

1325

630

63/

249

Cr

mg/

Kg

9.4

0.08

2520

6033

3/24

9C

um

g/K

g4.

571.

325

730

243/

249

Hg

µg/K

g1

0.14

3520

253

2/20

9N

im

g/K

g4.

260.

0425

1230

73/

249

Pbm

g/K

g0.

010.

0525

1030

223/

249

Sem

g/K

g2.

20.

008

353

3511

2/20

9Zn

mg/

Kg

18.9

23.1

255

307

3/24

Ana

lysi

s Ty

pe: T

isss

ue O

rgan

ics

Cru

ise

#P

aram

eter

Uni

tsQ

AM

DL

Tar

get

MD

L M

easu

red

Pre

cisi

on

Tar

get

Pre

cisi

on

Mea

sure

dA

ccur

acy

Tar

get

Acc

urac

y M

easu

red

Bla

nk F

requ

ency

1

batc

h#(+

/- %

)(r

sd)*

(+/-

%)

(+/-

%)

7P

AH

sµg

/Kg

M15

705

2.0-

75±

207

± 20

105%

min

.7

PC

Bs

µg/K

gM

1570

10.

9-4.

4±

202

± 20

25%

min

.7

Pes

ticid

esµg

/Kg

M15

701

0.7-

2.2

± 20

2±

203

5% m

in.

9P

AH

sµg

/Kg

M16

285

.9-3

2.2

± 20

6±

205

5% m

in.

9P

AH

sµg

/Kg

M16

315

.9-3

2.2

± 20

NA

± 20

15%

min

.9

PC

Bs

µg/K

gM

1628

1.8

-2.2

± 20

3±

209

5% m

in.

9P

CB

sµg

/Kg

M16

311

.8-2

.2±

20N

A±

2011

5% m

in.

9P

estic

ides

µg/K

gM

1628

10.

4-1.

1±

205

± 20

225%

min

.9

Pes

ticid

esµg

/Kg

M16

311

.4-1

.1±

20N

A±

2026

5% m

in.

* re

lativ

e st

anda

rd d

evia

tion

1 M

axim

um B

atch

siz

e is

20

sam

ples

.

A–14


Tab

le 5

. Ref

eren

ce t

oxic

ant

and

QA

in

form

atio

n f

or t

he

aqu

atic

bio

assa

ys.

Tab

le 6

. Ph

ysic

al/c

hem

ical

mea

sure

men

ts o

f te

st s

olu

tion

s an

d Q

A i

nfo

rmat

ion

for

th

e se

dim

ent

bio

assa

ys. n

.d.

mea

ns

mea

sure

men

t be

low

th

e de

tect

ion

lim

it o

f 0.

01 m

g/L

.

Sal

inity

(‰

)E

C50

*E

C25

**Q

A N

otes

:Fe

brua

ryM

ytilu

s ed

ulis

25–3

015

12C

ontro

ls fa

iled

to m

eet %

nor

mal

dev

elop

men

t (%

ND

) of 7

0% o

n tw

o da

tes:

coef

ficie

nt o

f var

iatio

n:13

.713

.72/

8/95

67%

ND

—no

sig

nific

ant e

ffect

on

inte

rpre

tatio

n.2/

15/9

5 44

%N

D—

test

term

inat

ed d

ue to

unc

ontro

labl

e co

nditi

ons.

(this

affe

cts

Nap

a R

iver

, Griz

zly

Bay

, Sac

ram

ento

Riv

er, S

an J

oaqu

in R

iver

)M

ysid

opsi

s ba

hia

25–3

06

5N

o ex

cept

ions

coef

ficie

nt o

f var

iatio

n:12

.79.

4A

ugus

tM

ysid

opsi

s ba

hia

20–3

06

4G

row

th in

con

trol s

ampl

es w

ere

slig

htly

less

than

the

prot

ocol

of >

= 0.

20 m

g.

coef

ficie

nt o

f var

iatio

n:13

.19.

0A

vera

ge w

as 0

.18

mg/

mys

id. H

owev

er, g

row

th o

f fie

ld s

ampl

es e

xcee

ded

prot

ocol

.Lo

w g

row

th o

f con

trol t

houg

ht n

ot to

affe

ct in

terp

reta

tion.

Sac

ram

ento

Riv

er s

ampl

e ha

d lo

w g

row

th a

t 50%

but

not

at 1

00%

.S

ince

no

nega

tive

effe

ct fo

und

in 1

00%

sam

ple,

Sac

ram

ento

Riv

er ju

dged

not

to b

e to

xic.

Cra

ssos

trea

giga

sT

ests

not

per

form

edO

yste

rs w

ere

unab

le to

pro

duce

via

ble

gam

etes

.

*Con

cent

ratio

n of

refe

renc

e to

xica

nt a

t whi

ch 5

0% o

f the

org

anis

ms

show

effe

cts.

**C

once

ntra

tion

of re

fere

nce

toxi

cant

at w

hich

25%

of t

he o

rgan

ism

s sh

ow e

ffect

s.

EC

501

Sal

inity

Uni

oniz

edH

ydro

gen

QA

Not

es(C

dCl 2

)%

Am

mon

iaS

ulfid

e2

mg/

Lm

g/L

mg/

LFe

brua

ryE

ohau

stor

ius

estu

ariu

s3–

815

–16

n.d.

–0.0

180.

001–

0.00

8A

mph

ipod

sur

viva

l in

all c

ontro

l sam

ples

was

96

+/- 4

.2%

indi

catin

g te

st o

rgan

ism

s w

ere

heal

thy

and

not a

ffect

ed b

y te

st c

ondi

tions

.M

ytilu

s ed

ulis

em

bryo

s1.

5–5.

527

–31

n.d.

–0.0

95n.

d.–0

.011

Mea

n %

nor

mal

dev

elop

men

t of t

est c

ontro

ls w

as 9

5 +/

- 2.6

%

wel

l abo

ve p

roto

col m

inim

um o

f 70%

.A

ugus

tE

ohau

stor

ius

estu

ariu

s3–

3312

–17

0.00

3–0.

937

n.d.

Am

phip

od s

urvi

val i

n al

l con

trol s

ampl

es w

as 1

00 +

/- 0%

indi

catin

g te

st o

rgan

ism

s w

ere

heal

thy

and

not a

ffect

ed b

y te

st c

ondi

tions

.M

ytilu

s ed

ulis

em

bryo

s1.

5–5.

527

–29

n.d.

–132

n.d.

Mea

n %

nor

mal

dev

elop

men

t of t

est c

ontro

ls w

as 1

09 +

/- 6%

w

ell a

bove

pro

toco

l min

ium

um o

f 70%

. (V

alue

exc

eeds

100

bec

ause

of v

aria

bilit

y in

est

imat

e of

the

num

ber o

f em

byos

intro

duce

d in

to th

e te

st c

onta

iner

s.)

1 E

ffect

s co

ncen

tratio

n of

refe

renc

e to

xica

nt a

t whi

ch 5

0% o

f the

org

anis

ms

exhi

bit e

ffect

s.2 F

rom

the

over

lyin

g w

ater

Appendices

A–15

Tab

le 1

. Con

ven

tion

al w

ater

qu

alit

y p

aram

eter

s (a

t 1

met

er d

epth

), 1

995.

For

con

vers

ion

of µ

M t

o µg

/L, u

se t

he

foll

owin

g at

omic

wei

ght

mu

ltip

lier

s: P

= 3

1; C

= 1

2; N

= 1

4; S

i = 2

8,. =

no

data

, NA

= n

otan

alyz

ed, N

D =

dat

a n

ot q

uan

tifi

able

, NS

= n

ot s

ampl

edAppendix CData Tables

Station Code

Station

Date

Cruise

Ammonia

Chlorophyll-a

Conductivity

DO

DOC

Hardness

Nitrate

Nitrite

pH

Phaeophytin

Phosphate

Salinity

Silicates

Temperature

TSS

µM

mg/

m3

mho

mg/

Lµ

Mµ

Mµ

Mµ

Mp

Hm

g/m

3µ

M‰

µM

˚Cm

g/L

BA

10C

oyot

e C

reek

02/0

7/95

715

.211

.214

900

8.2

324

.20

3.2

5.1

7.6

5.0

12.7

10.9

191.

814

.023

.9B

A20

Sou

th B

ay02

/06/

957

7.9

29.0

1990

08.

128

0.

76.4

2.8

7.7

16.2

8.7

14.8

152.

913

.76.

0B

A30

Dum

barto

n B

ridge

02/0

6/95

75.

414

.520

500

9.4

276

.76

.12.

47.

78.

17.

615

.814

9.0

14.2

3.2

BA

40R

edw

ood

Cre

ek02

/07/

957

9.4

23.8

2100

08.

724

8.

44.8

1.9

7.7

12.2

4.8

16.2

141.

213

.76.

9B

B15

San

Bru

no S

hoal

02/0

6/95

78.

23.

219

500

8.3

227

.29

.01.

47.

61.

73.

415

.114

6.1

12.7

3.4

BB

30O

yste

r Poi

nt02

/06/

957

8.6

9.8

1700

09.

323

2.

36.0

1.4

7.6

4.9

3.5

15.3

171.

112

.21.

6B

B70

Ala

med

a02

/08/

957

6.7

29.0

1700

09.

023

9.

31.3

1.1

7.8

16.6

2.6

13.5

220.

313

.02.

8B

C10

Yer

ba B

uena

Isla

nd02

/08/

957

25.5

15.7

1650

09.

522

3.

24.8

1.2

7.8

10.2

2.4

13.2

161.

212

.43.

3B

C20

Gol

den

Gat

e02

/09/

957

2.5

10.7

2650

08.

814

9.

17.5

1.0

7.8

7.0

1.4

23.0

95.6

12.2

2.0

BC

30R

icha

rdso

n B

ay02

/09/

957

6.2

2.1

1590

08.

124

0.

26.9

1.1

7.7

1.2

2.3

11.6

187.

013

.03.

4B

C41

Poi

nt Is

abel

02/0

8/95

74.

524

.215

009.

124

9.

23.9

0.9

7.8

16.2

2.1

11.5

189.

313

.52.

2B

C60

Red

Roc

k02

/08/

957

4.8

6.5

9300

9.3

256

.27

.31.

07.

64.

32.

27.

420

9.8

12.1

24.1

BD

15P

etal

uma

Riv

er02

/13/

957

7.9

45.3

4250

9.9

364

580

50.5

2.0

7.7

30.7

4.7

3.2

405.

012

.011

0.2

BD

20S

an P

ablo

Bay

02/1

3/95

74.

49.

713

700

9.0

205

.20

.61.

07.

77.

11.

811

.237

4.0

11.8

15.0

BD

30P

inol

e P

oint

02/1

3/95

74.

317

.916

700

9.1

217

.23

.91.

07.

911

.61.

813

.238

1.0

12.2

6.0

BD

40D

avis

Poi

nt02

/13/

957

4.7

15.1

1180

09.

122

6.

25.4

1.1

7.8

9.2

2.0

9.0

386.

611

.863

.1B

D50

Nap

a R

iver

02/1

4/95

75.

76.

523

209.

123

832

028

.80.

97.

64.

82.

3N

D16

6.9

10.8

62.7

BF1

0P

ache

co C

reek

02/1

4/95

74.

012

.625

79.

722

172

29.7

0.7

7.7

8.2

1.7

ND

218.

311

.034

.8B

F20

Griz

zly

Bay

02/1

4/95

73.

07.

414

89.

820

860

26.2

0.7

7.7

5.7

1.7

ND

133.

110

.644

.3B

F40

Hon

ker B

ay02

/14/

957

2.5

7.2

135

9.9

216

6423

.20.

67.

75.

11.

8N

D11

6.7

10.8

39.9

BG

20S

acra

men

to R

iver

02/1

5/95

72.

615

.913

89.

620

768

25.3

0.5

7.7

11.1

1.5

ND

134.

610

.145

.5B

G30

San

Joa

quin

Riv

er02

/15/

957

5.2

6.1

131

9.6

340

6440

.61.

07.

53.

11.

9N

D13

0.6

11.1

23.0

C-1

-3S

unny

vale

02/0

7/95

713

0.9

46.8

1620

7.7

578

390

548.

844

.67.

526

.465

.8N

D34

3.3

14.7

31.7

C-3

-0S

an J

ose

02/0

7/95

749

.114

.270

006.

646

068

048

3.0

11.2

7.6

8.2

39.5

4.7

359.

315

.628

.4B

A10

Coy

ote

Cre

ek04

/24/

958

9.6

204.

014

000

8.1

389

.18

5.1

8.0

8.0

100.

814

.19.

314

3.5

17.7

172.

7B

A20

Sou

th B

ay04

/25/

958

5.6

72.6

1870

08.

029

2.

41.6

3.6

8.0

38.6

6.9

13.6

133.

516

.948

.4B

A30

Dum

barto

n B

ridge

04/2

4/95

85.

744

.618

200

8.5

342

.43

.83.

68.

027

.97.

213

.313

1.0

16.9

72.3

BA

40R

edw

ood

Cre

ek04

/24/

958

0.6

17.6

2080

08.

721

9.

15.8

1.4

8.0

10.0

0.1

15.8

118.

115

.618

.3B

B15

San

Bru

no S

hoal

04/2

5/95

82.

723

2.0

2150

09.

024

5.

12.3

1.4

8.1

48.8

3.6

16.2

124.

215

.46.

3B

B30

Oys

ter P

oint

04/2

4/95

82.

014

.622

000

9.4

174

.7.

20.

77.

97.

81.

817

.013

2.7

13.4

4.2

BB

70A

lam

eda

04/2

6/95

80.

917

5.3

2380

09.

015

8.

15.1

0.6

8.0

96.8

1.7

18.9

112.

213

.64.

2B

C10

Yer

ba B

uena

Isla

nd04

/27/

958

0.3

5.3

2240

09.

217

3.

14.1

0.5

7.9

2.6

1.5

18.1

141.

413

.57.

3B

C20

Gol

den

Gat

e04

/26/

958

0.6

64.1

3120

07.

912

4.

19.2

0.5

7.9

36.9

1.8

27.0

84.9

11.9

1.4

BC

30R

icha

rdso

n B

ay04

/26/

958

0.2

30.8

2650

08.

916

8.

5.5

0.4

8.0

16.1

1.3

21.8

88.5

13.9

4.6

BC

41P

oint

Isab

el04

/26/

958

0.2

36.2

2200

09.

817

6.

12.9

0.5

8.1

21.4

1.6

17.3

155.

614

.659

.9

A–16


Tab

le 1

. Con

ven

tion

al w

ater

qu

alit

y p

aram

eter

s (a

t 1

met

er d

epth

), 1

995

(con

tin

ued

).F

or c

onve

rsio

n o

f µM

to

µg/L

, use

th

e fo

llow

ing

atom

ic w

eigh

t m

ult

ipli

ers:

P =

31;

C =

12;

N =

14;

Si =

28,

. = n

o da

ta, N

A =

not

anal

yzed

, ND

= d

ata

not

qu

anti

fiab

le, N

S =

not

sam

pled

Station Code

Station

Date

Cruise

Ammonia

Chlorophyll-a

Conductivity

DO

DOC

Hardness

Nitrate

Nitrite

pH

Phaeophytin

Phosphate

Salinity

Silicates

Temperature

TSS

µM

mg/

m3

mho

mg/

Lµ

Mµ

Mµ

Mµ

Mp

Hm

g/m

3µ

M‰

µM

˚Cm

g/L

BC

60R

ed R

ock

04/2

7/95

80.

932

.625

100

8.4

145

.15

.90.

58.

017

.91.

720

.912

9.0

13.2

3.6

BD

15P

etal

uma

Riv

er04

/19/

958

14.7

106.

360

007.

551

763

042

.82.

27.

812

.98.

54.

715

0.6

13.9

414.

4B

D20

San

Pab

lo B

ay04

/19/

958

5.3

27.0

8900

9.1

222

.12

.60.

77.

817

.42.

36.

621

2.7

12.7

148.

4B

D30

Pin

ole

Poi

nt04

/20/

958

4.9

7.5

4350

08.

922

040

013

.90.

57.

84.

31.

72.

220

4.2

13.6

73.1

BD

40D

avis

Poi

nt04

/19/

958

4.3

2.6

5800

8.7

228

630

15.3

0.4

7.7

1.4

2.1

5.8

175.

613

.190

.1B

D50

Nap

a R

iver

04/1

8/95

83.

61.

135

59.

623

376

12.3

0.5

7.8

0.6

1.5

ND

245.

313

.962

.7B

F10

Pac

heco

Cre

ek04

/20/

958

2.9

2.5

121

10.2

214

4811

.80.

47.

91.

21.

6N

D26

5.0

13.1

54.9

BF2

0G

rizzl

y B

ay04

/20/

958

2.8

1.1

125

10.3

211

6010

.90.

47.

90.

61.

6N

D25

7.4

12.7

141.

7B

F40

Hon

ker B

ay04

/20/

958

2.1

ND

130

10.0

199

608.

50.

37.

9N

D1.

4N

D26

2.4

12.6

54.5

BG

20S

acra

men

to R

iver

04/1

8/95

82.

50.

111

89.

919

356

8.7

0.3

7.6

ND

1.1

ND

192.

812

.339

.3B

G30

San

Joa

quin

Riv

er04

/18/

958

3.7

ND

134

9.9

295

6816

.00.

77.

7N

D2.

1N

D19

0.2

13.7

24.0

C-1

-3S

unny

vale

04/2

5/95

818

.880

.352

006.

157

262

045

7.0

21.7

8.1

183.

036

.42.

614

1.1

18.2

82.4

C-3

-0S

an J

ose

04/2

5/95

823

.231

6.5

3200

7.3

462

510

495.

312

.87.

920

3.0

24.4

2.6

220.

918

.918

1.0

BA

10C

oyot

e C

reek

08/1

4/95

98.

32.

633

700

5.9

279

.64

.73.

17.

81.

716

.321

.817

5.0

24.1

19.4

BA

20S

outh

Bay

08/1

5/95

910

.42.

830

900

5.5

304

.63

.84.

97.

72.

019

.719

.919

6.0

23.4

21.5

BA

30D

umba

rton

Brid

ge08

/15/

959

8.1

1.9

3330

06.

225

0.

40.5

2.0

7.8

2.9

14.8

22.1

170.

022

.955

.6B

A40

Red

woo

d C

reek

08/1

5/95

99.

10.

835

300

6.4

171

.22

.81.

57.

91.

38.

523

.812

2.0

22.4

20.2

BB

15S

an B

runo

Sho

al08

/14/

959

5.3

0.9

3520

07.

018

1.

19.2

1.3

7.8

0.5

7.8

23.8

93.0

22.6

3.8

BB

30O

yste

r Poi

nt08

/15/

959

5.7

0.8

3720

06.

026

6.

6.2

0.8

7.9

0.9

3.1

27.2

71.0

19.4

5.0

BB

70A

lam

eda

08/1

6/95

96.

61.

237

100

5.8

316

.13

.71.

27.

80.

54.

526

.093

.020

.40.

3B

C10

Yer

ba B

uena

Isla

nd08

/16/

959

7.1

1.2

3710

06.

212

3.

5.1

0.7

7.8

1.0

2.3

27.5

65.0

18.6

2.3

BC

20G

olde

n G

ate

08/1

6/95

9N

D25

.438

500

9.2

159

.0.

10.

18.

25.

30.

932

.529

.013

.30.

5B

C30

Ric

hard

son

Bay

08/1

7/95

91.

611

.036

000

8.0

148

.2.

00.

38.

02.

12.

027

.872

.017

.83.

4B

C41

Poi

nt Is

abel

08/1

7/95

92.

51.

036

100

6.8

116

.3.

80.

67.

81.

52.

127

.557

.017

.30.

4B

C60

Red

Roc

k08

/17/

959

3.2

4.8

3430

07.

312

4.

2.9

0.4

7.9

1.1

2.4

23.0

79.0

18.2

2.7

BD

15P

etal

uma

Riv

er08

/21/

959

ND

16.1

2640

07.

319

6.

ND

0.3

7.8

3.3

3.4

17.5

87.0

21.8

70.6

BD

20S

an P

ablo

Bay

08/2

1/95

90.

913

.830

500

7.9

134

.3.

30.

48.

03.

02.

121

.459

.020

.39.

8B

D30

Pin

ole

Poi

nt08

/21/

959

0.9

19.3

2930

07.

514

0.

3.8

0.4

7.9

3.0

2.1

20.4

81.0

19.9

12.3

BD

40D

avis

Poi

nt08

/21/

959

3.8

6.6

2370

06.

913

1.

8.1

0.3

7.8

1.2

2.5

15.4

110.

020

.014

.4B

D50

Nap

a R

iver

08/2

2/95

91.

44.

521

200

7.1

188

.3.

70.

47.

81.

42.

314

.811

4.0

20.3

9.3

BF1

0P

ache

co C

reek

08/2

2/95

94.

42.

279

007.

815

999

013

.60.

57.

71.

32.

65.

521

8.0

21.3

16.3

BF2

0G

rizzl

y B

ay08

/22/

959

3.2

2.6

8400

8.6

165

990

14.5

0.6

7.7

1.4

2.6

5.2

164.

021

.525

.6B

F40

Hon

ker B

ay08

/22/

959

1.8

2.2

2200

8.1

162

270

13.9

1.1

7.7

3.3

2.3

1.2

129.

021

.759

.2B

G20

Sac

ram

ento

Riv

er08

/23/

959

4.2

1.9

NS

8.0

146

5611

.71.

17.

71.

71.

80.

027

1.0

21.5

21.0

BG

30S

an J

oaqu

in R

iver

08/2

3/95

92.

03.

519

08.

018

976

12.1

0.6

7.7

2.9

2.1

0.0

196.

023

.326

.5C

-1-3

Sun

nyva

le08

/14/

959

31.6

4.5

2220

04.

558

1.

171.

911

.07.

77.

531

.613

.524

3.0

25.0

192.

0C

-3-0

San

Jos

e08

/14/

959

36.9

3.6

1320

04.

145

6.

474.

721

.17.

65.

536

.87.

822

9.0

25.3

186.

6

Appendices

A–17

Tabl

e 2.

Dis

solv

ed c

once

ntra

tions

of t

race

ele

men

ts in

wat

er (

at 1

met

er d

epth

), 1

995.

. = n

o da

ta, N

A =

not

an

alyz

ed, N

D =

dat

a n

ot q

uan

tifi

able

, Q =

ou

tsid

e th

e Q

A li

mit

Station Code

Station

Date

Cruise

Ag

As

Cd

Cr

Cu

Hg

Ni

Pb

Se

Zn

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

BA

10C

oyot

e C

reek

02/0

7/95

70.

0018

2.14

0.06

0.31

3.03

0.00

254.

499

0.18

160.

466

6.16

1B

A20

Sou

th B

ay02

/06/

957

0.00

161.

940.

070.

162.

950.

0020

3.48

90.

0884

0.37

32.

640

BA

30D

umba

rton

Brid

ge02

/06/

957

0.00

211.

910.

070.

172.

780.

0021

3.24

80.

0738

0.29

82.

076

BA

40R

edw

ood

Cre

ek02

/07/

957

0.00

231.

630.

050.

182.

370.

0013

2.70

30.

0287

0.15

81.

266

BB

15S

an B

runo

Sho

al02

/06/

957

0.00

301.

530.

050.

162.

140.

0013

2.26

40.

0131

0.14

30.

888

BB

30O

yste

r Poi

nt02

/06/

957

0.00

271.

510.

040.

151.

920.

0013

2.20

90.

0121

0.12

20.

816

BB

70A

lam

eda

02/0

8/95

70.

0011

1.43

0.03

0.20

2.02

0.00

112.

192

0.01

300.

079

0.81

9B

C10

Yer

ba B

uena

Isla

nd02

/08/

957

0.00

131.

590.

030.

171.

890.

0012

2.08

80.

0179

0.11

60.

896

BC

20G

olde

n G

ate

02/0

9/95

70.

0016

1.37

0.03

0.15

1.00

0.00

061.

099

0.00

510.

065

0.38

4B

C30

Ric

hard

son

Bay

02/0

9/95

70.

0011

1.37

0.03

0.18

1.88

0.00

121.

972

0.01

560.

158

0.94

3B

C41

Poi

nt Is

abel

02/0

8/95

70.

0008

1.20

0.03

0.19

2.01

0.00

122.

164

0.01

780.

145

0.72

7B

C60

Red

Roc

k02

/08/

957

0.00

131.

140.

030.

472.

140.

0018

2.21

50.

0553

0.10

40.

815

BD

15P

etal

uma

Riv

er02

/13/

957

0.00

061.

910.

020.

213.

410.

0024

9.45

10.

0088

0.17

20.

598

BD

20S

an P

ablo

Bay

02/1

3/95

70.

0009

1.24

0.03

0.29

1.56

0.00

092.

018

0.02

190.

111

0.64

9B

D30

Pin

ole

Poi

nt02

/13/

957

0.00

081.

330.

030.

391.

660.

0015

2.11

10.

0341

0.16

40.

742

BD

40D

avis

Poi

nt02

/13/

957

0.00

071.

400.

030.

431.

930.

0021

2.21

70.

0187

0.27

30.

810

BD

50N

apa

Riv

er02

/14/

957

0.00

041.

250.

010.

371.

980.

0011

2.13

60.

0318

0.14

00.

511

BF1

0P

ache

co C

reek

02/1

4/95

70.

0005

1.35

0.01

0.20

1.99

0.00

121.

476

0.00

950.

127

0.22

7B

F20

Griz

zly

Bay

02/1

4/95

70.

0006

1.45

0.01

0.21

1.83

0.00

101.

498

0.00

850.

101

0.18

1B

F40

Hon

ker B

ay02

/14/

957

0.00

131.

630.

010.

641.

950.

0017

1.76

90.

0902

0.12

80.

701

BG

20S

acra

men

to R

iver

02/1

5/95

70.

0013

1.42

0.01

0.61

1.86

0.00

131.

564

0.07

530.

145

0.65

0B

G30

San

Joa

quin

Riv

er02

/15/

957

0.00

051.

370.

010.

182.

340.

0015

1.79

20.

0109

0.09

80.

445

C-1

-3S

unny

vale

02/0

7/95

70.

0180

0.74

0.02

0.23

1.76

0.00

272.

860

0.20

582.

080

17.3

60C

-3-0

San

Jos

e02

/07/

957

0.00

341.

490.

050.

383.

480.

0026

7.72

30.

4596

1.20

022

.408

BA

10C

oyot

e C

reek

04/2

4/95

80.

0016

2.59

0.07

0.18

4.29

0.00

224.

738

0.61

220.

697

5.49

7B

A20

Sou

th B

ay04

/25/

958

0.00

183.

100.

060.

212.

890.

0022

3.10

00.

0854

0.41

41.

040

BA

30D

umba

rton

Brid

ge04

/24/

958

0.00

142.

240.

060.

132.

800.

0017

2.88

20.

0671

0.32

30.

973

BA

40R

edw

ood

Cre

ek04

/24/

958

0.00

141.

820.

030.

111.

910.

0015

2.03

50.

0292

0.14

00.

570

BB

15S

an B

runo

Sho

al04

/25/

958

0.00

071.

800.

030.

121.

920.

0007

1.87

60.

0306

0.31

00.

486

BB

30O

yste

r Poi

nt04

/24/

958

0.00

061.

500.

030.

121.

160.

0006

1.30

70.

0061

0.19

40.

385

BB

70A

lam

eda

04/2

6/95

80.

0006

1.37

0.03

0.12

0.99

Q1.

096

0.00

590.

180

0.35

9B

C10

Yer

ba B

uena

Isla

nd04

/27/

958

0.00

071.

310.

050.

120.

96Q

1.13

00.

0054

0.16

00.

359

BC

20G

olde

n G

ate

04/2

6/95

80.

0009

1.61

0.07

0.12

0.47

Q0.

680

0.00

670.

116

0.29

7B

C30

Ric

hard

son

Bay

04/2

6/95

80.

0009

1.50

0.06

0.11

0.94

Q1.

065

0.00

670.

155

0.70

5B

C41

Poi

nt Is

abel

04/2

6/95

80.

0009

1.49

0.05

0.12

1.10

Q1.

214

0.00

580.

161

0.38

1B

C60

Red

Roc

k04

/27/

958

0.00

101.

550.

060.

120.

80N

D0.

978

0.00

380.

095

0.36

9

A–18


Station Code

Station

Date

Cruise

Ag

As

Cd

Cr

Cu

Hg

Ni

Pb

Se

Zn

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

µg/L

BD

15P

etal

uma

Riv

er04

/19/

958

0.00

052.

470.

030.

134.

770.

0016

8.07

30.

0065

0.26

90.

549

BD

20S

an P

ablo

Bay

04/1

9/95

80.

0008

1.41

0.02

0.14

1.55

Q1.

686

0.00

330.

192

0.34

7B

D30

Pin

ole

Poi

nt04

/20/

958

0.00

061.

250.

010.

131.

37N

D1.

222

0.00

430.

220

0.26

6B

D40

Dav

is P

oint

04/1

9/95

80.

0004

1.50

0.03

0.14

1.41

0.00

051.

748

0.00

460.

066

0.36

0B

D50

Nap

a R

iver

04/1

8/95

80.

0003

1.23

0.01

0.15

1.43

0.00

071.

231

0.01

690.

235

0.18

9B

F10

Pac

heco

Cre

ek04

/20/

958

0.00

151.

200.

010.

371.

490.

0010

1.23

70.

0779

0.17

00.

539

BF2

0G

rizzl

y B

ay04

/20/

958

0.00

181.

210.

010.

731.

660.

0016

1.34

90.

1052

0.17

90.

639

BF4

0H

onke

r Bay

04/2

0/95

80.

0020

1.23

0.01

0.89

1.78

0.00

181.

530

0.11

750.

105

0.80

8B

G20

Sac

ram

ento

Riv

er04

/18/

958

0.00

131.

020.

010.

341.

520.

0007

0.99

00.

0441

0.10

10.

440

BG

30S

an J

oaqu

in R

iver

04/1

8/95

80.

0020

1.29

0.01

0.57

1.62

0.00

231.

334

0.12

740.

301

0.72

3C

-1-3

Sun

nyva

le04

/25/

958

0.00

083.

470.

060.

194.

010.

0026

3.68

30.

2097

1.92

05.

179

C-3

-0S

an J

ose

04/2

5/95

80.

0009

2.49

0.07

0.20

4.05

0.00

186.

849

0.33

711.

270

14.3

51B

A10

Coy

ote

Cre

ek08

/14/

959

0.01

044.

830.

150.

134.

130.

0019

3.90

10.

0632

0.30

01.

219

BA

20S

outh

Bay

08/1

5/95

90.

0096

4.50

0.15

0.15

4.37

0.00

214.

407

0.06

910.

225

1.49

2B

A30

Dum

barto

n B

ridge

08/1

5/95

90.

0123

3.72

0.14

0.18

3.74

0.00

183.

349

0.04

630.

143

0.95

3B

A40

Red

woo

d C

reek

08/1

5/95

90.

0089

2.93

0.12

0.17

2.25

0.00

111.

967

0.02

210.

103

0.59

1B

B15

San

Bru

no S

hoal

08/1

4/95

90.

0095

3.46

0.12

0.13

2.16

0.00

111.

987

0.02

150.

090

0.49

4B

B30

Oys

ter P

oint

08/1

5/95

90.

0052

1.89

0.10

0.16

1.16

Q1.

091

0.01

02Q

0.50

4B

B70

Ala

med

a08

/16/

959

0.00

552.

230.

130.

141.

480.

0010

1.21

80.

0112

ND

0.61

4B

C10

Yer

ba B

uena

Isla

nd08

/16/

959

0.00

411.

890.

110.

111.

090.

0011

0.98

70.

0203

0.07

60.

750

BC

20G

olde

n G

ate

08/1

6/95

90.

0006

1.60

0.05

0.15

0.28

Q0.

472

0.00

31Q

0.09

4B

C30

Ric

hard

son

Bay

08/1

7/95

90.

0020

1.84

0.09

0.12

1.04

0.00

051.

031

0.00

69Q

0.47

2B

C41

Poi

nt Is

abel

08/1

7/95

90.

0048

1.67

0.10

0.08

1.08

0.00

070.

973

0.01

00Q

0.48

0B

C60

Red

Roc

k08

/17/

959

0.00

301.

800.

090.

131.

240.

0007

1.20

50.

0080

0.09

40.

422

BD

15P

etal

uma

Riv

er08

/21/

959

0.00

193.

140.

120.

132.

630.

0006

2.74

00.

0048

0.11

80.

488

BD

20S

an P

ablo

Bay

08/2

1/95

90.

0026

2.03

0.09

0.12

1.61

Q1.

429

0.00

79Q

0.38

4B

D30

Pin

ole

Poi

nt08

/21/

959

0.00

112.

410.

070.

081.

49Q

1.38

20.

0045

0.07

20.

361

BD

40D

avis

Poi

nt08

/21/

959

0.00

112.

090.

070.

101.

62Q

1.46

00.

0052

0.15

40.

471

BD

50N

apa

Riv

er08

/22/

959

0.00

102.

180.

070.

111.

98Q

2.10

00.

0075

0.14

20.

530

BF1

0P

ache

co C

reek

08/2

2/95

90.

0005

1.83

0.04

0.10

1.71

Q1.

085

0.00

560.

138

0.41

0B

F20

Griz

zly

Bay

08/2

2/95

90.

0006

1.74

0.05

0.10

1.76

0.00

061.

118

0.00

340.

126

0.37

2B

F40

Hon

ker B

ay08

/22/

959

0.00

031.

820.

020.

111.

56Q

0.86

60.

0061

0.12

00.

311

BG

20S

acra

men

to R

iver

08/2

3/95

90.

0009

1.59

0.01

0.14

1.47

0.00

100.

986

0.05

470.

076

0.51

2B

G30

San

Joa

quin

Riv

er08

/23/

959

0.00

021.

850.

010.

351.

550.

0005

0.71

60.

0115

0.10

80.

249

C-1

-3S

unny

vale

08/1

4/95

90.

0024

5.49

0.12

0.15

4.29

0.00

196.

118

0.22

710.

575

3.31

1C

-3-0

San

Jos

e08

/14/

959

0.00

213.

910.

090.

143.

870.

0020

10.9

360.

2762

0.66

69.

065

Tabl

e 2.

Dis

solv

ed c

once

ntra

tions

of t

race

ele

men

ts in

wat

er (

at 1

met

er d

epth

), 1

995

(con

tinue

d).

. = n

o da

ta, N

A =

not

an

alyz

ed, N

D =

dat

a n

ot q

uan

tifi

able

, Q =

ou

tsid

e th

e Q

A li

mit

Appendices

A–19

Tab

le 3

. Tot

al o

r n

ear

tota

l* c

once

ntr

atio

ns

of t

race

ele

men

ts i

n w

ater

(at

1 m

eter

dep

th),

199

5.. =

no

data

, NA

= n

ot a

nal

yzed

, ND

= d

ata

not

qu

anti

fiab

le, Q

= o

uts

ide

the

QA

lim

it

Station Code

Station

Date

Cruise

Ag

*A

sC

d*

Cr

Cu

*H

gN

i*P

b*

Se

Zn

*

µg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/L

BA

10C

oyot

e C

reek

02/0

7/95

70.

0156

2.18

0.06

704.

784.

240.

0208

8.29

1.28

0.61

11.9

8B

A20

Sou

th B

ay02

/06/

957

0.00

572.

020.

0710

1.49

3.33

0.00

784.

520.

390.

424.

40B

A30

Dum

barto

n B

ridge

02/0

6/95

70.

