102512 dust report 031314 final - city of chicago · executive summary es‐3 figure es‐2...

City of ChicagoFugitive Dust Study

March 2014

REPORT

ii

Table of Contents

ExecutiveSummary...................................................................................................................................................ES‐1

Section1 IntroductionandPurpose....................................................................................................................1‐1

Section2 ConceptualBulkMaterialStorageFacility......................................................................................2‐1

Section3 EmissionCalculations............................................................................................................................3‐1 3.1DropOperations........................................................................................................................................................3‐1 3.2TravelontheSurfaceofthePile.........................................................................................................................3‐2 3.3PavedRoads................................................................................................................................................................3‐2 3.4BulldozingandGrading..........................................................................................................................................3‐3 3.5WindErosionfromStockpiles.............................................................................................................................3‐4 3.6FugitiveDustEmissionEstimates.....................................................................................................................3‐5

Section4 DispersionModeling..............................................................................................................................4‐1 4.1AERMODReferences/Version.............................................................................................................................4‐1 4.2ModelingSetup...........................................................................................................................................................4‐1

4.2.1Terrain...............................................................................................................................................................4‐1 4.2.2ReceptorGrid..................................................................................................................................................4‐1 4.2.3MeteorologicalDataandLanduse.........................................................................................................4‐1 4.2.4PollutantsandAveragingTimes............................................................................................................4‐5

4.3EmissionSources......................................................................................................................................................4‐5 4.3.1SourceTypes...................................................................................................................................................4‐5 4.3.2ModelingApproach......................................................................................................................................4‐6

4.4PM10(24‐hr)andPM2.5(Annual,24‐hr)ModelingResults.....................................................................4‐7 4.4.1PetcokeMaterialHandlingModelingResults...................................................................................4‐7 4.4.2CoalMaterialHandlingModelingResults..........................................................................................4‐9 4.4.3WindErosionModelingforthePetcokeandCoalStoragePiles............................................4‐10

4.5InterpretationofModelPredictions...............................................................................................................4‐18 4.6ComparisontoBackgroundAirQualityinChicago..................................................................................4‐18

Section5 Conclusions...............................................................................................................................................5‐1

AppendixA PetroleumCokeData..............................................................................................................A‐1

AppendixB SlagData.....................................................................................................................................B‐1

AppendixC ModelingResultsFigures.......................................................................................................C‐1

Table of Contents

iii

List of Figures

FigureES‐1 EstimatesofTotalDustEmissions.......................................................................................................ES‐2 FigureES‐2 EstimatesofPM10Emissions...................................................................................................................ES‐3 FigureES‐3 EstimatesofPM2.5Emissions..................................................................................................................ES‐3 Figure2‐1 ConceptualBulkMaterialStorageFacilityConfigurationofArea,Volume,andLine

VolumeSources................................................................................................................................................2‐2 Figure4‐1 PolarandFencelineReceptorGrid..........................................................................................................4‐3 Figure4‐2 WindroseforChicagoMidwayAirport2008SurfaceObservations........................................4‐4 Figure4‐3 Highest24‐HourAveragePM10ConcentrationPredictionsforPetroleumCoke(All

Sources)............................................................................................................................................................4‐11 Figure4‐4 Highest24‐HourAveragePM2.5ConcentrationPredictionsforPetroleumCoke(All

Sources)............................................................................................................................................................4‐12 Figure4‐5 HighestAnnualAveragePM2.5ConcentrationPredictionsforPetroleumCoke(All

Sources)............................................................................................................................................................4‐13 Figure4‐6 Highest24‐HourAveragePM10ConcentrationPredictionsforCoal(AllSources)........4‐14 Figure4‐7 Highest24‐HourAveragePM2.5ConcentrationPredictionsforCoal(AllSources)........4‐15 Figure4‐8 HighestAnnualAveragePM2.5ConcentrationPredictionsforCoal(AllSources)...........4‐16 Figure4‐9 1‐HourAveragingPeriodPM10EmissionsWindErosionofaPetcokeStoragePile....4‐17 Figure4‐10 1‐HourAveragingPeriodPM10EmissionRateWindErosionofaCoalStoragePile...4‐17 Figure4‐11 AnnualAveragePM2.5ConcentrationsatMonitoringLocationsinChicago......................4‐19 Figure4‐12 24‐HourAveragePM2.5ConcentrationsatMonitoringLocationsinChicago...................4‐19 Figure4‐13 24‐HourAveragePM10ConcentrationsatMonitoringLocationsinChicago....................4‐20 Figure4‐3a 24‐HrAveragePetcokePM10EmissionsModeling;AllEquipmentEmissions..................C‐1Figure4‐3b 24‐HrAveragePetcokePM10EmissionsModeling;Bull‐dozer/GraderEmissions.........C‐2Figure4‐3c 24‐HrAveragePetcokePM10EmissionsModeling;DropEmissions....................................C‐3Figure4‐3d 24‐HrAveragePetcokePM10EmissionsModeling;PavedRoadEmissions......................C‐4Figure4‐3e 24‐HrAveragePetcokePM10EmissionsModeling;EmissionsfromTravelonPile

Surface..................................................................................................................................................................C‐5Figure4‐3f 24‐HrAveragePetcokePM10EmissionsModeling;WindErosionEmissionsfrom

Stockpile.............................................................................................................................................................C‐6Figure4‐4a 24‐HrAveragePetcokePM2.5EmissionsModeling;AllEquipmentEmissions................C‐7Figure4‐4b 24‐HrAveragePetcokePM2.5EmissionsModeling;Bull‐dozer/GraderEmissions.......C‐8Figure4‐4c 24‐HrAveragePetcokePM2.5EmissionsModeling;DropEmissions...................................C‐9Figure4‐4d 24‐HrAveragePetcokePM2.5EmissionsModeling;PavedRoadEmissions..................C‐10Figure4‐4e 24‐HrAveragePetcokePM2.5EmissionsModeling;EmissionsfromTravelonPile

Surface...............................................................................................................................................................C‐11Figure4‐4f 24‐HrAveragePetcokePM2.5EmissionsModeling;WindErosionEmissionsfrom

Stockpile..........................................................................................................................................................C‐12Figure4‐5a AnnualAveragePetcokePM2.5EmissionsModeling;AllEquipmentEmissions..........C‐13Figure4‐5b AnnualAveragePetcokePM2.5EmissionsModeling;Bull‐dozer/GraderEmissions.C‐14Figure4‐5c AnnualAveragePetcokePM2.5EmissionsModeling;DropEmissions..............................C‐15Figure4‐5d AnnualAveragePetcokePM2.5EmissionsModeling;PavedRoadEmissions................C‐16Figure4‐5e AnnualAveragePetcokePM2.5EmissionsModeling;EmissionsfromTravelonPile