0067

2.10

0.07

301.

483.

210.

0078

4.16

0.38

0.35

3.96

BA

40R

edw

ood

Cre

ek02

/07/

957

0.01

211.

930.

0570

1.53

2.81

0.00

513.

540.

350.

183.

39B

B15

San

Bru

no S

hoal

02/0

6/95

70.

0057

1.59

0.04

801.

412.

610.

0044

3.22

0.32

0.12

2.71

BB

30O

yste

r Poi

nt02

/06/

957

0.00

481.

820.

0460

1.26

2.49

0.00

483.

290.

230.

152.

36B

B70

Ala

med

a02

/08/

957

0.00

601.

540.

0380

0.80

2.29

0.00

272.

760.

150.

171.

98B

C10

Yer

ba B

uena

Isla

nd02

/08/

957

0.00

261.

550.

0320

0.85

2.27

0.00

252.

810.

150.

072.

01B

C20

Gol

den

Gat

e02

/09/

957

0.00

171.

300.

0260

0.53

1.32

0.00

111.

600.

080.

090.

98B

C30

Ric

hard

son

Bay

02/0

9/95

70.

0033

1.31

0.02

500.

842.

270.

0024

2.77

0.16

0.20

2.00

BC

41P

oint

Isab

el02

/08/

957

0.00

201.

200.

0250

0.80

2.34

0.00

302.

900.

170.

082.

04B

C60

Red

Roc

k02

/08/

957

0.00

781.

390.

0220

3.77

3.55

0.00

675.

040.

480.

084.

14B

D15

Pet

alum

a R

iver

02/1

3/95

70.

0303

2.63

0.04

9019

.71

8.96

0.04

1021

.89

3.04

0.17

17.0

7B

D20

San

Pab

lo B

ay02

/13/

957

0.00

361.

380.

0270

2.95

2.86

0.00

393.

960.

350.

163.

32B

D30

Pin

ole

Poi

nt02

/13/

957

0.00

291.

360.

0280

2.74

2.56

0.00

713.

770.

330.

183.

05B

D40

Dav

is P

oint

02/1

3/95

70.

0231

2.32

0.06

2014

.39

7.55

0.02

0812

.34

1.68

0.14

13.7

5B

D50

Nap

a R

iver

02/1

4/95

70.

0097

1.91

0.02

509.

665.

740.

0169

8.85

1.20

0.19

9.57

BF1

0P

ache

co C

reek

02/1

4/95

70.

0096

1.57

0.02

409.

055.

680.

0116

7.77

1.01

0.12

8.86

BF2

0G

rizzl

y B

ay02

/14/

957

0.00

751.

850.

0210

6.26

4.95

0.00

936.

520.

750.

137.

44B

F40

Hon

ker B

ay02

/14/

957

0.00

792.

500.

0240

6.53

4.91

0.00

846.

190.

690.

167.

65B

G20

Sac

ram

ento

Riv

er02

/15/

957

0.00

681.

780.

0250

6.62

4.68

0.00

666.

350.

620.

147.

46B

G30

San

Joa

quin

Riv

er02

/15/

957

0.00

671.

880.

0170

3.72

4.16

0.00

764.

750.

540.

135.

04C

-1-3

Sun

nyva

le02

/07/

957

0.08

211.

000.

0240

2.61

3.82

0.01

676.

111.

382.

2422

.56

C-3

-0S

an J

ose

02/0

7/95

70.

0360

1.69

0.04

704.

934.

860.

0222

11.1

31.

541.

2128

.79

BA

10C

oyot

e C

reek

04/2

4/95

80.

0407

3.17

0.09

5031

.45

11.7

90.

1050

22.3

17.

690.

6629

.02

BA

20S

outh

Bay

04/2

5/95

80.

0227

3.30

0.06

009.

315.

610.

0291

9.06

2.24

0.40

9.91

BA

30D

umba

rton

Brid

ge04

/24/

958

0.02

972.

690.

0630

13.4

87.

190.

0682

13.0

33.

780.

3814

.85

BA

40R

edw

ood

Cre

ek04

/24/

958

0.00

942.

030.

0410

3.12

3.22

0.00

964.

521.

040.

254.

19B

B15

San

Bru

no S

hoal

04/2

5/95

80.

0034

1.64

0.04

001.

082.

580.

0065

2.91

0.35

0.25

1.93

BB

30O

yste

r Poi

nt04

/24/

958

0.00

301.

510.

0400

0.50

1.66

0.00

141.

680.

130.

180.

86B

B70

Ala

med

a04

/26/

958

0.00

431.

470.

0740

0.74

1.84

0.00

522.

430.

320.

191.

78B

C10

Yer

ba B

uena

Isla

nd04

/27/

958

0.00

331.

630.

0480

1.64

1.80

0.00

342.

630.

350.

182.

23B

C20

Gol

den

Gat

e04

/26/

958

0.00

221.

490.

0600

0.47

0.69

0.00

110.

840.

120.

110.

74B

C30

Ric

hard

son

Bay

04/2

6/95

80.

0018

1.55

0.05

100.

781.

570.

0025

1.96

0.21

0.17

1.63

BC

41P

oint

Isab

el04

/26/

958

0.01

421.

980.

0480

7.78

4.17

0.01

947.

311.

850.

189.

23B

C60

Red

Roc

k04

/27/

958

0.00

281.

630.

0490

1.22

1.34

0.01

241.

910.

260.

131.

49

A–20


Tab

le 3

. Tot

al o

r n

ear

tota

l* c

once

ntr

atio

ns

of t

race

ele

men

ts i

n w

ater

(at

1 m

eter

dep

th),

199

5 (c

onti

nu

ed).

. = n

o da

ta, N

A =

not

an

alyz

ed, N

D =

dat

a n

ot q

uan

tifi

able

, Q =

ou

tsid

e th

e Q

A li

mit

Station Code

Station

Date

Cruise

Ag

*A

sC

d*

Cr

Cu

*H

gN

i*P

b*

Se

Zn

*

µg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/Lµg

/L

BC

60R

ed R

ock

04/2

7/95

80.

0028

1.63

0.04

901.

221.

340.

0124

1.91

0.26

0.13

1.49

BD

15P

etal

uma

Riv

er04

/19/

958

0.05

434.

420.

0740

42.9

815

.28

0.07

9333

.23

7.20

0.35

28.2

2B

D20

San

Pab

lo B

ay04

/19/

958

0.01

752.

530.

0540

24.8

310

.04

0.04

3518

.36

4.41

0.30

19.5

3B

D30

Pin

ole

Poi

nt04

/20/

958

0.01

171.

940.

0290

11.6

55.

460.

0138

9.81

1.70

0.17

9.84

BD

40D

avis

Poi

nt04

/19/

958

0.03

092.

400.

0710

21.7

110

.16

0.03

8115

.69

3.71

0.26

17.3

2B

D50

Nap

a R

iver

04/1

8/95

80.

0122

1.84

0.03

0011

.48

6.49

0.02

207.

941.

940.

1110

.27

BF1

0P

ache

co C

reek

04/2

0/95

80.

0063

1.65

0.02

807.

825.

100.

0095

6.21

1.09

0.32

7.01

BF2

0G

rizzl

y B

ay04

/20/

958

0.01

531.

830.

0660

19.8

29.

050.

0299

13.6

82.

550.

1714

.66

BF4

0H

onke

r Bay

04/2

0/95

80.

0082

1.65

0.03

008.

395.

390.

0140

7.02

1.16

0.20

7.61

BG

20S

acra

men

to R

iver

04/1

8/95

80.

0075

1.35

0.02

505.

794.

300.

0088

4.94

0.80

0.11

5.67

BG

30S

an J

oaqu

in R

iver

04/1

8/95

80.

0067

1.48

0.01

704.

183.

140.

0073

3.13

0.67

0.33

3.62

C-1

-3S

unny

vale

04/2

5/95

80.

0107

4.04

0.06

6012

.90

7.66

0.05

6611

.81

3.14

1.51

17.7

2C

-3-0

San

Jos

e04

/25/

958

0.08

293.

140.

0890

29.1

510

.68

0.09

0922

.67

6.51

1.45

39.6

4B

A10

Coy

ote

Cre

ek08

/14/

959

0.02

805.

010.

1400

6.00

5.13

0.01

586.

451.

180.

226.

59B

A20

Sou

th B

ay08

/15/

959

0.03

205.

270.

1400

8.10

5.47

0.01

907.

551.

480.

297.

56B

A30

Dum

barto

n B

ridge

08/1

5/95

90.

0280

4.59

0.13

009.

905.

200.

0262

7.96

2.12

0.19

9.31

BA

40R

edw

ood

Cre

ek08

/15/

959

0.02

603.

160.

1100

3.50

3.17

0.00

953.

880.

750.

133.

77B

B15

San

Bru

no S

hoal

08/1

4/95

90.

0120

3.41

0.11

001.

402.

780.

0058

3.07

0.35

0.11

2.35

BB

30O

yste

r Poi

nt08

/15/

959

0.01

102.

020.

1000

0.90

1.57

0.00

261.

570.

200.

081.

52B

B70

Ala

med

a08

/16/

959

0.01

302.

340.

1000

0.40

1.77

0.00

211.

690.

10N

D1.

08B

C10

Yer

ba B

uena

Isla

nd08

/16/

959

0.01

002.

020.

0900

0.60

1.33

0.00

221.

430.

18Q

1.48

BC

20G

olde

n G

ate

08/1

6/95

90.

0010

1.27

0.10

00N

D0.

19Q

0.35

0.01

Q0.

22B

C30

Ric

hard

son

Bay

08/1

7/95

90.

0050

1.86

0.10

000.

901.

420.

0027

1.71

0.21

0.11

1.63

BC

41P

oint

Isab

el08

/17/

959

0.00

901.

990.

0900

0.70

1.16

0.00

261.

390.

18Q

1.27

BC

60R

ed R

ock

08/1

7/95

90.

0060

2.16

0.09

00N

A2.

000.

0048

2.56

0.36

Q2.

51B

D15

Pet

alum

a R

iver

08/2

1/95

90.

0080

3.99

0.13

0012

.90

6.57

0.02

638.

932.

360.

1110

.51

BD

20S

an P

ablo

Bay

08/2

1/95

90.

0100

2.58

0.08

002.

702.

450.

0070

3.31

0.60

Q3.

69B

D30

Pin

ole

Poi

nt08

/21/

959

0.00

602.

150.

0800

2.20

2.03

0.00

442.

730.

330.

102.

56B

D40

Dav

is P

oint

08/2

1/95

90.

0080

2.30

0.07

002.

702.

580.

0067

3.51

0.60

0.14

.B

D50

Nap

a R

iver

08/2

2/95

90.

0070

2.23

0.08

002.

803.

120.

0071

4.08

0.55

0.18

3.49

BF1

0P

ache

co C

reek

08/2

2/95

90.

0080

2.20

0.04

003.

602.

900.

0070

3.03

0.53

0.09

3.83

BF2

0G

rizzl

y B

ay08

/22/

959

0.01

202.

290.

0500

4.70

3.46

0.01

033.

930.

840.

075.

15B

F40

Hon

ker B

ay08

/22/

959

0.01

102.

520.

0400

7.88

4.58

0.01

545.

751.

440.

117.

77B

G20

Sac

ram

ento

Riv

er08

/23/

959

0.00

701.

940.

0200

2.70

2.62

0.00

482.

700.

50Q

3.36

BG

30S

an J

oaqu

in R

iver

08/2

3/95

90.

0070

2.32

0.02

003.

802.

770.

0063

2.55

0.63

0.06

3.37

C-1

-3S

unny

vale

08/1

4/95

90.

0890

6.74

0.13

0039

.30

11.1

30.

1010

23.4

77.

490.

7129

.99

C-3

-0S

an J

ose

08/1

4/95

90.

1370

6.02

0.13

0026

.90

10.7

40.

1050

23.7

08.

080.

6731

.66

Appendices

A–21

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of A

lkan

es (S

FE

I)

Sum

of P

AH

s (S

FE

I)

Sum

of L

PA

Hs

(SF

EI)

Sum

of H

PA

Hs

(SF

EI)

Ant

hrac

ene

Phe

nant

hren

e

1-M

ethy

lphe

nant

hren

e

Ben

z(a)

anth

race

ne

pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L

BA10 Coyote Creek 02/07/95 7 13083 4050 420 3630 ND 420 ND NDBA30 Dumbarton Bridge 02/06/95 7 74610 5232 1982 3250 62 1500 420 NDBA40 Redwood Creek 02/07/95 7 26210 1487 250 1237 ND 250 ND NDBB70 Alameda 02/08/95 7 33750 2446 630 1816 ND 630 ND NDBC10 Yerba Buena Island 02/08/95 7 127770 4900 1330 3570 ND 1200 130 NDBC20 Golden Gate 02/09/95 7 76020 1661 670 991 ND 670 ND NDBC60 Red Rock 02/08/95 7 38360 1270 490 780 ND 490 ND NDBD15 Petaluma River 02/13/95 7 61460 1114 270 844 ND 270 ND NDBD20 San Pablo Bay 02/13/95 7 49140 1521 810 711 ND [700] [110] NDBD30 Pinole Point 02/13/95 7 28110 1880 610 1270 ND 610 ND NDBD40 Davis Point 02/13/95 7 34780 1760 870 890 ND 870 ND NDBD50 Napa River 02/14/95 7 21793 4166 1400 2766 ND 1400 ND NDBF20 Grizzly Bay 02/14/95 7 22698 1150 440 710 ND 440 ND NDBG20 Sacramento River 02/15/95 7 48200 997 260 737 ND 260 ND NDBG30 San Joaquin River 02/15/95 7 27560 612 180 432 ND 180 ND NDBA10 Coyote Creek 04/24/95 8 70370 5477 960 4517 ND 960 ND 87BA30 Dumbarton Bridge 04/24/95 8 27350 2531 1100 1431 ND 1100 ND QBA40 Redwood Creek 04/24/95 8 16070 1539 720 819 Q 720 Q QBB70 Alameda 04/26/95 8 22180 2306 1100 1206 Q 1100 ND NDBC10 Yerba Buena Island 04/27/95 8 29120 2535 1400 1135 Q 1400 Q QBC20 Golden Gate 04/26/95 8 43960 1678 1000 678 Q 1000 ND QBC60 Red Rock 04/27/95 8 27200 2040 1100 940 ND 1100 ND NDBD15 Petaluma River 04/19/95 8 33930 972 500 472 Q 500 ND QBD20 San Pablo Bay 04/19/95 8 28190 1557 860 697 Q [860] ND NDBD30 Pinole Point 04/20/95 8 26480 1863.8 1093 770.8 Q 1000 93 9.8BD40 Davis Point 04/19/95 8 80600 1950 1120 830 Q 1000 120 QBD50 Napa River 04/18/95 8 44290 3112 1700 1412 Q 1700 ND QBF20 Grizzly Bay 04/20/95 8 95770 812 490 322 Q [400] [90] QBG20 Sacramento River 04/18/95 8 42280 1222 640 582 Q 500 140 QBG30 San Joaquin River 04/18/95 8 14880 393 168 225 Q (140) 28 QBA10 Coyote Creek 08/14/95 9 134000 7824 3011 4813 21 2300 690 200BA30 Dumbarton Bridge 08/15/95 9 65770 6162 2693 3469 23 2500 170 75BA40 Redwood Creek 08/15/95 9 81600 6448 1908 4540 28 1400 480 150BB70 Alameda 08/16/95 9 61750 5339 2500 2839 Q 2100 400 150BC10 Yerba Buena Island 08/16/95 9 68170 8240 2490 5750 Q 1900 590 180BC20 Golden Gate 08/16/95 9 55690 4610 1150 3460 ND 730 420 160BC60 Red Rock 08/17/95 9 71300 6410 2720 3690 Q 2200 520 180BD15 Petaluma River 08/21/95 9 65000 4084 860 3224 ND 510 350 130BD20 San Pablo Bay 08/21/95 9 83310 4949 1947 3002 37 1400 510 170BD30 Pinole Point 08/21/95 9 53870 5919 2189 3730 19 1600 570 150BD40 Davis Point 08/21/95 9 101000 6417 2306 4111 26 1800 480 150BD50 Napa River 08/22/95 9 62880 4832 1310 3522 ND 880 430 120BF20 Grizzly Bay 08/22/95 9 67930 4137 1487 2650 17 970 500 130BG20 Sacramento River 08/23/95 9 87200 5445 1225 4220 45 [620] [560] [220]BG30 San Joaquin River 08/23/95 9 66800 4253 1193 3060 43 670 480 150

[ ] Internal standard recovery < 70% ( ) Internal standard recovery > 120%

Table 4. Dissolved PAH and Alkanes concentrations in water samples (at 1 meterdepth), 1995. ND = not detected, NS = not sampled, Q = outside the QA limit, LPAHs = lowmolecular weight PAHs, HPAHs = high molecular weight PAHs.

A–22


Table 4. Dissolved PAH and Alkanes concentrations in water samples (at 1 meter depth),1995 (continued). ND = not detected, NS = not sampled, Q = outside the QA limit, LPAHs = lowmolecular weight PAHs, HPAHs = high molecular weight PAHs.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Chr

ysen

e

Flu

oran

then

e

Pyr

ene

Ben

zo(a

)pyr

ene

Ben

zo(e

)pyr

ene

Ben

zo(b

)flu

oran

then

e

Ben

zo(k

)flu

oran

then

e

Dib

enz(

a,h)

anth

race

ne

Inde

no(1

,2,3

-cd)

pyre

ne

pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L

BA10 Coyote Creek 02/07/95 7 290 1400 1700 ND 120 120 ND ND NDBA30 Dumbarton Bridge 02/06/95 7 230 1800 870 ND 240 110 ND ND NDBA40 Redwood Creek 02/07/95 7 130 940 89 ND ND 78 ND ND NDBB70 Alameda 02/08/95 7 86 1200 530 ND ND ND ND ND NDBC10 Yerba Buena Island 02/08/95 7 160 1800 1500 ND ND 110 ND ND NDBC20 Golden Gate 02/09/95 7 61 790 140 ND ND ND ND ND NDBC60 Red Rock 02/08/95 7 ND 590 90 ND ND 100 ND ND NDBD15 Petaluma River 02/13/95 7 62 460 230 ND ND 92 ND ND NDBD20 San Pablo Bay 02/13/95 7 ND [620] [91] ND ND ND ND ND NDBD30 Pinole Point 02/13/95 7 ND 630 640 ND ND ND ND ND NDBD40 Davis Point 02/13/95 7 ND 730 160 ND ND ND ND ND NDBD50 Napa River 02/14/95 7 76 1100 1500 ND ND 90 ND ND NDBF20 Grizzly Bay 02/14/95 7 ND 330 380 ND ND ND ND ND NDBG20 Sacramento River 02/15/95 7 20 240 280 ND 69 92 36 ND NDBG30 San Joaquin River 02/15/95 7 72 140 220 ND ND ND ND ND NDBA10 Coyote Creek 04/24/95 8 430 1400 190 ND 370 740 220 130 950BA30 Dumbarton Bridge 04/24/95 8 62 960 31 ND 130 200 48 ND NDBA40 Redwood Creek 04/24/95 8 31 650 ND ND ND 110 28 ND NDBB70 Alameda 04/26/95 8 ND 980 Q ND ND 190 36 ND NDBC10 Yerba Buena Island 04/27/95 8 35 1100 ND ND ND ND ND ND NDBC20 Golden Gate 04/26/95 8 18 660 ND ND ND ND ND ND NDBC60 Red Rock 04/27/95 8 ND 940 ND ND ND ND ND ND NDBD15 Petaluma River 04/19/95 8 35 420 17 ND ND ND ND ND NDBD20 San Pablo Bay 04/19/95 8 47 [620] 30 ND ND ND ND ND NDBD30 Pinole Point 04/20/95 8 39 670 52 ND ND ND ND ND NDBD40 Davis Point 04/19/95 8 53 690 87 ND ND ND ND ND NDBD50 Napa River 04/18/95 8 62 1000 350 ND ND ND ND ND NDBF20 Grizzly Bay 04/20/95 8 22 [300] ND ND ND ND ND ND NDBG20 Sacramento River 04/18/95 8 32 310 240 ND ND ND ND ND NDBG30 San Joaquin River 04/18/95 8 24 (61) (140) ND ND ND ND ND NDBA10 Coyote Creek 08/14/95 9 540 2200 1300 ND 290 190 93 ND NDBA30 Dumbarton Bridge 08/15/95 9 200 1900 540 ND 160 140 74 220 160BA40 Redwood Creek 08/15/95 9 410 1400 630 190 350 330 220 440 420BB70 Alameda 08/16/95 9 400 1200 520 75 190 120 84 100 NDBC10 Yerba Buena Island 08/16/95 9 450 3100 730 220 310 210 210 ND 340BC20 Golden Gate 08/16/95 9 260 280 150 200 270 270 280 770 820BC60 Red Rock 08/17/95 9 450 1600 650 ND 210 160 100 140 200BD15 Petaluma River 08/21/95 9 370 990 1400 ND 130 150 54 ND NDBD20 San Pablo Bay 08/21/95 9 430 1100 980 ND 170 98 54 ND NDBD30 Pinole Point 08/21/95 9 390 1400 950 ND 170 210 110 160 190BD40 Davis Point 08/21/95 9 500 1700 1500 ND 130 92 39 ND NDBD50 Napa River 08/22/95 9 410 1700 1200 ND 92 ND ND Q QBF20 Grizzly Bay 08/22/95 9 360 870 990 ND 130 120 50 ND NDBG20 Sacramento River 08/23/95 9 [610] [460] [1200] ND [260] [460] [200] [390] [420]BG30 San Joaquin River 08/23/95 9 500 390 970 ND 180 300 90 200 280

[ ] Internal standard recovery < 70% ( ) Internal standard recovery > 120%

Appendices

A–23

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of A

lkan

es (S

FE

I)

Sum

of P

AH

s (S

FE

I)

Sum

of L

PA

Hs

(SF

EI)

Sum

of H

PA

Hs

(SF

EI)

Ant

hrac

ene

Phe

nant

hren

e

1-M

ethy

lphe

nant

hren

e

Ben

z(a)

anth

race

ne

pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L

BA10 Coyote Creek 02/07/95 7 247503 70212 2722 67490 92 2320 310 1900BA30 Dumbarton Bridge 02/06/95 7 159019 39362 3212 36150 62 2600 550 740BA40 Redwood Creek 02/07/95 7 117190 29248 1131 28117 ND 1050 81 410BB70 Alameda 02/08/95 7 95220 5946 860 5086 ND 860 ND NDBC10 Yerba Buena Island 02/08/95 7 207950 8993 1560 7433 ND 1430 130 63BC20 Golden Gate 02/09/95 7 131810 3199 850 2349 ND 850 ND NDBC60 Red Rock 02/08/95 7 213690 5902 930 4972 ND 930 ND 82BD15 Petaluma River 02/13/95 7 410517 92684 4080 88604 350 3170 560 3500BD20 San Pablo Bay 02/13/95 7 161970 6483 1260 5223 ND 1150 110 82BD30 Pinole Point 02/13/95 7 180590 8206 1146 7060 ND 1070 76 NDBD40 Davis Point 02/13/95 7 361500 24710 3140 21570 100 2670 370 790BD50 Napa River 02/14/95 7 377252 32906 4590 28316 120 4000 470 1200BF20 Grizzly Bay 02/14/95 7 159075 6706 1046 5660 ND 960 86 NDBG20 Sacramento River 02/15/95 7 304300 4092 484 3348 ND 650 94 NDBG30 San Joaquin River 02/15/95 7 164680 2822 680 2142 280 400 ND NDBA10 Coyote Creek 04/24/95 8 488630 452477 17960 434517 2200 13960 1800 18087BA30 Dumbarton Bridge 04/24/95 8 380200 401331 18100 383231 2300 14100 1700 17000BA40 Redwood Creek 04/24/95 8 115700 74449 3230 71219 70 2820 340 2200BB70 Alameda 04/26/95 8 81500 14097 1725 12372 Q 1670 55 66BC10 Yerba Buena Island 04/27/95 8 95560 13838 2036 11802 Q 1970 66 57BC20 Golden Gate 04/26/95 8 83080 4654 1240 3414 Q 1240 ND 16BC60 Red Rock 04/27/95 8 78620 9157 1604 7553 Q 1560 44 33BD15 Petaluma River 04/19/95 8 1235330 504872 32200 472672 4100 24500 3600 24000BD20 San Pablo Bay 04/19/95 8 402820 75357 6660 68697 470 5360 830 3500BD30 Pinole Point 04/20/95 8 439362 24074.8 3184 20891 31 (2700) (453) (510)BD40 Davis Point 04/19/95 8 513523 60190 6640 53550 (420) (5300) (920) (2200)BD50 Napa River 04/18/95 8 261144 20229 3497 16732 37 3200 260 760BF20 Grizzly Bay 04/20/95 8 510110 27878 3346 24532 96 2800 450 1200BG20 Sacramento River 04/18/95 8 159940 3155 1017 2138 Q 810 207 58BG30 San Joaquin River 04/18/95 8 14880 8973 168 8805 Q 140 28 [190]BA10 Coyote Creek 08/14/95 9 283500 60806 5383 55423 73 4200 1110 1300BA30 Dumbarton Bridge 08/15/95 9 283570 107044 6843 100201 (333) (5700) (810) (3175)BA40 Redwood Creek 08/15/95 9 279300 42843 3868 38975 28 3000 840 970BB70 Alameda 08/16/95 9 93240 8119 2880 5239 Q 2420 460 270BC10 Yerba Buena Island 08/16/95 9 105110 13657 2970 10687 Q 2270 700 390BC20 Golden Gate 08/16/95 9 93910 6069 1312 4757 ND 850 462 196BC60 Red Rock 08/17/95 9 158120 13083 3173 9910 Q 2610 563 470BD15 Petaluma River 08/21/95 9 367900 54894 3060 51834 (200) (2110) (750) (1430)BD20 San Pablo Bay 08/21/95 9 224510 15599 2627 12972 37 1920 670 420BD30 Pinole Point 08/21/95 9 158890 13756 2826 10930 46 2060 720 400BD40 Davis Point 08/21/95 9 241800 17133 3092 14041 42 2380 670 550BD50 Napa River 08/22/95 9 238270 14812 1990 12822 ND 1390 600 500BF20 Grizzly Bay 08/22/95 9 325690 . . . NS NS NS NSBG20 Sacramento River 08/23/95 9 318960 9545 1625 7920 45 890 690 380BG30 San Joaquin River 08/23/95 9 389070 7279 1553 5726 43 900 610 300

[ ] Internal standard recovery < 70% ( ) Internal standard recovery of particulate > 120%

Table 5. Total (particulate plus dissolved) PAH and Alkanes concentrations in watersamples, 1995 (at 1 meter depth). ND = not detected, NS = not sampled, Q = outside the QA limit,LPAHs = low molecular weight PAHs, HPAHs = high molecular weight PAHs.

A–24


Table 5. Total (particulate plus dissolved) PAH and Alkanes concentrations in watersamples, 1995 (at 1 meter depth; continued). ND = not detected, NS = not sampled, Q = outsidethe QA limit, LPAHs = low molecular weight PAHs, HPAHs = high molecular weight PAHs.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Chr

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e

Flu

oran

then

e

Pyr

ene

Ben

zo(a

)pyr

ene

Ben

zo(e

)pyr

ene

Ben

zo(b

)flu

oran

then

e

Ben

zo(k

)flu

oran

then

e

Dib

enz(

a,h)

anth

race

ne

Inde

no(1

,2,3

-cd)

pyre

ne


BA10 Coyote Creek 02/07/95 7 3390 8000 11200 3300 8020 12120 4400 1430 13730BA30 Dumbarton Bridge 02/06/95 7 2830 5900 4470 ND 4840 6910 2500 730 7230BA40 Redwood Creek 02/07/95 7 2630 4140 3189 ND 3900 5178 2100 440 6130BB70 Alameda 02/08/95 7 566 1820 760 ND 560 830 390 ND 160BC10 Yerba Buena Island 02/08/95 7 670 2520 1760 ND 660 970 470 100 220BC20 Golden Gate 02/09/95 7 261 1160 250 ND 260 330 88 ND NDBC60 Red Rock 02/08/95 7 530 1260 560 ND 630 950 340 ND 620BD15 Petaluma River 02/13/95 7 5262 8960 13230 9600 9400 15092 5000 1830 16730BD20 San Pablo Bay 02/13/95 7 550 1440 601 ND 640 880 420 ND 610BD30 Pinole Point 02/13/95 7 750 1570 1460 ND 860 1100 430 60 830BD40 Davis Point 02/13/95 7 2100 3730 3960 360 2500 3800 1300 300 2730BD50 Napa River 02/14/95 7 2476 5100 6300 210 2800 4590 1600 510 3530BF20 Grizzly Bay 02/14/95 7 630 1180 940 ND 760 1000 580 70 500BG20 Sacramento River 02/15/95 7 460 830 630 71 419 622 176 ND 140BG30 San Joaquin River 02/15/95 7 312 510 430 ND 270 480 140 ND NDBA10 Coyote Creek 04/24/95 8 17430 40400 57190 54000 48370 66740 25220 11130 95950BA30 Dumbarton Bridge 04/24/95 8 22062 38960 56031 45000 39130 57200 21048 8800 78000BA40 Redwood Creek 04/24/95 8 4431 7950 10000 Q 9300 14110 4628 1600 17000BB70 Alameda 04/26/95 8 1100 2780 1300 Q 1700 2190 976 360 1900BC10 Yerba Buena Island 04/27/95 8 1135 2700 1100 Q 1600 2200 620 390 2000BC20 Golden Gate 04/26/95 8 328 1350 110 ND 450 790 260 ND 110BC60 Red Rock 04/27/95 8 740 2240 610 Q 980 1300 590 220 840BD15 Petaluma River 04/19/95 8 20035 67420 90017 51000 47000 68000 22000 8200 75000BD20 San Pablo Bay 04/19/95 8 3647 11620 15030 2200 7300 9500 3800 1100 11000BD30 Pinole Point 04/20/95 8 (1339) (4370) (4752) ND (2200) (2500) (1500) (420) (3300)BD40 Davis Point 04/19/95 8 (2653) (11690) (14087) (2000) (4800) (6200) (2500) (720) (6700)BD50 Napa River 04/18/95 8 1162 4100 3850 Q 1600 2100 900 260 2000BF20 Grizzly Bay 04/20/95 8 1522 5600 6300 270 2200 2900 1200 340 3000BG20 Sacramento River 04/18/95 8 212 840 470 ND 160 210 88 33 67BG30 San Joaquin River 04/18/95 8 [294] [381] [750] [1100] [550] [850] [500] [490] [3700]BA10 Coyote Creek 08/14/95 9 5140 7800 7900 10 7990 10190 3993 1100 10000BA30 Dumbarton Bridge 08/15/95 9 (8100) (11300) (12540) 32 (14160) (20140) (8074) (2520) (20160)BA40 Redwood Creek 08/15/95 9 4010 5300 4830 255 5550 6430 3820 1290 6520BB70 Alameda 08/16/95 9 750 1700 620 75 650 730 344 100 NDBC10 Yerba Buena Island 08/16/95 9 1070 3930 1030 287 1020 1130 780 400 650BC20 Golden Gate 08/16/95 9 380 380 173 278 390 390 390 1050 1130BC60 Red Rock 08/17/95 9 1230 2700 1110 ND 1310 1460 920 340 370BD15 Petaluma River 08/21/95 9 (4770) (5890) (8500) Q (7630) (9550) (4254) (810) (9000)BD20 San Pablo Bay 08/21/95 9 1530 2300 2380 ND 1870 2398 654 220 1200BD30 Pinole Point 08/21/95 9 1270 2500 1950 ND 1370 1710 490 420 820BD40 Davis Point 08/21/95 9 1600 3000 3000 ND 1830 2192 599 270 1000BD50 Napa River 08/22/95 9 1610 3000 2600 ND 1492 1700 880 150 890BF20 Grizzly Bay 08/22/95 9 NS NS NS NS NS NS NS NS NSBG20 Sacramento River 08/23/95 9 1060 960 1720 ND 710 1090 420 670 910BG30 San Joaquin River 08/23/95 9 1020 750 1360 ND 530 750 270 370 376

[ ] Internal standard recovery < 70% ( ) Internal standard recovery of particulate > 120%

Appendices

A–25

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of P

CB

s (S

FE

I)

PC

B 0

03/3

0

PC

B 0

08

PC

B 0

15

PC

B 0

18

PC

B 0

27

PC

B 0

28

PC

B 0

29

PC

B 0

31

PC

B 0

44

PC

B 0

49

PC

B 0

52

PC

B 0

60

PC

B 0

64

PC

B 0

66

pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L

BA10 Coyote Creek 02/07/95 7 353 . 8.6 . 17.0 1.4 25.0 ND 22.0 11.0 12.0 36.0 ND . 8.2

BA30 Dumbarton Bridge 02/06/95 7 1156 . 17.0 . 42.0 8.5 180.0 ND 140.0 30.0 18.0 60.0 ND . 28.0

BA40 Redwood Creek 02/07/95 7 219 . 4.1 . 7.2 ND 17.6 ND 14.0 10.0 9.3 18.0 ND . 6.1

BB70 Alameda 02/08/95 7 128 . 2.8 . 4.4 ND 9.9 ND 6.9 4.5 7.2 5.2 ND . 4.5

BC10 Yerba Buena Island 02/08/95 7 286 . 19.0 . 15.0 ND 29.0 ND 30.0 12.0 22.0 12.9 ND . 4.3

BC20 Golden Gate 02/09/95 7 191 . 4.0 . 3.1 ND 23.5 ND 16.5 5.4 10.5 ND ND . 5.6

BC60 Red Rock 02/08/95 7 112 . 6.3 . 2.3 ND 8.5 ND 7.8 6.0 4.4 9.1 ND . 4.0

BD15 Petaluma River 02/13/95 7 132 . 2.0 . 2.7 0.9 5.9 ND 4.9 3.7 1.5 4.4 ND . 4.0

BD20 San Pablo Bay 02/13/95 7 337 . 2.1 . 4.3 3.0 M ND M 2.7 7.6 17.0 ND . 4.6

BD30 Pinole Point 02/13/95 7 81 . 1.5 . 2.7 ND 5.5 ND 4.0 3.8 3.2 3.5 ND . 2.3

BD40 Davis Point 02/13/95 7 74 . 0.6 . 2.8 ND 3.3 ND 2.7 2.6 1.8 2.0 ND . 2.3

BD50 Napa River 02/14/95 7 84 . 1.6 . 2.8 ND 4.2 ND 3.7 2.6 1.1 2.2 ND . 2.0

BF20 Grizzly Bay 02/14/95 7 75 . 3.1 . 2.8 ND 6.2 ND 6.0 2.5 2.6 2.2 ND . 2.2

BG20 Sacramento River 02/15/95 7 76 . 2.2 . 3.0 ND 7.3 ND 5.8 2.8 4.9 M ND . 2.4

BG30 San Joaquin River 02/15/95 7 102 . 1.9 . 2.2 ND 7.5 ND 6.4 3.6 3.0 12.0 ND . 3.4

BA10 Coyote Creek 04/24/95 8 448 . 8.7 M 29.0 2.2 23.0 1.2 20.0 16.0 5.2 6.2 8.3 . 33.0

BA30 Dumbarton Bridge 04/24/95 8 327 . 9.0 M 12.0 ND 11.0 0.7 11.0 9.8 10.0 9.6 6.4 . 16.0