Surface.............................................................................................................................................................C‐17Figure4‐5f AnnualAveragePetcokePM2.5EmissionsModeling;WindErosionEmissionsfrom

Stockpile..........................................................................................................................................................C‐18Figure4‐6a 24‐HrAverageCoalPM10EmissionsModeling;AllEquipmentEmissions.....................C‐19

Table of Contents

iv

Figure4‐6b 24‐HrAverageCoalPM10EmissionsModeling;Bull‐dozer/GraderEmissions.............C‐20Figure4‐6c 24‐HrAverageCoalPM10EmissionsModeling;DropEmissions.........................................C‐21Figure4‐6d 24‐HrAverageCoalPM10EmissionsModeling;PavedRoadEmissions...........................C‐22Figure4‐6e 24‐HrAverageCoalPM10EmissionsModeling;EmissionsfromTravelonPile

Surface...............................................................................................................................................................C‐23Figure4‐6f 24‐HrAverageCoalPM10EmissionsModeling;WindErosionEmissionsfrom

Stockpile..........................................................................................................................................................C‐24Figure4‐7a 24‐HrAverageCoalPM2.5EmissionsModeling;AllEquipmentEmissions.....................C‐25Figure4‐7b 24‐HrAverageCoalPM2.5EmissionsModeling;Bull‐dozer/GraderEmissions............C‐26Figure4‐7c 24‐HrAverageCoalPM2.5EmissionsModeling;DropEmissions........................................C‐27Figure4‐7d 24‐HrAverageCoalPM2.5EmissionsModeling;PavedRoadEmissions..........................C‐28Figure4‐7e 24‐HrAverageCoalPM2.5EmissionsModeling;EmissionsfromTravelonPile

Surface..............................................................................................................................................................C‐29Figure4‐7f 24‐HrAverageCoalPM2.5EmissionsModeling;WindErosionEmissionsfrom

Stockpile..........................................................................................................................................................C‐30Figure4‐8a AnnualAverageCoalPM2.5EmissionsModeling;AllEquipmentEmissions..................C‐31Figure4‐8b AnnualAverageCoalPM2.5EmissionsModeling;Bull‐dozer/GraderEmissions.........C‐32Figure4‐8c AnnualAverageCoalPM2.5EmissionsModeling;DropEmissions......................................C‐33Figure4‐8d AnnualAverageCoalPM2.5EmissionsModeling;PavedRoadEmissions........................C‐34Figure4‐8e AnnualAverageCoalPM2.5EmissionsModeling;EmissionsfromTravelonPile Surface..............................................................................................................................................................C‐35Figure4‐8f AnnualAverageCoalPM2.5EmissionsModeling;WindErosionEmissionsfrom

Stockpile..........................................................................................................................................................C‐36Figure4‐9 1‐HourAveragingPeriodPM10Emissions;WindErosionofaPetcokeStoragePile..C‐37Figure4‐10 1‐HourAveragingPeriodPM10EmissionRate;WindErosionofaCoalStoragePile.C‐38

List of Tables

Table2‐1 CharacteristicsofBulkMaterials.............................................................................................................2‐3 Table3‐1 TSPEmissionSummary...............................................................................................................................3‐7 Table3‐2 PM10EmissionSummary.............................................................................................................................3‐8 Table3‐3 PM2.5EmissionSummary............................................................................................................................3‐9 Table4‐1 ModelingSourceSummary........................................................................................................................4‐8 Table4‐2 AERMODModelingResultsSummaryforPetcokeMaterialHandling...................................4‐9 Table4‐3 AERMODModelingResultsSummaryforCoalMaterialHandling.........................................4‐10

ES‐1

Executive Summary

TheCityofChicago(City)hasproposedregulationsfortheHandlingandStorageofBulkMaterialPilestocontrolpotentialemissionsofdustfromfacilitiesthatprocessandstorebulkmaterials.Thisstudyevaluatesthepotentialmechanismsofdustgenerationassociatedwithbulkmaterialpiles,andisdesignedtoinformtheCityconcerningtheimportanceofactivitiesthat,ifunmitigated,couldproduceexcessivedustandadverselyaffectambientairquality.Thestudyfindsthatbulkmaterialpilescaningeneralbesignificantsourcesofdustandcontributetolocalizedexceedancesofambientairqualitystandards.Ofthematerialsevaluated(petcoke,coal,Mesabaore,andslag),potentialemissionsofpetcokewerefoundtobehighest.Factorsimportanttofugitivedustgenerationincludebulkmaterialpropertiessuchassiltcontent,materialhandlingprocedures,andmeteorologicalconditionssuchasdryweatherandhighwinds.

ProceduresdevelopedbytheU.S.EnvironmentalProtectionAgency(EPA)wereimplementedtoestimatepotentialdustemissionsfrommaterialhandlingandstorageactivities,including:

materialdroppingoperations(fromtruckdumping,front‐endloaderuse,conveyors,etc.);

bulldozingandgrading;

vehicletravelonpavedroadsandtheunpavedsurfaceofthestoragepile;and

surfacewinderosionfromstockpiles.

Dustemissionsfrommanyoftheseactivitiesdependuponbulkmaterialcharacteristicssuchasgrainsize(primarilysiltcontent),moisturecontent,andbulkdensity.PertherequestoftheCity,dustemissionswereevaluatedfromfourbulkmaterials:

petroleumcoke(petcoke);

coal;

Mesabaore(enrichedincopperandnickel);and

slag.

Spreadsheetcalculationsweredevelopedtoestimatepotentialemissionsofeachbulkmaterialfromeachsource.AconceptualbulkmaterialprocessingandstoragefacilitywasconstructedusingparametersfromtheCity’sdraftregulationsandknowledgeofactivitiestypicalofbulkmaterialhandling.EPA’sAP42emissionfactormethodswereimplementedusingmaterial‐specificparametersasappropriate.Mitigationeffortswerenotconsideredinordertoestimateconservativeworst‐casedustemissions.

ResultsofthedustemissioncalculationsarepresentedinFigureES‐1(totaldust),FigureES‐2(PM10,orparticulatematterwithaerodynamicdiameterlessthan10µm),andFigureES‐3(PM2.5,orparticulatematterwithaerodynamicdiameterlessthan2.5µm).Comparingbetweenfigures,totaldustemissionsaremuchhigherthanthoseofPM10andPM2.5,reflectiveofthenatureoffugitivedustsourcestoreleaselargerparticlesizes.Thehighestemissionestimatesareforbulldozingoperations,whichdependstronglyonthematerialsiltcontent.Emissionestimatesfromthetravelofhaultrucks

Executive Summary

ES‐2

onthepavedaccessroadandfromgradingthestockpilematerialarethesameforallbulkmaterialsasthecalculationmethodsforthesetwoactivitiesdonotdependonmaterialproperties.Overall,emissionestimatesarehighestforthepetroleumcokematerial.Estimatesofwinderosionemissionsfromthestockpile,thoughlowerthanothersourcesonanannualbasis,maybeofelevatedimportanceonanepisodicbasisastheemissionsareassumedtooccuroveraverylimitednumberofhoursperyear.

ThefugitivedustemissionestimatesweresubsequentlyusedasinputtotheAERMODdispersionmodeltopredicttheincrementalconcentrationsofparticulatematterinambientairthatcouldresultfromtheactivitiesatabulkprocessingandstoragefacility.Akeyaspectofthecalculationsinvolvedthelinkageofhourlyemissionestimatestothemeteorologicaldatausedinthedispersionmodelingstudy.ThepredictedincrementalconcentrationsofPM10andPM2.5exceedthelevelsofNationalAmbientAirQualityStandards(NAAQSs)foranumberoftheemissionsourcesconsidered.SincebackgroundlevelsofPM10andPM2.5alreadyaccountforsubstantialfractionsoftheNAAQSs,substantialmitigationeffortsmayberequiredonthepartofoperatorsofbulkmaterialprocessingandstoragefacilitiestoensurethatfugitivedustemissionsdonotleadtolocalizedexceedancesofambientairqualitystandards.

Figure ES‐1 Estimates of Total Dust Emissions

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PetroleumCoke

Coal Mesaba Ore Slag

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Grading Material

Bulldozing Material

Paved Roads

Travel on the Stockpile

Drop Operations

Executive Summary

ES‐3

Figure ES‐2 Estimates of PM10 Emissions

Figure ES‐3 Estimates of PM2.5 Emissions

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Paved Roads


Drop Operations

1‐1

Section 1

Introduction and Purpose

Thepresenceandmovementofbulksolidmaterialscanleadtoinadvertent,fugitiveemissionsofdusttotheair.TheCityofChicagohasproposedregulationsfortheHandlingandStorageofBulkMaterialPilestocontrolpotentialemissionsfromfacilitiesthatprocessandstorebulkmaterials.

Thisfugitiveduststudyevaluatesthepotentialmechanismsofdustgenerationassociatedwithbulkmaterialpiles.ThestudyisdesignedtoinformtheCityconcerningtheimportanceofactivitiesthatifunmitigatedmightproducedustandaffectambientairquality.ProceduresdevelopedbytheU.S.EnvironmentalProtectionAgencyareimplementedtoestimatepotentialdustemissionsfrommaterialhandlingactivities,includingdroppingoperations(fromtruckdumping,front‐endloaderuse,conveyors,etc.),bulldozing,vehicletravelonpavedroadsandthesurfaceofthepile,andsurfacewinderosionfromstockpiles.Asdustemissionsofmanyoftheseactivitiesdependuponbulkmaterialcharacteristicssuchasgrainsizeandmoisturecontent,severaldifferentbulksolidmaterialsareevaluated.Predictedemissionsareusedinconjunctionwithairdispersionmodelingtoestimatepotentiallevelsofdustinambientairthatresultfromoperationofabulksolidmaterialstorageandprocessingfacility.

2‐1

Section 2

Conceptual Bulk Material Storage Facility

Thefugitiveduststudyfocusesonagenericbutrepresentativebulkmaterialprocessingfacility.Theconceptualfacilityisnotdesignedtorepresentaspecificbulksolidmaterialsprocessingfacility,butratherismodeledafterspecificationsintheCity’sdraftregulationsandincludesavarietyofprocessescapableofgeneratingdust,someorallofwhichmayberelevanttospecificfacilities.

Forsimplicity,astoragepilecoveringacirculararealfootprintisassumed.Thetopofthepileisassumedtobeconicalfrustuminshape,withsideslopesleadingtoaflattop.Thevolumeofmaterialstorageisassumedtobe100,000cubicyards(yd3),and2,000tonsperday(tpd)ofmaterialisassumedtobeprocessedforfivedayseachweek.

Figure2‐1depictstheconfigurationoftheconceptualbulkmaterialstoragefacility.Apavedaccessroadisassumedtoapproachthefacilityfromtheeastandruntangentialtotheoutsideofthepile.Haultrucksareassumedtotraversetheaccessroadanddepositloadsoffreshmaterialatthenorthernedgeofthepile.Abulldozerandgraderareassumedtomovethebulkmaterialandshapethepile.Afront‐endloaderandanarticulatedtruckareassumedtomovematerialonthesurfaceofthestoragepileandfacilitatetheloadingofaconveyorthatplacesthebulkmaterialonrailcarsorbargesforshipmentoutofthefacility.Theassumedequipmentandoperationsaregenericinconstruction,butaredesignedtorepresentthespectrumofactivitiestypicallyfoundatbulkmaterialstoragefacilities.

Thesizeofthestoragepileisdeterminedbytheassumedvolumeandshapeofthepile.Basedonanassumedratioof0.4ofthediameterofthetop(flat)portionofthepilecomparedtoitsbaseandanassumedpileheightof30feet,thebaseddiameterofthepileiscalculatedtobe469feet.Theresultingexposedsurfacearea(basedontheassumedconicalfrustumshape)is176,325ft2.

Fourdifferentbulkmaterialsareexaminedtoconsiderarangeofcharacteristicsthatinfluencedustemissions.ThebulkmaterialswereselectedinconjunctionwithdiscussionswiththeCityofChicago,andareselectedtoberepresentativeofmaterialslikelyhandledatlocalstorageandprocessingfacilities.Propertiesofthefourmaterials,asgatheredfromsampleanalysesandinformationintheliterature,aresummarizedinTable2‐1.