BA40 Redwood Creek 04/24/95 8 206 . 2.3 M 5.0 ND 13.0 ND 17.0 5.4 5.6 4.1 2.1 . 8.1

BB70 Alameda 04/26/95 8 104 . 1.3 M 2.6 ND 5.2 ND 5.4 2.4 1.2 4.9 1.6 . 3.7

BC10 Yerba Buena Island 04/27/95 8 121 . 4.0 M 7.1 ND 6.4 1.7 6.6 5.1 4.1 4.2 1.6 . 6.9

BC20 Golden Gate 04/26/95 8 107 . 1.1 M 4.4 ND 5.8 ND 7.0 4.4 4.1 12.0 ND . 4.5

BC60 Red Rock 04/27/95 8 92 . 1.4 M 2.7 ND 3.7 ND 4.7 2.8 3.3 2.9 ND . 5.5

BD15 Petaluma River 04/19/95 8 139 . 1.5 M 4.1 0.8 4.7 2.0 3.0 4.7 4.0 16.0 1.1 . 5.8

BD20 San Pablo Bay 04/19/95 8 120 . 1.1 M 3.4 0.5 2.8 0.6 2.3 3.2 3.9 2.5 2.1 . 6.2

BD30 Pinole Point 04/20/95 8 124 . 1.2 M 4.7 ND 3.8 0.6 4.8 3.9 3.7 4.4 1.3 . 6.9

BD40 Davis Point 04/19/95 8 128 . 1.1 M 5.2 ND 4.5 ND 4.4 2.5 3.3 2.3 1.4 . 13.0

BD50 Napa River 04/18/95 8 125 . 1.6 M 4.7 1.1 5.6 1.5 3.5 4.6 6.3 2.7 ND . 7.5

BF20 Grizzly Bay 04/20/95 8 96 . 1.1 M 2.1 ND 5.7 ND 5.9 3.9 6.1 1.5 ND . 8.4

BG20 Sacramento River 04/18/95 8 562 . 4.4 M 11.0 12.0 45.0 ND 64.0 12.0 9.6 16.0 7.6 . 17.0

BG30 San Joaquin River 04/18/95 8 108 . 0.9 M 4.4 ND 3.1 ND 3.4 3.6 3.7 4.9 ND . 7.7

BA10 Coyote Creek 08/14/95 9 455 ND ND ND 14.0 4.3 23.0 11.0 24.0 9.4 6.1 15.0 2.5 4.3 13.0

BA30 Dumbarton Bridge 08/15/95 9 233 ND 5.8 ND 9.5 ND 10.0 0.8 17.0 7.9 4.6 5.4 3.0 2.5 6.9

BA40 Redwood Creek 08/15/95 9 204 ND ND ND 6.4 ND 7.6 0.5 15.0 5.9 2.6 ND 2.8 1.9 22.0

BB70 Alameda 08/16/95 9 137 ND 1.7 ND 4.0 ND 5.7 1.2 8.8 3.2 2.5 5.3 1.9 1.5 5.4

BC10 Yerba Buena Island 08/16/95 9 93 ND 2.4 ND 4.2 ND 6.1 2.7 10.0 3.7 2.2 M 1.5 1.6 3.1

BC20 Golden Gate 08/16/95 9 55 ND 2.4 ND 1.8 ND 3.8 1.6 6.6 1.3 0.9 M 1.4 0.8 2.0

BC60 Red Rock 08/17/95 9 90 ND ND ND 4.9 ND 6.4 1.0 10.0 3.4 1.6 3.3 2.3 1.7 1.4

BD15 Petaluma River 08/21/95 9 113 ND 3.2 ND 3.7 ND 6.4 0.7 9.2 3.9 1.3 4.0 1.8 2.2 2.9

BD20 San Pablo Bay 08/21/95 9 86 ND 3.5 ND 4.2 ND 5.0 ND 8.4 3.2 0.9 4.8 1.6 1.7 2.9

BD30 Pinole Point 08/21/95 9 79 ND 2.5 ND 4.1 ND 5.0 2.6 6.6 3.3 1.8 2.1 2.1 1.6 3.6

BD40 Davis Point 08/21/95 9 96 ND 2.4 ND 3.7 ND 5.5 1.0 8.3 3.2 1.4 1.8 2.3 1.5 3.8

BD50 Napa River 08/22/95 9 116 ND 2.2 ND 4.8 ND 6.5 1.7 8.8 4.0 1.1 3.4 2.9 2.0 4.0

BF20 Grizzly Bay 08/22/95 9 163 ND ND ND 9.1 ND 10.0 0.9 16.0 6.1 1.8 12.0 3.3 3.5 4.0

Table 6. Dissolved PCB concentrations in water samples, 1995.. = no data, ND = not detected, M = matrix interference, CE = coelution

BG20 Sacramento River 08/23/95 9 116 ND 2.3 ND 6.0 ND 7.7 ND 12.0 3.3 2.0 5.5 2.2 1.8 4.4

BG30 San Joaquin River 08/23/95 9 116 ND 2.2 ND 5.4 ND 7.9 3.2 11.0 4.7 1.7 4.0 2.5 2.6 3.4

A–26


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

PC

B 0

70

PC

B 0

74

PC

B 0

84

PC

B 0

85

PC

B 0

87

PC

B 0

89

PC

B 0

95

PC

B 0

97

PC

B 0

99

PC

B 1

01

PC

B 1

03

PC

B 1

05

PC

B 1

10

PC

B 1

14

PC

B 1

18


BA10 Coyote Creek 02/07/95 7 17.0 5.2 . 6.9 12.0 . 15.0 6.9 8.5 27.0 ND 1.0 11.0 ND 12.0

BA30 Dumbarton Bridge 02/06/95 7 57.0 23.0 . M 37.0 . 35.0 26.0 27.0 63.0 ND 12.0 M ND 59.0

BA40 Redwood Creek 02/07/95 7 9.0 3.6 . 2.3 9.6 . 7.6 4.3 6.0 9.8 ND 0.9 6.9 ND 8.6

BB70 Alameda 02/08/95 7 5.2 2.1 . 1.4 4.9 . 5.2 2.4 3.2 8.4 ND 0.9 4.7 ND 4.3

BC10 Yerba Buena Island 02/08/95 7 16.0 6.8 . 4.0 11.0 . 3.5 3.5 4.7 7.8 ND 1.9 12.9 ND 11.0

BC20 Golden Gate 02/09/95 7 6.4 4.8 . 3.0 6.8 . 8.2 3.7 3.7 5.6 ND ND 11.8 ND 8.6

BC60 Red Rock 02/08/95 7 4.8 2.0 . M 4.3 . 3.8 1.9 2.1 4.6 ND 0.8 3.0 ND 3.5

BD15 Petaluma River 02/13/95 7 4.5 2.3 . 2.8 6.2 . 4.8 2.2 4.1 9.2 ND 0.5 7.2 ND 6.2

BD20 San Pablo Bay 02/13/95 7 11.0 4.4 . M 9.9 . 12.0 8.1 4.9 14.0 ND 8.0 M ND 22.0

BD30 Pinole Point 02/13/95 7 3.3 1.2 . 1.1 M . 3.1 1.4 2.1 5.0 ND 0.5 4.9 ND 3.5

BD40 Davis Point 02/13/95 7 3.7 1.7 . M ND . 3.6 1.2 3.5 5.5 ND 0.5 2.8 ND 3.3

BD50 Napa River 02/14/95 7 3.5 1.2 . 1.6 4.6 . 3.8 1.3 2.2 5.0 ND ND 3.2 ND 3.5

BF20 Grizzly Bay 02/14/95 7 3.6 1.4 . 2.9 2.3 . 3.2 1.2 2.1 3.9 ND ND 2.3 ND 3.0

BG20 Sacramento River 02/15/95 7 3.4 1.3 . 2.9 2.1 . 3.8 0.8 2.9 4.1 ND ND 4.2 ND 3.3

BG30 San Joaquin River 02/15/95 7 4.4 1.3 . 3.2 2.9 . 3.9 1.3 2.7 5.3 ND ND 3.9 ND 3.5

BA10 Coyote Creek 04/24/95 8 11.0 4.9 . M 9.1 . 40.0 7.4 14.0 25.0 ND ND 18.0 ND 13.0

BA30 Dumbarton Bridge 04/24/95 8 9.9 4.7 . M 6.4 . 27.0 5.7 12.0 17.0 ND 0.6 20.0 ND 11.0

BA40 Redwood Creek 04/24/95 8 6.1 3.1 . M 3.9 . 14.0 5.2 4.7 13.0 ND 0.5 13.0 ND 9.4

BB70 Alameda 04/26/95 8 1.5 1.0 . M 4.9 . 7.3 2.5 2.7 4.9 ND ND 4.1 ND 4.5

BC10 Yerba Buena Island 04/27/95 8 4.6 2.5 . M 2.2 . 8.8 1.7 3.0 6.6 ND ND 7.7 ND 3.5

BC20 Golden Gate 04/26/95 8 3.6 2.0 . M 2.4 . 7.9 2.2 2.6 4.7 ND ND 3.2 ND 3.5

BC60 Red Rock 04/27/95 8 3.6 1.4 . M 1.8 . 7.2 1.0 2.8 3.3 ND ND 3.1 ND 3.7

BD15 Petaluma River 04/19/95 8 2.2 1.8 . M 2.2 . 10.0 1.5 4.1 5.6 ND ND 6.7 ND 4.0

BD20 San Pablo Bay 04/19/95 8 4.0 1.8 . M 2.3 . 10.0 1.2 4.0 8.4 ND ND 6.3 ND 3.7

BD30 Pinole Point 04/20/95 8 3.4 2.1 . M 2.4 . 10.0 1.4 3.9 7.1 ND ND 5.9 ND 5.9

BD40 Davis Point 04/19/95 8 4.4 2.0 . M 2.7 . 11.0 1.1 4.3 7.5 ND ND 1.1 ND 4.2

BD50 Napa River 04/18/95 8 3.8 2.0 . M 2.2 . 10.0 1.6 4.0 7.6 ND ND 5.1 ND 4.3

BF20 Grizzly Bay 04/20/95 8 2.8 2.8 . M 1.0 . 6.8 ND 1.5 4.0 ND ND 5.4 ND 3.9

BG20 Sacramento River 04/18/95 8 15.0 8.6 . M 11.0 . 20.0 9.5 7.5 37.0 ND 1.2 46.0 ND 38.0

BG30 San Joaquin River 04/18/95 8 2.4 1.4 . M 1.6 . 7.0 3.0 2.6 7.3 ND ND 7.6 ND 3.5

BA10 Coyote Creek 08/14/95 9 17.0 8.6 ND 2.5 5.5 4.0 14.0 7.5 9.7 16.0 ND 4.6 21.0 . 31.0

BA30 Dumbarton Bridge 08/15/95 9 8.5 4.1 ND 1.5 3.0 0.9 16.0 4.4 5.4 12.0 ND 2.0 12.0 . 12.0

BA40 Redwood Creek 08/15/95 9 5.6 3.9 ND 1.1 2.6 1.2 16.0 3.2 4.1 10.0 ND 1.9 9.2 . 11.0

BB70 Alameda 08/16/95 9 3.0 1.8 ND 0.9 1.9 1.0 11.0 1.6 3.6 5.8 ND 1.6 4.6 . 5.1

BC10 Yerba Buena Island 08/16/95 9 2.5 1.7 ND 0.7 1.8 0.9 6.4 1.9 2.7 5.3 ND 0.9 4.5 . 2.9

BC20 Golden Gate 08/16/95 9 3.6 1.3 ND ND 0.9 0.5 2.6 0.7 1.1 1.9 ND 0.7 1.7 . 3.6

BC60 Red Rock 08/17/95 9 3.1 2.5 ND 0.7 1.7 0.9 1.9 1.4 1.9 4.1 ND 1.2 3.6 . 5.2

BD15 Petaluma River 08/21/95 9 2.6 1.1 ND 0.9 2.0 1.6 5.1 2.3 3.0 4.9 ND 0.5 5.5 . 3.6

BD20 San Pablo Bay 08/21/95 9 2.2 1.6 ND 0.6 1.7 1.4 4.8 1.8 2.0 3.7 ND ND 4.4 . 3.8

BD30 Pinole Point 08/21/95 9 2.2 1.5 ND ND 1.4 1.0 7.4 1.4 2.1 3.4 ND 0.6 2.9 . 2.8

BD40 Davis Point 08/21/95 9 2.7 1.1 ND 0.7 1.0 1.2 8.8 1.8 2.5 3.6 ND 1.1 3.8 . 4.7

BD50 Napa River 08/22/95 9 3.2 2.1 ND 0.7 2.0 1.4 11.0 1.9 3.0 4.8 ND 1.2 4.7 . 5.3

BF20 Grizzly Bay 08/22/95 9 5.0 1.7 ND 1.1 3.3 2.0 7.9 2.7 3.2 6.2 ND 1.1 7.6 . 4.8

Table 6. Dissolved PCB concentrations in water samples, 1995 (continued).. = no data, ND = not detected, M = matrix interference, CE = coelution

BG20 Sacramento River 08/23/95 9 3.3 2.1 ND 0.8 2.4 1.2 7.9 1.6 2.0 4.2 ND 1.3 4.3 . 5.4

BG30 San Joaquin River 08/23/95 9 3.1 1.9 ND 0.6 2.2 1.7 11.0 1.7 2.1 4.4 ND 0.7 4.1 . 4.0

Appendices

A–27


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of P

CB

s (S

FE

I)

PC

B 1

19

PC

B 1

28

PC

B 1

32

PC

B 1

37

PC

B 1

38

PC

B 1

41

PC

B 1

46

PC

B 1

49

PC

B 1

51

PC

B 1

53

PC

B 1

56

PC

B 1

57

PC

B 1

58

PC

B 1

67


BA10 Coyote Creek 02/07/95 7 353 CE 2.4 4.5 1.1 16.0 . . 22.0 . 21.0 0.9 0.5 2.1 .

BA30 Dumbarton Bridge 02/06/95 7 1156 6.0 20.0 24.0 2.5 79.0 . . 46.0 . 64.0 1.3 0.5 11.0 .

BA40 Redwood Creek 02/07/95 7 219 CE 1.7 3.2 0.6 11.9 . . 12.0 . 15.0 0.9 0.5 1.6 .

BB70 Alameda 02/08/95 7 128 ND 1.2 2.0 ND 5.9 . . 7.6 . 6.4 0.8 ND 1.1 .

BC10 Yerba Buena Island 02/08/95 7 286 ND 2.5 2.5 2.0 11.9 . . 8.9 . 10.0 3.8 1.1 2.2 .

BC20 Golden Gate 02/09/95 7 191 ND 1.9 2.7 1.9 16.4 . . 8.0 . 12.2 1.3 0.7 1.3 .

BC60 Red Rock 02/08/95 7 112 ND 0.9 1.9 ND 4.4 . . 4.9 . 5.5 0.7 0.5 0.9 .

BD15 Petaluma River 02/13/95 7 132 CE 1.3 2.3 ND 11.0 . . 8.0 . 9.8 ND 1.0 1.1 .

BD20 San Pablo Bay 02/13/95 7 337 6.8 13.0 13.0 2.2 49.0 . . 25.0 . 39.0 5.3 1.7 4.0 .

BD30 Pinole Point 02/13/95 7 81 ND 0.7 1.8 ND 3.2 . . 6.0 . 3.7 0.6 ND 1.0 .

BD40 Davis Point 02/13/95 7 74 ND ND 1.8 ND 5.4 . . 4.8 . 6.1 0.5 ND ND .

BD50 Napa River 02/14/95 7 84 ND 0.7 1.9 ND 8.9 . . 5.7 . 4.1 ND ND 0.9 .

BF20 Grizzly Bay 02/14/95 7 75 ND ND 1.4 ND 4.7 . . 3.7 . 3.1 ND ND 0.5 .

BG20 Sacramento River 02/15/95 7 76 ND ND 1.2 ND 3.1 . . 3.8 . 3.2 ND ND ND .

BG30 San Joaquin River 02/15/95 7 102 ND 0.8 1.9 ND 5.1 . . 5.3 . 5.4 ND ND 0.5 .

BA10 Coyote Creek 04/24/95 8 448 ND 2.6 6.0 ND 24.0 . . 28.0 1.1 31.0 0.6 ND 3.3 .

BA30 Dumbarton Bridge 04/24/95 8 327 ND 1.8 4.7 ND 19.0 . . 21.0 1.6 25.0 ND ND 2.4 .

BA40 Redwood Creek 04/24/95 8 206 ND 2.3 3.1 ND 12.0 . . 12.0 ND 16.0 1.3 ND 1.5 .

BB70 Alameda 04/26/95 8 104 ND 1.1 1.9 ND 8.2 . . 6.7 ND 8.7 ND ND 1.0 .

BC10 Yerba Buena Island 04/27/95 8 121 ND 0.6 1.5 ND 5.4 . . 6.7 ND 7.5 ND ND 0.7 .

BC20 Golden Gate 04/26/95 8 107 ND 0.6 1.5 ND 4.6 . . 6.1 ND 6.7 ND ND ND .

BC60 Red Rock 04/27/95 8 92 ND 0.6 1.5 ND 6.0 . . 5.6 ND 7.2 ND 0.1 0.7 .

BD15 Petaluma River 04/19/95 8 139 ND 0.7 2.1 ND 11.0 . . 8.4 ND 9.1 ND ND 3.1 .

BD20 San Pablo Bay 04/19/95 8 120 ND 0.8 1.9 ND 7.7 . . 8.8 ND 11.0 ND ND 0.8 .

BD30 Pinole Point 04/20/95 8 124 ND 0.8 2.2 ND 6.6 . . 8.7 ND 8.8 ND ND 0.5 .

BD40 Davis Point 04/19/95 8 128 ND ND 2.2 ND 8.3 . . 9.3 0.5 10.0 ND ND 1.0 .

BD50 Napa River 04/18/95 8 125 ND 0.8 1.8 0.7 7.5 . . 8.2 0.8 8.8 ND ND 0.8 .

BF20 Grizzly Bay 04/20/95 8 96 ND 0.7 1.6 ND 4.6 . . 5.3 0.7 6.3 ND ND 3.0 .

BG20 Sacramento River 04/18/95 8 562 0.9 8.1 7.6 1.3 36.0 . . 24.0 1.5 34.0 4.3 3.3 5.0 .

BG30 San Joaquin River 04/18/95 8 108 ND 0.8 1.8 0.9 7.6 . . 7.3 0.6 7.5 0.7 ND 1.7 .

BA10 Coyote Creek 08/14/95 9 455 . 1.9 8.9 ND 29.0 3.6 2.5 33.0 7.4 35.0 2.2 0.5 3.3 0.8

BA30 Dumbarton Bridge 08/15/95 9 233 . 0.9 4.1 ND 16.0 1.0 1.6 14.0 4.4 18.0 0.5 ND 1.7 ND

BA40 Redwood Creek 08/15/95 9 204 . 0.9 3.8 ND 14.0 1.1 1.5 9.9 4.4 16.0 ND ND 1.4 ND

BB70 Alameda 08/16/95 9 137 . 0.6 2.4 ND 14.0 0.7 0.9 9.5 2.5 12.0 ND ND 1.1 ND

BC10 Yerba Buena Island 08/16/95 9 93 . ND 2.1 ND 2.8 0.7 0.7 3.8 1.8 3.8 ND ND 0.7 ND

BC20 Golden Gate 08/16/95 9 55 . ND 0.9 ND 1.9 ND ND 5.2 0.7 1.8 ND ND ND ND

BC60 Red Rock 08/17/95 9 90 . ND 1.8 ND 3.7 0.8 0.5 6.0 1.4 3.5 ND ND 0.8 ND

BD15 Petaluma River 08/21/95 9 113 . 0.6 2.8 ND 8.3 0.6 0.8 5.8 2.4 10.0 0.5 ND 0.9 ND

BD20 San Pablo Bay 08/21/95 9 86 . ND 2.1 ND 2.6 0.6 0.5 4.0 2.0 3.4 ND ND ND ND

BD30 Pinole Point 08/21/95 9 79 . ND 1.5 ND 3.1 0.6 ND 3.9 1.3 2.7 ND ND ND ND

BD40 Davis Point 08/21/95 9 96 . ND 1.8 ND 4.3 0.8 0.5 6.5 1.4 4.7 ND ND 0.8 ND

BD50 Napa River 08/22/95 9 116 . 0.5 2.2 ND 6.9 0.8 0.5 7.9 1.9 5.6 ND ND 0.9 ND

BF20 Grizzly Bay 08/22/95 9 163 . 0.6 3.6 ND 9.5 1.0 0.7 7.2 3.9 11.0 ND ND 0.9 ND

BG20 Sacramento River 08/23/95 9 116 . 0.5 2.3 ND 3.6 0.7 0.5 8.6 3.1 4.3 ND ND 0.9 ND

BG30 San Joaquin River 08/23/95 9 116 . 0.5 2.8 ND 3.6 0.8 0.5 7.5 2.5 3.9 ND ND 0.7 ND

A–28


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

PC

B 1

70

PC

B 1

74

PC

B 1

77

PC

B 1

78

PC

B 1

80

PC

B 1

83

PC

B 1

87

PC

B 1

89

PC

B 1

94

PC

B 1

95

PC

B 1

98

PC

B 2

00

PC

B 2

03

PC

B 2

06

PC

B 2

07


BA10 Coyote Creek 02/07/95 7 1.3 3.7 3.9 . 2.9 1.5 2.6 ND . ND 0.8 . ND 1.9 ND

BA30 Dumbarton Bridge 02/06/95 7 2.8 3.9 4.1 . 16.0 2.3 3.8 ND . 0.5 1.1 . 2.7 1.8 ND

BA40 Redwood Creek 02/07/95 7 1.3 2.5 3.5 . 2.2 1.4 2.0 ND . 0.6 0.8 . 1.2 1.6 ND

BB70 Alameda 02/08/95 7 1.2 1.9 2.5 . 2.7 1.1 2.7 ND . ND 0.5 . 1.1 1.6 ND

BC10 Yerba Buena Island 02/08/95 7 0.6 1.9 2.1 . 1.6 0.9 2.6 ND . ND 0.5 . 1.9 1.7 ND

BC20 Golden Gate 02/09/95 7 0.6 1.9 1.2 . 1.7 1.6 3.1 ND . ND ND . 1.4 1.1 0.7

BC60 Red Rock 02/08/95 7 0.9 2.2 2.5 . 2.3 0.9 2.1 ND . ND ND . 1.2 1.4 ND

BD15 Petaluma River 02/13/95 7 1.4 2.3 3.8 . 2.2 2.0 2.5 ND . ND 1.0 . 1.1 1.6 ND

BD20 San Pablo Bay 02/13/95 7 2.1 11.0 20.0 . 2.7 1.9 2.5 ND . ND ND . ND 1.7 ND

BD30 Pinole Point 02/13/95 7 ND 3.4 2.1 . 2.2 1.0 1.0 ND . ND ND . ND 1.3 ND

BD40 Davis Point 02/13/95 7 ND 2.3 2.5 . 1.3 1.3 1.0 ND . ND 0.8 . ND 1.9 ND

BD50 Napa River 02/14/95 7 0.6 1.8 2.3 . 1.4 2.3 0.5 ND . ND 0.6 . 0.5 1.3 ND

BF20 Grizzly Bay 02/14/95 7 ND 1.8 1.5 . 1.3 1.2 0.8 ND . ND ND . 0.7 1.2 ND

BG20 Sacramento River 02/15/95 7 0.7 1.6 1.5 . 1.0 ND 0.7 ND . ND ND . 0.5 1.2 ND

BG30 San Joaquin River 02/15/95 7 ND 2.2 2.2 . 1.4 1.1 1.2 ND . ND ND . ND 1.7 0.9

BA10 Coyote Creek 04/24/95 8 5.0 12.0 9.8 . 9.6 3.9 11.0 ND . 0.7 ND . 3.1 1.6 ND

BA30 Dumbarton Bridge 04/24/95 8 3.4 8.4 8.1 . 6.5 3.1 9.2 ND . ND ND . 1.6 1.6 ND

BA40 Redwood Creek 04/24/95 8 1.8 5.2 3.9 . 3.7 1.5 4.6 ND . ND ND . 0.8 1.0 ND

BB70 Alameda 04/26/95 8 1.0 4.6 2.1 . 2.5 0.9 1.8 ND . ND ND . 1.0 1.0 ND

BC10 Yerba Buena Island 04/27/95 8 0.8 2.8 1.6 . 1.4 0.8 1.9 ND . ND ND . 0.5 1.0 ND

BC20 Golden Gate 04/26/95 8 ND 3.2 2.4 . 1.3 0.8 2.0 ND . ND ND . 0.8 1.4 ND

BC60 Red Rock 04/27/95 8 1.1 3.8 2.5 . 2.3 0.9 2.8 ND . ND ND . 0.8 1.0 ND

BD15 Petaluma River 04/19/95 8 1.6 4.7 2.9 . 3.2 1.0 3.1 ND . ND ND . 0.8 1.2 ND

BD20 San Pablo Bay 04/19/95 8 1.3 4.4 3.2 . 3.5 0.9 3.4 ND . ND ND . 0.6 0.9 ND

BD30 Pinole Point 04/20/95 8 1.5 4.7 2.8 . 3.4 0.9 3.4 ND . ND ND . 0.7 1.1 ND

BD40 Davis Point 04/19/95 8 1.2 5.0 2.9 . 4.6 1.1 3.7 ND . ND ND . 1.2 1.4 ND

BD50 Napa River 04/18/95 8 1.1 4.2 2.4 . 3.2 0.7 2.7 ND . ND ND . 0.8 1.2 ND

BF20 Grizzly Bay 04/20/95 8 0.8 3.2 1.7 . 1.6 ND 2.6 ND . ND ND . 0.7 ND ND

BG20 Sacramento River 04/18/95 8 6.2 9.6 7.7 . 10.0 1.7 5.9 ND . ND ND . 1.2 1.2 ND

BG30 San Joaquin River 04/18/95 8 ND 3.5 1.7 . 2.3 0.5 1.2 ND . ND 0.7 . 0.6 0.6 ND

BA10 Coyote Creek 08/14/95 9 4.7 5.6 4.3 1.1 18.0 5.3 11.0 ND 1.4 0.5 ND 5.3 1.0 0.7 ND

BA30 Dumbarton Bridge 08/15/95 9 1.3 1.8 1.7 0.5 3.1 1.8 4.5 ND ND ND ND 1.3 ND ND ND

BA40 Redwood Creek 08/15/95 9 1.2 1.9 1.5 0.6 2.5 2.1 3.4 ND ND ND ND 2.8 ND ND ND

BB70 Alameda 08/16/95 9 1.0 0.9 0.9 ND 1.7 0.8 2.2 1.2 ND ND ND 0.6 ND 0.7 ND

BC10 Yerba Buena Island 08/16/95 9 0.7 0.8 0.7 ND 1.3 0.7 1.6 ND ND ND ND 0.7 ND 0.7 ND

BC20 Golden Gate 08/16/95 9 ND 0.6 ND ND 0.9 0.5 0.9 ND ND ND ND ND ND 0.6 ND

BC60 Red Rock 08/17/95 9 0.6 0.7 0.7 ND 1.4 0.5 1.6 ND ND ND ND 0.6 0.1 0.6 ND

BD15 Petaluma River 08/21/95 9 0.7 0.8 0.9 ND 1.6 1.1 2.4 ND ND ND ND ND ND ND ND

BD20 San Pablo Bay 08/21/95 9 0.6 0.7 0.7 ND 1.2 0.9 1.6 ND ND ND ND 0.5 ND ND ND

BD30 Pinole Point 08/21/95 9 ND 0.6 0.5 ND 0.9 0.8 1.3 ND ND ND ND ND ND ND ND

BD40 Davis Point 08/21/95 9 0.7 0.8 0.7 ND 1.4 0.8 1.8 ND ND ND ND 0.6 ND ND ND

BD50 Napa River 08/22/95 9 0.6 0.8 0.6 ND 1.5 0.5 1.7 ND ND ND ND 0.8 ND ND ND


BF20 Grizzly Bay 08/22/95 9 0.9 1.3 1.1 ND 2.0 1.6 3.0 ND ND ND ND 0.6 ND 0.5 ND

BG20 Sacramento River 08/23/95 9 0.7 0.9 0.7 ND 1.8 0.8 1.9 ND ND ND ND 0.8 ND 0.5 ND

BG30 San Joaquin River 08/23/95 9 0.8 1.0 0.8 ND 1.5 0.7 2.2 ND ND ND ND ND ND 0.5 ND

Appendices

A–29

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of P

CB

s (S

FE

I)

PC

B 0

03/3

0

PC

B 0

08

PC

B 0

15

PC

B 0

18

PC

B 0

27

PC

B 0

28

PC

B 0

29

PC

B 0

31

PC

B 0

44

PC

B 0

49

PC

B 0

52

PC

B 0

60

PC

B 0

64

PC

B 0

66


BA10 Coyote Creek 02/07/95 7 1595 . 13.2 . 20.6 1.4 46.0 ND 47.0 27.0 31.0 55.0 ND . 40.2

BA30 Dumbarton Bridge 02/06/95 7 1696 . 17.8 . 46.3 8.5 192 ND 153 34.5 29 78 ND . 47

BA40 Redwood Creek 02/07/95 7 642 . 6.1 . 8.4 ND 25.4 ND 21.5 12.1 12.1 28.0 ND . 17.1

BB70 Alameda 02/08/95 7 245 . 2.8 . 6 ND 11.8 ND 9.2 5.7 8.8 8.3 ND . 6.5

BC10 Yerba Buena Island 02/08/95 7 396 . 19.0 . 15.0 ND 32.6 ND 33.6 13.6 23.9 14.2 ND . 7.0

BC20 Golden Gate 02/09/95 7 261 . 4 . 3.1 ND 25.8 0.7 18.4 5.4 10.5 1.6 ND . 8.5

BC60 Red Rock 02/08/95 7 212 . 6.3 . 4.2 ND 11.8 ND 11.5 9.2 6.1 12.4 ND . 7.3

BD15 Petaluma River 02/13/95 7 771 . 3.3 . 4.5 0.9 16.9 ND 18.9 7.7 5.6 19.4 ND . 24

BD20 San Pablo Bay 02/13/95 7 416 . 2.1 . 4.3 3.0 1.9 ND 2.2 3.4 9.0 19.9 ND . 7.2

BD30 Pinole Point 02/13/95 7 185 . 1.5 . 2.7 ND 8.1 ND 6.8 4.9 4.2 7.1 ND . 4.9

BD40 Davis Point 02/13/95 7 370 . 1.2 . 4.5 0.7 10.3 ND 10.8 6.1 5.4 8.3 ND . 12.3

BD50 Napa River 02/14/95 7 649 . 2.9 . 5.6 ND 13.7 ND 15.7 6 5.9 16.2 ND . 20

BF20 Grizzly Bay 02/14/95 7 168 . 3.1 . 2.8 ND 9.7 ND 9.5 4.2 3.9 5.0 ND . 4.5

BG20 Sacramento River 02/15/95 7 240 . 2.2 . 3 ND 9.9 ND 8.1 4.2 7 M ND . 8.6

BG30 San Joaquin River 02/15/95 7 163 . 1.9 . 2.2 ND 9.2 ND 8.2 4.1 3.6 14.4 ND . 4.5

BA10 Coyote Creek 04/24/95 8 6018 . 32.7 M 59.0 4.5 91.0 3.8 104.0 77.0 77.2 6.2 29.3 . 193.0

BA30 Dumbarton Bridge 04/24/95 8 4081 . 24.0 M 22.0 0.9 46.0 0.7 58.0 41.8 52.0 9.6 20.4 . 115.0

BA40 Redwood Creek 04/24/95 8 982 . 4.7 M 6.6 ND 17.6 ND 23.1 12.1 14.2 11.8 12.1 . 27.1

BB70 Alameda 04/26/95 8 493 . 1.3 M 3.3 ND 8.1 ND 8.5 7.0 5.9 16.9 7.1 . 13.2

BC10 Yerba Buena Island 04/27/95 8 338 . 4.6 M 7.8 ND 9.5 1.7 9.2 7.5 6.8 12.5 4.5 . 12.8

BC20 Golden Gate 04/26/95 8 200 . 1.6 M 4.4 ND 6.8 ND 7.7 4.4 4.1 15.6 ND . 8.0

BC60 Red Rock 04/27/95 8 257 . 2.6 M 3.3 ND 5.6 ND 6.9 4.2 5.5 2.9 2.5 . 11.2

BD15 Petaluma River 04/19/95 8 6974 . 28.5 M 22.1 3.8 75.7 6.1 96.0 76.7 94.0 146.0 69.1 . 175.8

BD20 San Pablo Bay 04/19/95 8 1361 . 6.5 M 8.4 0.5 16.8 1.3 21.3 17.2 22.9 32.5 15.1 . 39.2

BD30 Pinole Point 04/20/95 8 724 . 2.7 M 7.5 ND 12.3 0.6 14.5 11.7 12.1 56.4 6.6 . 24.9

BD40 Davis Point 04/19/95 8 1174 . 5.1 M 10.0 ND 18.5 0.7 22.4 17.5 21.3 19.3 14.4 . 47.0

BD50 Napa River 04/18/95 8 607 . 3.1 M 8.3 1.1 12.8 2.2 11.5 11.7 13.7 10.2 4.3 . 19.5

BF20 Grizzly Bay 04/20/95 8 562 . 2.4 M 2.1 ND 12.6 ND 12.9 9.9 11.5 8.6 3.3 . 20.4

BG20 Sacramento River 04/18/95 8 658 . 4.4 M 11.0 12.0 47.0 ND 65.4 14.0 10.4 18.0 7.6 . 19.5

BG30 San Joaquin River 04/18/95 8 0 . NA NA NA NA NA NA NA NA NA NA NA . NA

BA10 Coyote Creek 08/14/95 9 1239 ND 2.5 5.2 11.8 4.3 38.0 11.6 41.0 17.3 11.9 22.6 9.2 7.4 36.0

BA30 Dumbarton Bridge 08/15/95 9 1395 ND 8.3 5.4 16.2 ND 28.0 1.7 36.0 17.9 12.0 18.4 13.0 6.5 36.9

BA40 Redwood Creek 08/15/95 9 663 ND 3.3 ND 7.5 ND 13.8 0.5 23.5 9.4 5.3 M 7.4 3.2 37.0

BB70 Alameda 08/16/95 9 227 ND 2.2 ND 4.0 ND 7.1 1.2 12.4 4.7 3.1 5.3 2.5 1.5 7.3

BC10 Yerba Buena Island 08/16/95 9 231 ND 2.4 ND 4.9 ND 8.3 2.7 12.8 5.1 3.5 1.5 3.3 2.3 5.4

BC20 Golden Gate 08/16/95 9 83 ND 2.4 ND 1.8 ND 5.1 1.6 8.6 1.8 1.5 5.0 1.4 0.8 2.0

BC60 Red Rock 08/17/95 9 226 ND ND ND 5.9 ND 9.6 1.0 13.9 5.0 3.0 3.3 4.3 2.8 4.3

BD15 Petaluma River 08/21/95 9 798 ND 3.2 ND 6.8 ND 18.4 0.7 22.2 10.1 5.9 9.7 8.1 5.1 20.9

BD20 San Pablo Bay 08/21/95 9 278 ND 3.5 ND 5.5 ND 9.1 0.6 14.0 5.8 2.3 6.6 3.5 2.6 6.9

BD30 Pinole Point 08/21/95 9 268 ND 2.5 ND 5.1 ND 8.1 3.2 11.3 5.5 3.2 5.0 3.8 2.7 7.0