2‐2

LegendforSources

SLINE1 Lineof18volumesourcesforpavedroademissions(haultrucks)

SLINE2 Lineof6volumesourcesforemissionsfromtravelonthepilesurface(articulatedtruckandfront‐endloader)for24‐hourmodeling

UAREA1 Areasourceforemissionsfromtravelonthepilesurface(articulatedtruckandfront‐endloader)forannualmodeling

PAREA1

FAREA1

Areasourcesforbulldozingandgradingfor24‐hourandannualmodeling,respectively

CAREA1 Areasourceforwinderosionfromstockpiles

VOL1toVOL5

Dropsourcesfromconveyor(1‐3),haultruckdumping(4),andarticulatedtruckloading(5)

Figure 2‐1 Conceptual Bulk Material Storage Facility Configuration of Area, Volume, and Line Volume Sources

Section 2 Conceptual Bulk Material Storage Facility

2‐3

Table 2‐1 Characteristics of Bulk Materials

Property Material

Petcoke Coal Mesaba Ore Slag

Silt (%) 21.2 (a) 4.6 (c) 3 (e) 0.55 (f)

Moisture (%) 6.7 (a) 4.8 (c) 1 (e) 8.69 (f)

Bulk Density (lb/ft3) 50 (b) 50 (d) 135 (e) 60 (g)

Data sources: (a) Average of measurements from two petcoke samples (Appendix A) (b) http://www.petroleumhpv.org/docs/pet_coke/2000‐08‐30Pet%20Coke%20Robust%20Summary.pdf (c) AP42 Table 13.2.4‐1 values for coal in iron and steel industry (d) Typical bituminous value, http://www.tapcoinc.com/content/product_data/Tapco_Catalog_09_p88‐94.pdf (e) http://s3.amazonaws.com/zanran_storage/www.isamill.com/ContentPages/2534118165.pdf#page=8 (f) Average of measurements from three slag samples obtained by CDPH from a local bulk material handling company (Appendix B) (g) http://www.aqua‐calc.com/page/density‐table/substance/slag‐coma‐and‐blank‐furn‐point‐‐blank‐granulated

3‐1

Section 3

Emission Calculations

FugitivedustemissionsareestimatedaccordingtomethodsrecommendedbytheU.S.EnvironmentalProtectionAgency(EPA)initsCompilationofAirPollutantEmissionFactors(AP42)document.AP42hasevolvedtoanon‐linereferencedocumentthatcontainsnumerouschaptersdevotedtoestimatingfugitivedustemissions(http://www.epa.gov/ttn/chief/ap42/index.html).

ThespecificAP42sectionsthatareusedtoestimatepotentialfugitivedustemissionsfrombulkmaterialstoragefacilitiesaredescribedinsubsequentsections.Someoftheemissionfactorsdependonwindvelocities,andarehencetiedtometeorologicaldata(describedinSection4.2.3).Dustemissionsarecalculatedonanhourlybasistocomplementsubsequentairdispersionmodeling.Withtheexceptionofwinderosionfromstockpiles,emissionsareestimatedduringassumedhoursoffacilityoperationfrom7:00AMthrough5:00PM(tenhoursperday)forfivedayseachweek.

3.1 Drop Operations Dustcanbegeneratedeachtimeamaterialistransferredfromonelocationtoanothervia“dropping”operations.AP42Section13.2.4providesthefollowingequationtoestimatetheseemissions:

0.0032 5

.

2

.

wherethetermsare:

E Dustemissionperunitofmaterialhandled(lb/ton); k Particlesizemultiplier(1fortotaldust,0.35forPM10,and0.053forPM2.5); U Meanwindspeed(mph);and M Moisturecontentofthebulkmaterial(%).

Fivedropoperationsareassumedtooccuracrosstheconceptualbulkmaterialstorageandprocessingfacility:

Duringtheunloadingofincominghaultrucks;

Duringtheloadingofanarticulatedtruckbythefront‐endloader;and

Atthreepointsonaconveyorsystem(conveyorloading,anintermediatetransferpoint,andtheloadingofoutgoingrailcarsorbarges).

Aprocessingrateof2,000tonsperdayisassumedforeachdropoperationundertheassumptionofquasi‐steady‐stateoperation(equalmaterialinflowsandoutflows).Theprocessingrateisassumedtobedistributedevenlyoverfacilityoperatinghours.

Section 3 Emission Calculations

3‐2

3.2 Travel on the Surface of the Pile

Dustcanbegeneratedwhenoff‐roadvehiclestraveldirectlyacrossthesurfaceofthebulkmaterialstoragepile.AP42Section13.2.2providesthefollowingequationtoestimatetheseemissions:

12 3

wherethetermsare:

E Dustemissionpervehiclemiletraveled(lb/VMT); s Siltcontentofthebulkmaterial(%);

k Particlesizemultiplierforindustrialroads(4.9lb/VMTfortotaldust,1.5lb/VMTforPM10,and0.15lb/VMTforPM2.5);

a Particlesizedependentconstant(0.7fortotaldust,0.9forPM10,and0.9forPM2.5); b Empiricalconstantequalto0.45;and W Averageweightofthevehiclestravelingonthesurface(tons).Siltcontentisspecifictothebulkmaterial(seeTable2‐1).Twovehiclesareassumedtotravelonthestorageandprocessingpile:

afront‐endloaderwithatareweightof14.5tonsandbucketcapacityof6.5cubicfeet;and

anarticulatedtruckwithatareweightof30tonsandcarryingcapacityof40tons.

Eachvehicleisassumedtoloadorcarry2,000ton/dayofbulkmaterial.Thearticulatedtruckisassumedtomaketripsacrossthepile,traversingatotalof8.9milesperday.Thefront‐endloaderisassumedtotravelhalfofthisdistance(4.45milesperday).Theaveragevehicleweightof38.9‐40.1tonsisestimatedbyweightingtheaverageloadedandunloadedweightsofthevehiclesbytheassumedtraveldistances(thevaluedependstoasmallextentonthebulkdensityofthematerial).

3.3 Paved Roads Dustcanalsobegeneratedbyon‐roadvehiclesthatresuspendsiltedmaterialfrompavedroadways.AP42Section13.2.1providesthefollowingequationtoestimatetheseemissions:

. .

wherethetermsare:

E Dustemissionpervehiclemiletraveled(lb/VMT);k Particlesizemultiplier(0.011lb/VMTfortotaldust,0.0022lb/VMTforPM10,and

0.00054lb/VMTforPM2.5); sL Roadsurfacesiltloading(g/m2);and W Averageweightofthevehiclestravelingtheroad(tons).

Thesiltloadinginthiscaseisnotspecificallygermanetothebulkmaterial,butratherreflectsthedegreeoffinedustcoveringtheroadduetoallsources.Amid‐rangesLvalueof70g/m2isselectedfromvaluesdocumentedinAP42Table13.2.1‐3,asdevelopedfrommeasurementsinthesandandgravelprocessingindustry.Anaveragevehicleweightof40tonsisassignedtoWastheaverageloadedandunloadedweightofahaultruckwithatareweightof30tonscarrying20tonsofbulk


3‐3

materialtothestorageandprocessingfacility.Theone‐waydistanceoftravelassumedbyahaultruckis100feetfromthegatetothehaulroadplus369feetalongtheoutsideofthematerialpile(onequarterofthepilecircumference).Allowingfordoublethedistancetogoinandoutofthefacilityandthe100trucksnecessarytodeliverbulkmaterial,haultrucksareassumedtotravelatotalof17.8vehiclemileseachdayoffacilityoperation.