BD40 Davis Point 08/21/95 9 295 ND 2.4 ND 5.1 ND 10.2 1.0 14.2 5.4 2.3 4.2 5.2 2.6 8.4

BD50 Napa River 08/22/95 9 295 ND 2.2 ND 5.7 ND 10.2 2.2 13.3 6.2 2.7 5.7 5.3 3.2 7.2

Table 7. Total (particulate plus dissolved) PCB concentrations in water samples, 1995 (at 1meter depth). . = no data, ND = not detected, M = matrix interference, CE = coelution

BF20 Grizzly Bay 08/22/95 9 342 ND ND ND 10.2 ND 14.7 0.9 21.3 8.1 3.5 12.0 5.3 4.4 8.1

BG20 Sacramento River 08/23/95 9 160 ND 2.3 ND 7.1 ND 9.4 ND 14.0 4.0 2.0 6.3 2.2 1.8 5.2

BG30 San Joaquin River 08/23/95 9 182 ND 2.2 ND 5.4 ND 9.8 3.2 13.9 5.5 2.6 5.1 2.5 2.6 4.8

A–30


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

PC

B 0

70

PC

B 0

74

PC

B 0

84

PC

B 0

85

PC

B 0

87

PC

B 0

89

PC

B 0

95

PC

B 0

97

PC

B 0

99

PC

B 1

01

PC

B 1

03

PC

B 1

05

PC

B 1

10

PC

B 1

14

PC

B 1

18


BA10 Coyote Creek 02/07/95 7 45.0 17.2 . 17.9 32.0 . 60.0 21.9 35.5 82.0 ND 17.0 75.0 ND 70.0

BA30 Dumbarton Bridge 02/06/95 7 71 28.6 . 5.6 47 . 46 30.4 46 100 ND 15.7 31 ND 91

BA40 Redwood Creek 02/07/95 7 19.0 8.3 . 7.3 18.5 . 16.9 9.5 14.4 33.8 ND 4.2 29.9 ND 33.6

BB70 Alameda 02/08/95 7 8.5 3.5 . 2.4 7.6 . 8.2 3.7 6 14.4 ND 1.6 9.2 ND 10.7

BC10 Yerba Buena Island 02/08/95 7 18.6 8.1 . 5.1 16.5 . 8.6 4.8 7.2 13.4 ND 3.7 17.0 ND 16.2

BC20 Golden Gate 02/09/95 7 8.3 5.61 . 3 10.2 . 11.5 5.3 5.8 9.6 ND 1 15.3 ND 11.5

BC60 Red Rock 02/08/95 7 8.2 3.6 . 1.5 8.5 . 9.1 3.1 4.3 9.8 ND 1.5 7.3 ND 9.5

BD15 Petaluma River 02/13/95 7 23.5 9.4 . 20.8 16.2 . 31.8 10.4 23.1 42.2 ND 2.9 46.2 ND 46.2

BD20 San Pablo Bay 02/13/95 7 14.0 5.9 . M 13.2 . 16.7 9.2 7.1 18.2 ND 8.5 3.9 ND 26.6

BD30 Pinole Point 02/13/95 7 7.3 3.4 . 2.2 3.5 . 6.4 2.8 5 10.7 ND 1 8.1 ND 9.7

BD40 Davis Point 02/13/95 7 11.1 7.9 . 3.1 6.2 . 16.2 5.5 11.5 21.5 ND 1.4 21.8 ND 21.3

BD50 Napa River 02/14/95 7 19.5 8 . 19.6 15.6 . 25.8 5.6 18.2 34 ND 2.1 28.2 ND 37.5

BF20 Grizzly Bay 02/14/95 7 7.2 2.7 . 6.0 4.7 . 6.3 2.3 4.4 8.9 ND ND 7.3 ND 7.8

BG20 Sacramento River 02/15/95 7 8.8 2.6 . 7 5.2 . 13.8 4.41 7.1 17.1 ND 0.8 18.2 ND 17.3

BG30 San Joaquin River 02/15/95 7 6.6 2.4 . 4.6 3.8 . 6.2 2.1 4.1 8.9 ND ND 6.9 ND 6.9

BA10 Coyote Creek 04/24/95 8 141.0 55.9 . M 91.1 . 230.0 79.4 164.0 325.0 ND 3.9 328.0 ND 293.0

BA30 Dumbarton Bridge 04/24/95 8 87.9 40.7 . M 58.4 . 147.0 53.7 109.0 227.0 ND 3.4 230.0 ND 221.0

BA40 Redwood Creek 04/24/95 8 19.1 9.8 . M 14.9 . 41.0 15.2 24.7 54.0 ND 1.3 55.0 ND 45.4

BB70 Alameda 04/26/95 8 8.2 4.2 . M 10.8 . 23.3 9.0 12.0 26.9 ND ND 25.1 ND 18.5

BC10 Yerba Buena Island 04/27/95 8 8.0 4.8 . M 5.3 . 17.1 5.2 8.0 16.6 ND ND 18.7 ND 12.1

BC20 Golden Gate 04/26/95 8 5.8 3.2 . M 3.9 . 12.0 3.4 4.8 10.2 ND 0.6 10.3 ND 8.0

BC60 Red Rock 04/27/95 8 7.3 3.2 . M 4.5 . 14.5 3.3 6.9 12.2 ND ND 10.2 ND 10.7

BD15 Petaluma River 04/19/95 8 122.2 64.8 . M 93.2 . 260.0 90.5 184.1 385.6 2.9 3.4 426.7 ND 334.0

BD20 San Pablo Bay 04/19/95 8 29.0 11.8 . M 21.3 . 55.0 19.2 31.0 62.4 ND 0.6 78.3 ND 64.7

BD30 Pinole Point 04/20/95 8 16.4 8.7 . M 11.2 . 33.0 9.2 18.9 37.1 ND ND 38.9 ND 33.9

BD40 Davis Point 04/19/95 8 22.4 11.5 . M 20.7 . 53.0 16.1 33.3 53.5 ND 0.7 63.1 ND 56.2

BD50 Napa River 04/18/95 8 12.8 6.9 . M 9.5 . 30.0 8.1 15.0 26.6 ND ND 34.1 ND 24.3

BF20 Grizzly Bay 04/20/95 8 12.4 8.3 . M 7.9 . 23.8 3.7 9.2 25.0 ND 0.5 34.4 ND 26.9

BG20 Sacramento River 04/18/95 8 17.4 9.7 . M 12.6 . 23.5 10.4 9.4 41.8 ND 2.2 52.0 ND 41.3

BG30 San Joaquin River 04/18/95 8 NA NA . NA NA . NA NA NA NA NA NA NA NA NA

BA10 Coyote Creek 08/14/95 9 35.0 18.6 ND 6.2 12.9 5.1 39.0 17.4 27.7 44.0 ND 17.6 53.0 . 88.0

BA30 Dumbarton Bridge 08/15/95 9 33.5 16.1 ND 7.8 12.1 3.1 53.0 19.4 32.4 51.0 ND 20.0 58.0 . 96.0

BA40 Redwood Creek 08/15/95 9 14.4 7.9 ND 3.4 6.3 2.1 31.0 8.4 14.1 26.0 ND 9.9 28.2 . 50.0

BB70 Alameda 08/16/95 9 4.7 3.0 ND 0.9 2.9 1.0 16.2 2.8 5.0 9.3 ND 3.1 7.7 . 12.0

BC10 Yerba Buena Island 08/16/95 9 4.1 3.1 ND 1.5 3.2 1.3 9.5 3.5 5.8 10.5 ND 2.9 9.9 . 13.9

BC20 Golden Gate 08/16/95 9 4.2 1.3 ND ND 1.5 0.5 4.7 1.2 1.6 3.7 ND 0.7 2.6 . 5.0

BC60 Red Rock 08/17/95 9 5.4 3.8 ND 1.4 3.2 1.7 5.9 3.2 5.4 12.0 ND 3.1 10.0 . 16.2

BD15 Petaluma River 08/21/95 9 11.3 5.2 ND 3.7 7.6 4.3 28.1 13.3 20.0 34.9 ND 11.5 36.5 . 45.6

BD20 San Pablo Bay 08/21/95 9 4.9 3.2 ND 1.5 3.6 2.0 10.2 4.5 6.3 10.4 ND 3.3 13.6 . 16.8

BD30 Pinole Point 08/21/95 9 4.8 2.8 ND 0.9 3.6 1.9 13.0 4.2 6.8 13.4 ND 2.9 12.1 . 13.8

BD40 Davis Point 08/21/95 9 6.0 2.7 ND 1.6 3.0 2.1 18.8 4.2 7.1 13.6 ND 4.1 13.6 . 17.7

BD50 Napa River 08/22/95 9 5.6 3.4 ND 1.4 3.6 2.3 15.3 4.7 7.6 14.8 ND 3.8 13.8 . 16.3

Table 7. Total (particulate plus dissolved) PCB concentrations in water samples, 1995 (at 1meter depth; continued). . = no data, ND = not detected, M = matrix interference, CE = coelution

BF20 Grizzly Bay 08/22/95 9 8.2 3.0 0.8 1.9 4.9 2.7 15.6 5.1 6.4 16.2 ND 3.6 15.9 . 16.8

BG20 Sacramento River 08/23/95 9 4.1 2.1 ND 0.8 3.1 1.2 9.4 2.2 2.7 6.8 ND 1.3 7.1 . 8.1

BG30 San Joaquin River 08/23/95 9 4.6 2.5 ND 0.6 2.9 1.7 13.3 3.0 3.6 8.4 ND 1.5 7.9 . 8.5

Appendices

A–31

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of P

CB

s (S

FE

I)

PC

B 1

19

PC

B 1

28

PC

B 1

32

PC

B 1

37

PC

B 1

38

PC

B 1

41

PC

B 1

46

PC

B 1

49

PC

B 1

51

PC

B 1

53

PC

B 1

56

PC

B 1

57

PC

B 1

58

PC

B 1

67


BA10 Coyote Creek 02/07/95 7 1595 CE 18.4 29.5 3.5 116.0 . . 103.0 . 135.0 17.9 8.3 8.9 .

BA30 Dumbarton Bridge 02/06/95 7 1696 6 28.6 35 5 136 . . 86 . 120 4.3 2.1 17.1 .

BA40 Redwood Creek 02/07/95 7 642 CE 8.1 12.0 2.7 56.9 . . 46.0 . 60.0 7.2 2.6 6.1 .

BB70 Alameda 02/08/95 7 245 CE 3.3 4.3 2 18.9 . . 16.3 . 17.8 2.2 0.77 2.8 .

BC10 Yerba Buena Island 02/08/95 7 396 ND 4.2 4.5 2.0 20.2 . . 16.0 . 18.3 5.0 2.0 3.6 .

BC20 Golden Gate 02/09/95 7 261 ND 2.86 3.9 3.5 21.2 . . 12.2 . 17.3 2.2 0.7 2.01 .

BC60 Red Rock 02/08/95 7 212 0.5 2.6 3.6 0.5 12.2 . . 11.8 . 10.6 1.2 0.5 2.3 .

BD15 Petaluma River 02/13/95 7 771 CE 9.5 15.3 1.8 60 . . 51 . 74.8 4 4.69 4.1 .

BD20 San Pablo Bay 02/13/95 7 416 6.8 13.9 14.7 2.7 53.3 . . 30.7 . 43.6 6.2 1.7 4.9 .

BD30 Pinole Point 02/13/95 7 185 ND 2.39 4.1 0.6 13.4 . . 13.6 . 13.7 1.5 0.5 2.05 .

BD40 Davis Point 02/13/95 7 370 ND 3.6 6.0 1.7 30.4 . . 25.8 . 32.1 2.9 1.8 1.9 .

BD50 Napa River 02/14/95 7 649 ND 7.61 12.9 1.7 67.9 . . 42.7 . 60.1 9 3.3 3.6 .

BF20 Grizzly Bay 02/14/95 7 168 0.7 ND 3.5 ND 12.3 . . 9.9 . 8.3 ND ND 1.1 .

BG20 Sacramento River 02/15/95 7 240 1.1 1.1 4.7 0.8 20.1 . . 14.8 . 17.2 1 ND 1.4 .

BG30 San Joaquin River 02/15/95 7 163 ND 0.8 3.4 ND 10.6 . . 9.5 . 10.9 ND ND 0.5 .

BA10 Coyote Creek 04/24/95 8 6018 17.0 58.6 95.0 8.3 484.0 . . 378.0 121.1 541.0 45.6 10.0 54.3 .

BA30 Dumbarton Bridge 04/24/95 8 4081 7.1 45.8 63.7 6.4 349.0 . . 251.0 77.6 415.0 33.0 6.4 33.4 .

BA40 Redwood Creek 04/24/95 8 982 ND 10.7 15.1 1.5 79.0 . . 64.0 15.0 107.0 6.0 1.2 7.6 .

BB70 Alameda 04/26/95 8 493 ND 5.8 8.1 0.9 39.2 . . 34.7 8.4 53.7 1.5 0.6 4.0 .

BC10 Yerba Buena Island 04/27/95 8 338 ND 2.7 5.4 ND 23.4 . . 21.7 0.9 30.5 1.0 ND 2.9 .

BC20 Golden Gate 04/26/95 8 200 ND 1.3 3.6 ND 12.0 . . 12.4 ND 15.7 ND ND 1.1 .

BC60 Red Rock 04/27/95 8 257 ND 2.5 4.6 ND 21.0 . . 17.6 0.6 26.2 0.6 0.1 2.4 .

BD15 Petaluma River 04/19/95 8 6974 13.0 80.7 102.1 11.0 571.0 . . 398.4 140.0 679.1 64.0 24.0 45.1 .

BD20 San Pablo Bay 04/19/95 8 1361 2.3 12.8 20.9 1.9 101.7 . . 83.8 24.0 131.0 12.0 2.9 10.2 .

BD30 Pinole Point 04/20/95 8 724 1.3 5.8 10.7 0.8 45.6 . . 43.7 9.8 60.8 3.1 1.8 6.1 .

BD40 Davis Point 04/19/95 8 1174 2.3 11.0 19.2 1.5 91.3 . . 74.3 21.5 109.0 6.2 1.3 8.3 .

BD50 Napa River 04/18/95 8 607 ND 6.3 9.6 0.7 41.5 . . 39.2 10.8 53.8 2.1 0.6 4.8 .

BF20 Grizzly Bay 04/20/95 8 562 ND 6.3 11.6 ND 43.6 . . 33.3 10.7 53.3 3.0 0.8 7.7 .

BG20 Sacramento River 04/18/95 8 658 0.9 9.1 9.3 1.3 45.7 . . 29.3 2.1 42.5 4.9 3.3 6.4 .

BG30 San Joaquin River 04/18/95 8 0 NA NA NA NA NA . . NA NA NA NA NA NA .

BA10 Coyote Creek 08/14/95 9 1239 . 9.9 28.9 ND 110.0 9.0 12.5 86.0 20.4 106.0 7.2 1.8 8.9 4.4

BA30 Dumbarton Bridge 08/15/95 9 1395 . 14.9 34.1 ND 136.0 8.8 17.6 88.0 24.4 128.0 9.1 3.2 15.7 4.4

BA40 Redwood Creek 08/15/95 9 663 . 4.8 14.8 ND 66.0 3.7 7.0 40.9 12.0 62.0 2.3 1.1 4.4 2.0

BB70 Alameda 08/16/95 9 227 . 1.3 5.0 ND 25.0 1.5 1.7 15.9 4.1 22.0 ND ND 2.1 ND

BC10 Yerba Buena Island 08/16/95 9 231 . 0.8 5.8 ND 18.8 1.9 1.9 14.8 5.0 17.8 0.9 ND 2.1 ND

BC20 Golden Gate 08/16/95 9 83 . ND 1.5 ND 3.5 ND ND 8.0 1.5 3.3 ND ND ND ND

BC60 Red Rock 08/17/95 9 226 . 1.1 5.6 ND 17.7 1.9 1.8 16.0 4.4 18.5 ND ND 2.1 ND

BD15 Petaluma River 08/21/95 9 798 . 7.8 21.8 ND 78.3 4.5 9.6 53.8 15.4 79.0 4.4 0.9 6.8 2.5

BD20 San Pablo Bay 08/21/95 9 278 . 1.6 7.5 ND 23.6 1.8 2.2 19.0 6.4 23.4 0.5 ND 4.2 0.7

BD30 Pinole Point 08/21/95 9 268 . 1.4 6.6 ND 22.1 1.9 1.8 18.9 5.7 24.7 0.6 ND 1.9 0.6

BD40 Davis Point 08/21/95 9 295 . 1.7 7.1 ND 24.3 2.2 2.3 20.5 5.0 24.7 ND ND 2.6 0.6

BD50 Napa River 08/22/95 9 295 . 1.8 7.2 ND 25.9 2.1 2.2 20.9 5.2 24.6 ND ND 3.1 ND

Table 7. Total (particulate plus dissolved) PCB concentrations in water samples, 1995 (continued).. = no data, ND = not detected, M = matrix interference, CE = coelution

BF20 Grizzly Bay 08/22/95 9 342 . 2.1 8.5 ND 29.5 2.1 2.2 19.2 7.4 29.0 ND ND 2.6 ND

BG20 Sacramento River 08/23/95 9 160 . 1.0 4.0 ND 6.3 0.7 1.0 12.6 4.6 6.8 ND ND 1.9 ND

BG30 San Joaquin River 08/23/95 9 182 . 1.1 5.1 ND 7.3 1.3 1.1 14.2 4.6 7.7 ND ND 1.6 ND

A–32


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

PC

B 1

70

PC

B 1

74

PC

B 1

77

PC

B 1

78

PC

B 1

80

PC

B 1

83

PC

B 1

87

PC

B 1

89

PC

B 1

94

PC

B 1

95

PC

B 1

98

PC

B 2

00

PC

B 2

03

PC

B 2

06

PC

B 2

07


BA10 Coyote Creek 02/07/95 7 30.3 99.7 75.9 . 68.9 20.5 59.6 1.9 . 3.3 1.9 . 25.0 11.2 1.4

BA30 Dumbarton Bridge 02/06/95 7 6.2 24.9 24.1 . 28 6.3 25.8 ND . 2.3 4.7 . 8.5 5.6 1.5

BA40 Redwood Creek 02/07/95 7 7.8 23.5 20.5 . 19.2 5.0 21.0 ND . 3.5 1.7 . 6.4 4.5 1.0

BB70 Alameda 02/08/95 7 3.8 5.2 8 . 5.7 2.5 5.7 ND . 0.69 1.9 . 3.5 4.4 ND

BC10 Yerba Buena Island 02/08/95 7 2.3 4.8 6.5 . 9.1 2.2 5.1 ND . 0.7 1.7 . 4.4 4.9 0.6

BC20 Golden Gate 02/09/95 7 1.43 3.9 4 . 5 2.33 5.5 ND . ND 0.71 . 2.4 3.4 1.3

BC60 Red Rock 02/08/95 7 2.6 4.6 5.2 . 4.3 2.1 4.3 ND . 0.8 1.1 . 3.3 3.0 ND

BD15 Petaluma River 02/13/95 7 11.4 33.3 36.8 . 30.2 6.2 27.5 1.1 . 1.9 5.05 . 8.1 8.8 1.6

BD20 San Pablo Bay 02/13/95 7 3.6 13.6 24.3 . 4.8 3.1 4.8 ND . 0.5 1.1 . 1.9 3.2 ND

BD30 Pinole Point 02/13/95 7 1.1 6.6 7.6 . 4.8 2.4 3.6 ND . 0.7 1.3 . 2.3 2.9 ND

BD40 Davis Point 02/13/95 7 4.2 14.3 12.5 . 15.3 4.4 10.5 0.7 . 1.4 3.2 . 4.3 4.6 1.1

BD50 Napa River 02/14/95 7 9.46 27.8 29.3 . 24.4 6.1 22.5 1.2 . 1.9 4.31 . 6.8 5.5 1

BF20 Grizzly Bay 02/14/95 7 1.5 5.2 7.5 . 3.7 2.8 3.0 ND . 0.9 1.3 . 3.2 3.1 ND

BG20 Sacramento River 02/15/95 7 2.4 5.2 7.3 . 3.6 4.4 3.1 ND . ND 1.2 . 2.7 2.8 ND

BG30 San Joaquin River 02/15/95 7 1.1 4.5 5.7 . 3.0 2.2 2.6 ND . 1.0 0.9 . 1.7 3.1 0.9

BA10 Coyote Creek 04/24/95 8 165.0 362.0 319.8 . 369.6 77.9 261.0 5.5 . 29.7 6.3 . 143.1 67.6 8.3

BA30 Dumbarton Bridge 04/24/95 8 113.4 218.4 228.1 . 246.5 55.1 199.2 3.8 . 19.0 3.7 . 88.6 41.6 6.7

BA40 Redwood Creek 04/24/95 8 20.8 51.2 50.9 . 50.7 12.5 43.6 ND . 2.6 0.5 . 20.8 9.8 1.4

BB70 Alameda 04/26/95 8 12.0 27.6 23.1 . 21.5 7.2 19.8 ND . 1.1 0.5 . 7.8 4.8 1.0

BC10 Yerba Buena Island 04/27/95 8 9.3 16.8 13.6 . 13.4 4.1 11.9 ND . 0.7 ND . 2.6 4.4 ND

BC20 Golden Gate 04/26/95 8 3.1 9.3 6.9 . 6.4 2.0 6.1 ND . 0.1 0.2 . 2.0 3.4 ND

BC60 Red Rock 04/27/95 8 4.2 14.8 11.3 . 11.9 3.6 11.0 ND . 0.6 ND . 2.6 3.8 ND

BD15 Petaluma River 04/19/95 8 181.6 354.7 372.9 . 413.2 99.0 313.1 7.9 . 34.0 9.3 . 190.8 93.2 15.0

BD20 San Pablo Bay 04/19/95 8 39.3 74.4 70.2 . 79.5 18.9 55.4 0.5 . 4.7 2.4 . 35.6 18.9 2.5

BD30 Pinole Point 04/20/95 8 15.5 33.7 31.8 . 32.4 8.4 25.4 ND . 2.1 1.2 . 16.7 9.3 1.2

BD40 Davis Point 04/19/95 8 32.2 63.0 57.9 . 61.6 15.1 45.7 0.6 . 3.8 2.3 . 23.2 14.4 2.1

BD50 Napa River 04/18/95 8 14.1 35.2 29.4 . 32.2 7.2 22.7 ND . 2.0 1.3 . 17.8 8.8 1.2

BF20 Grizzly Bay 04/20/95 8 12.8 28.2 26.7 . 27.6 6.6 21.6 ND . 2.2 1.8 . 18.7 7.9 1.8

BG20 Sacramento River 04/18/95 8 9.0 16.2 12.7 . 15.8 2.7 8.8 ND . ND ND . 3.9 3.5 0.6

BG30 San Joaquin River 04/18/95 8 NA NA NA . NA NA NA NA . NA NA . NA NA NA

BA10 Coyote Creek 08/14/95 9 28.7 19.6 20.3 4.5 67.0 18.3 43.0 1.5 15.4 3.1 0.5 19.3 3.8 4.5 1.2

BA30 Dumbarton Bridge 08/15/95 9 37.3 19.8 24.7 6.6 72.1 19.8 60.5 2.7 22.0 3.8 0.5 21.3 3.9 11.0 1.7

BA40 Redwood Creek 08/15/95 9 14.2 9.6 9.5 3.1 31.5 9.5 24.4 0.9 8.1 1.4 ND 12.3 1.7 2.6 0.6

BB70 Alameda 08/16/95 9 3.3 2.3 2.6 0.6 4.8 2.4 5.6 1.2 1.3 ND ND 2.4 ND 1.6 ND

BC10 Yerba Buena Island 08/16/95 9 4.4 3.1 3.5 0.6 11.3 2.8 6.4 ND 2.0 0.5 ND 3.0 0.6 2.0 ND

BC20 Golden Gate 08/16/95 9 ND 1.1 ND ND 1.6 0.5 1.9 ND ND ND ND ND ND 1.2 ND

BC60 Red Rock 08/17/95 9 4.0 3.1 3.4 0.6 5.8 2.6 6.4 ND 1.9 ND ND 2.1 0.6 2.0 ND

BD15 Petaluma River 08/21/95 9 21.7 11.8 14.9 3.0 44.6 12.1 33.4 1.1 12.0 2.5 ND 10.0 2.6 8.8 1.3

BD20 San Pablo Bay 08/21/95 9 4.8 4.2 4.5 0.9 13.2 3.6 8.9 ND 1.4 ND ND 2.8 0.7 1.6 ND

BD30 Pinole Point 08/21/95 9 3.7 4.1 3.9 0.9 11.9 3.7 9.2 ND 2.1 ND ND 2.3 0.7 1.2 ND

BD40 Davis Point 08/21/95 9 5.2 4.5 4.2 0.9 13.4 3.6 9.0 ND 2.5 ND ND 2.8 0.9 1.3 ND

BD50 Napa River 08/22/95 9 4.5 4.1 4.1 0.8 12.5 3.2 8.6 ND 2.4 0.6 ND 2.7 0.7 1.5 ND

Table 7. Total (particulate plus dissolved) PCB concentrations in water samples, 1995 (continued).. = no data, ND = not detected, M = matrix interference, CE = coelution

BF20 Grizzly Bay 08/22/95 9 5.1 4.4 4.6 0.8 13.0 3.9 9.4 ND 2.5 0.5 ND 2.9 0.8 2.1 ND

BG20 Sacramento River 08/23/95 9 2.1 1.9 1.6 ND 3.6 1.6 3.8 ND 0.8 ND ND 1.5 ND 1.4 ND

BG30 San Joaquin River 08/23/95 9 2.5 2.9 2.5 ND 3.6 1.6 5.1 ND 0.9 ND ND 1.0 ND 1.3 ND

Appendices

A–33

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of D

DT

s (S

FE

I)

o,p'

-DD

D

o,p'

-DD

E

o,p'

-DD

T

p,p'

-DD

D

p,p'

-DD

E

p,p'

-DD

T

Sum

of C

hlor

dane

s (S

FE

I)

Alp

ha-C

hlor

dane

Gam

ma-

Chl

orda

ne

cis-

Non

achl

or

tran

s-N

onac

hlor

Hep

tach

lor

Hep

tach

lor E

poxi

de

Oxy

chlo

rdan

e


BA10 Coyote Creek 02/07/95 7 353 38 7 ND 180 89 39 418 140 120 18 87 ND 42 11

BA30 Dumbarton Bridge 02/06/95 7 137 5 6 ND 61 59 7 128 31 62 3 32 ND ND ND

BA40 Redwood Creek 02/07/95 7 141 11 7 ND 84 39 ND 204 57 49 9 44 ND 41 4

BB70 Alameda 02/08/95 7 167 17 4 ND 82 41 23 161 35 26 6 13 ND 79 3

BC10 Yerba Buena Island 02/08/95 7 64 2 3 ND 12 48 ND 143 15 21 5 18 ND 83 2

BC20 Golden Gate 02/09/95 7 51 1 2 ND 14 33 ND 178 9 10 3 16 ND 140 ND

BC60 Red Rock 02/08/95 7 170 24 3 ND 80 63 ND 145 26 25 6 16 ND 70 2

BD15 Petaluma River 02/13/95 7 261 30 5 ND 140 66 20 138 39 29 7 24 ND 39 ND

BD20 San Pablo Bay 02/13/95 7 76 ND 4 ND 14 58 ND 155 19 17 4 13 ND 100 2

BD30 Pinole Point 02/13/95 7 139 13 1 ND 80 45 ND 61 21 18 5 17 ND ND ND

BD40 Davis Point 02/13/95 7 157 15 5 ND 86 51 ND 82 20 21 5 21 ND 11 4

BD50 Napa River 02/14/95 7 274 15 7 ND 150 71 31 98 30 24 5 22 ND 17 ND

BF20 Grizzly Bay 02/14/95 7 184 4 4 ND 92 76 8 228 20 14 3 11 ND 180 ND

BG20 Sacramento River 02/15/95 7 130 8 1 ND 33 82 6 68 14 11 3 10 ND 30 ND

BG30 San Joaquin River 02/15/95 7 208 ND 6 ND 66 120 16 246 26 27 4 17 ND 170 3

BA10 Coyote Creek 04/24/95 8 328 35 4 ND 130 120 39 456 100 93 23 63 18 146 13

BA30 Dumbarton Bridge 04/24/95 8 300 46 2 2 160 68 22 233 42 51 16 40 9 62 13


BB70 Alameda 04/26/95 8 141 5 ND 1 96 23 16 75 17 17 7 12 ND 22 ND

BC10 Yerba Buena Island 04/27/95 8 172 23 2 2 100 38 8 78 18 18 9 17 ND 12 4

BC20 Golden Gate 04/26/95 8 85 12 3 2 31 28 9 47 9 10 6 10 ND 9 3

BC60 Red Rock 04/27/95 8 105 10 1 1 60 31 2 33 7 6 4 7 ND 9 ND

BD15 Petaluma River 04/19/95 8 242 13 8 3 130 63 25 177 35 32 7 18 ND 80 5

BD20 San Pablo Bay 04/19/95 8 253 24 4 3 150 57 16 182 38 40 13 26 ND 61 4

BD30 Pinole Point 04/20/95 8 329 7 6 4 180 90 43 243 44 47 15 25 ND 107 5

BD40 Davis Point 04/19/95 8 287 11 3 4 140 90 40 153 39 42 10 25 ND 33 3

BD50 Napa River 04/18/95 8 553 37 7 6 360 100 44 145 36 40 9 33 ND 24 3

BF20 Grizzly Bay 04/20/95 8 248 9 9 2 120 94 14 119 23 17 8 16 ND 56 ND

BG20 Sacramento River 04/18/95 8 277 9 7 1 110 138 11 42 6 10 3 11 ND 12 ND

BG30 San Joaquin River 04/18/95 8 433 4 10 4 210 190 15 109 25 31 6 23 ND 23 ND


BA30 Dumbarton Bridge 08/15/95 9 157 25 4 ND 85 35 8 122 39 32 12 19 ND 18 2

BA40 Redwood Creek 08/15/95 9 123 19 1 ND 70 26 8 106 32 32 10 17 ND 13 3

BB70 Alameda 08/16/95 9 86 5 2 1 46 18 14 40 14 11 5 8 ND ND 2

BC10 Yerba Buena Island 08/16/95 9 89 14 ND 2 48 12 13 54 14 11 3 10 2 11 3

BC20 Golden Gate 08/16/95 9 7 ND ND ND ND 3 5 21 5 5 ND 4 4 3 ND

BC60 Red Rock 08/17/95 9 99 9 1 ND 63 20 5 50 14 12 4 14 ND 4 2

BD15 Petaluma River 08/21/95 9 178 29 2 ND 110 29 8 67 21 16 7 13 ND 8 2



BD40 Davis Point 08/21/95 9 230 35 2 1 150 28 15 121 34 35 10 20 ND 18 4

BD50 Napa River 08/22/95 9 176 26 2 1 110 31 7 80 24 18 8 18 ND 9 3

Table 8. Dissolved pesticide concentrations in water samples, 1995 (at 1meter depth). ND = not detected, NS = not sampled

BF20 Grizzly Bay 08/22/95 9 246 36 4 2 140 49 15 101 30 23 10 23 2 10 3

BG20 Sacramento River 08/23/95 9 278 35 5 3 96 130 9 106 27 25 6 28 2 18 ND

BG30 San Joaquin River 08/23/95 9 249 36 4 1 90 109 9 149 45 40 10 36 4 11 4

A–34


Table 8. Dissolved pesticide concentrations in water samples, 1995 (at 1 meter depth; continued).ND = not detected, NS = not sampled

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Die

ldrin

End

rin

Sum

of H

CH

s (S

FE

I)

Alp

ha-H

CH

Bet

a-H

CH

Del

ta-H

CH

Gam

ma-

HC

H

Hex

achl

orob

enze

ne

Mire

x

Dac

thal

Dia

zino

n

pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L pg/L

BA10 Coyote Creek 02/07/95 7 ND ND 1874 250 180 44 1400 12 ND 1100 7700

BA30 Dumbarton Bridge 02/06/95 7 3 120 1699 590 230 9 870 22 ND 1700 8700

BA40 Redwood Creek 02/07/95 7 7 28 1265 400 150 15 700 11 ND 1400 5900

BB70 Alameda 02/08/95 7 ND ND 780 290 130 ND 360 10 ND 720 7200

BC10 Yerba Buena Island 02/08/95 7 ND 7 540 190 86 34 230 16 ND 640 8100

BC20 Golden Gate 02/09/95 7 ND 7 773 340 150 3 280 10 ND 710 5300

BC60 Red Rock 02/08/95 7 15 ND 104 22 63 ND 19 10 ND 990 5400

BD15 Petaluma River 02/13/95 7 18 ND 886 310 100 46 430 13 ND 1300 11000

BD20 San Pablo Bay 02/13/95 7 10 5 483 210 150 3 120 ND ND 620 7100

BD30 Pinole Point 02/13/95 7 6 8 622 240 100 2 280 8 ND 470 5900

BD40 Davis Point 02/13/95 7 ND 2 120 20 67 11 22 13 ND 240 1900

BD50 Napa River 02/14/95 7 4 8 139 34 51 3 51 12 ND 580 5700

BF20 Grizzly Bay 02/14/95 7 ND 4 117 M 72 21 24 9 ND 300 7100

BG20 Sacramento River 02/15/95 7 28 ND 39 7 3 8 21 7 ND 660 7800

BG30 San Joaquin River 02/15/95 7 ND ND 29 6 16 ND 7 16 ND 1200 7600

BA10 Coyote Creek 04/24/95 8 ND ND 430 75 170 65 120 20 ND 430 5800

BA30 Dumbarton Bridge 04/24/95 8 87 ND 1374 440 140 14 780 12 ND 710 7300

BA40 Redwood Creek 04/24/95 8 66 ND 929 350 110 9 460 7 ND 530 3400

BB70 Alameda 04/26/95 8 26 ND 388 140 140 8 100 28 ND 200 2000

BC10 Yerba Buena Island 04/27/95 8 ND ND 757 370 150 7 230 ND ND 290 2400

BC20 Golden Gate 04/26/95 8 ND ND 930 500 210 ND 220 12 ND 85 840

BC60 Red Rock 04/27/95 8 ND ND 249 110 78 ND 61 10 ND 120 1400


BD20 San Pablo Bay 04/19/95 8 16 ND 723 350 74 9 290 16 ND 340 4300

BD30 Pinole Point 04/20/95 8 41 ND 618 250 62 6 300 19 ND 870 4100

BD40 Davis Point 04/19/95 8 ND ND 683 300 74 9 300 20 ND 440 3900

BD50 Napa River 04/18/95 8 5 ND 575 190 53 22 310 18 ND 490 5000

BF20 Grizzly Bay 04/20/95 8 ND ND 164 25 26 58 55 15 ND 230 2700

BG20 Sacramento River 04/18/95 8 3 ND 100 29 15 21 35 25 ND 51 3900

BG30 San Joaquin River 04/18/95 8 ND ND 183 59 63 ND 61 27 ND 250 4600

BA10 Coyote Creek 08/14/95 9 140 ND 946 220 110 56 560 7 ND 130 2900

BA30 Dumbarton Bridge 08/15/95 9 77 ND 715 180 120 45 370 2 ND 82 2200

BA40 Redwood Creek 08/15/95 9 98 ND 574 280 140 4 150 2 ND 80 1900

BB70 Alameda 08/16/95 9 49 4 632 290 140 22 180 3 ND 38 900

BC10 Yerba Buena Island 08/16/95 9 48 2 634 310 160 4 160 2 ND 36 460

BC20 Golden Gate 08/16/95 9 5 2 730 420 210 ND 100 3 ND 11 ND

BC60 Red Rock 08/17/95 9 67 ND 604 320 130 4 150 3 ND 54 560


BD20 San Pablo Bay 08/21/95 9 60 ND 652 310 120 22 200 3 ND 82 830

BD30 Pinole Point 08/21/95 9 42 ND 593 280 110 23 180 ND ND 84 730

BD40 Davis Point 08/21/95 9 104 ND 871 370 150 21 330 2 ND 130 1900

BD50 Napa River 08/22/95 9 39 ND 486 220 76 20 170 ND ND 100 320

End

osul

fan

I

End

osul

fan

II

End

osul

fan

Sul

fate

Oxa

diaz

on

Chl

orpy

rifos

pg/L pg/L pg/L pg/L pg/L

ND ND ND 3100 610

ND ND ND 14000 180

ND ND ND 400 450

ND ND ND 91 280

ND ND ND 120 130

ND ND ND 110 93

ND ND ND 120 120

ND ND ND 210 210

ND ND ND 160 120

ND ND ND 83 120

ND ND ND 99 44

ND ND ND 96 100

ND ND ND 110 67

ND ND ND 260 53

ND ND ND 130 170

ND ND ND ND 290

ND ND ND ND 110

ND ND ND ND 120

ND ND ND ND 50

ND ND ND ND 120

ND ND ND ND 14

ND ND ND ND 11

ND ND ND ND 180

ND ND ND ND 260

ND ND ND ND 300

ND ND ND 30 380

ND ND ND 4 380

ND ND ND 20 110

ND ND ND 26 57

ND ND ND 37 240

ND ND ND 11 2

ND ND ND ND 1

ND ND ND 8 2

ND ND ND ND 2

ND ND ND 9 4

ND ND ND 3 10

ND ND ND ND 6

ND ND ND 7 1

ND ND ND 3 7

ND ND ND ND 2

ND ND ND 3 13

ND ND ND ND 14

BF20 Grizzly Bay 08/22/95 9 129 ND 610 220 66 4 320 4 ND 180 1800 ND ND ND 12 29

BG20 Sacramento River 08/23/95 9 162 ND 27 ND 14 4 10 3 ND 200 1500 ND ND ND 7 18

BG30 San Joaquin River 08/23/95 9 72 ND 47 5 22 4 15 14 ND 280 1900 ND ND ND 8 19

Appendices

A–35

Table 9. Total (particulate plus dissolved) pesticide concentrations in water samples,1995 (at 1 meter depth). ND = not detected, NS = not sampled.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of D

DT

s (S

FE

I)

o,p'

-DD

D

o,p'

-DD

E

o,p'

-DD

T

p,p'

-DD

D

p,p'

-DD

E

p,p'

-DD

T

Sum

of C

hlor

dane

s (S

FE

I)

Alp

ha-C

hlor

dane

Gam

ma-

Chl

orda

ne

cis-

Non

achl

or

tran

s-N

onac

hlor

Hep

tach

lor

Hep

tach

lor E

poxi

de

Oxy

chlo

rdan

e



BA30 Dumbarton Bridge 02/06/95 7 327 14 9 ND 120 145 39 213 55 83 13 62 ND ND ND


BB70 Alameda 02/08/95 7 250 21 7 ND 99 83 40 177 40 30 7 18 ND 79 3

BC10 Yerba Buena Island 02/08/95 7 106 2 4 ND 12 88 ND 165 18 24 5 22 ND 94 2

BC20 Golden Gate 02/09/95 7 79 1 4 ND 14 60 ND 185 12 13 3 18 ND 140 ND

BC60 Red Rock 02/08/95 7 309 28 7 ND 111 163 ND 201 32 31 7 23 ND 105 2

BD15 Petaluma River 02/13/95 7 1370 92 22 ND 570 406 280 340 74 62 23 57 ND 124 ND

BD20 San Pablo Bay 02/13/95 7 237 7 10 ND 40 139 42 193 24 23 5 17 ND 121 2

BD30 Pinole Point 02/13/95 7 322 20 3 ND 116 145 38 79 26 22 8 23 ND ND ND

BD40 Davis Point 02/13/95 7 885 32 26 ND 216 431 180 187 33 34 10 38 ND 68 4

BD50 Napa River 02/14/95 7 1018 53 23 ND 310 401 231 260 51 45 13 49 ND 102 ND

BF20 Grizzly Bay 02/14/95 7 491 7 24 ND 100 346 13 241 24 20 3 13 ND 182 ND

BG20 Sacramento River 02/15/95 7 435 8 16 ND 53 352 6 106 18 16 5 13 ND 54 ND

BG30 San Joaquin River 02/15/95 7 366 ND 14 ND 66 270 16 254 28 30 4 19 ND 170 3

BA10 Coyote Creek 04/24/95 8 3058 255 69 ND 1230 1434 70 1235 320 313 118 264 18 177 25


BA40 Redwood Creek 04/24/95 8 400 43 3 1 210 141 2 185 34 37 17 41 ND 47 10

BB70 Alameda 04/26/95 8 395 20 7 2 177 143 46 136 30 31 14 32 ND 30 ND

BC10 Yerba Buena Island 04/27/95 8 376 38 5 4 170 151 8 110 25 27 14 24 ND 16 4

BC20 Golden Gate 04/26/95 8 160 19 8 2 54 61 17 53 11 13 6 11 ND 9 3

BC60 Red Rock 04/27/95 8 199 12 8 1 64 112 2 59 13 14 8 11 ND 13 ND

BD15 Petaluma River 04/19/95 8 6828 193 155 7 2630 3178 665 781 195 192 86 184 2 109 14



BD40 Davis Point 04/19/95 8 2266 121 59 9 810 1190 77 331 88 92 34 73 ND 40 3

BD50 Napa River 04/18/95 8 1401 40 55 8 392 842 64 213 50 61 18 53 ND 28 3

BF20 Grizzly Bay 04/20/95 8 1754 13 94 4 157 1455 31 196 47 40 16 31 ND 62 ND

BG20 Sacramento River 04/18/95 8 728 11 29 1 127 548 11 83 19 23 3 26 ND 12 ND

BG30 San Joaquin River 04/18/95 8 NS NS NS NS NS NS NS 0 NS NS NS NS NS NS NS

BA10 Coyote Creek 08/14/95 9 520 61 12 4 210 195 39 222 64 61 27 46 ND 21 3

BA30 Dumbarton Bridge 08/15/95 9 601 62 19 3 255 215 47 213 64 57 28 41 ND 21 2

BA40 Redwood Creek 08/15/95 9 268 29 8 ND 128 82 22 134 39 42 14 24 ND 13 3

BB70 Alameda 08/16/95 9 117 5 2 1 56 27 25 43 14 11 5 8 ND 3 2

BC10 Yerba Buena Island 08/16/95 9 151 16 4 2 68 32 29 65 17 14 5 12 2 11 3

BC20 Golden Gate 08/16/95 9 30 ND 2 ND 9 11 8 32 8 8 ND 6 4 5 ND

BC60 Red Rock 08/17/95 9 214 11 4 ND 108 71 19 64 18 16 5 18 ND 4 2

BD15 Petaluma River 08/21/95 9 723 68 10 2 310 279 55 118 33 30 15 26 ND 12 2



BD40 Davis Point 08/21/95 9 444 49 5 1 217 124 48 146 40 43 14 26 ND 18 4

BD50 Napa River 08/22/95 9 375 40 5 2 179 122 27 106 31 25 11 25 ND 11 3

Die

ldrin

End

rin

pg/L pg/L

ND ND

3 120

10 28

ND ND

ND 9

ND 7

17 ND

23 ND

10 5

6 8

3 2

10 8

ND 4

30 ND

ND ND

20 ND

94 ND

71 ND

26 ND

ND ND

3 ND

ND ND

45 ND

38 ND

45 ND

4 ND

10 ND

ND ND

3 ND

NS NS

155 ND

97 ND

103 ND

51 4

53 2

20 5

73 ND

61 ND

67 ND

51 ND

106 ND

46 ND

BF20 Grizzly Bay 08/22/95 9 180 NS 8 3 NS 169 NS 0 NS NS NS NS NS NS NS 135 ND

BG20 Sacramento River 08/23/95 9 470 35 15 3 99 310 9 116 30 28 6 32 2 18 ND 169 ND

BG30 San Joaquin River 08/23/95 9 399 45 7 1 108 229 9 165 49 43 10 40 4 15 4 75 ND

A–36


Table 9. Total (particulate plus dissolved) pesticide concentrations in water samples,1995 (at 1 meter depth; continued). ND = not detected, NS = not sampled.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of H

CH

s (S

FE

I)

Alp

ha-H

CH

Bet

a-H

CH

Del

ta-H

CH

Gam

ma-

HC

H

Hex

achl

orob

enze

ne

Mire

x

Dac

thal

Dia

zino

n


BA10 Coyote Creek 02/07/95 7 1906 253 184 49 1419 19 ND 1135 7700

BA30 Dumbarton Bridge 02/06/95 7 1726 597 244 9 875 25 ND 1700 8700

BA40 Redwood Creek 02/07/95 7 1275 403 153 15 704 14 ND 1418 5900

BB70 Alameda 02/08/95 7 785 290 132 ND 363 10 ND 739 7200

BC10 Yerba Buena Island 02/08/95 7 540 190 86 34 230 16 ND 661 8100

BC20 Golden Gate 02/09/95 7 773 340 150 3 280 10 ND 725 5300

BC60 Red Rock 02/08/95 7 114 22 68 2 23 14 ND 1020 5400

BD15 Petaluma River 02/13/95 7 916 316 116 46 438 36 ND 1388 11150

BD20 San Pablo Bay 02/13/95 7 486 213 150 3 120 3 ND 638 7100

BD30 Pinole Point 02/13/95 7 631 243 103 2 282 15 ND 491 5900

BD40 Davis Point 02/13/95 7 135 24 73 11 26 30 ND 306 2100

BD50 Napa River 02/14/95 7 151 37 55 3 56 31 ND 653 5870

BF20 Grizzly Bay 02/14/95 7 124 5 74 21 24 16 ND 359 7100

BG20 Sacramento River 02/15/95 7 51 14 8 8 21 11 ND 770 7800

BG30 San Joaquin River 02/15/95 7 78 28 35 ND 15 27 ND 1212 7600

BA10 Coyote Creek 04/24/95 8 491 80 185 68 158 63 ND 491 7000



BB70 Alameda 04/26/95 8 399 146 140 8 105 31 ND 200 2000


BC20 Golden Gate 04/26/95 8 932 502 210 ND 220 14 ND 85 840

BC60 Red Rock 04/27/95 8 267 119 81 ND 67 14 ND 123 1400

BD15 Petaluma River 04/19/95 8 795 354 123 13 305 168 ND 429 4400


BD30 Pinole Point 04/20/95 8 632 253 66 6 308 43 ND 890 4410

BD40 Davis Point 04/19/95 8 697 300 79 9 309 53 ND 491 4420

BD50 Napa River 04/18/95 8 586 193 56 22 315 37 ND 517 5200

BF20 Grizzly Bay 04/20/95 8 172 30 29 58 55 51 ND 230 2700

BG20 Sacramento River 04/18/95 8 115 33 18 21 43 32 ND 57 3900

BG30 San Joaquin River 04/18/95 8 NS NS NS NS NS NS NS NS NS

BA10 Coyote Creek 08/14/95 9 961 222 113 62 563 10 1 136 2900



BB70 Alameda 08/16/95 9 632 290 140 22 180 3 ND 38 900


BC20 Golden Gate 08/16/95 9 744 423 217 ND 105 5 ND 31 ND

BC60 Red Rock 08/17/95 9 606 320 130 6 150 5 ND 61 560

BD15 Petaluma River 08/21/95 9 490 233 103 12 143 6 1 81 640


BD30 Pinole Point 08/21/95 9 601 282 112 26 182 ND ND 90 730

BD40 Davis Point 08/21/95 9 880 372 152 25 332 4 ND 132 1900

BD50 Napa River 08/22/95 9 493 220 76 25 172 ND ND 105 320

BF20 Grizzly Bay 08/22/95 9 0 NS NS NS NS 8 1 188 1800 ND ND ND 15 29

BG20 Sacramento River 08/23/95 9 27 ND 14 4 10 3 ND 209 1500 ND ND ND 7 21

BG30 San Joaquin River 08/23/95 9 47 5 22 4 15 17 ND 284 1900 ND ND ND 8 20

End

osul

fan

I

End

osul

fan

II

End

osul

fan

Sul

fate

Oxa

diaz

on

Chl

orpy

rifos

pg/L pg/L pg/L pg/L pg/L

ND ND ND 3145 650

ND ND ND 14000 209

ND ND ND 418 458

ND ND ND 91 286

ND ND ND 132 134

ND ND ND 110 99

ND ND ND 120 139

ND ND ND 225 253

ND ND ND 160 132

ND ND ND 93 131

ND ND ND 147 75

ND ND ND 154 145

ND ND ND 110 75

ND ND ND 283 58

ND ND ND 130 183

ND ND ND 12 400

ND ND ND ND 161

ND ND ND ND 140

ND ND ND ND 68

ND ND ND ND 137

ND ND ND ND 19

ND ND ND 8 24

ND ND ND ND 450

ND ND ND ND 410

ND ND ND ND 391

ND ND ND 30 520

ND ND ND 4 423

ND ND ND 20 163

ND ND ND 26 69

NS NS NS NS 240

ND ND ND 18 4

ND ND ND 6 6

ND ND ND 12 9

ND ND ND ND 2

ND ND ND 9 4

ND ND ND 30 11

ND ND ND 4 7

ND ND ND 13 3

ND ND ND 3 8

ND ND ND ND 2

ND ND ND 3 14

ND ND ND 3 15

Appendices

A–37

Myt

ilus

edul

isM

ysid

opsi

s ba

hia

Sta

tion

Cod

eS

tatio

nD

ate

Mea

n %

Nor

mal

Dev

elop

men

tM

ean

% S

urvi

val

100%

Am

bien

t Wat

erC

ontr

ol10

0% A

mbi

ent W

ater

Con

trol

BA

10C

oyot

e C

reek

02/0

7/95

8867

100

93B

A40

Red

woo

d C

reek

02/0

7/95

8967

9393

BB

70A

lam

eda

02/0

8/95

9795

8880

BC

10Y

erba

Bue

na Is

land

02/0

8/95

9995

9380

BC

60R

ed R

ock

02/0

8/95

9595

8080

BD

15P

etal

uma

Riv

er02

/13/

9588

9195

93B

D30

Pin

ole

Poi

nt02

/13/

9590

9195

93B

D50

Nap

a R

iver

02/1

4/95

N/A

N

/A

8895

BF2

0G

rizzl

y B

ay02

/14/

95N

/A

N/A

98

95B

G20

Sac

ram

ento

Riv

er02

/15/

95N

/A

N/A

93

100

BG

30S

an J

oaqu

in R

iver

02/1

5/95

N/A

N

/A

83*

100

C-1

-3S

unny

vale

02/0

7/95

7367

8093

C-3

-0S

an J

ose

02/0

7/95

8467

8893

Cra

ssos

trea

giga

sM

ysid

opsi

s ba

hia

Sta

tion

Cod

eS

tatio

nD

ate

Mea

n %

Nor

mal

Dev

elop

men

tM

ean

% S

urvi

val

100%

Am

bien

t Wat

erC

ontr

ol10

0% A

mbi

ent W

ater

Con

trol

BA

10C

oyot

e C

reek

08/1

4/95

FF

100

95B

A40

Red

woo

d C

reek

08/1

5/95

FF

9590

BB

70A

lam

eda

08/1

6/95

FF

9895

BC

10Y

erba

Bue

na Is

land

08/1

6/95

FF

9810

0B

C60

Red

Roc

k08

/17/

95F

F10

093

BD

15P

etal

uma

Riv

er08

/21/

95F

F95

95B

D30

Pin

ole

Poi

nt08

/21/

95F

F85

95B

D50

Nap

a R

iver

08/2

2/95

FF

8890

BF2

0G

rizzl

y B

ay08

/22/

95F

F90

90B

G20

Sac

ram

ento

Riv

er08

/23/

95F

F93

98B

G30

San

Joa

quin

Riv

er08

/23/

95F

F95

98C

-1-3

Sun

nyva

le08

/14/

95F

F95

92.5

C-3

-0S

an J

ose

08/1

4/95

FF

92.5

92.5

F

In A

ugus

t, th

e oy

ster

sto

cks

did

not p

rodu

ce v

iabl

e sp

erm

or e

ggs

whi

ch re

sulte

d in

ex

trem

ely

poor

ferti

lizat

ion

and

none

of t

he te

sts

wer

e su

cces

sful

.N

/AT

est t

erm

inat

ed d

ue to

con

trol f

ailu

re.

Tab

le 1

0. W

ater

tox

icit

y d

ata

for

1995

RM

P c

ruis

es.

* S

tatis

tical

ly s

igni

fican

tly d

iffer

ent f

rom

the

cont

rol a

t the

0.0

5 le

vel

A–38


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

% C

lay

(<4u

m)

% S

ilt (4

um -

63um

)

% S

and

(63u

m -

2mm

)

% G

rave

l+S

hell

(>2m

m)

Dep

th (

met

ers)

Am

mon

ia

Hyd

roge

n S

ulfid

e

pH

TO

C

Tot

al S

ulfid

e

% % % % mg/L mg/L pH % mg/L

BA10 Coyote Creek 02/22/95 7 44 15 37 4 6 1.05 0.007 7.72 0.625 0.066

BA21 South Bay 02/21/95 7 72 25 3 0 4 4.36 0.017 7.17 0.96 0.058

BA30 Dumbarton Bridge 02/21/95 7 68 27 5 0 8 0.34 0.003 7.75 1.24 0.032

BA41 Redwood Creek 02/21/95 7 48 19 21 12 3.5 0.62 0.005 7.62 1.64 0.038

BB15 San Bruno Shoal 02/21/95 7 54 28 16 2 12 2.41 0.009 7.14 1.11 0.03

BB30 Oyster Point 02/20/95 7 46 21 27 6 8.5 3.01 0.006 7.46 1.17 0.034

BB70 Alameda 02/21/95 7 50 26 24 0 10 0.84 0.009 7.31 1.01 0.04

BC11 Yerba Buena Island 02/20/95 7 46 21 29 3 6.5 0.53 0.007 7.54 1.24 0.044

BC21 Horseshoe Bay 02/20/95 7 38 28 34 0 12 2.4 0.012 7.26 1.01 0.046

BC32 Richardson Bay 02/20/95 7 33 40 27 0 3 0.46 0.009 7.07 0.8 0.026

BC41 Point Isabel 02/20/95 7 54 35 11 0 2.5 0.57 0.007 7.21 1.04 0.026

BC60 Red Rock 02/17/95 7 5 2 89 4 10.5 0.55 ND 7.53 0.54 ND

BD15 Petaluma River 02/17/95 7 70 27 3 0 4 3.69 0.011 7.02 1.44 0.03

BD22 San Pablo Bay 02/17/95 7 52 33 14 2 4 1.95 0.017 7.2 0.95 0.06

BD31 Pinole Point 02/17/95 7 79 15 6 0 7 3.37 0.026 7 1.46 0.068

BD41 Davis Point 02/17/95 7 21 9 67 2 7.3 1.52 0.004 7.5 0.98 0.024

BD50 Napa River 02/17/95 7 70 23 4 3 3.3 2.72 0.01 7.26 1.365 0.04

BF10 Pacheco Creek 02/16/95 7 7 4 89 0 6 0.84 0.004 7.46 0.7 0.024

BF21 Grizzly Bay 02/16/95 7 62 37 1 0 2.5 1.84 ND 7.32 1.375 ND

BF40 Honker Bay 02/16/95 7 62 35 3 0 3 1.95 ND 7.44 1.48 ND

BG20 Sacramento River 02/16/95 7 8 4 87 0 8.5 0.21 ND 7.01 0.271 ND

BG30 San Joaquin River 02/16/95 7 34 30 36 0 6.5 2.74 0.019 6.48 0.52 0.028

C-1-3 Sunnyvale 02/22/95 7 8 4 88 0 2.5 4.07 0.022 7.61 0.345 0.16

C-3-0 San Jose 02/22/95 7 13 5 76 5 3.5 0.9 0.016 7.75 0.527 0.154

BA10 Coyote Creek 08/30/95 9 73 23 3 1 6 0.42 0.011 7.55 1.42 0.073

BA21 South Bay 08/29/95 9 67 31 2 0 4 5.22 ND 7.15 1.33 ND

BA30 Dumbarton Bridge 08/30/95 9 60 36 4 0 8 5.01 0.02 6.9 1.25 0.046

BA41 Redwood Creek 08/29/95 9 58 22 13 7 3.5 0.22 ND 7.49 1.13 ND

BB15 San Bruno Shoal 08/29/95 9 45 21 30 4 12 0.49 ND 7.79 0.88 ND

BB30 Oyster Point 08/30/95 9 48 20 30 2 8.5 1.35 0.024 7.29 1.05 0.099

BB70 Alameda 08/28/95 9 69 28 5 0 10 1.94 0.013 7.34 2.22 0.059

BC11 Yerba Buena Island 08/28/95 9 71 21 7 1 6.5 1.06 0.036 7.47 1.68 0.206

BC21 Horseshoe Bay 08/28/95 9 19 12 66 3 12 0.63 0.013 7.61 0.55 0.095

BC32 Richardson Bay 08/28/95 9 41 39 20 0 3 0.66 0.009 7.04 0.93 0.024

BC41 Point Isabel 08/28/95 9 51 37 12 0 2.5 0.54 ND 7.41 1.12 ND

BC60 Red Rock 08/25/95 9 4 1 85 10 10.5 0.26 0.034 7.89 NA 0.459

BD15 Petaluma River 08/25/95 9 64 25 8 3 4 2.68 ND 7.52 1.2 ND

BD22 San Pablo Bay 08/25/95 9 57 33 9 1 4 0.27 ND 7.66 1.36 ND

BD31 Pinole Point 08/25/95 9 43 20 37 0 7 4.49 ND 7 1.08 ND

BD41 Davis Point 08/25/95 9 14 6 79 1 7.3 0.25 0.03 7.68 0.37 0.259

BD50 Napa River 08/25/95 9 77 21 2 0 3.3 0.66 0.012 7.27 1.5 0.046

BF10 Pacheco Creek 08/24/95 9 17 8 74 0 6 0.35 0.036 7.76 0.65 0.361

BF21 Grizzly Bay 08/24/95 9 63 34 3 1 2.5 1.16 ND 7.45 1.4 ND

BF40 Honker Bay 08/24/95 9 61 31 7 0 3 1.11 ND 6.82 1.46 ND

BG20 Sacramento River 08/24/95 9 18 9 73 0 8.5 0.53 ND 7.22 0.77 ND

BG30 San Joaquin River 08/24/95 9 40 39 21 0 6.5 0.73 ND 6.32 0.55 ND

C-1-3 Sunnyvale 08/29/95 9 33 15 53 0 2.5 2.12 ND 7.64 0.71 NDC-3-0 San Jose 08/29/95 9 52 20 28 0 3.5 2.78 0.016 7 1.22 0.042

Table 11. General characteristics of sediment samples, 1995.ND = not detected, NA = not analyzed

Appendices

A–39

Table 12. Concentration of trace elements for sediment samples, 1995.S

tatio

n C

ode

Sta

tion

Dat

e

Cru

ise

A g Al As C d Cr C u F e mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg

BA10 Coyote Creek 02/22/95 7 0.32 18218 6.1 0.20 66.8 31.1 29423

BA21 South Bay 02/21/95 7 0.48 24748 8.0 0.17 85.9 43.1 38304

BA30 Dumbarton Bridge 02/21/95 7 0.50 22619 11.4 0.22 84.7 47.2 38122

BA41 Redwood Creek 02/21/95 7 0.54 25768 10.9 0.34 80.4 40.4 33758

BB15 San Bruno Shoal 02/21/95 7 0.37 25945 10.2 0.20 81.5 37.6 32990

BB30 Oyster Point 02/20/95 7 0.38 24288 6.9 0.17 78.8 35.7 31907

BB70 Alameda 02/21/95 7 0.45 25894 9.8 0.23 90.2 41.4 35346

BC11 Yerba Buena Island 02/20/95 7 0.28 17874 9.5 0.19 58.7 30.1 23675

BC21 Horseshoe Bay 02/20/95 7 0.24 22258 8.3 0.23 78.8 31.4 30791

BC32 Richardson Bay 02/20/95 7 0.21 21466 9.0 0.18 71.9 31.1 30634

BC41 Point Isabel 02/20/95 7 0.25 23106 12.0 0.14 83.4 40.1 33858

BC60 Red Rock 02/17/95 7 0.02 9692 8.2 0.04 59.3 10.3 26710

BD15 Petaluma River 02/17/95 7 0.29 34345 11.2 0.36 102.5 55.9 43673

BD22 San Pablo Bay 02/17/95 7 0.28 23312 13.7 0.19 78.7 46.6 35016

BD31 Pinole Point 02/17/95 7 0.23 32873 15.4 0.43 102.7 70.6 47886

BD41 Davis Point 02/17/95 7 0.10 18095 6.7 0.15 70.3 27.3 31576

BD50 Napa River 02/17/95 7 0.33 28189 12.6 0.30 95.8 63.8 43794

BF10 Pacheco Creek 02/16/95 7 0.03 16213 6.0 0.12 67.1 14.6 30540

BF21 Grizzly Bay 02/16/95 7 0.25 25589 15.7 0.30 89.8 59.7 40255

BF40 Honker Bay 02/16/95 7 0.22 27929 13.3 0.37 93.6 63.5 42698

BG20 Sacramento River 02/16/95 7 0.04 15718 10.0 0.27 66.4 20.7 26853

BG30 San Joaquin River 02/16/95 7 0.08 27137 14.2 0.22 74.7 39.7 31446

C-1-3 Sunnyvale 02/22/95 7 0.07 11896 2.0 0.17 55.6 22.7 20640

C-3-0 San Jose 02/22/95 7 0.36 12231 6.1 0.26 70.0 21.1 22962

BA10 Coyote Creek 08/30/95 9 0.43 29207 9.8 0.18 96.1 41.0 41500

BA21 South Bay 08/29/95 9 0.38 26947 11.6 0.16 89.8 38.3 38579

BA30 Dumbarton Bridge 08/30/95 9 0.38 18783 9.1 0.16 77.4 37.3 32568

BA41 Redwood Creek 08/29/95 9 0.56 23468 9.4 0.25 85.4 39.1 35040

BB15 San Bruno Shoal 08/29/95 9 0.42 16784 8.2 0.18 72.8 32.0 26179

BB30 Oyster Point 08/30/95 9 0.37 19709 9.4 0.21 77.9 34.9 30473

BB70 Alameda 08/28/95 9 0.24 19209 13.4 0.17 76.8 42.1 32393

BC11 Yerba Buena Island 08/28/95 9 0.28 26243 12.4 0.18 82.9 42.1 36382

BC21 Horseshoe Bay 08/28/95 9 0.14 13156 6.0 0.13 61.1 16.9 22043

BC32 Richardson Bay 08/28/95 9 0.23 24373 12.8 0.24 78.7 31.7 31383

BC41 Point Isabel 08/28/95 9 0.23 27834 11.9 0.17 92.5 36.4 34058

BC60 Red Rock 08/25/95 9 0.01 11896 8.3 0.04 69.8 7.2 27986

BD15 Petaluma River 08/25/95 9 0.26 13804 18.2 0.31 89.6 49.6 30186

BD22 San Pablo Bay 08/25/95 9 0.21 25833 15.1 0.23 78.5 41.0 35273

BD31 Pinole Point 08/25/95 9 0.15 23565 12.1 0.24 81.0 41.3 34433

BD41 Davis Point 08/25/95 9 0.05 13944 8.4 0.11 73.1 17.2 25680

BD50 Napa River 08/25/95 9 0.31 26484 14.5 0.22 101.5 56.7 37208

BF10 Pacheco Creek 08/24/95 9 0.04 14128 8.6 0.11 66.4 15.2 27058

BF21 Grizzly Bay 08/24/95 9 0.25 23088 16.1 0.26 67.2 39.8 42395

BF40 Honker Bay 08/24/95 9 0.21 32633 14.0 0.26 88.9 45.3 41869

BG20 Sacramento River 08/24/95 9 0.05 18683 8.9 0.26 86.4 21.8 32690

BG30 San Joaquin River 08/24/95 9 0.08 27787 17.5 0.20 67.4 35.2 34060

C-1-3 Sunnyvale 08/29/95 9 0.22 20510 6.0 0.17 69.1 24.9 28103

C-3-0 San Jose 08/29/95 9 0.96 21185 8.2 0.75 97.7 49.8 34018

A–40


Table 12. Concentration of trace elements for sediment samples, 1995 (continued).

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

H g M n Ni P b S e Z n mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg

BA10 Coyote Creek 02/22/95 7 0.277 695 72.3 23.3 0.426 94

BA21 South Bay 02/21/95 7 0.392 903 83.4 31.4 0.528 126

BA30 Dumbarton Bridge 02/21/95 7 0.388 484 81.2 32.1 0.493 128

BA41 Redwood Creek 02/21/95 7 0.238 517 72.5 26.9 0.236 109

BB15 San Bruno Shoal 02/21/95 7 0.307 445 70.2 23.9 0.218 103

BB30 Oyster Point 02/20/95 7 0.281 392 69.3 20.4 0.479 99

BB70 Alameda 02/21/95 7 0.330 355 78.7 37.8 0.587 112

BC11 Yerba Buena Island 02/20/95 7 0.241 283 49.9 18.2 0.335 81

BC21 Horseshoe Bay 02/20/95 7 0.196 296 68.0 25.0 0.418 95

BC32 Richardson Bay 02/20/95 7 0.263 307 64.7 23.3 0.308 90

BC41 Point Isabel 02/20/95 7 0.328 381 73.1 24.0 0.438 107

BC60 Red Rock 02/17/95 7 0.027 537 59.2 11.7 0.076 58

BD15 Petaluma River 02/17/95 7 0.423 936 116.6 29.1 0.664 148

BD22 San Pablo Bay 02/17/95 7 0.351 511 76.8 22.5 0.289 112

BD31 Pinole Point 02/17/95 7 0.320 811 117.5 16.9 0.391 137

BD41 Davis Point 02/17/95 7 0.124 408 70.8 14.9 0.170 82

BD50 Napa River 02/17/95 7 0.390 720 96.7 30.3 0.461 140

BF10 Pacheco Creek 02/16/95 7 0.047 377 71.9 5.9 0.080 64

BF21 Grizzly Bay 02/16/95 7 0.338 879 92.9 30.5 0.565 127

BF40 Honker Bay 02/16/95 7 0.324 988 97.2 26.0 0.548 133

BG20 Sacramento River 02/16/95 7 0.058 575 83.1 9.7 0.131 78

BG30 San Joaquin River 02/16/95 7 0.343 451 57.5 14.0 0.455 67

C-1-3 Sunnyvale 02/22/95 7 0.110 400 57.9 16.5 0.217 70

C-3-0 San Jose 02/22/95 7 0.132 888 78.2 16.3 0.243 72

BA10 Coyote Creek 08/30/95 9 0.494 1151 98.6 37.4 0.385 133

BA21 South Bay 08/29/95 9 0.374 1093 86.3 30.1 0.284 115

BA30 Dumbarton Bridge 08/30/95 9 0.368 761 77.2 27.5 0.254 108

BA41 Redwood Creek 08/29/95 9 0.391 441 83.6 34.7 0.258 116

BB15 San Bruno Shoal 08/29/95 9 0.277 320 67.3 27.7 0.233 92

BB30 Oyster Point 08/30/95 9 0.269 383 76.4 26.4 0.302 98

BB70 Alameda 08/28/95 9 0.320 667 80.2 22.1 0.341 103

BC11 Yerba Buena Island 08/28/95 9 0.240 488 84.9 25.4 0.387 110

BC21 Horseshoe Bay 08/28/95 9 0.116 193 55.9 14.8 0.166 60

BC32 Richardson Bay 08/28/95 9 0.297 235 70.5 45.6 0.219 100

BC41 Point Isabel 08/28/95 9 0.324 269 81.3 28.8 0.295 106

BC60 Red Rock 08/25/95 9 0.021 424 65.1 10.7 0.051 55

BD15 Petaluma River 08/25/95 9 0.427 777 93.6 43.9 0.459 126

BD22 San Pablo Bay 08/25/95 9 0.306 445 80.1 24.9 0.407 104

BD31 Pinole Point 08/25/95 9 0.205 466 91.5 16.7 0.313 107

BD41 Davis Point 08/25/95 9 0.077 305 73.5 9.6 0.089 73

BD50 Napa River 08/25/95 9 0.404 589 103.5 31.9 0.407 144

BF10 Pacheco Creek 08/24/95 9 0.091 316 73.3 6.6 0.142 65

BF21 Grizzly Bay 08/24/95 9 0.344 848 68.3 30.7 0.338 94

BF40 Honker Bay 08/24/95 9 0.348 698 85.8 24.8 0.440 116

BG20 Sacramento River 08/24/95 9 0.055 496 84.2 11.3 0.135 86

BG30 San Joaquin River 08/24/95 9 0.423 486 52.6 16.2 0.369 61

C-1-3 Sunnyvale 08/29/95 9 0.307 728 63.8 22.4 0.307 78

C-3-0 San Jose 08/29/95 9 0.400 595 105.7 50.6 0.406 148

Appendices

A–41

Table 13. PAH and alkanes concentrations in sediment, 1995.ND = not detected. Data in dry weight.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of A

lkan

es (S

FE

I)

Sum

of P

AH

s (S

FE

I)

Sum

of L

PA

Hs

(SF

EI)

Sum

of H

PA

Hs

(SF

EI)

Bip

heny

l

Nap

htha

lene

1-M

ethy

lnap

htha

lene

2-M

ethy

lnap

htha

lene

2,6-

Dim

ethy

lnap

htha

lene

2,3,

5-Tr

imet

hyln

apht

hale

ne

Ace

naph

then

e

Ace

naph

thyl

ene

Ant

hrac

ene

Dib

enzo

thio

phen

e

Flu

oren

e

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 1005 1451 199 1252 6 20 5 8 5 2 5 14 29 5 8