3.4 Bulldozing and Grading Bulldozersarelikelytobeusedtomovematerialsshortdistances,suchasfromthedumpareasofhaultruckstowardthestoragepileorworkinglimitedareasofthepile.Gradersarelikelytobeusedtomaintainthegeneralshapeoftheentirepile.Abulldozerandgraderareassumedtoeachoperate50%ofthetimeattheconceptualbulkmaterialfacility.AP42Section11.9(Table11.9‐1)providesthefollowingequationsforestimatingdustemissionsduringthecourseoftheiroperations.Forthebulldozer,theemissionfactorsare:

Totaldust.

.

PM.

.

PM . .

.

.

wherethetermsare:

EB Dustemissionpertime(lb/hr); Empiricalconstantof78.4lb/hr(petroleumcokeandcoal)or5.7lb/hr(Mesabaore

andslag); Empiricalconstantof18.6lb/hr(petroleumcokeandcoal)or1.0lb/hr(Mesabaore

andslag); s Siltcontentofthebulkmaterial(%); M Moisturecontentofthebulkmaterial(%); k10 PM10particlesizemultiplierequalto0.75;and

k2.5 PM2.5particlesizemultiplierequalto0.022(petroleumcokeandcoal)or0.105(Mesabaoreandslag).

Emissionsfromgradingoperationsareestimatedas:

wherethetermsare:

EG Dustemissionpertime(lb/VMT); Empiricalconstantof0.051lb/VMTforPM10and0.040lb/VMTfortotaldustand

PM2.5; Empiricalconstantof2forPM10and2.5fortotaldustandPM2.5; k Particlesizemultiplierequalto1(totaldust),0.6(PM10),or0.031(PM2.5); S Averagespeedofthegrader(mph).

TheaverageAP42defaultmedianvalueof7.1mphisassumedfortheaveragevehiclespeedS.Atthisspeed,thegraderwilltravel3.55milesonthestoragepileeachhourifutilizedhalfthetime.


3‐4

3.5 Wind Erosion from Stockpiles Windsofsufficientstrengthcancausedusttoblowoffofstoragepiles,especiallyifthematerialisfineanddry.AP42Section13.2.5providesthefollowingequationforestimatingdustemissionsduetowinderosionfromstockpiles:

58 ∗ ∗ 25 ∗ ∗

wherethetermsare:

P Dustemissionperunitarea(g/m2);

k Particlesizemultiplier(1fortotaldust,0.5forPM10,and0.075forPM2.5); u* Frictionvelocity(m/s);and ut* Thresholdfrictionvelocity(m/s).

Theequationforfrictionvelocityappliesonlywhentheatmosphericfrictionvelocityexceedsthethresholdfrictionvelocity.Additionally,winderosioneventstypicallyoccurunderdryconditionsoverapilethathasrecentlyexperiencedsurfacedisturbance.Oncefinematerialshaveblownoffthesurface,thelayermustbereplenishedbeforethenextwinderosioneventcanoccur.

Twocalculationsareperformedtoestimatethepotentialmagnitudeofemissionsduetowinderosionfromstockpiles.First,aworst‐caseassumptionismadethatonewinderosioneventcouldoccureachday(providedthefrictionvelocityexceedsthethresholdforatleastonehourduringtheday).Suchasituationmightoccurduringperiodsofextendeddrynesswhilethestoragepileremainsactiveandthesurfaceisroutinelyreplenished.Second,theassumptionismadethattherecouldbeonaverageonewinderosioneventeachmonth.Thedailyandmonthlywinderosionmodelsarethusdesignedtotestthesensitivityofthewinderosionalgorithms.

HourlyestimatesofthefrictionvelocityareavailablefromtheAERMETpreprocessingprogram,whichestimatesu*valuesinthecourseofpreparingmeteorologicaldataforusebytheAERMODdispersionmodel.Thethresholdfrictionvelocityut*dependsontheparticlesizecharacteristicsofthebulkmaterial.AP42Table13.2.5‐1providesdatafromafieldprocedureforestimatingut*.Acurve‐fitofthedata(R2=0.9995)yieldstheequationforut*(incm/s):

∗ 64.43 .

whereOisthemidpointopeningsize(inmm)ofthesievesthatindicatethestatisticalmodeofanempirically‐derivedgrainsizedistribution(followingthemethoddescribedinAP42Section13.2.5).Estimatesofut*forthefourbulkmaterialsexaminedare:

47cm/sforpetroleumcoke,basedonanaverageestimatederivedfromgrainsizeanalysesoftwosamples(AppendixA);

54cm/sto112cm/sforcoal,basedonspecificvaluesreportedinAP42section13.2.5;

187cm/sforMesabaore,basedondatafromareportedgrainsizeanalysisparticlesizedistribution(http://s3.amazonaws.com/zanran_storage/www.isamill.com/ContentPages/2534118165.pdf#page=8);and

61cm/sforslag,basedontheresultsofagrainsizeanalysis(AppendixB).


3‐5

Overeachdailyperiod,theequationtopredictevent‐basedwinderosionisappliedtothehourofthedaywiththehighesthourlyfrictionvelocity.Inaddition,frictionvelocityestimatesfromthemeteorologicaldataarereducedbyafactorof0.9toaccountforreducedwindspeedsthatwouldbeexpectedtooccuroverastoragepileasitactsasapartialobstructiontosurfacewinds(asdescribedinAP42Section13.2.4).

3.6 Fugitive Dust Emission Estimates Theequationsforfugitivedustemissionsfromthevarioussourceswereimplementedinaspreadsheetinconjunctionwithhourlymeteorologicaldataforthe2008calendaryear.Emissionestimateswerederivedfortotalsuspendedparticulate(TSP,ortotaldust)anditssubcomponentsPM10andPM2.5.Summariesoftheannualemissiontotals,intons/year,areprovidedinTable3‐1(TSP),Table3‐2(PM10),andTable3‐3(PM2.5).