BA21 South Bay 02/21/95 7 1517 2339 239 2101 9 26 7 9 9 4 10 16 35 5 10


BA41 Redwood Creek 02/21/95 7 1060 2448 338 2110 8 31 6 10 7 3 9 26 48 8 15

BB15 San Bruno Shoal 02/21/95 7 1137 2314 353 1961 10 51 7 12 8 3 14 22 43 9 13

BB30 Oyster Point 02/20/95 7 1203 2638 344 2294 12 35 13 16 10 8 14 18 43 7 14

BB70 Alameda 02/21/95 7 1450 3722 939 2783 19 53 30 39 19 8 116 20 115 19 79


BC21 Horseshoe Bay 02/20/95 7 1291 2154 369 1785 9 30 9 12 10 3 16 24 51 10 18

BC32 Richardson Bay 02/20/95 7 957 2409 339 2069 9 35 8 13 8 5 10 20 48 8 15

BC41 Point Isabel 02/20/95 7 1386 2955 427 2528 11 42 14 19 10 7 14 21 60 10 14

BC60 Red Rock 02/17/95 7 222 59 21 38 3 5 3 3 ND ND ND ND 2 ND ND

BD15 Petaluma River 02/17/95 7 3003 1555 168 1387 6 26 5 8 5 ND 5 12 17 4 7

BD22 San Pablo Bay 02/17/95 7 1748 1934 219 1715 10 20 8 9 7 5 9 11 26 5 8

BD31 Pinole Point 02/17/95 7 4183 420 97 323 6 11 ND 9 13 ND 6 ND 8 4 5

BD41 Davis Point 02/17/95 7 743 228 35 194 1 5 ND 3 2 ND ND 2 4 ND 2

BD50 Napa River 02/17/95 7 3017 1092 162 930 9 16 8 11 10 7 6 6 16 5 11

BF10 Pacheco Creek 02/16/95 7 411 85 27 58 2 5 ND 4 2 3 2 ND 2 ND 2

BF21 Grizzly Bay 02/16/95 7 2822 586 79 508 4 11 5 9 5 3 ND 5 8 ND 5

BF40 Honker Bay 02/16/95 7 4559 796 116 679 5 15 6 10 7 3 3 5 12 3 6

BG20 Sacramento River 02/16/95 7 705 90 40 49 6 9 7 6 2 ND ND ND 1 ND 2

BG30 San Joaquin River 02/16/95 7 861 58 2 56 ND ND ND ND ND ND ND ND ND ND ND

BA10 Coyote Creek 08/30/95 9 1293 1644 221 1422 10 28 8 13 10 5 6 12 20 6 9

BA21 South Bay 08/29/95 9 1256 1957 314 1643 19 35 10 15 12 4 10 17 37 5 14


BA41 Redwood Creek 08/29/95 9 870 1765 195 1570 7 21 4 11 6 2 8 11 19 5 7

BB15 San Bruno Shoal 08/29/95 9 893 1742 238 1504 8 25 5 7 9 5 9 12 26 6 11

BB30 Oyster Point 08/30/95 9 493 1365 182 1183 8 19 5 7 6 3 7 12 22 5 7

BB70 Alameda 08/28/95 9 1438 2278 474 1804 8 22 8 12 13 9 11 20 74 13 20


BC21 Horseshoe Bay 08/28/95 9 527 1229 240 989 6 15 5 7 5 5 7 15 56 4 11

BC32 Richardson Bay 08/28/95 9 672 2344 287 2056 9 25 5 8 8 5 13 16 38 5 10

BC41 Point Isabel 08/28/95 9 1068 2206 344 1862 8 27 8 10 8 6 13 19 58 7 14

BC60 Red Rock 08/25/95 9 104 16 2 14 1 ND ND ND ND ND ND ND ND ND ND

BD15 Petaluma River 08/25/95 9 1134 1490 133 1357 5 22 ND 6 5 5 5 9 13 4 6

BD22 San Pablo Bay 08/25/95 9 2037 2415 292 2123 10 30 7 9 7 4 9 15 37 9 10

BD31 Pinole Point 08/25/95 9 2228 466 90 376 4 9 4 5 5 2 4 4 9 3 6

BD41 Davis Point 08/25/95 9 511 112 26 86 2 3 ND ND ND ND 3 ND 2 ND 3

BD50 Napa River 08/25/95 9 2212 969 116 854 6 15 ND 10 8 ND 4 5 12 4 8

BF10 Pacheco Creek 08/24/95 9 1021 317 122 195 3 4 3 4 3 ND 11 1 8 4 13

BF21 Grizzly Bay 08/24/95 9 2779 577 90 487 6 11 ND 8 7 4 5 3 7 3 5

BF40 Honker Bay 08/24/95 9 3124 527 77 450 5 9 ND 7 5 3 ND 4 8 2 6

BG20 Sacramento River 08/24/95 9 1374 60 5 54 1 ND ND ND ND ND ND ND ND ND ND

BG30 San Joaquin River 08/24/95 9 1015 82 8 74 1 3 ND ND ND ND ND ND ND ND ND

A–42


Table 13. PAH and alkanes concentrations in sediment, 1995 (continued).ND = not detected. Data in dry weight.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Phe

nant

hren

e

1-M

ethy

lphe

nant

hren

e

Ben

z(a)

anth

race

ne

Chr

ysen

e

Flu

oran

then

e

Pyr

ene

Ben

zo(a

)pyr

ene

Ben

zo(e

)pyr

ene

Ben

zo(b

)flu

oran

then

e

Ben

zo(k

)flu

oran

then

e

Dib

enz(

a,h)

anth

race

ne

Per

ylen

e

Ben

zo(g

hi)p

eryl

ene

Inde

no(1

,2,3

-cd)

pyre

ne

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 83 9 62 77 171 231 143 90 150 24 16 32 142 115

BA21 South Bay 02/21/95 7 88 10 114 151 237 432 243 150 225 85 21 61 203 180

BA30 Dumbarton Bridge 02/21/95 7 127 20 141 161 331 552 299 180 284 85 21 70 232 205

BA41 Redwood Creek 02/21/95 7 147 20 128 140 275 361 255 149 246 52 27 56 229 192

BB15 San Bruno Shoal 02/21/95 7 140 18 115 136 286 375 216 135 63 203 23 52 197 161

BB30 Oyster Point 02/20/95 7 137 17 122 151 309 554 253 154 260 46 19 59 194 172

BB70 Alameda 02/21/95 7 390 31 197 201 488 517 303 179 291 106 24 65 216 195

BC11 Yerba Buena Island 02/20/95 7 72 8 64 71 148 190 128 75 120 32 13 29 115 92

BC21 Horseshoe Bay 02/20/95 7 159 18 122 136 273 343 201 115 198 41 21 54 152 129

BC32 Richardson Bay 02/20/95 7 142 20 128 162 282 331 256 145 237 66 26 55 208 173

BC41 Point Isabel 02/20/95 7 179 26 189 184 377 492 294 164 272 87 21 71 198 179

BC60 Red Rock 02/17/95 7 5 ND 2 4 5 7 4 3 4 2 ND ND 4 3

BD15 Petaluma River 02/17/95 7 65 8 64 77 168 244 159 105 143 46 16 53 174 138

BD22 San Pablo Bay 02/17/95 7 90 10 95 104 235 364 193 119 181 58 13 64 154 134

BD31 Pinole Point 02/17/95 7 32 4 14 25 46 72 29 22 34 7 ND 21 31 22

BD41 Davis Point 02/17/95 7 12 3 10 16 28 37 18 14 7 22 2 8 18 14

BD50 Napa River 02/17/95 7 49 8 47 63 137 169 93 66 98 36 8 50 89 74

BF10 Pacheco Creek 02/16/95 7 5 ND 4 3 15 16 4 3 5 2 ND ND 4 3

BF21 Grizzly Bay 02/16/95 7 21 3 21 39 54 95 49 37 58 12 4 44 52 43

BF40 Honker Bay 02/16/95 7 36 6 35 46 81 104 71 49 71 24 9 54 77 58

BG20 Sacramento River 02/16/95 7 6 2 3 5 7 10 5 4 5 2 ND ND 5 4

BG30 San Joaquin River 02/16/95 7 2 ND 2 2 3 3 2 2 3 1 ND 36 2 1

BA10 Coyote Creek 08/30/95 9 84 11 69 99 162 216 157 105 181 38 18 51 174 153

BA21 South Bay 08/29/95 9 121 15 93 122 189 250 183 116 209 37 25 49 193 177

BA30 Dumbarton Bridge 08/30/95 9 150 21 128 155 265 355 244 147 266 56 28 65 237 223

BA41 Redwood Creek 08/29/95 9 84 9 79 114 173 234 184 115 182 46 20 55 192 178

BB15 San Bruno Shoal 08/29/95 9 102 13 92 101 166 224 180 110 175 33 22 48 187 166

BB30 Oyster Point 08/30/95 9 73 7 73 78 133 181 135 83 136 38 15 41 141 128

BB70 Alameda 08/28/95 9 212 53 174 182 223 300 204 109 188 45 25 53 157 144

BC11 Yerba Buena Island 08/28/95 9 70 10 63 72 103 133 108 71 111 25 12 46 112 99

BC21 Horseshoe Bay 08/28/95 9 94 9 69 86 127 165 105 60 119 21 12 32 98 94

BC32 Richardson Bay 08/28/95 9 130 14 125 148 259 332 236 142 231 76 25 69 209 206

BC41 Point Isabel 08/28/95 9 148 17 125 158 251 313 214 123 207 32 24 60 183 173

BC60 Red Rock 08/25/95 9 1 ND 1 1 2 2 2 1 2 ND ND ND 2 1

BD15 Petaluma River 08/25/95 9 47 6 58 82 136 195 151 105 170 23 15 71 185 166

BD22 San Pablo Bay 08/25/95 9 129 16 138 156 246 338 250 154 243 55 29 66 231 216

BD31 Pinole Point 08/25/95 9 31 4 23 32 45 57 40 25 43 5 5 19 44 36

BD41 Davis Point 08/25/95 9 11 1 4 7 14 15 9 6 9 3 1 ND 10 8

BD50 Napa River 08/25/95 9 38 6 41 55 85 112 79 56 100 95 11 49 94 76

BF10 Pacheco Creek 08/24/95 9 64 4 14 22 43 36 12 10 21 3 1 9 12 10

BF21 Grizzly Bay 08/24/95 9 27 4 26 34 45 61 49 37 60 7 6 49 64 48

BF40 Honker Bay 08/24/95 9 25 3 22 33 46 63 43 34 53 10 5 39 56 45

BG20 Sacramento River 08/24/95 9 3 1 4 6 6 9 6 4 7 2 ND ND 6 5

BG30 San Joaquin River 08/24/95 9 3 ND 2 4 4 5 3 2 3 ND ND 45 3 2

Appendices

A–43

Table 14. PCB concentrations in sediment, 1995.. = no data ND = not detected, M = matrix interference. Data in dry weight.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of P

CB

s (S

FE

I)

PC

B 0

07/9

PC

B 0

08/5

PC

B 0

15

PC

B 0

16/3

2

PC

B 0

18

PC

B 0

22/5

1

PC

B 0

24/2

7

PC

B 0

25

PC

B 0

28

PC

B 0

29

PC

B 0

31

PC

B 0

33/5

3/20

PC

B 0

37/4

2/59

PC

B 0

40

PC

B 0

41/6

4

PC

B 0

44

PC

B 0

45

PC

B 0

46

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 5 ND ND ND ND ND 0.72 ND ND ND ND ND ND ND ND ND ND ND ND

BA21 South Bay 02/21/95 7 3 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA30 Dumbarton Bridge 02/21/95 7 5 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA41 Redwood Creek 02/21/95 7 11 ND ND ND ND ND 1.10 ND ND ND ND ND ND ND ND ND ND ND ND

BB15 San Bruno Shoal 02/21/95 7 5 ND ND ND ND ND 0.76 ND ND ND ND ND ND ND ND ND ND ND ND

BB30 Oyster Point 02/20/95 7 4 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BB70 Alameda 02/21/95 7 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC11 Yerba Buena Island 02/20/95 7 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 02/20/95 7 11 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC32 Richardson Bay 02/20/95 7 5 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC41 Point Isabel 02/20/95 7 4 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC60 Red Rock 02/17/95 7 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD15 Petaluma River 02/17/95 7 3 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD22 San Pablo Bay 02/17/95 7 2 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD31 Pinole Point 02/17/95 7 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD41 Davis Point 02/17/95 7 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD50 Napa River 02/17/95 7 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF10 Pacheco Creek 02/16/95 7 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF21 Grizzly Bay 02/16/95 7 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF40 Honker Bay 02/16/95 7 6 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BG20 Sacramento River 02/16/95 7 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BG30 San Joaquin River 02/16/95 7 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA10 Coyote Creek 08/30/95 9 18 ND ND ND 0.93 ND ND ND ND 0.56 ND ND ND ND ND M ND ND ND

BA21 South Bay 08/29/95 9 15 ND ND ND 0.83 ND ND ND ND ND ND ND ND ND ND M ND ND ND

BA30 Dumbarton Bridge 08/30/95 9 21 ND ND ND 0.90 ND ND ND ND ND ND ND ND ND ND M ND ND ND

BA41 Redwood Creek 08/29/95 9 17 ND 0.50 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BB15 San Bruno Shoal 08/29/95 9 11 ND 0.67 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BB30 Oyster Point 08/30/95 9 11 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BB70 Alameda 08/28/95 9 4 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BC11 Yerba Buena Island 08/28/95 9 4 ND 0.77 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BC21 Horseshoe Bay 08/28/95 9 5 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BC32 Richardson Bay 08/28/95 9 12 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BC41 Point Isabel 08/28/95 9 9 ND 0.53 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BC60 Red Rock 08/25/95 9 0 ND 0.30 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BD15 Petaluma River 08/25/95 9 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BD22 San Pablo Bay 08/25/95 9 3 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BD31 Pinole Point 08/25/95 9 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BD41 Davis Point 08/25/95 9 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BD50 Napa River 08/25/95 9 6 ND 0.75 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BF10 Pacheco Creek 08/24/95 9 3 ND 0.41 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BF21 Grizzly Bay 08/24/95 9 3 ND 0.79 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BF40 Honker Bay 08/24/95 9 3 ND ND ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BG20 Sacramento River 08/24/95 9 1 ND 0.53 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

BG30 San Joaquin River 08/24/95 9 1 ND 0.64 ND ND ND ND ND ND ND ND ND ND ND ND M ND ND ND

A–44


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

PC

B 0

47/4

8/75

PC

B 0

49

PC

B 0

52

PC

B 0

56/6

0

PC

B 0

66

PC

B 0

70

PC

B 0

74

PC

B 0

82

PC

B 0

83

PC

B 0

84

PC

B 0

85

PC

B 0

87/1

15

PC

B 0

88

PC

B 0

92

PC

B 0

97

PC

B 0

99

PC

B 1

00

PC

B 1

01/9

0

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA21 South Bay 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA30 Dumbarton Bridge 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA41 Redwood Creek 02/21/95 7 ND ND ND ND ND ND ND 0.52 ND ND ND ND ND ND ND ND ND ND

BB15 San Bruno Shoal 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BB30 Oyster Point 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BB70 Alameda 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.70

BC11 Yerba Buena Island 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND 0.45 ND ND ND ND ND 0.43

BC21 Horseshoe Bay 02/20/95 7 ND ND ND ND 0.43 ND ND ND ND ND ND ND ND ND 0.66 ND ND ND

BC32 Richardson Bay 02/20/95 7 ND ND ND ND 0.51 ND ND ND ND ND ND ND ND ND ND ND ND ND

BC41 Point Isabel 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC60 Red Rock 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD15 Petaluma River 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD22 San Pablo Bay 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD31 Pinole Point 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD41 Davis Point 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD50 Napa River 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF10 Pacheco Creek 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF21 Grizzly Bay 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF40 Honker Bay 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BG20 Sacramento River 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BG30 San Joaquin River 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA10 Coyote Creek 08/30/95 9 ND ND 0.54 ND 0.71 ND ND ND ND ND ND ND ND ND ND ND ND 0.80

BA21 South Bay 08/29/95 9 ND ND ND ND 0.60 ND ND ND ND ND ND ND ND ND ND ND ND 0.75

BA30 Dumbarton Bridge 08/30/95 9 ND ND 0.66 ND 0.70 ND ND ND ND ND ND ND ND ND ND 0.71 ND 1.33

BA41 Redwood Creek 08/29/95 9 ND ND 0.64 ND ND 0.43 ND ND ND ND ND 0.59 ND ND ND 0.74 ND 1.29

BB15 San Bruno Shoal 08/29/95 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.46 ND 0.67

BB30 Oyster Point 08/30/95 9 ND ND ND ND 0.58 ND ND ND ND ND ND ND ND ND ND ND ND 0.50

BB70 Alameda 08/28/95 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC11 Yerba Buena Island 08/28/95 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 08/28/95 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.34

BC32 Richardson Bay 08/28/95 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.62

BC41 Point Isabel 08/28/95 9 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.53






BD50 Napa River 08/25/95 9 ND ND 0.54 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BF10 Pacheco Creek 08/24/95 9 ND ND ND 1.89 ND ND ND ND ND ND ND ND ND ND ND ND ND ND


BF40 Honker Bay 08/24/95 9 ND ND ND 0.54 ND ND ND ND ND ND ND ND ND ND ND ND ND ND



Table 14. PCB concentrations in sediment, 1995 (continued).. = no data, ND = not detected, M = matrix interference. Data in dry weight.

Appendices

A–45


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of P

CB

s (S

FE

I)

PC

B 1

05

PC

B 1

07/1

08/1

44

PC

B 1

10/7

7

PC

B 1

18

PC

B 1

28

PC

B 1

29

PC

B 1

36

PC

B 1

37/1

76

PC

B 1

38/1

60

PC

B 1

41/1

79

PC

B 1

46

PC

B 1

49/1

23

PC

B 1

51

PC

B 1

53/1

32

PC

B 1

56/1

71

PC

B 1

58

PC

B 1

67

PC

B 1

70/1

90

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 5 ND ND . ND 1.24 ND ND ND 0.57 ND ND 0.45 ND 0.55 ND ND ND 0.47

BA21 South Bay 02/21/95 7 3 ND ND . ND 1.62 ND ND ND ND ND ND ND ND 0.59 ND ND ND 0.87

BA30 Dumbarton Bridge 02/21/95 7 5 ND ND . ND 2.18 ND ND ND 0.62 ND ND ND ND 0.81 ND ND ND 1.24

BA41 Redwood Creek 02/21/95 7 11 ND ND . ND 1.91 ND ND ND 0.63 ND ND 0.48 ND 0.66 ND ND ND 5.27

BB15 San Bruno Shoal 02/21/95 7 5 ND ND . ND 1.56 ND ND ND ND ND ND ND ND ND ND ND ND 2.56

BB30 Oyster Point 02/20/95 7 4 ND ND . ND 2.10 ND ND ND 0.52 ND ND ND ND 0.65 ND ND ND 0.58

BB70 Alameda 02/21/95 7 9 ND ND . 0.75 2.02 ND ND ND 1.33 ND ND 0.66 ND 1.78 ND ND ND 0.64

BC11 Yerba Buena Island 02/20/95 7 7 ND ND . 0.49 1.38 ND ND ND 0.89 ND ND 0.70 ND 0.79 ND ND ND 0.66

BC21 Horseshoe Bay 02/20/95 7 11 ND ND . 0.49 2.15 ND ND ND 0.54 ND ND 0.64 ND 0.62 ND ND 0.47 3.27

BC32 Richardson Bay 02/20/95 7 5 ND ND . ND 3.15 ND ND ND 0.39 ND ND 0.51 ND ND ND ND ND 0.67

BC41 Point Isabel 02/20/95 7 4 ND ND . ND 2.48 ND ND ND ND ND ND ND ND 0.73 ND ND ND 0.52

BC60 Red Rock 02/17/95 7 0 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD15 Petaluma River 02/17/95 7 3 ND ND . ND 0.86 ND ND ND ND ND ND ND ND ND ND ND ND 1.76

BD22 San Pablo Bay 02/17/95 7 2 ND ND . ND 1.67 ND ND ND ND ND ND ND ND ND ND ND ND ND

BD31 Pinole Point 02/17/95 7 0 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD41 Davis Point 02/17/95 7 0 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD50 Napa River 02/17/95 7 1 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.77

BF10 Pacheco Creek 02/16/95 7 1 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND 1.02

BF21 Grizzly Bay 02/16/95 7 1 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND 1.24

BF40 Honker Bay 02/16/95 7 6 ND ND . ND ND ND ND ND 0.62 ND ND ND ND ND ND ND ND 5.20

BG20 Sacramento River 02/16/95 7 0 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.49

BG30 San Joaquin River 02/16/95 7 0 ND ND . ND ND ND ND ND ND ND ND ND ND ND ND ND ND 0.42

BA10 Coyote Creek 08/30/95 9 18 0.54 ND 1.28 2.08 ND ND ND ND 2.38 ND ND 0.81 ND 2.23 ND ND ND M

BA21 South Bay 08/29/95 9 15 0.58 ND 1.14 1.88 ND ND ND ND 2.24 ND ND 0.65 ND 2.14 ND ND ND M

BA30 Dumbarton Bridge 08/30/95 9 21 0.78 ND 1.75 2.61 ND ND ND ND 2.74 ND ND 0.80 ND 2.61 ND ND ND M

BA41 Redwood Creek 08/29/95 9 17 0.53 ND 1.66 1.65 ND ND ND ND 2.38 ND ND 0.97 ND 2.63 ND ND ND M

BB15 San Bruno Shoal 08/29/95 9 11 ND ND 0.95 0.89 ND ND ND ND 1.61 ND ND 0.66 ND 1.87 ND ND ND M

BB30 Oyster Point 08/30/95 9 11 ND ND 0.80 1.22 ND ND ND ND 1.77 ND ND 0.63 ND 1.62 ND ND ND M

BB70 Alameda 08/28/95 9 4 ND ND ND ND ND ND ND ND 1.10 ND ND ND ND 1.44 ND ND ND M

BC11 Yerba Buena Island 08/28/95 9 4 ND ND ND ND ND ND ND ND 1.15 ND ND ND ND 1.20 ND ND ND M

BC21 Horseshoe Bay 08/28/95 9 5 ND ND 0.35 0.53 ND ND ND ND 0.93 ND ND ND ND 0.87 ND ND ND M

BC32 Richardson Bay 08/28/95 9 12 ND ND 0.93 1.12 ND ND ND ND 1.96 ND ND 0.69 ND 1.89 ND ND ND M

BC41 Point Isabel 08/28/95 9 9 ND ND 0.79 0.75 ND ND ND ND 1.39 ND ND 0.54 ND 1.48 ND ND ND M

BC60 Red Rock 08/25/95 9 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND M

BD15 Petaluma River 08/25/95 9 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND M

BD22 San Pablo Bay 08/25/95 9 3 ND ND 0.48 ND ND ND ND ND 0.74 ND ND ND ND 0.81 ND ND ND M

BD31 Pinole Point 08/25/95 9 1 ND ND ND ND ND ND ND ND 0.50 ND ND ND ND 0.44 ND ND ND M

BD41 Davis Point 08/25/95 9 0 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND M

BD50 Napa River 08/25/95 9 6 ND ND 0.60 ND ND ND ND ND 0.99 ND ND ND ND 1.07 ND ND ND M

BF10 Pacheco Creek 08/24/95 9 3 ND ND ND ND ND ND ND ND 0.36 ND ND ND ND ND ND ND ND M

BF21 Grizzly Bay 08/24/95 9 3 ND ND ND ND ND ND ND ND 0.81 ND ND ND ND 0.82 ND ND ND M

BF40 Honker Bay 08/24/95 9 3 ND ND 0.52 ND ND ND ND ND 0.82 ND ND ND ND 0.81 ND ND ND M

BG20 Sacramento River 08/24/95 9 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND M

BG30 San Joaquin River 08/24/95 9 1 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND M

A–46



Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

PC

B 1

72

PC

B 1

74

PC

B 1

77

PC

B 1

78

PC

B 1

80

PC

B 1

83

PC

B 1

85

PC

B 1

87/1

82/1

59

PC

B 1

89

PC

B 1

91

PC

B 1

94

PC

B 1

95/2

08

PC

B 1

96/2

03

PC

B 2

00

PC

B 2

01

PC

B 2

05

PC

B 2

06

PC

B 2

09

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 ND ND 0.61 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA21 South Bay 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA30 Dumbarton Bridge 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BA41 Redwood Creek 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BB15 San Bruno Shoal 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BB30 Oyster Point 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BB70 Alameda 02/21/95 7 ND ND ND ND 0.85 ND ND 0.52 ND ND ND ND ND ND ND ND ND ND

BC11 Yerba Buena Island 02/20/95 7 ND ND 0.81 ND 0.52 ND ND ND ND ND ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 02/20/95 7 ND ND ND ND 1.51 ND ND ND ND ND ND ND ND ND ND ND ND ND

BC32 Richardson Bay 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BC41 Point Isabel 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND






BD50 Napa River 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND



BF40 Honker Bay 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND



BA10 Coyote Creek 08/30/95 9 ND ND 0.74 0.95 1.65 0.54 ND 0.85 ND ND ND ND ND ND 0.59 ND ND ND

BA21 South Bay 08/29/95 9 ND ND 0.62 1.22 1.43 ND ND 0.73 ND ND ND ND ND ND 0.65 ND ND ND

BA30 Dumbarton Bridge 08/30/95 9 ND 0.60 0.60 1.32 1.60 ND ND 0.74 ND ND ND ND ND ND 0.69 ND ND ND

BA41 Redwood Creek 08/29/95 9 ND 0.51 ND ND 1.16 ND ND 0.69 ND ND ND ND ND ND 0.50 ND ND 0.42

BB15 San Bruno Shoal 08/29/95 9 ND 0.53 ND ND 1.12 ND ND 0.68 ND ND ND ND ND ND 0.50 ND ND 0.43

BB30 Oyster Point 08/30/95 9 ND 0.51 0.53 0.69 1.31 ND ND 0.68 ND ND ND ND ND ND 0.60 ND ND ND

BB70 Alameda 08/28/95 9 ND ND ND ND 1.34 ND ND ND ND ND ND ND ND ND ND ND ND ND

BC11 Yerba Buena Island 08/28/95 9 ND ND ND ND 1.22 ND ND ND ND ND ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 08/28/95 9 ND ND ND 0.46 0.70 ND ND 0.36 ND ND ND ND ND ND ND ND ND ND

BC32 Richardson Bay 08/28/95 9 ND 0.52 0.45 1.34 1.35 0.43 ND 0.47 ND ND ND ND ND ND 0.42 ND ND ND

BC41 Point Isabel 08/28/95 9 ND 0.52 ND ND 1.00 ND ND 0.48 ND ND ND ND ND ND 0.50 ND ND 0.47


BD15 Petaluma River 08/25/95 9 ND ND ND 0.69 ND ND ND ND ND ND ND ND ND ND ND ND ND ND

BD22 San Pablo Bay 08/25/95 9 ND ND ND ND 0.67 ND ND ND ND ND ND ND ND ND ND ND ND ND



BD50 Napa River 08/25/95 9 ND ND ND ND 0.84 ND ND ND ND ND ND ND ND ND ND ND ND 0.72


BF21 Grizzly Bay 08/24/95 9 ND ND ND ND 0.70 ND ND ND ND ND ND ND ND ND ND ND ND ND

BF40 Honker Bay 08/24/95 9 ND ND ND ND 0.79 ND ND ND ND ND ND ND ND ND ND ND ND ND



Appendices

A–47

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Sum

of D

DT

s (S

FE

I)

o,p'

-DD

D

o,p'

-DD

E

o,p'

-DD

T

p,p'

-DD

D

p,p'

-DD

E

p,p'

-DD

T

Sum

of C

hlor

dane

s (S

FE

I)

Alp

ha-C

hlor

dane

Gam

ma-

Chl

orda

ne

cis-

Non

achl

or

tran

s-N

onac

hlor

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 1.322 ND ND ND 0.532 0.79 ND ND ND ND ND NDBA21 South Bay 02/21/95 7 0.924 ND ND ND 0.456 0.469 ND ND ND ND ND NDBA30 Dumbarton Bridge 02/21/95 7 0.94 ND ND ND 0.492 0.448 ND ND ND ND ND NDBA41 Redwood Creek 02/21/95 7 0.846 ND ND ND 0.422 0.424 ND ND ND ND ND NDBB15 San Bruno Shoal 02/21/95 7 0.753 ND ND ND 0.401 0.353 ND ND ND ND ND NDBB30 Oyster Point 02/20/95 7 0.883 ND ND ND 0.511 0.372 ND ND ND ND ND NDBB70 Alameda 02/21/95 7 1.255 ND ND ND 0.777 0.478 ND ND ND ND ND NDBC11 Yerba Buena Island 02/20/95 7 1.765 0.202 ND ND 1.03 0.532 ND ND ND ND ND NDBC21 Horseshoe Bay 02/20/95 7 2.021 0.275 ND ND 1.232 0.513 ND 0.257 0.257 ND ND NDBC32 Richardson Bay 02/20/95 7 1.343 0.258 ND ND 0.624 0.461 ND ND ND ND ND NDBC41 Point Isabel 02/20/95 7 1.344 ND ND ND 0.93 0.413 ND ND ND ND ND NDBC60 Red Rock 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBD15 Petaluma River 02/17/95 7 0.893 ND ND ND 0.473 0.42 ND ND ND ND ND NDBD22 San Pablo Bay 02/17/95 7 1.038 ND ND ND 0.552 0.486 ND ND ND ND ND NDBD31 Pinole Point 02/17/95 7 0.594 ND ND ND ND 0.594 ND ND ND ND ND NDBD41 Davis Point 02/17/95 7 0.836 ND ND ND 0.32 0.516 ND ND ND ND ND NDBD50 Napa River 02/17/95 7 1.285 ND ND ND 0.691 0.594 ND ND ND ND ND NDBF10 Pacheco Creek 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBF21 Grizzly Bay 02/16/95 7 1.068 ND ND ND 0.587 0.481 ND ND ND ND ND NDBF40 Honker Bay 02/16/95 7 1.668 ND ND ND 0.641 1.027 ND ND ND ND ND NDBG20 Sacramento River 02/16/95 7 0.422 ND ND ND 0.169 0.253 ND ND ND ND ND NDBG30 San Joaquin River 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBA10 Coyote Creek 08/30/95 9 6.87 0.74 ND ND 2.91 2.7 0.52 1.69 0.44 0.32 0.39 0.54BA21 South Bay 08/29/95 9 5.6 0.52 ND ND 2.55 2.02 0.51 0.94 0.29 ND 0.31 0.34BA30 Dumbarton Bridge 08/30/95 9 4.68 0.52 ND ND 2.14 1.68 0.34 0.25 ND ND 0.25 NDBA41 Redwood Creek 08/29/95 9 2.47 0.46 ND ND 1.05 0.96 ND ND ND ND ND NDBB15 San Bruno Shoal 08/29/95 9 2.88 0.64 ND ND 1.35 0.89 ND ND ND ND ND NDBB30 Oyster Point 08/30/95 9 2.79 0.39 ND ND 1.43 0.97 ND ND ND ND ND NDBB70 Alameda 08/28/95 9 4.63 1.08 ND ND 2.07 1.48 ND ND ND ND ND NDBC11 Yerba Buena Island 08/28/95 9 6.52 0.64 ND ND 2.18 1.31 2.39 ND ND ND ND NDBC21 Horseshoe Bay 08/28/95 9 2.32 0.24 ND ND 1.4 0.68 ND ND ND ND ND NDBC32 Richardson Bay 08/28/95 9 3.15 0.39 ND ND 1.56 0.91 0.29 ND ND ND ND NDBC41 Point Isabel 08/28/95 9 4.03 0.76 ND ND 2.1 1.17 ND ND ND ND ND NDBC60 Red Rock 08/25/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBD15 Petaluma River 08/25/95 9 1.44 ND ND ND 0.95 0.49 ND ND ND ND ND NDBD22 San Pablo Bay 08/25/95 9 3.98 0.72 ND ND 1.56 1.46 0.24 ND ND ND ND NDBD31 Pinole Point 08/25/95 9 3.57 0.49 ND ND 1.29 1.54 0.25 ND ND ND ND NDBD41 Davis Point 08/25/95 9 1.07 ND ND ND 0.49 0.58 ND ND ND ND ND NDBD50 Napa River 08/25/95 9 4.77 0.67 ND ND 2.12 1.98 ND ND ND ND ND NDBF10 Pacheco Creek 08/24/95 9 1.3 0.21 ND ND 0.48 0.61 ND ND ND ND ND NDBF21 Grizzly Bay 08/24/95 9 4.57 0.56 ND ND 1.93 1.61 0.47 ND ND ND ND NDBF40 Honker Bay 08/24/95 9 4.17 0.62 ND ND 1.75 1.8 ND ND ND ND ND NDBG20 Sacramento River 08/24/95 9 1.02 ND ND ND 0.46 0.56 ND ND ND ND ND NDBG30 San Joaquin River 08/24/95 9 ND ND ND ND ND ND ND ND ND ND ND ND

Table 15. Pesticide concentrations in sediment samples, 1995.ND = not detected. Data in dry weight.

A–48


Table 15. Pesticide concentrations in sediment samples, 1995 (continued).ND = not detected. Data in dry weight.

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Hep

tach

lor

Hep

tach

lor E

poxi

de

Oxy

chlo

rdan

e

Ald

rin

Die

ldrin

End

rin

Alp

ha-H

CH

Bet

a-H

CH

Del

ta-H

CH

Gam

ma-

HC

H

Hex

achl

orob

enze

ne

Mire

x

ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g ng/g

BA10 Coyote Creek 02/22/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBA21 South Bay 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBA30 Dumbarton Bridge 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBA41 Redwood Creek 02/21/95 7 ND ND ND ND ND ND 0.262 ND ND ND ND NDBB15 San Bruno Shoal 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBB30 Oyster Point 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBB70 Alameda 02/21/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBC11 Yerba Buena Island 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBC21 Horseshoe Bay 02/20/95 7 ND ND ND ND ND ND 0.33 ND ND ND ND NDBC32 Richardson Bay 02/20/95 7 ND ND ND ND ND ND 0.291 ND ND ND ND NDBC41 Point Isabel 02/20/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBC60 Red Rock 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBD15 Petaluma River 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBD22 San Pablo Bay 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBD31 Pinole Point 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBD41 Davis Point 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBD50 Napa River 02/17/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBF10 Pacheco Creek 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBF21 Grizzly Bay 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBF40 Honker Bay 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBG20 Sacramento River 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBG30 San Joaquin River 02/16/95 7 ND ND ND ND ND ND ND ND ND ND ND NDBA10 Coyote Creek 08/30/95 9 ND ND ND ND 0.34 ND ND 0.41 ND ND ND NDBA21 South Bay 08/29/95 9 ND ND ND ND 0.33 ND ND ND ND ND ND NDBA30 Dumbarton Bridge 08/30/95 9 ND ND ND ND ND ND ND 0.31 ND ND ND NDBA41 Redwood Creek 08/29/95 9 ND ND ND ND 0.27 ND ND ND ND ND ND NDBB15 San Bruno Shoal 08/29/95 9 ND ND ND ND 0.22 ND ND ND ND ND ND NDBB30 Oyster Point 08/30/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBB70 Alameda 08/28/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBC11 Yerba Buena Island 08/28/95 9 ND ND ND ND ND ND ND ND ND 0.32 0.51 NDBC21 Horseshoe Bay 08/28/95 9 ND ND ND ND ND ND ND ND ND ND 0.56 NDBC32 Richardson Bay 08/28/95 9 ND ND ND ND ND ND ND 0.28 ND ND ND NDBC41 Point Isabel 08/28/95 9 ND ND ND ND 0.29 ND ND ND ND ND ND NDBC60 Red Rock 08/25/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBD15 Petaluma River 08/25/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBD22 San Pablo Bay 08/25/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBD31 Pinole Point 08/25/95 9 ND ND ND ND 0.23 ND 0.4 ND ND ND ND NDBD41 Davis Point 08/25/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBD50 Napa River 08/25/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBF10 Pacheco Creek 08/24/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBF21 Grizzly Bay 08/24/95 9 ND ND ND ND 0.27 ND ND ND ND ND 0.45 NDBF40 Honker Bay 08/24/95 9 ND ND ND ND 0.25 ND ND ND ND ND 0.31 NDBG20 Sacramento River 08/24/95 9 ND ND ND ND ND ND ND ND ND ND ND NDBG30 San Joaquin River 08/24/95 9 ND ND ND ND ND ND ND ND ND ND ND ND

Appendices

A–49

Myt

ilus

Eoh

aust

oriu

s

Sta

tion

Cod

eS

tatio

nD

ate

Mea

n %

Nor

mal

D

evel

opm

ent

SD

- M

ean

% N

orm

al

Dev

elop

men

tM

ean

% S

urvi

val

SD

- M

ean

% S

urvi

val

Con

trol

N/A

N/A

952.