Thecompiledemissionestimatesreflectthenatureofthedependenciesoftheunderlyingfactorsthataffectemissions.Emissionestimatesforthepavedroadandgradingsourcesarethesameforallfourmaterialsastherearenodependenciesonbulkmaterialpropertiesintheconstitutivemodelequations.Petroleumcoke,duetoitshighsiltcontent,generatesthehighestemissionestimatesforoff‐roadvehiclestravelingonthepilesurface,bulldozing,andwinderosionfromstockpiles.Mesabaoreproducesthehighestemissionestimatesfordroppingoperations(materialhandling)becauseofitslowmoisturecontent.1Stockpilewinderosionestimatesaregreatestforpetroleumcoke,andlowest(zero)forMesabaore(forwhichthethresholdfrictionvelocityisneverexceededinthehourlymeteorologicaldata).Stockpilewinderosionestimatesforthemonthlyeventmodelareasubstantialfractionofthoseofthedailyeventmodel,reflectiveofthenatureoftheunderlyingnon‐linearmodelequationthatpredictsveryhighemissionsunderelevatedwindconditions.

Totalfugitivedustemissionsarehighestforthepetroleumcokematerial,butcanbesubstantial(oftheorderof100tons/yearormore)forallmaterials.Thegenericassumptionsregardingfacilitysize,materialhandlingpractices,andequipmentconfigurationandutilizationcanbeexpectedtobedifferentinpracticeatactualfacilities,andfacility‐specificassessmentsmaybeusefulingeneratingmoreaccurateestimatesofemissions.

Thefugitiveduststudydoesnotexplicitlyconsiderdustcontrolmeasuresinordertohighlightprocessescapableofproducingdustemissions.Mostfugitivedustemissionsareamenabletocontrol.Forexample,pavedroademissionscanbereducedthroughstreetsweepingandtargetedapplicationofwater.Manyestimatesarealsomadewithconservativeassumptionsdesignedtooverestimatelikelyemissions(suchasthepremisethatdryconditionswillpersistforlongperiodsoftime).

Therearealsouncertaintiesinherenttotheestimationoffugitivedustemissions.Thefugitivedustemissionestimatesmustthereforebeinterpretedwithcaution.SomesenseofthereliabilityofthemethodsisprovidedintheAP42sectionsfromwhichthepredictiveequationsaretaken,andreadersareencouragedtoreviewtheU.S.EPA’sdescriptions.

1ThemoisturecontentoftheMesabaore(astakenfromtheliterature)isnotablylowerthanthatfortheothermaterialsconsidered.Asmoisturecontentisexpressedasaweightpercentageandtheorehasahigherbulkdensity,thevolumefractionofwaterishigherthanrepresented(relativetoothermaterials).AstheAP42equationformaterialdroppingemissionsdoesnotaccountfordifferencesinbulkdensity,dropemissionestimatesfortheMesabaorematerialmaybeoverstatedrelativetotheothermaterials.


3‐6

TheU.S.EPAAP42emissionfactorsarederivedfromempiricaldatatoidentifyandcapturethevariablesthatmostinfluencefugitivedustemissions.Manyoftheemissionfactorsdependonbulkmaterialproperties.Sincethesamehandlingassumptionsareusedtoevaluateeachmaterial,comparisonsbetweenmaterialsindicatetrendsandtendenciesbasedonthecharacteristicsofthematerialsthatcanbeinfluencedbyfacility‐specificcontrolandmitigationmeasures.


3‐7

Table 3‐1 TSP Emission Summary


Silt (%) 21.2 4.6 3 0.55

Moisture (%) 6.7 4.8 1 8.69

Threshold Friction Velocity (u

*t, m/s)

0.47 0.54 to 1.12 1.88 0.62

Bulk Density (lb/ft3) 50 50 135 60

Total Suspended Particulate (TSP) Emissions (tons/year)

Drop operations 2.2 3.6 32.0 1.6

Travel on Pile Surface 20.2 6.9 5.2 1.6

Paved Roads 52.5 52.5 52.5 52.5

Bulldozing Material 168.8 41.6 13.9 0.1

Grading Material 24.9 24.9 24.9 24.9

Wind erosion from stockpiles (daily)

57.9 0.8 to 41.5 0 27.6

Wind erosion from stockpiles (monthly)

11.2 0.8 to 9.7 0 8.0

Total (daily wind erosion) 326 130 to 171 129 108

Total (once per month wind erosion)

280 130 to 139 129 89

Percentage hours greater than friction velocity threshold

37% 0.6% to 26% 0% 18%


3‐8

Table 3‐2 PM10 Emission Summary


Silt (%) 21.2 4.6 3 0.55

Moisture (%) 6.7 4.8 1 8.7


*t, m/s)

0.47 0.54 to 1.12 1.88 0.62


PM10 Emissions (tons/year)



Paved Roads 10.5 10.5 10.5 10.5




29.0 0.4 to 20.8 0 13.8


5.6 0.4 to 4.8 0 4.0



93 31 to 35 33 22


37% 0.6% to 26% 0% 18%


3‐9

Table 3‐3 PM2.5 Emission Summary


Silt (%) 21.2 4.6 3 0.55

Moisture (%) 6.7 4.8 1 8.69


*t, m/s)

0.47 0.54 to 1.12 1.88 0.62


PM2.5 Emissions (tons/year)



Paved Roads 2.6 2.6 2.6 2.6




4.3 0.1 to 3.1 0 2.1


0.8 0.1 to 0.7 0 0.6



9 5 to 5 7 4


37% 0.6% to 26% 0% 18%

4‐1

Section 4

Dispersion Modeling

4.1 AERMOD References/Version DispersionmodelingwasconductedusingthelatestversionoftheU.S.EPA‐approvedAERMODdispersionmodelingsystem(AERMODVersion13350)andtheLakesEnvironmentalAERMODViewgraphicuserinterfaceversion8.5.0.AERMODisacomputer‐basedmathematicaldispersionmodelthatcanpredictambientconcentrationsofpollutantsthatresultfromreleasestotheatmosphere.AERMODalgorithmsassumethat:

Asource’splumeissteady‐state,

TheverticalandhorizontalconcentrationdistributionsfitaGaussiandistributioninthestableboundarylayer(SBL),and

Fortheconvectiveboundarylayer(CBL),thehorizontalconcentrationdistributionisGaussianandverticaldistributionfitsabi‐Gaussianprobabilitydensityfunction.

AERMODuseshour‐by‐hourmeteorologicaldatatopredictthepatternsofambientconcentrationsofpollutantsovertime.Matchedwithhour‐by‐hourestimatesoffugitivedustemissions,AERMODiscapableofpredictingbothshort‐termandlong‐termestimatesoftheimpactsofbulkmaterialprocessingandstoragefacilitiesonambientairquality.

4.2 Modeling Setup 4.2.1 Terrain Digitalelevationmodeldatawasnotrequiredbecausetheterrainsurroundingthesourcewasassumedtobeflat.