696

4.2

BA

21S

outh

Bay

02/2

2/95

924

76*

6.5

BA

41R

edw

ood

Cre

ek02

/21/

9594

5.9

75*

11.2

BB

15S

an B

runo

Sho

al02

/21/

9590

7.8

77*

9.7

BB

70A

lam

eda

02/2

1/95

973.

354

*23

BC

11Y

erba

Bue

na Is

land

02/2

0/95

938

899.

6B

C21

Hor

sesh

oe B

ay02

/20/

9590

2.8

869.

6B

C60

Red

Roc

k02

/17/

9539

*5

974.

5B

D41

Dav

is P

oint

02/1

7/95

945.

494

8.2

BD

50N

apa

Riv

er02

/17/

9592

5.9

78*

13B

F21

Griz

zly

Bay

02/1

6/95

0*0

80*

9.4

BG

20S

acra

men

to R

iver

02/1

6/95

0*0

956.

1B

G30

San

Joa

quin

Riv

er02

/16/

950*

080

*7.

9

Myt

ilus

Eoh

aust

oriu

s

Sta

tion

Cod

eS

tatio

nD

ate

Mea

n %

Nor

mal

D

evel

opm

ent

SD

- M

ean

% N

orm

al

Dev

elop

men

tM

ean

% S

urvi

val

SD

- M

ean

% S

urvi

val

Con

trol

N/A

N/A

[109

]6

100

0B

A21

Sou

th B

ay08

/29/

9597

991

9B

A41

Red

woo

d C

reek

08/2

9/95

9816

63*

26B

B15

San

Bru

no S

hoal

08/2

9/95

[101

]6

8311

BB

70A

lam

eda

08/2

8/95

85*

886

13B

C11

Yer

ba B

uena

Isla

nd08

/28/

9577

*8

54*

19B

C21

Hor

sesh

oe B

ay08

/28/

9599

389

*4

BC

60R

ed R

ock

08/2

5/95

9510

944

BD

41D

avis

Poi

nt08

/25/

9510

03

962

BD

50N

apa

Riv

er08

/25/

9510

08

85*

4B

F21

Griz

zly

Bay

08/2

4/95

39*

293

4B

G20

Sac

ram

ento

Riv

er08

/24/

950*

010

00

BG

30S

an J

oaqu

in R

iver

08/2

4/95

0*0

964

* S

igni

fican

tly d

iffer

ent f

rom

labo

rato

ry c

ontro

ls b

ased

on

sepa

rate

-var

ianc

e t-t

ests

(1 ta

iled,

alp

ha =

0.0

1).

[ ] V

alue

s ar

e >1

00%

bec

ause

mor

e la

rvae

wer

e co

unte

d at

the

end

of th

e te

st th

an in

ocul

ated

em

bryo

s at

the

begi

nnin

g of

the

test

.

Tab

le 1

6. S

edim

ent

toxi

city

dat

a fo

r 19

95 R

MP

cru

ises

.

A–50


Station Code Station Date C

ruis

e

SpeciesCondition Index–

Mean Condition Index–

Standard DeviationSurvival Per Species (%)

BA10 Coyote Creek 4/25/95 7 CGIG 0.089 0.008 96.6BA30 Dumbarton Bridge 4/25/95 7 MCAL 0.103 0.01 18.1BA40 Redwood Creek 4/25/95 7 MCAL 0.136 0.03 17.5BB71 Alameda 4/25/95 7 MCAL 0.109 0.004 92.5BC10 Yerba Buena Island 4/25/95 7 MCAL 0.113 0.003 91.9BC21 Horseshoe Bay 4/26/95 7 MCAL 0.104 0.004 97.5BC61 Red Rock 4/26/95 7 MCAL 0.077 0.004 36.5BD15 Petaluma River 4/26/95 7 CFLU 0.144 0.013 65BD15 Petaluma River 4/26/95 7 CGIG . . 0BD20 San Pablo Bay 4/26/95 7 CGIG 0.075 0.004 91.9BD30 Pinole Point 4/26/95 7 MCAL . . 0BD40 Davis Point 4/26/95 7 CGIG 0.061 0.005 76.5BD50 Napa River 4/26/95 7 CGIG 0.033 0.002 83.2BF20 Grizzly Bay 4/27/95 7 CFLU 0.134 0.006 88.8BF20 Grizzly Bay 4/27/95 7 CGIG . . 0BF20 Grizzly Bay 4/27/95 7 OLUR . . 0BG20 Sacramento River 4/27/95 7 CFLU 0.116 0.007 62.3BG30 San Joaquin River 4/27/95 7 CFLU 0.123 0.005 70.6T-0 Lake Isabella 1/20/95 7 CFLU 0.159 0.005 NAT-0 Dabob Bay, WA 1/20/95 7 CGIG 0.055 0.003 NAT-0 Bodega Head 1/20/95 7 MCAL 0.074 0.002 NAT-1 Dabob Bay, WA 6/1/95 7 CGIG 0.108 0.011 NAT-1 Bodega Head 6/15/95 7 MCAL 0.089 0.002 NAT-1 Lake Isabella 6/16/95 7 CFLU 0.164 0.008 NA

BA10 Coyote Creek 9/12/95 9 CGIG 0.04 0.002 60BA30 Dumbarton Bridge 9/12/95 9 MCAL 0.059 0.002 89BA40 Redwood Creek 9/12/95 9 MCAL 0.059 0.001 96BB70 Alameda 9/12/95 9 MCAL 0.083 0.002 99BC10 Yerba Buena Island 9/12/95 9 MCAL 0.085 0.003 97BC21 Horseshoe Bay 9/13/95 9 MCAL 0.131 0.007 98BC21 Horseshoe Bay 9/13/95 9 OLUR . . 88BC61 Red Rock 9/13/95 9 MCAL 0.072 0.003 99BC61 Red Rock 9/13/95 9 OLUR . . 97BD15 Petaluma River 9/13/95 9 CFLU . . 2BD15 Petaluma River 9/13/95 9 CGIG 0.06 0.01 25BD15 Petaluma River 9/13/95 9 OLUR . . 0BD20 San Pablo Bay 9/13/95 9 CGIG NA NA NABD30 Pinole Point 9/13/95 9 MCAL 0.067 0.002 99BD30 Pinole Point 9/13/95 9 OLUR . . 97BD40 Davis Point 9/13/95 9 CGIG 0.11 0.03 64BD40 Davis Point 9/13/95 9 OLUR . . 50BD50 Napa River 9/13/95 9 CGIG 0.06 0.01 33BF20 Grizzly Bay 9/14/95 9 CFLU 0.099 0.003 96BF20 Grizzly Bay 9/14/95 9 OLUR . . 0BG20 Sacramento River 9/14/95 9 CFLU 0.085 0.005 90BG30 San Joaquin River 9/14/95 9 CFLU 0.091 0.004 76T-0 Lake Isabella 6/16/95 9 CFLU 0.164 0.008 NAT-0 Tomales Bay 6/16/95 9 CGIG 0.15 0.01 NAT-0 Bodega Head 6/16/95 9 MCAL 0.089 0.002 NAT-1 Lake Isabella 9/14/95 9 CFLU 0.137 . .T-1 Tomales Bay 9/14/95 9 CGIG 0.149 . .T-1 Bodega Head 9/14/95 9 MCAL 0.106 . .

CGIG–Crassostrea gigas , CFLU–Corbicula fluminea , MCAL–Mytilus californianus , OLUR–Ostrea lurida

Table 17. Bivalve condition index and survival, 1995.. = no data, NA = not analyzed

Appendices

A–51

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Spe

cies

A g Al As C d Cr C u H g Ni mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg

BA10 Coyote Creek 4/25/95 7 CGIG 6.25 417 5.6 10.6 5.6 218 0.174 5

BA30 Dumbarton Bridge 4/25/95 7 MCAL 0.13 326 10.9 2.1 34.4 9 0.222 29

BA40 Redwood Creek 4/25/95 7 MCAL 0.24 286 9.1 3.1 21.4 7 0.181 18

BB71 Alameda 4/25/95 7 MCAL 0.16 786 12.0 3.9 19.4 10 0.233 17

BC10 Yerba Buena Island 4/25/95 7 MCAL 0.09 955 10.8 3.4 21.8 9 0.250 18

BC21 Horseshoe Bay 4/26/95 7 MCAL 0.23 699 13.2 4.7 43.2 12 0.284 35

BC61 Red Rock 4/26/95 7 MCAL 0.16 1042 10.8 6.9 61.9 12 0.277 51

BD15 Petaluma River 4/26/95 7 CFLU 0.17 534 19.0 0.5 6.0 38 0.146 7

BD20 San Pablo Bay 4/26/95 7 CGIG 2.39 403 7.4 16.4 18.7 282 0.139 15

BD40 Davis Point 4/26/95 7 CGIG 5.33 871 9.8 20.0 16.0 245 0.158 13

BD50 Napa River 4/26/95 7 CGIG 2.37 425 7.9 36.5 77.2 285 0.138 62

BF20 Grizzly Bay 4/27/95 7 CFLU 0.11 437 18.8 0.6 12.0 46 0.150 9

BG20 Sacramento River 4/27/95 7 CFLU 0.06 187 18.3 0.4 5.8 26 0.149 5

BG30 San Joaquin River 4/27/95 7 CFLU 0.05 104 19.9 0.3 9.0 17 0.158 7

T-0 Lake Isabella 1/20/95 7 CFLU 0.08 94 16.7 0.6 8.2 45 0.121 6

T-0 Dabob Bay, WA 1/20/95 7 CGIG 3.60 14 8.7 6.7 20.3 110 0.103 15

T-0 Bodega Head 1/20/95 7 MCAL 0.13 188 14.9 8.5 63.8 10 0.301 54

BA10 Coyote Creek 9/12/95 9 CGIG 2.16 435 16.4 16.2 9.1 867 0.349 8

BA30 Dumbarton Bridge 9/12/95 9 MCAL 0.44 250 14.0 7.7 14.3 7 0.292 13

BA40 Redwood Creek 9/12/95 9 MCAL 0.36 305 16.3 7.4 31.3 7 0.313 26

BB71 Alameda 9/12/95 9 MCAL 0.27 383 17.2 7.9 42.2 10 0.358 32

BC10 Yerba Buena Island 9/12/95 9 MCAL 0.27 626 13.9 6.8 6.5 9 0.370 6

BC21 Horseshoe Bay 9/13/95 9 MCAL 0.24 350 10.3 4.5 4.8 8 0.165 4

BC61 Red Rock 9/13/95 9 MCAL 0.09 604 15.3 5.2 9.5 8 0.320 7

BD15 Petaluma River 9/13/95 9 CGIG 3.59 262 10.6 17.3 5.3 520 0.239 4

BD30 Pinole Point 9/13/95 9 MCAL 0.19 390 18.3 7.4 11.9 8 0.390 10

BD40 Davis Point 9/13/95 9 CGIG 4.30 382 10.0 15.4 6.9 513 0.301 5

BD50 Napa River 9/13/95 9 CGIG 5.60 342 10.7 14.1 13.9 519 0.165 11

BF20 Grizzly Bay 9/14/95 9 CFLU 0.20 371 23.6 0.8 4.6 60 0.303 3

BG20 Sacramento River 9/14/95 9 CFLU 0.15 320 23.8 1.0 8.8 59 0.289 6

BG30 San Joaquin River 9/14/95 9 CFLU 0.18 383 23.8 1.0 6.7 60 0.295 5

T-0 Lake Isabella 6/16/95 9 CFLU 0.09 141 18.3 0.6 1.3 37 0.168 1

T-0 Tomales Bay 6/16/95 9 CGIG 1.74 166 9.1 7.1 3.2 106 0.230 2

T-0 Bodega Head 6/16/95 9 MCAL 0.09 181 18.8 5.5 4.4 5 0.288 4

CGIG—Crassostrea gigas , CFLU—Corbicula fluminea , MCAL—Mytilus californianus * Tins are reported in terms of total tin.

Table 18. Trace element concentrations in bivalve tissues, 1995.. = no data, ND = not detected. Data expressed as dry weight. T-0 = time of bivalvedeployment into the Estuary from the source indicated under station name heading.

A–52


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Spe

cies

P b S e Z n DBT MBT TBT TTBT mg/kg mg/kg mg/kg µg/kg Sn* µg/kg Sn* µg/kg Sn* µg/kg Sn*

BA10 Coyote Creek 4/25/95 7 CGIG 0.52 4.0 1443 ND ND 53 ND

BA30 Dumbarton Bridge 4/25/95 7 MCAL 0.69 1.9 114 ND ND 42 ND

BA40 Redwood Creek 4/25/95 7 MCAL 0.33 2.1 69 12 ND 23 ND

BB71 Alameda 4/25/95 7 MCAL 0.27 4.5 157 11 ND 53 ND

BC10 Yerba Buena Island 4/25/95 7 MCAL 2.50 3.1 124 14 ND 73 ND

BC21 Horseshoe Bay 4/26/95 7 MCAL 0.43 4.4 179 10 ND 57 ND

BC61 Red Rock 4/26/95 7 MCAL 0.63 3.4 193 ND ND 63 ND

BD15 Petaluma River 4/26/95 7 CFLU 0.44 1.6 84 ND ND 50 ND

BD20 San Pablo Bay 4/26/95 7 CGIG 0.23 5.4 1312 ND ND 112 ND

BD40 Davis Point 4/26/95 7 CGIG 0.29 6.5 1282 ND ND 111 ND

BD50 Napa River 4/26/95 7 CGIG 0.29 6.2 1613 ND ND 127 ND

BF20 Grizzly Bay 4/27/95 7 CFLU 0.50 1.4 68 12 ND 33 ND

BG20 Sacramento River 4/27/95 7 CFLU 0.07 1.7 33 10 ND 17 ND

BG30 San Joaquin River 4/27/95 7 CFLU 0.09 1.9 29 9 ND 26 ND

T-0 Lake Isabella 1/20/95 7 CFLU 0.13 1.6 68 ND ND 8 ND

T-0 Dabob Bay, WA 1/20/95 7 CGIG 0.14 1.6 859 ND ND 39 ND

T-0 Bodega Head 1/20/95 7 MCAL 0.89 3.4 198 ND ND ND ND

BA10 Coyote Creek 9/12/95 9 CGIG 1.32 11.0 2050 ND ND 18 ND

BA30 Dumbarton Bridge 9/12/95 9 MCAL 2.13 3.3 237 ND ND 1 ND

BA40 Redwood Creek 9/12/95 9 MCAL 2.87 3.1 303 ND ND 10 ND

BB71 Alameda 9/12/95 9 MCAL 2.09 3.3 266 22 ND 24 ND

BC10 Yerba Buena Island 9/12/95 9 MCAL 2.13 3.4 213 ND ND 68 ND

BC21 Horseshoe Bay 9/13/95 9 MCAL 1.49 4.3 127 ND ND 36 ND

BC61 Red Rock 9/13/95 9 MCAL 1.91 2.8 200 ND ND 23 ND

BD15 Petaluma River 9/13/95 9 CGIG 0.49 9.7 1217 ND ND 26 ND

BD30 Pinole Point 9/13/95 9 MCAL 1.79 2.7 217 ND ND 14 ND

BD40 Davis Point 9/13/95 9 CGIG 0.69 4.2 1207 ND ND 72 ND

BD50 Napa River 9/13/95 9 CGIG 0.54 7.2 1257 16 ND 55 ND

BF20 Grizzly Bay 9/14/95 9 CFLU 0.37 2.9 92 41 ND 48 ND

BG20 Sacramento River 9/14/95 9 CFLU 0.24 2.4 91 ND ND 23 ND

BG30 San Joaquin River 9/14/95 9 CFLU 0.25 2.3 96 ND ND 22 37.80

T-0 Lake Isabella 6/16/95 9 CFLU 0.14 1.6 72 ND ND ND ND

T-0 Tomales Bay 6/16/95 9 CGIG 0.17 4.3 454 ND ND 2 ND

T-0 Bodega Head 6/16/95 9 MCAL 1.26 5.1 150 ND ND 1 ND

CGIG—Crassostrea gigas , CFLU—Corbicula fluminea , MCAL—Mytilus californianus * Tins are reported in terms of total tin.

Table 18. Trace element concentrations in bivalve tissues, 1995 (continued).. = no data, ND = not detected. Data expressed as dry weight. T-0 = time of bivalvedeployment into the Estuary from the source indicated under station name heading.

Appendices

A–53

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Spe

cies

Tot

al P

AH

s (S

FE

I)

Tot

al L

PA

Hs

(SF

EI)

Tot

al H

PA

Hs

(SF

EI)

1-M

ethy

lnap

htha

lene

1-M

ethy

lphe

nant

hren

e

2,3,

5-Tr

imet

hyln

apht

hale

ne

2,6-

Dim

ethy

lnap

htha

lene

2-M

ethy

lnap

htha

lene

Ace

naph

then

e

Ace

naph

thyl

ene

Ant

hrac

ene

Ben

z(a)

anth

race

ne

Ben

zo(a

)pyr

ene

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 04/25/95 7 CGIG 557 10 547 ND ND ND ND ND ND ND 10 24 22

BA30 Dumbarton Bridge 04/25/95 7 MCAL 65 19 46 ND ND ND ND 19 ND ND ND ND ND

BA40 Redwood Creek 04/25/95 7 MCAL 54 0 54 ND ND ND ND ND ND ND ND ND ND

BB71 Alameda 04/25/95 7 MCAL 209.04 22 188 ND 12 ND ND ND ND ND 9 9 12

BC10 Yerba Buena Island 04/25/95 7 MCAL 128.29 15 113 ND ND ND ND ND 8 ND 7 ND 4

BC21 Horseshoe Bay 04/26/95 7 MCAL 127.95 36 92 ND ND ND ND 19 9 ND 8 ND 4

BC60 Red Rock 04/26/95 7 MCAL 105.04 0 105 ND ND ND ND ND ND ND ND ND 6

BD15 Petaluma River 04/26/95 7 CFLU 561.18 56 505 ND 9 12 8 17 ND ND 11 10 6

BD20 San Pablo Bay 04/26/95 7 CGIG 311.05 0 311 ND ND ND ND ND ND ND ND 12 12

BD40 Davis Point 04/26/95 7 CGIG 597.06 21 577 ND ND ND 21 ND ND ND ND 39 15

BD50 Napa River 04/26/95 7 CGIG 658.16 0 658 ND ND ND ND ND ND ND ND 44 14

BF20 Grizzly Bay 04/27/95 7 CFLU 211.46 5 206 ND 5 ND ND ND ND ND ND 7 ND

BG20 Sacramento River 04/27/95 7 CFLU 231.25 26 205 ND 7 ND 11 ND ND ND 8 14 ND

BG30 San Joaquin River 04/27/95 7 CFLU 190.74 5 186 ND 5 ND ND ND ND ND ND 8 ND

T-0 Lake Isabella 01/20/95 7 CFLU 154.68 32 123 8 ND ND 6 12 ND ND 6 ND ND

T-0 Dabob Bay, WA 01/20/95 7 CGIG 145.69 9 137 ND ND ND ND ND ND ND 9 7 ND

T-0 Bodega Head 01/20/95 7 MCAL 63.94 21 42 ND ND ND 8 10 ND ND 3 ND ND

BA10 Coyote Creek 09/12/95 9 CGIG 809.09 8 801 ND ND ND ND ND ND ND 8 30 49

BA30 Dumbarton Bridge 09/12/95 9 MCAL 68.39 7 62 ND ND ND ND ND ND ND 7 ND ND

BA40 Redwood Creek 09/12/95 9 MCAL 111.17 17 94 ND ND ND ND 11 ND ND 6 6 6

BB71 Alameda 09/12/95 9 MCAL 129.72 16 114 ND ND ND ND 8 ND ND 8 6 6

BC10 Yerba Buena Island 09/12/95 9 MCAL 184.08 27 158 ND ND ND ND 9 ND 5 13 8 6

BC21 Horseshoe Bay 09/13/95 9 MCAL 131.97 26 106 ND ND ND ND 12 5 ND 9 5 3

BC60 Red Rock 09/13/95 9 MCAL 101.26 16 85 ND ND ND ND 8 ND ND 8 5 4

BD15 Petaluma River 09/13/95 9 CGIG 1139.27 37 1102 ND ND ND ND 11 ND 8 18 45 73

BD30 Pinole Point 09/13/95 9 MCAL 72.74 8 64 ND ND ND ND ND ND ND 8 ND ND

BD40 Davis Point 09/13/95 9 CGIG 735.28 17 719 ND ND ND ND ND ND ND 17 46 25

BD50 Napa River 09/13/95 9 CGIG 783.52 70 713 7 12 ND 7 11 7 7 19 46 23

BF20 Grizzly Bay 09/14/95 9 CFLU 527.17 45 482 ND ND ND ND 7 ND 9 29 23 7

BG20 Sacramento River 09/14/95 9 CFLU 302.38 30 272 ND ND ND ND 13 ND 6 11 12 ND

BG30 San Joaquin River 09/14/95 9 CFLU 354.58 39 315 ND 13 ND ND 8 ND 6 14 15 ND

T-0 Lake Isabella 06/16/95 9 CFLU 66.26 8 58 ND ND ND ND 6 ND ND 3 ND ND

T-0 Tomales Bay 06/16/95 9 CGIG 134.07 47 87 12 ND ND 7 26 ND ND 2 3 ND

T-0 Bodega Head 06/16/95 9 MCAL 30.69 10 21 ND ND ND ND 8 ND ND 2 ND ND

CGIG—Crassostrea gigas , CFLU—Corbicula fluminea , MCAL—Mytilus californianus

Table 19. PAH concentrations in bivalve tissues, 1995.. = no data, ND = not detected. Data expressed as dry weight. T-0 = time of bivalve deployment intothe Estuary from the source indicated under station name heading. LPAHs= low molecular weightPAHs, HPAHs = high molecular weight PAHs.

A–54


Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Spe

cies

Ben

zo(b

)flu

oran

then

e

Ben

zo(e

)pyr

ene

Ben

zo(g

hi)p

eryl

ene

Ben

zo(k

)flu

oran

then

e

Bip

heny

l

Chr

ysen

e

Dib

enz(

a,h)

anth

race

ne

Dib

enzo

thio

phen

e

Flu

oran

then

e

Flu

oren

e

Inde

no(1

,2,3

-cd)

pyre

ne

Nap

htha

lene

Per

ylen

e

Phe

nant

hren

e

Pyr

ene

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 04/25/95 7 CGIG 53 55 25 17 ND 59 ND ND 88 ND 11 22 ND 37 135

BA30 Dumbarton Bridge 04/25/95 7 MCAL ND ND ND ND ND 5 ND ND 6 ND ND 16 ND 11 9

BA40 Redwood Creek 04/25/95 7 MCAL ND ND ND ND ND 8 ND ND 6 ND ND 20 ND 12 8

BB71 Alameda 04/25/95 7 MCAL 11 7 9 4 ND 15 ND ND 24 6 6 22 ND 26 35

BC10 Yerba Buena Island 04/25/95 7 MCAL 6 5 5 ND ND 8 ND ND 15 8 ND 22 ND 22 19

BC21 Horseshoe Bay 04/26/95 7 MCAL 5 5 ND ND ND 11 ND ND ND 10 ND 23 ND 33 ND

BC60 Red Rock 04/26/95 7 MCAL ND 5 ND ND ND 10 ND ND 15 ND ND 30 ND 20 20

BD15 Petaluma River 04/26/95 7 CFLU 11 15 9 5 ND 34 ND 5 147 10 5 14 ND 61 172

BD20 San Pablo Bay 04/26/95 7 CGIG 20 21 8 8 ND 28 ND ND 67 ND ND 27 ND 28 82

BD40 Davis Point 04/26/95 7 CGIG 35 28 14 34 ND 49 ND ND 129 14 7 30 ND 67 115

BD50 Napa River 04/26/95 7 CGIG 36 37 ND 24 ND 75 ND ND 153 ND ND 47 ND 67 163

BF20 Grizzly Bay 04/27/95 7 CFLU 4 6 ND ND 5 22 ND ND 66 ND ND ND ND 27 69

BG20 Sacramento River 04/27/95 7 CFLU ND 2 ND ND ND 15 ND ND 69 ND ND 14 ND 32 59

BG30 San Joaquin River 04/27/95 7 CFLU 4 4 ND ND ND 19 ND ND 42 ND ND 16 ND 26 67

T-0 Lake Isabella 01/20/95 7 CFLU ND ND ND ND ND ND ND 3 24 11 ND 20 4 43 18

T-0 Dabob Bay, WA 01/20/95 7 CGIG 8 6 ND ND ND ND ND ND 34 ND ND 36 ND 11 34

T-0 Bodega Head 01/20/95 7 MCAL ND ND ND ND ND ND ND 2 4 ND ND 19 ND 13 4

BA10 Coyote Creek 09/12/95 9 CGIG 131 100 68 28 ND 64 7 4 91 ND 29 17 23 21 139

BA30 Dumbarton Bridge 09/12/95 9 MCAL 5 3 4 ND ND ND ND 4 7 ND ND 13 ND 11 14

BA40 Redwood Creek 09/12/95 9 MCAL 8 5 5 ND ND ND ND 5 10 ND ND 17 4 10 18

BB71 Alameda 09/12/95 9 MCAL 6 5 5 4 ND 9 ND 3 16 ND ND 15 ND 13 27

BC10 Yerba Buena Island 09/12/95 9 MCAL 9 6 6 ND ND 12 ND 3 27 9 4 14 3 24 27

BC21 Horseshoe Bay 09/13/95 9 MCAL 4 3 5 ND ND 5 ND 3 17 6 ND 12 ND 24 18

BC60 Red Rock 09/13/95 9 MCAL 6 3 5 ND ND 6 ND 2 10 5 ND 12 3 10 13

BD15 Petaluma River 09/13/95 9 CGIG 146 111 56 40 ND 88 6 5 143 ND 35 15 64 17 258

BD30 Pinole Point 09/13/95 9 MCAL 6 4 4 ND ND ND ND 5 8 ND ND 14 ND 10 13

BD40 Davis Point 09/13/95 9 CGIG 73 59 19 20 ND 62 3 5 158 ND 11 10 28 24 175

BD50 Napa River 09/13/95 9 CGIG 61 53 20 21 ND 65 5 7 145 8 10 12 32 27 177

BF20 Grizzly Bay 09/14/95 9 CFLU 19 24 8 3 ND 43 ND 3 130 ND 4 12 15 19 172

BG20 Sacramento River 09/14/95 9 CFLU 10 12 5 3 ND 33 ND 5 59 ND ND 12 6 10 105

BG30 San Joaquin River 09/14/95 9 CFLU 9 13 4 ND ND 37 ND 2 58 ND ND 12 6 11 148

T-0 Lake Isabella 06/16/95 9 CFLU 3 2 ND ND ND 7 ND 1 16 ND ND 6 3 6 13

T-0 Tomales Bay 06/16/95 9 CGIG ND 2 ND ND ND 8 ND 2 18 ND ND 16 4 12 23

T-0 Bodega Head 06/16/95 9 MCAL ND ND ND ND ND ND ND 2 ND ND ND 11 ND 4 4


Table 19. PAH concentrations in bivalve tissues, 1995 (continued).. = no data, ND = not detected. Data expressed as dry weight. T-0 = time of bivalve deployment into theEstuary from the source indicated under station name heading. LPAHs = low molecular weight PAHs, HPAHS= high molecular weight PAHs

Appendices

A–55

Table 20. PCB congeners in bivalve tissues, 1995.M = matrix interference, ND = not detected. Data expressed as dry weight. T-0 = time of bivalve deployment intothe Estuary from the source indicated under station name heading.

Sta

tion

C

od

e

Sta

tio

n

Da

te

Cru

ise

Sp

ec

ies

Tot

al

PC

Bs

(SF

EI)

PC

B

00

7/9

PC

B

00

8/5

PC

B

01

5

PC

B

01

6/3

2

PC

B

01

8

PC

B

02

2/5

1

PC

B

02

4/2

7

PC

B

02

5

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 4/25/95 7 CGIG 457 ND ND ND ND ND ND ND 3.1

BA30 Dumbarton Bridge 4/25/95 7 MCAL 191 ND ND ND ND ND ND ND 3.2

BA40 Redwood Creek 4/25/95 7 MCAL 174 ND ND ND ND ND ND ND 3.0

BB71 Alameda 4/25/95 7 MCAL 180 ND ND ND ND ND ND ND ND

BC10 Yerba Buena Island 4/25/95 7 MCAL 171 ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 4/26/95 7 MCAL 95 ND ND ND ND ND ND ND ND

BC60 Red Rock 4/26/95 7 MCAL 79 ND ND ND ND ND ND ND ND

BD15 Petaluma River 4/26/95 7 CFLU 286 ND ND ND ND 1.7 ND ND 4.0

BD20 San Pablo Bay 4/26/95 7 CGIG 144 ND ND ND ND ND ND ND ND

BD40 Davis Point 4/26/95 7 CGIG 92 ND ND ND ND ND ND ND ND

BD50 Napa River 4/26/95 7 CGIG 148 ND ND ND ND ND ND ND ND

BF20 Grizzly Bay 4/27/95 7 CFLU 271 ND ND ND 3.9 2.7 2.8 ND ND

BG20 Sacramento River 4/27/95 7 CFLU 219 ND ND ND 4.1 ND ND 1.9 ND

BG30 San Joaquin River 4/27/95 7 CFLU 228 ND ND ND 4.3 ND ND ND ND

T-0 Lake Isabella 1/20/95 7 CFLU 70 ND ND ND ND ND ND ND ND

T-0 Dabob Bay, WA 1/20/95 7 CGIG 3 ND ND ND ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL 22 ND M ND 1.3 ND ND ND ND

BA10 Coyote Creek 9/12/95 9 CGIG 219 ND ND ND ND ND ND ND ND

BA30 Dumbarton Bridge 9/12/95 9 MCAL 130 ND ND ND ND ND ND ND ND

BA40 Redwood Creek 9/12/95 9 MCAL 132 ND ND ND ND ND ND ND ND

BB71 Alameda 9/12/95 9 MCAL 118 ND ND ND ND ND ND ND ND

BC10 Yerba Buena Island 9/12/95 9 MCAL 96 ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 9/13/95 9 MCAL 48 ND ND ND ND ND ND ND ND

BC60 Red Rock 9/13/95 9 MCAL 55 ND ND ND ND ND ND ND ND

BD15 Petaluma River 9/13/95 9 CGIG 322 ND ND ND ND ND ND ND ND

BD30 Pinole Point 9/13/95 9 MCAL 59 ND ND ND ND ND ND ND ND

BD40 Davis Point 9/13/95 9 CGIG 205 2.9 ND ND ND ND ND ND ND

BD50 Napa River 9/13/95 9 CGIG 159 ND ND ND ND ND ND ND ND

BF20 Grizzly Bay 9/14/95 9 CFLU 269 ND ND ND ND 2.6 ND ND ND

BG20 Sacramento River 9/14/95 9 CFLU 236 ND ND ND ND 4.0 ND ND ND

BG30 San Joaquin River 9/14/95 9 CFLU 223 ND ND 1.5 ND 4.0 ND ND 2.1

T-0 Lake Isabella 6/16/95 9 CFLU 14 ND ND ND ND ND ND ND ND

T-0 Tomales Bay 6/16/95 9 CGIG 64 ND ND ND ND ND ND ND ND

T-0 Bodega Head 6/16/95 9 MCAL 10 ND 2.8 ND ND ND ND 1.0 ND

PC

B

02

6

PC

B

02

8

PC

B

02

9

PC

B

03

1

µg/kg µg/kg µg/kg µg/kg

ND 2.2 3.4 ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND 1.5 ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND 2.7 ND

2.4 ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

ND ND ND ND

CGIG—Crassostrea gigas, CFLU—Corbicula fluminea, MCAL—Mytilus californianus

A–56


Table 20. PCB congeners in bivalve tissues, 1995 (continued).M = matrix interference, ND = not detected. Data expressed as dry weight. T-0 = time of bivalve deploymentinto the Estuary from the source indicated under station name heading.

Sta

tion

C

od

e

Sta

tio

n

Da

te

Cru

ise

Sp

ec

ies

PC

B

03

3/5

3/2

0

PC

B

03

7/4

2/5

9

PC

B

04

0

PC

B

04

1/6

4

PC

B

04

4

PC

B

04

5

PC

B

04

6

PC

B

04

7/4

8/7

5

PC

B

04

9


BA10 Coyote Creek 4/25/95 7 CGIG ND ND ND M 7.1 ND ND 3.0 6.0

BA30 Dumbarton Bridge 4/25/95 7 MCAL ND ND ND M 5.1 ND ND ND 3.4

BA40 Redwood Creek 4/25/95 7 MCAL ND ND ND M 5.4 ND ND ND 2.8

BB71 Alameda 4/25/95 7 MCAL ND ND ND M 2.5 ND ND ND 2.5

BC10 Yerba Buena Island 4/25/95 7 MCAL ND ND ND M 2.8 ND ND ND 2.8

BC21 Horseshoe Bay 4/26/95 7 MCAL ND ND ND M 1.9 ND ND ND 2.0

BC60 Red Rock 4/26/95 7 MCAL ND ND ND M ND ND ND ND ND

BD15 Petaluma River 4/26/95 7 CFLU ND ND ND M 7.7 ND ND ND 4.1

BD20 San Pablo Bay 4/26/95 7 CGIG ND ND ND M ND ND ND ND ND

BD40 Davis Point 4/26/95 7 CGIG ND ND ND M ND ND ND ND ND

BD50 Napa River 4/26/95 7 CGIG ND ND ND M ND ND ND ND ND

BF20 Grizzly Bay 4/27/95 7 CFLU ND ND ND M 6.3 ND ND ND 3.1

BG20 Sacramento River 4/27/95 7 CFLU ND 1.1 ND M 7.7 ND ND ND 3.7

BG30 San Joaquin River 4/27/95 7 CFLU ND ND ND M 6.9 ND ND ND 2.9

T-0 Lake Isabella 1/20/95 7 CFLU ND ND ND M 3.9 ND ND ND 1.6

T-0 Dabob Bay, WA 1/20/95 7 CGIG ND ND ND M ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL ND ND ND M ND ND ND ND ND

BA10 Coyote Creek 9/12/95 9 CGIG ND ND ND M ND ND ND 2.9 2.6

BA30 Dumbarton Bridge 9/12/95 9 MCAL ND ND ND M ND ND ND ND 2.4

BA40 Redwood Creek 9/12/95 9 MCAL ND ND ND M 2.0 ND ND ND 1.9

BB71 Alameda 9/12/95 9 MCAL ND ND ND M ND ND ND ND 1.5

BC10 Yerba Buena Island 9/12/95 9 MCAL ND ND ND M ND ND ND ND 1.3

BC21 Horseshoe Bay 9/13/95 9 MCAL ND ND ND M ND ND ND ND 1.1

BC60 Red Rock 9/13/95 9 MCAL ND ND ND M ND ND ND ND ND

BD15 Petaluma River 9/13/95 9 CGIG ND ND ND M 3.4 ND ND 1.9 ND

BD30 Pinole Point 9/13/95 9 MCAL ND ND ND M ND ND ND ND ND

BD40 Davis Point 9/13/95 9 CGIG ND ND ND M 2.2 ND ND 1.7 2.5

BD50 Napa River 9/13/95 9 CGIG ND ND ND M 1.6 ND ND ND 2.2

BF20 Grizzly Bay 9/14/95 9 CFLU ND 3.7 ND M 8.0 ND ND ND 4.0

BG20 Sacramento River 9/14/95 9 CFLU ND 4.7 ND M 8.6 ND ND ND 3.7

BG30 San Joaquin River 9/14/95 9 CFLU ND 3.9 ND M 8.3 ND ND ND 5.1

T-0 Lake Isabella 6/16/95 9 CFLU ND ND ND M ND ND ND ND ND

T-0 Tomales Bay 6/16/95 9 CGIG ND 1.4 ND M 3.5 ND ND ND 2.3

T-0 Bodega Head 6/16/95 9 MCAL ND ND ND M ND ND 2.1 ND ND


PC

B

05

2

PC

B

05

6/6

0

PC

B

06

6

PC

B

07

0

µg/kg µg/kg µg/kg µg/kg

12.8 5.7 3.6 10.6

5.6 ND 1.8 5.0

5.1 ND ND 4.7

4.1 1.9 ND 3.0

4.6 1.6 ND 3.7

3.1 2.7 ND ND

ND ND ND ND

16.4 3.9 1.9 15.2

3.1 3.7 ND ND

ND 3.5 ND ND

5.3 7.3 ND ND

15.8 4.8 ND 23.4

15.2 5.4 ND 18.9

17.9 4.5 2.2 19.4

2.4 ND 3.4 3.2

ND ND ND ND

ND ND ND ND

2.4 ND ND 2.3

2.5 1.9 ND 3.1

2.7 ND ND 2.7

2.6 1.3 ND 1.9

2.5 1.8 ND 2.2

1.8 ND ND 1.4

1.3 ND ND 1.3

5.7 3.7 2.7 5.4

ND ND ND ND

3.6 3.0 ND 3.4

3.1 1.7 ND 2.9

13.3 4.4 1.6 4.8

14.2 4.1 1.7 4.1

13.4 3.5 1.8 4.7

ND ND ND ND

4.3 1.4 ND 1.2

ND ND ND ND

Appendices

A–57

Table 20. PCB congeners in bivalve tissues, 1995 (continued).M = matrix interference, ND = not detected. Data expressed as dry weight. T-0 = time of bivalvedeployment into the Estuary from the source indicated under station name heading.