4.2.2 Receptor Grid Anon‐uniformpolarreceptorgridcenteredonthesourceconsistsof36radials(oneevery10degrees)thatintersectsixreceptorringsatdistancesof115,140,170,220,280and350metersfromthesource.Thegridconsistsof216receptorseachassumedtobeatground‐level(0.0metershigh).

Fencelinereceptorswerealsoincludedinthemodelandlocatedevery10metersalongthevirtualpropertyboundaryforatotalof36receptors.ThereceptorgridisshowninFigure4.1.

4.2.3 Meteorological Data and Land Use AsdescribedinSection3.4,hourlysurfacemeteorologicaldataforMidwayAirport(StationID72534,baseelevation607feetand10meteranemometerheight),Chicago,IL,andupperairdatafromLincoln,IL(StationID4833)for2008wereobtainedfromathirdpartyvendor.ThedataaspurchasedhaveundergonethequalityassuranceprocessrequiredbyEPAtoidentifyandfillinmissingdata.ThesurfaceandupperairmeteorologicaldatawerepreparedforuseinAERMODusingtheAERMETmeteorologicaldatapreprocessorandLakesEnvironmentalAERMETViewGraphicUser

Section 4 Dispersion Modeling

4‐2

InterfaceVersion8.50.Processingofthesurfacefileindicatedmorethan99percentdataavailabilityoutof8,711recordsused.

Surfaceparameters(albedo,Bowenratioandsurfaceroughness)weredeterminedusingtheAERSURFACEpreprocessorandsurfacedatafromtheNationalLandCoverDatabaseforthestateofIllinoisbasedontheNorthAmericanDatum83.AERSURFACEevaluated30degreesectorsoverafullcircletogenerate12setsofthethreeparameters(oneforeachsector).

ThemeteorologicaldataoutputfromAERMETissummarizedinthewindroseshowninFigure4.2.Windsmostcommonlyoriginatefromthesouth‐southwestandwesterlydirectionsingeneral,thoughwindsoriginatefromalldirectionsforatleastsomepercentageoftime.Theaveragewindspeedoverthe8,711availablemeasurements2forcalendaryear2008was9.7mph(treatingcalmconditionsas0).Hourlyaveragewindsexceeded15mph13%ofthetimeand20mph4%ofthetime.

2 Wind speeds were missing from 73 hours during the 2008 calendar year. These hours are assigned a code of 999 by AERMET and are ignored by AERMOD in dispersion modeling, as are 500 additional hours that are reported as calm conditions (with 0 wind speed). For the purpose of estimating annual emission totals, hours with missing wind speeds were assigned the average values of wind speeds of the previous and subsequent hours, and calm conditions were assigned a wind speed of 0.25 m/s (half of the lowest measureable wind speed).


4‐3

Figure 4‐1 Polar and Fenceline Receptor Grid


4‐4

Figure 4‐2 Windrose for Chicago Midway Airport 2008 Surface Observations


4‐5

4.2.4 Pollutants and Averaging Times Modelingwasconductedforemissionsofparticulatematterlessthan10micrometersaerodynamicdiameter(PM10)andparticulatematterlessthan2.5micronaerodynamicdiameter(PM2.5)frompetcokeandcoalmaterialhandlingoperations.ThesourcesthatcomprisethematerialhandlingoperationarediscussedinSection4.3.ModelingofPM10wasconductedfora24‐houraveragingtimeforbothpetcokeandcoalmaterialhandlingoperationsinrecognitionofPM10’sNationalAmbientAirQualityStandard(NAAQS).Similarly,modelingofPM2.5wasconductedforannualand24‐houraveragingperiodsforpetcokeandcoalhandlingoperationsinrecognitionofPM2.5’sNAAQSs.Inaddition,1‐houraveragePM10modelingwasconductedtoexaminespecificimpactsofthewinderosionfromstockpilessourceforbothpetcokeandcoal.

Particulatematterdepositionusingparticlesizedatawasnotconsideredforanymodelingruns,resultinginnoremovalofmassfromtheplume,andhencelikelymoreconservativepredictionsofimpactstoambientair.

4.3 Emission Sources 4.3.1 Source Types AERMODhasthecapabilityofmodelingvarioustypesoffugitivedustsourcesthatincludeareasources,volumesources,andlinesourcesaslinevolumesources.3Areasourcesareappropriatetomodelgroundlevelreleaseswithnoplumerisesuchasstoragepiles.Volumesourcesapplytoconveyorsandothersourceswhereaplumewouldbegeneratedfromadrop‐likeoperation.Linesourcesincluderoadways.AERMODcanbeusedtomodellinesourcesasaseriesofadjacentvolumesources.

Areasourceswereusedformodelinganyvariationsinareatothestoragepilesurfacesuchasforbulldozeroperationsinaspecificarea.Areasourceemissionratesaresimplytheequipmentemissionrateinmasspertimedividedbythetotalsourcearea.Forshort‐termmodelingapplicationswhereabulldozerwouldbeworkinginaspecificareaofthestoragepile,itsemissionratewouldbedistributedoverthatlocalizedarea,usuallyafractionofthetotalarea.Forlong‐termmodelingapplicationsoverayearormorewhereabulldozerwouldbeworkingovertheentirefaceofthestoragepile,theemissionratewouldappropriatelybedistributedbythetotalstoragepileworkingfacearea.Thereleaseheightsforareasourceswereassumedtobezero(ground‐level).

Forthisevaluation,roadways,bothpavedandunpaved(trafficoverthebulkmaterialsurface),weremodeledasadjacentvolumesourcesinaccordancewithEPAguidance.4Thetopofthesource’splumeheightisgivenas1.7timesthevehicleheightandthesource’splumereleaseheightiscalculatedas½ofthetopoftheplumeheight.Therecommendedplumewidthiscalculatedasthevehiclewidthplussixmetersforasinglelaneroad,whichistheapproachusedforthismodelingevaluation.Theinitialverticalplumesizeiscalculatedastheplumeheightdividedbyafactorof2.15,andtheinitialhorizontalplumeheightiscalculatedastheplumewidthdividedby2.15.

3 AERMOD as issued by EPA does not contain algorithms for line sources. The Lakes Environmental interface to AERMOD allows specification of line sources that are translated into series of adjacent volume sources. 4 Volume II of the U.S. EPA User’s Guide for the Industrial Source Complex (ISC3) Dispersion Models (U.S. EPA, 1992).