PC

B

09

9

PC

B

10

0

PC

B

10

1/9

0

µg/kg µg/kg µg/kg

12.4 ND 28.6

4.2 ND 11.7

4.2 ND 9.2

6.1 ND 11.0

5.3 ND 11.2

3.3 ND 6.5

3.1 ND 5.7

6.1 ND 14.4

5.1 ND 8.2

3.5 ND 6.2

7.9 ND 9.0

3.5 ND 7.9

3.2 ND 6.0

3.0 ND 7.1

1.7 ND 3.3

ND ND ND

ND ND ND

8.7 . 14.6

5.5 . 10.1

6.0 . 9.7

7.1 . 9.8

4.8 . 7.0

3.2 . 4.0

3.1 . 4.1

17.2 . 25.2

2.5 . 4.0

7.9 . 12.5

6.7 . 9.7

7.5 . 12.8

4.1 . 10.7

3.5 . 9.5

1.1 . 1.9

2.9 . 4.6

ND . ND

Sta

tion

C

od

e

Sta

tio

n

Da

te

Cru

ise

Sp

ec

ies

Tot

al

PC

Bs

(SF

EI)

PC

B

07

4

PC

B

08

2

PC

B

08

3

PC

B

08

4

PC

B

08

5

PC

B

08

7/1

15

PC

B

08

8

PC

B

09

2

PC

B

09

7

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 4/25/95 7 CGIG 457 5.1 3.6 ND 22.7 ND 5.4 8.6 9.8 8.7

BA30 Dumbarton Bridge 4/25/95 7 MCAL 191 3.2 2.1 ND 9.8 ND 2.1 5.6 ND 4.4

BA40 Redwood Creek 4/25/95 7 MCAL 174 2.9 ND ND 5.2 ND 2.4 4.8 ND 4.8

BB71 Alameda 4/25/95 7 MCAL 180 1.6 2.0 ND 3.5 ND 2.5 2.5 3.7 4.7

BC10 Yerba Buena Island 4/25/95 7 MCAL 171 2.1 3.3 ND 5.4 ND 2.5 2.5 2.2 4.0

BC21 Horseshoe Bay 4/26/95 7 MCAL 95 ND 2.2 ND 2.9 ND ND ND 2.5 3.0

BC60 Red Rock 4/26/95 7 MCAL 79 ND 2.6 ND 6.2 ND ND ND ND 3.4

BD15 Petaluma River 4/26/95 7 CFLU 286 2.3 2.9 3.4 14.3 ND 1.9 6.0 6.3 9.0

BD20 San Pablo Bay 4/26/95 7 CGIG 144 ND 5.2 ND 3.9 ND ND ND 3.6 5.6

BD40 Davis Point 4/26/95 7 CGIG 92 ND 3.1 ND 3.1 ND ND ND ND 3.2

BD50 Napa River 4/26/95 7 CGIG 148 ND ND ND 5.8 ND ND ND 5.0 5.7

BF20 Grizzly Bay 4/27/95 7 CFLU 271 1.7 8.2 1.5 3.9 ND 2.1 3.3 5.3 12.9

BG20 Sacramento River 4/27/95 7 CFLU 219 1.8 6.2 ND 2.1 ND 1.6 1.9 5.0 10.7

BG30 San Joaquin River 4/27/95 7 CFLU 228 ND 7.6 ND 4.1 ND 1.7 2.4 5.8 10.2

T-0 Lake Isabella 1/20/95 7 CFLU 70 ND ND ND ND ND ND ND 1.5 3.7

T-0 Dabob Bay, WA 1/20/95 7 CGIG 3 ND ND ND ND ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL 22 ND ND ND 14.4 ND ND ND ND ND

BA10 Coyote Creek 9/12/95 9 CGIG 219 ND ND ND ND ND 3.3 ND ND 4.2

BA30 Dumbarton Bridge 9/12/95 9 MCAL 130 ND ND ND 3.7 ND 2.2 1.9 ND 3.1

BA40 Redwood Creek 9/12/95 9 MCAL 132 ND ND ND 2.6 ND 1.9 ND ND 2.6

BB71 Alameda 9/12/95 9 MCAL 118 ND ND ND 1.4 ND 1.6 ND 1.5 2.1

BC10 Yerba Buena Island 9/12/95 9 MCAL 96 ND ND ND 1.2 ND ND ND ND 1.5

BC21 Horseshoe Bay 9/13/95 9 MCAL 48 ND 0.9 ND 1.7 ND ND ND ND 1.1

BC60 Red Rock 9/13/95 9 MCAL 55 ND ND ND ND ND ND ND ND 1.3

BD15 Petaluma River 9/13/95 9 CGIG 322 2.5 ND 3.4 4.8 ND 3.7 4.2 2.9 6.2

BD30 Pinole Point 9/13/95 9 MCAL 59 ND ND ND 2.7 ND ND ND ND 2.2

BD40 Davis Point 9/13/95 9 CGIG 205 1.9 1.7 ND 5.3 ND 1.9 2.2 6.7 3.9

BD50 Napa River 9/13/95 9 CGIG 159 1.6 1.6 ND 4.2 ND ND 1.8 5.8 3.1

BF20 Grizzly Bay 9/14/95 9 CFLU 269 2.1 2.8 1.2 6.5 ND 2.5 3.4 7.1 10.6

BG20 Sacramento River 9/14/95 9 CFLU 236 1.8 3.8 ND 4.1 ND 1.7 ND 6.2 9.1

BG30 San Joaquin River 9/14/95 9 CFLU 223 2.0 3.8 ND 4.8 ND 1.9 2.2 4.9 8.8

T-0 Lake Isabella 6/16/95 9 CFLU 14 ND ND ND 2.7 ND ND ND ND ND

T-0 Tomales Bay 6/16/95 9 CGIG 64 ND 2.1 ND 2.1 ND ND ND 1.3 2.9

T-0 Bodega Head 6/16/95 9 MCAL 10 ND ND ND M ND ND ND ND ND


A–58



Sta

tion

C

od

e

Sta

tio

n

Da

te

Cru

ise

Sp

ec

ies

PC

B

10

5

PC

B

10

7/1

08

/14

4

PC

B

11

0/7

7

PC

B

11

8

PC

B

12

8

PC

B

12

9

PC

B

13

6

PC

B

13

7/1

76

PC

B

13

8/1

60


BA10 Coyote Creek 4/25/95 7 CGIG 4.1 9.9 24.4 20.4 2.8 ND ND 3.7 41.3

BA30 Dumbarton Bridge 4/25/95 7 MCAL 1.9 3.1 10.9 8.9 2.1 ND ND 2.0 17.7

BA40 Redwood Creek 4/25/95 7 MCAL 1.9 4.0 7.3 8.2 ND ND ND 2.3 18.3

BB71 Alameda 4/25/95 7 MCAL 1.7 3.7 9.3 7.5 1.8 ND ND 3.7 20.6

BC10 Yerba Buena Island 4/25/95 7 MCAL 1.9 2.6 8.8 7.7 2.0 ND ND 3.1 17.8

BC21 Horseshoe Bay 4/26/95 7 MCAL ND 2.1 4.9 4.0 ND ND ND 2.4 12.8

BC60 Red Rock 4/26/95 7 MCAL ND ND 5.1 3.1 ND ND ND 3.1 11.3

BD15 Petaluma River 4/26/95 7 CFLU 2.7 2.6 11.4 14.3 3.7 2.1 ND 5.2 21.4

BD20 San Pablo Bay 4/26/95 7 CGIG ND 3.9 7.4 5.6 2.6 ND ND 5.9 16.8

BD40 Davis Point 4/26/95 7 CGIG ND ND 5.3 3.6 ND ND ND 4.3 12.5

BD50 Napa River 4/26/95 7 CGIG ND ND 7.1 5.4 ND ND ND 6.4 18.3

BF20 Grizzly Bay 4/27/95 7 CFLU 2.0 ND 8.6 9.8 8.7 3.8 ND 15.0 24.9

BG20 Sacramento River 4/27/95 7 CFLU 1.8 ND 6.6 9.3 4.7 3.7 ND 11.0 19.4

BG30 San Joaquin River 4/27/95 7 CFLU 1.9 ND 7.5 10.2 4.5 4.3 ND 8.7 17.7

T-0 Lake Isabella 1/20/95 7 CFLU ND ND 3.2 7.0 ND ND ND ND 6.3

T-0 Dabob Bay, WA 1/20/95 7 CGIG ND ND ND ND ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL ND ND ND ND ND ND ND ND 2.2

BA10 Coyote Creek 9/12/95 9 CGIG 2.2 5.0 10.5 14.9 ND ND ND ND 22.0

BA30 Dumbarton Bridge 9/12/95 9 MCAL ND 2.8 8.3 9.5 3.0 ND ND ND 16.5

BA40 Redwood Creek 9/12/95 9 MCAL 1.9 2.8 7.5 8.9 2.5 ND ND ND 18.1

BB71 Alameda 9/12/95 9 MCAL 1.8 2.6 6.3 6.7 1.9 ND ND ND 14.4

BC10 Yerba Buena Island 9/12/95 9 MCAL ND 1.8 4.8 7.2 ND ND ND ND 11.7

BC21 Horseshoe Bay 9/13/95 9 MCAL ND 0.8 3.2 3.5 ND ND ND ND 6.4

BC60 Red Rock 9/13/95 9 MCAL ND 1.1 3.5 4.0 ND ND ND ND 8.3

BD15 Petaluma River 9/13/95 9 CGIG 2.8 2.5 19.6 13.7 ND ND 2.2 ND 24.5

BD30 Pinole Point 9/13/95 9 MCAL ND ND 4.2 5.2 ND ND ND ND 9.3

BD40 Davis Point 9/13/95 9 CGIG 2.1 3.8 10.4 9.6 1.8 ND ND 1.8 19.2

BD50 Napa River 9/13/95 9 CGIG ND 3.1 8.8 8.0 ND ND ND ND 15.2

BF20 Grizzly Bay 9/14/95 9 CFLU 3.0 3.5 13.9 14.0 4.4 ND ND 5.5 25.1

BG20 Sacramento River 9/14/95 9 CFLU 3.5 2.5 9.8 14.4 2.1 ND ND 4.8 20.9

BG30 San Joaquin River 9/14/95 9 CFLU 2.3 3.3 10.5 13.8 3.4 ND ND 5.1 18.6

T-0 Lake Isabella 6/16/95 9 CFLU ND ND ND 1.1 ND ND ND ND 1.6

T-0 Tomales Bay 6/16/95 9 CGIG 1.1 ND 3.8 5.6 ND ND ND ND 5.4

T-0 Bodega Head 6/16/95 9 MCAL ND ND ND ND ND ND ND ND 1.3


PC

B

14

1/1

79

PC

B

14

6

PC

B

14

9/1

23


11.5 6.2 32.1

5.5 3.6 13.3

5.6 3.4 12.7

3.1 3.1 12.2

3.1 2.3 11.4

2.2 ND 6.7

4.0 ND 5.8

3.8 3.7 12.7

4.1 ND 12.0

ND ND 7.8

4.4 ND 10.6

4.8 ND 10.6

3.3 ND 6.2

5.8 ND 6.7

7.4 ND 2.2

ND ND ND

ND ND ND

3.4 5.9 16.7

ND 2.9 8.6

ND 3.4 8.7

ND 2.8 7.5

ND 1.7 5.7

ND ND 3.0

ND ND 4.0

1.9 6.5 32.0

ND ND 4.2

2.9 3.9 14.4

2.9 2.9 11.7

3.6 3.5 13.7

3.3 2.1 9.0

2.4 2.1 8.6

ND ND ND

1.5 ND 1.9

ND ND ND

Appendices

A–59


PC

B

17

8

PC

B

18

0

PC

B

18

3


3.4 24.5 6.7

ND 10.1 3.7

ND 11.6 4.2

ND 13.1 4.6

ND 16.5 3.8

ND 7.6 3.0

ND 6.9 3.0

1.5 11.6 4.5

ND 12.9 5.2

ND 11.5 3.6

ND 16.1 5.8

1.8 12.4 8.9

ND 14.9 6.2

1.4 12.2 5.2

ND 3.8 ND

ND ND ND

ND ND ND

ND 7.5 ND

ND 7.2 ND

ND 8.7 ND

ND 9.5 1.9

ND 12.0 1.3

ND 4.0 ND

ND 4.5 ND

ND 10.8 3.0

ND 5.0 ND

ND 16.7 2.0

ND 14.5 1.7

ND 20.4 4.1

ND 28.2 2.8

ND 21.1 3.0

ND ND ND

ND 3.1 ND

ND ND ND

Sta

tion

C

od

e

Sta

tio

n

Da

te

Cru

ise

Sp

ec

ies

Tot

al

PC

Bs

(SF

EI)

PC

B

15

1

PC

B

15

3/1

32

PC

B

15

6/1

71

PC

B

15

8

PC

B

16

7

PC

B

17

0/1

90

PC

B

17

2

PC

B

17

4

PC

B

17

7

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 4/25/95 7 CGIG 457 8.9 67.3 ND ND ND ND ND ND 5.8

BA30 Dumbarton Bridge 4/25/95 7 MCAL 191 3.9 26.9 ND ND ND ND ND ND 2.0

BA40 Redwood Creek 4/25/95 7 MCAL 174 3.7 25.5 ND ND ND ND ND ND 2.2

BB71 Alameda 4/25/95 7 MCAL 180 3.3 27.7 ND ND 2.0 ND ND ND 2.2

BC10 Yerba Buena Island 4/25/95 7 MCAL 171 3.0 23.4 ND ND 1.8 ND ND ND 1.6

BC21 Horseshoe Bay 4/26/95 7 MCAL 95 ND 14.7 ND ND ND ND ND ND ND

BC60 Red Rock 4/26/95 7 MCAL 79 ND 12.6 ND ND ND ND ND ND ND

BD15 Petaluma River 4/26/95 7 CFLU 286 4.3 36.9 1.8 3.2 2.1 1.6 ND ND 2.1

BD20 San Pablo Bay 4/26/95 7 CGIG 144 ND 20.9 ND ND ND ND ND ND ND

BD40 Davis Point 4/26/95 7 CGIG 92 ND 15.3 ND ND ND ND ND ND ND

BD50 Napa River 4/26/95 7 CGIG 148 ND 21.1 ND ND ND ND ND ND ND

BF20 Grizzly Bay 4/27/95 7 CFLU 271 2.7 29.1 1.8 2.7 2.4 ND ND ND ND

BG20 Sacramento River 4/27/95 7 CFLU 219 ND 25.7 1.9 2.6 2.0 ND ND ND ND

BG30 San Joaquin River 4/27/95 7 CFLU 228 2.5 26.7 2.0 2.5 1.9 ND ND ND ND

T-0 Lake Isabella 1/20/95 7 CFLU 70 ND 15.9 ND ND ND ND ND ND ND

T-0 Dabob Bay, WA 1/20/95 7 CGIG 3 ND 3.0 ND ND ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL 22 ND 2.6 ND ND 1.5 ND ND ND ND

BA10 Coyote Creek 9/12/95 9 CGIG 219 4.8 57.7 ND ND ND 5.6 ND ND 3.4

BA30 Dumbarton Bridge 9/12/95 9 MCAL 130 2.4 24.0 ND ND ND 2.5 ND ND ND

BA40 Redwood Creek 9/12/95 9 MCAL 132 2.7 26.8 ND ND ND ND ND ND ND

BB71 Alameda 9/12/95 9 MCAL 118 2.1 21.9 ND ND ND ND ND ND 1.5

BC10 Yerba Buena Island 9/12/95 9 MCAL 96 1.6 19.0 ND ND ND 2.8 ND ND ND

BC21 Horseshoe Bay 9/13/95 9 MCAL 48 ND 8.4 ND ND ND 1.5 ND ND ND

BC60 Red Rock 9/13/95 9 MCAL 55 ND 11.8 ND ND ND 3.7 ND ND ND

BD15 Petaluma River 9/13/95 9 CGIG 322 4.2 78.2 ND ND ND 7.6 ND ND 4.8

BD30 Pinole Point 9/13/95 9 MCAL 59 ND 10.6 ND ND ND 6.7 ND ND ND

BD40 Davis Point 9/13/95 9 CGIG 205 3.0 33.4 ND ND ND 3.9 ND ND 2.0

BD50 Napa River 9/13/95 9 CGIG 159 2.7 26.8 ND ND ND 4.9 ND ND 1.7

BF20 Grizzly Bay 9/14/95 9 CFLU 269 2.6 39.4 ND ND 1.9 1.3 ND ND 1.7

BG20 Sacramento River 9/14/95 9 CFLU 236 1.7 36.9 ND ND 1.7 ND ND ND ND

BG30 San Joaquin River 9/14/95 9 CFLU 223 1.9 29.5 ND ND 1.8 ND ND ND ND

T-0 Lake Isabella 6/16/95 9 CFLU 14 ND 1.5 ND ND ND 1.6 ND ND ND

T-0 Tomales Bay 6/16/95 9 CGIG 64 ND 11.9 ND ND ND ND ND ND ND

T-0 Bodega Head 6/16/95 9 MCAL 10 ND 1.1 ND ND ND 1.3 ND ND ND


A–60



Sta

tion

C

od

e

Sta

tio

n

Da

te

Cru

ise

Sp

ec

ies

PC

B

18

5

PC

B

18

7/1

82

/15

9

PC

B

18

9

PC

B

19

1

PC

B

19

4

PC

B

19

5/2

08

PC

B

19

6/2

03

PC

B

20

0

PC

B

20

1

PC

B

20

5

PC

B

20

6

PC

B

20

9

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/k

BA10 Coyote Creek 4/25/95 7 CGIG ND 21.9 ND ND ND ND ND ND ND ND ND ND

BA30 Dumbarton Bridge 4/25/95 7 MCAL ND 8.2 ND ND ND ND ND ND ND ND ND ND

BA40 Redwood Creek 4/25/95 7 MCAL ND 8.9 ND ND ND ND ND ND ND ND ND ND

BB71 Alameda 4/25/95 7 MCAL ND 8.6 ND ND ND ND ND ND ND ND ND ND

BC10 Yerba Buena Island 4/25/95 7 MCAL ND 6.4 ND ND ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 4/26/95 7 MCAL ND 4.5 ND ND ND ND ND ND ND ND ND ND

BC60 Red Rock 4/26/95 7 MCAL ND 3.7 ND ND ND ND ND ND ND ND ND ND

BD15 Petaluma River 4/26/95 7 CFLU ND 8.3 ND ND ND ND 1.4 ND ND ND ND ND

BD20 San Pablo Bay 4/26/95 7 CGIG ND 8.5 ND ND ND ND ND ND ND ND ND ND

BD40 Davis Point 4/26/95 7 CGIG ND 5.4 ND ND ND ND ND ND ND ND ND ND

BD50 Napa River 4/26/95 7 CGIG ND 7.1 ND ND ND ND ND ND ND ND ND ND

BF20 Grizzly Bay 4/27/95 7 CFLU 1.7 6.2 ND ND ND ND ND ND ND ND ND ND

BG20 Sacramento River 4/27/95 7 CFLU ND 3.5 ND ND ND ND ND ND ND ND ND ND

BG30 San Joaquin River 4/27/95 7 CFLU ND 3.5 ND ND ND ND ND ND ND ND ND ND

T-0 Lake Isabella 1/20/95 7 CFLU ND ND ND ND ND ND ND ND ND ND ND ND

T-0 Dabob Bay, WA 1/20/95 7 CGIG ND ND ND ND ND ND ND ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL ND ND ND ND ND ND ND ND ND ND ND ND

BA10 Coyote Creek 9/12/95 9 CGIG ND 18.2 ND ND ND ND ND ND ND ND ND ND

BA30 Dumbarton Bridge 9/12/95 9 MCAL ND 5.8 ND ND ND ND ND ND ND ND ND ND

BA40 Redwood Creek 9/12/95 9 MCAL ND 7.3 ND ND ND ND ND ND ND ND ND ND

BB71 Alameda 9/12/95 9 MCAL ND 5.8 ND ND ND ND ND ND ND ND ND ND

BC10 Yerba Buena Island 9/12/95 9 MCAL ND 4.0 ND ND ND ND ND ND ND ND ND ND

BC21 Horseshoe Bay 9/13/95 9 MCAL ND 2.0 ND ND ND ND ND ND ND ND ND ND

BC60 Red Rock 9/13/95 9 MCAL ND 2.9 ND ND ND ND ND ND ND ND ND ND

BD15 Petaluma River 9/13/95 9 CGIG ND 14.4 ND ND ND ND ND ND ND ND ND ND

BD30 Pinole Point 9/13/95 9 MCAL ND 2.6 ND ND ND ND ND ND ND ND ND ND

BD40 Davis Point 9/13/95 9 CGIG ND 10.4 ND ND ND ND ND ND ND ND ND ND

BD50 Napa River 9/13/95 9 CGIG ND 8.6 ND ND ND ND ND ND ND ND ND ND

BF20 Grizzly Bay 9/14/95 9 CFLU ND 8.7 ND ND ND ND ND ND ND ND ND ND

BG20 Sacramento River 9/14/95 9 CFLU ND 5.4 ND ND ND ND ND ND ND ND ND ND

BG30 San Joaquin River 9/14/95 9 CFLU ND 5.5 ND ND ND ND ND ND ND ND ND ND

T-0 Lake Isabella 6/16/95 9 CFLU ND ND ND ND ND ND ND ND ND ND ND 2.5

T-0 Tomales Bay 6/16/95 9 CGIG ND ND ND ND ND ND ND ND ND ND ND ND

T-0 Bodega Head 6/16/95 9 MCAL ND ND ND ND ND ND ND ND ND ND ND ND


Appendices

A–61

Sta

tion

Cod

e

Sta

tion

Dat

e

Cru

ise

Spe

cies

Sum

DD

Ts

(SF

EI)

o,p'

-DD

D

o,p'

-DD

E

o,p'

-DD

T

p,p'

-DD

D

p,p'

-DD

E

p,p'

-DD

T

Sum

Chl

orda

nes

(SF

EI)

Alp

ha-C

hlor

dane

Gam

ma-

Chl

orda

ne

cis-

Non

achl

or

tran

s-N

onac

hlor

µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 4/25/95 7 CGIG 227 16.7 3.4 10.1 49.0 120.3 27.8 142.4 40.4 34.3 20.0 40.4

BA30 Dumbarton Bridge 4/25/95 7 MCAL 78 7.3 1.6 2.4 19.7 40.9 5.7 63.4 15.2 17.9 8.0 15.6

BA40 Redwood Creek 4/25/95 7 MCAL 57 5.1 ND 1.5 15.5 31.0 3.9 55.0 12.2 15.7 6.7 12.3

BB71 Alameda 4/25/95 7 MCAL 81 7.0 2.2 2.0 19.2 42.8 7.9 27.6 7.2 7.4 3.6 6.6

BC10 Yerba Buena Island 4/25/95 7 MCAL 82 6.8 2.7 3.6 19.1 40.9 9.1 34.0 10.4 8.5 4.3 8.1

BC21 Horseshoe Bay 4/26/95 7 MCAL 69 5.9 2.7 2.5 14.8 36.5 7.0 21.5 7.0 5.7 2.7 5.0

BC60 Red Rock 4/26/95 7 MCAL 87 7.8 3.7 2.4 17.6 46.8 8.6 28.9 10.1 7.7 3.4 6.0

BD15 Petaluma River 4/26/95 7 CFLU 213 14.5 8.0 5.1 50.2 122.5 13.2 79.5 22.5 18.6 12.4 19.7

BD20 San Pablo Bay 4/26/95 7 CGIG 166 12.5 3.9 7.7 29.8 94.7 17.8 33.2 8.3 7.6 6.5 10.8

BD40 Davis Point 4/26/95 7 CGIG 124 8.0 3.2 5.6 21.8 70.4 15.1 29.1 7.4 7.6 5.2 9.0

BD50 Napa River 4/26/95 7 CGIG 175 12.5 5.6 4.8 33.8 101.1 17.1 42.2 9.6 11.6 6.8 14.2

BF20 Grizzly Bay 4/27/95 7 CFLU 249 14.9 6.4 6.6 40.6 160.5 19.6 45.7 9.0 11.7 8.4 15.4

BG20 Sacramento River 4/27/95 7 CFLU 223 11.3 5.9 4.5 29.0 152.0 20.0 41.1 6.9 10.4 8.0 14.7

BG30 San Joaquin River 4/27/95 7 CFLU 246 11.9 6.9 5.9 35.3 166.4 20.2 48.8 10.2 11.3 7.8 16.0

T-0 Lake Isabella 1/20/95 7 CFLU 80 3.5 2.9 ND 11.0 62.7 ND 16.8 3.1 3.7 3.5 6.5

T-0 Dabob Bay, WA 1/20/95 7 CGIG 4 ND ND ND ND 3.6 ND 0.0 ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL 15 1.9 0.7 ND 1.7 11.0 ND 8.6 6.4 1.5 ND 0.8

BA10 Coyote Creek 9/12/95 9 CGIG 66 5.2 1.5 2.6 12.0 43.5 1.3 20.9 6.2 3.5 4.4 6.8

BA30 Dumbarton Bridge 9/12/95 9 MCAL 41 4.4 0.9 1.8 12.1 22.3 ND 20.4 6.9 4.8 3.8 4.9

BA40 Redwood Creek 9/12/95 9 MCAL 31 3.3 ND 1.4 8.6 17.5 ND 16.3 5.7 4.1 2.8 3.7

BB71 Alameda 9/12/95 9 MCAL 30 2.9 1.1 0.9 8.9 14.0 2.0 9.6 3.6 2.2 1.5 2.2

BC10 Yerba Buena Island 9/12/95 9 MCAL 29 2.9 ND 0.7 9.5 14.2 1.6 8.8 3.4 2.3 1.1 1.9

BC21 Horseshoe Bay 9/13/95 9 MCAL 26 2.8 0.5 ND 10.0 11.9 1.1 6.0 2.3 1.5 0.7 1.5

BC60 Red Rock 9/13/95 9 MCAL 33 3.0 0.6 ND 9.9 18.5 1.3 7.9 3.1 2.0 1.1 1.7

BD15 Petaluma River 9/13/95 9 CGIG 182 12.3 4.3 2.3 52.8 106.2 4.1 19.2 5.4 4.1 4.0 5.7

BD30 Pinole Point 9/13/95 9 MCAL 50 4.8 ND 1.2 15.5 26.7 1.9 12.7 4.7 3.7 1.8 2.5

BD40 Davis Point 9/13/95 9 CGIG 146 10.1 3.1 3.2 37.9 84.9 6.6 25.1 6.9 5.7 5.0 7.5

BD50 Napa River 9/13/95 9 CGIG 120 8.6 2.2 2.1 29.7 73.3 4.7 20.1 5.3 4.6 3.7 6.4

BF20 Grizzly Bay 9/14/95 9 CFLU 217 13.7 2.7 1.0 52.7 135.6 11.4 40.1 9.8 8.9 6.9 13.4

BG20 Sacramento River 9/14/95 9 CFLU 236 14.0 3.6 2.0 37.4 161.3 17.4 35.5 8.5 7.5 5.7 12.7

BG30 San Joaquin River 9/14/95 9 CFLU 209 11.7 2.4 1.3 35.3 146.7 11.9 36.4 8.7 7.7 5.9 12.4

T-0 Lake Isabella 6/16/95 9 CFLU 19 0.8 1.0 0.6 3.3 10.9 2.2 7.9 2.4 1.0 2.3 2.2

T-0 Tomales Bay 6/16/95 9 CGIG 70 2.2 2.6 0.5 7.8 53.7 2.7 17.2 4.1 3.0 2.5 6.8

T-0 Bodega Head 6/16/95 9 MCAL 9 0.6 ND ND 1.7 6.1 0.8 4.3 3.0 0.8 ND 0.5


Table 21. Pesticide concentrations in bivalve tissues, 1995.ND = not detected. Data expressed as dry weight. T-0 = time of bivalve deployment into the Estuaryfrom the source indicated under station name heading.

A–62


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µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg µg/kg

BA10 Coyote Creek 4/25/95 7 CGIG ND 3.3 4.0 ND 22.6 ND 2.1 ND ND 3.0 ND ND

BA30 Dumbarton Bridge 4/25/95 7 MCAL ND 4.8 2.0 ND 31.7 2.6 2.9 0.9 ND 2.4 ND ND

BA40 Redwood Creek 4/25/95 7 MCAL ND 6.1 2.0 ND 37.1 ND 3.3 ND ND 2.5 ND ND

BB71 Alameda 4/25/95 7 MCAL ND 1.7 1.0 ND 22.0 1.2 2.1 ND ND 1.5 ND ND

BC10 Yerba Buena Island 4/25/95 7 MCAL ND 1.7 0.9 ND 23.0 1.3 2.2 ND ND 1.3 ND ND

BC21 Horseshoe Bay 4/26/95 7 MCAL ND 1.2 ND ND 17.0 ND 2.5 ND ND 1.3 ND ND

BC60 Red Rock 4/26/95 7 MCAL ND 1.7 ND ND 27.1 ND 2.5 ND ND 1.3 ND ND

BD15 Petaluma River 4/26/95 7 CFLU ND 3.7 2.6 ND 18.7 3.9 1.9 ND ND 10.5 1.5 ND

BD20 San Pablo Bay 4/26/95 7 CGIG ND ND ND ND 9.2 ND 2.3 ND ND ND ND ND

BD40 Davis Point 4/26/95 7 CGIG ND ND ND ND 7.4 ND 1.8 ND ND ND ND ND

BD50 Napa River 4/26/95 7 CGIG ND ND ND ND 14.2 ND 3.2 ND ND 2.6 ND ND

BF20 Grizzly Bay 4/27/95 7 CFLU ND ND 1.2 ND 22.2 2.5 1.8 ND ND 9.2 1.6 ND

BG20 Sacramento River 4/27/95 7 CFLU ND ND 1.2 ND 21.5 ND ND ND ND 10.8 1.4 ND

BG30 San Joaquin River 4/27/95 7 CFLU ND 2.4 1.1 ND 20.4 2.4 1.7 0.7 ND 6.4 2.6 ND

T-0 Lake Isabella 1/20/95 7 CFLU ND ND ND ND 1.2 ND 1.8 ND ND 6.1 0.7 ND

T-0 Dabob Bay, WA 1/20/95 7 CGIG ND ND ND ND ND ND 2.2 ND ND ND ND ND

T-0 Bodega Head 1/20/95 7 MCAL ND ND ND ND 9.5 1.3 2.6 0.8 ND 1.1 ND ND

BA10 Coyote Creek 9/12/95 9 CGIG ND ND ND ND ND 3.2 ND ND ND 2.9 ND ND

BA30 Dumbarton Bridge 9/12/95 9 MCAL ND ND ND ND 10.2 1.9 1.5 ND ND 1.5 ND ND

BA40 Redwood Creek 9/12/95 9 MCAL ND ND ND ND 8.9 1.1 1.8 ND ND 1.4 ND ND

BB71 Alameda 9/12/95 9 MCAL ND ND ND ND 6.9 ND 1.3 ND ND 0.8 ND ND

BC10 Yerba Buena Island 9/12/95 9 MCAL ND ND ND ND 6.6 1.5 1.1 ND ND ND ND ND

BC21 Horseshoe Bay 9/13/95 9 MCAL ND ND ND ND 5.2 1.0 2.1 1.0 ND 0.9 ND ND

BC60 Red Rock 9/13/95 9 MCAL ND ND ND ND 6.3 1.1 1.3 ND ND ND ND ND

BD15 Petaluma River 9/13/95 9 CGIG ND ND ND ND 3.5 ND 2.0 ND ND ND ND ND

BD30 Pinole Point 9/13/95 9 MCAL ND ND ND ND 12.2 3.4 2.3 ND ND 1.7 1.1 ND

BD40 Davis Point 9/13/95 9 CGIG ND ND ND ND 5.4 5.4 1.5 ND ND 3.0 ND ND

BD50 Napa River 9/13/95 9 CGIG ND ND ND ND 4.4 3.4 1.2 ND ND 2.3 ND ND

BF20 Grizzly Bay 9/14/95 9 CFLU ND ND 1.0 3.4 9.6 ND 1.6 ND ND 2.3 2.3 ND

BG20 Sacramento River 9/14/95 9 CFLU ND ND 1.1 2.2 11.4 ND 1.3 ND ND 2.1 2.5 ND

BG30 San Joaquin River 9/14/95 9 CFLU ND 0.7 0.8 ND 11.2 ND 1.3 ND ND 2.4 5.2 ND

T-0 Lake Isabella 6/16/95 9 CFLU ND ND ND ND 1.0 0.6 2.5 1.1 ND 1.3 ND ND

T-0 Tomales Bay 6/16/95 9 CGIG ND ND 0.8 ND 1.0 ND 1.7 ND ND 2.5 1.9 ND

T-0 Bodega Head 6/16/95 9 MCAL ND ND ND ND 4.8 0.9 3.8 1.3 ND 1.0 0.5 ND


Table 21. Pesticide concentrations in bivalve tissues, 1995 (continued).ND = not detected. Data expressed as dry weight. T-0 = time of bivalve deployment into the Estuary from thesource indicated under station name heading.

1995 rmp annual report - usgs · 2004. 7. 20. · the 1995 regional monitoring program (rmp) annual...

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