4‐6

4.3.2 Modeling Approach Themodelingapproachconsideredagenericbulkmaterialprocessingfacilitythatincludesvariousmaterialhandlingoperationsandstorage.Figure2.1showstheconceptualbulkmaterialstoragefacilitywiththeprimefeaturebeingalargestoragepileshapedasaconicalfrustum.Thematerialhandlingoperationswouldincludetypicalheavyequipmentactivitysuchas:

Resupplyofmaterialtothestoragepileviaon‐roadhaultruckactivity;

Preparationandmaintenanceofthestoragepilewithabulldozerandgrader;

Materialtransportwithintheconfinesofthesiteandoverthesurfaceofthestoragepileusingafront‐endloaderandarticulateddumptruck;

Conveyanceofmaterialforloadingoperationswithamulti‐segmentconveyorsystem.

Allofthisequipmentmightnotbeusedateveryfacility,butthegoalofthisstudyistoconsiderallpossiblemeansbywhichfugitivedustemissionsmightarise.Withtheexceptionofthestoragepileitself,theemissionsourcesareprimarilydefinedbytheuseofheavyequipmentandtrucksatspecificareaswithinconfinesof‐andaround‐thesiteboundary.Thesourcesandprimaryareasofoperationusedasinputstothemodelareasfollows:

Winderosionofthewholestoragepilecouldoccurannuallyasthesurfaceisintermittentlydisturbed.Thestoragepilewasmodeledasanareasourcesubjecttowinderosion;thereforetheemissionratesinputtothemodelwerederivedfromwinderosionequationsdescribedinSection3.5.

Abulldozerandgraderwouldlikelyoperateinanominalrectangularareatoconstantlyreshapethestoragepileasmaterialisaddedandremoved.Emissionsfromtheseactivitieswouldmainlybethedustfromthebulldozertracksandthegraderblade.Thissourcewasmodeledasrectangularareasourcelocatedontheeastsideofthefacilityforshort‐term(daily)operations,butemissionsweredistributedoverthefullstoragepileareaforlong‐termprojections.TheemissionratesinputtothemodelwerederivedfromequationsdescribedinSection3.4.

Haultrucksbringingnewmaterialtothefacilityfordepositandprocessingareassumedtotravelonthepavedperimeterroadanddumpmaterialonthenorthsideofthestoragepile.Thesourcesfromthisactivitywouldbedustemissionsmobilizedfromthepavementbytrucktiresandthedumpingemissionswherethematerialisunloadedatthenorthsideofthepile.Thepavedroadwayisassumedtooriginatefromaneastentranceandextendalongtheedgeofthestoragepiletothenorthwherematerialunloadingwouldoccur.Emissionswouldincludetheroundtripintoandoutofthesite.Thetrucktripemissionsweremodeledasalinevolumesource,whichisaseriesofnearlyequalvolumesourcesfromthebeginningoftheroutetotheend.TheemissionratesfortrucktraveloverpavedroadthatwereinputtothemodelwerederivedfromequationsdescribedinSection3.3.Theunloadingofthenewmaterialatthenorthsideofstoragepilewasmodeledasasinglevolumesource.TheemissionratesfortruckunloadingwerederivedfromdropoperationequationsdescribedinSection3.1.

Anarticulateddumptruckandfront‐endloaderoperatingonthefaceofthestoragepilewouldtravelalongamakeshiftunpavedroadonthesurfaceofthestoragepilebetweenthelocation


4‐7

wherethehaultrucksunloadandthecenterofthepile.Thefrontendloaderwouldfillthearticulateddumptruckatthenorthsideofthesiteandtheywouldtraveltogethertothecenterofthesitewherethedumptruckwouldunloaditsmaterialandthefront‐endloaderwouldloadmaterialontotheconveyorinlethopper.TheloadingofthearticulateddumptruckwasmodeledasasinglevolumesourceusingemissionratesderivedfromthedropequationsdescribedinSection3.1.Travel‐relatedemissionsoftheloaderanddumptruckontheunpavedroad(bulkmaterialsurface)betweenthecenterofthepileandthenorthsideofthepileweremodeledusingemissionratesderivedfromunpavedroadequationsdescribedinSection3.2.Thepavedroadwastreatedasaseriesofnominallyequalvolumesources.ThearticulateddumptruckunloadingneartheconveyorwasmodeledasasinglevolumesourceusingemissionratesderivedfromthedropequationsdescribedinSection3.1.

Theconveyorwouldbecoveredexceptatthreepositionsinthesystem,theinlet,anintermediatesegmentchangeinconveyanceandtheoutletoftheconveyorsystem.Thetwopointswherefugitiveemissionswouldoccurwouldbeattheintermediatesegmentchangeandtheoutlet.Theoutletiswherebargeandtraincarloadingwouldoccur.TheconveyorsystemoutletandintermediatelocationsweremodeledassinglevolumesourcesusingemissionratesderivedfromthedropequationsdescribedinSection3.1.

Table4‐1summarizeseachoftheseactivitiesandhowtheyaredefinedformodelingpurposes.

4.4 PM10 (24‐hr) and PM2.5 (Annual, 24‐hr) Modeling Results Petcokeandcoalmaterialhandlingoperationsweremodeledforthemaximum24‐houraveragePM10concentrationsandthemaximumannual‐averageand24‐houraveragePM2.5concentrations.AERMODwassetuptoallowtheevaluationofindividualandgroupsoffugitiveemissionsources.Themodelingresultsarepresentedinthefollowingsections.

4.4.1 Petcoke Material Handling Modeling Results ThepetcokematerialhandlingmodelingresultsandcorrespondingfiguresthatgraphicallysummarizethemodelingresultsaredescribedinTable4‐2.EachmodelingscenarioisrepresentedbyacorrespondingfigurethatisdescribedinthetableandincludedinAppendixC.Figuresdepictingthepredictedimpactsofallsources(summedtogether)arealsoincludedinthissection.

AsShowninTable4‐2,predictedconcentrationsof24‐houraveragedPM10and24‐houraveragePM2.5greatlyexceedNationalAmbientAirQualityStandards(NAAQSs).Amongthesourcegroups,bulldozer/graderoperationsarepredictedtoresultinthemaximumincrementalconcentration(4,899µg/m3forPM10and317µg/m3forPM2.5,bothatthesamereceptor).Substantialimpactsarealsopredictedforthepavedandunpavedroadsources.Fortheannualaveragingperiod,thetotalpredictedconcentrationofPM2.5onlymodestlyexceededtheleveloftheNAAQS.Intermsofindividualsources,pavedroademissionsdominatethetotalpredictedannual‐averagePM2.5concentrationandthesource‐specificmaximumPM2.5concentrationof14µg/m3wouldoccuralongtheperimeterroad.ThisconcentrationexceedstheNAAQSof12µg/m3and(asexpectedforaground‐levelsource)thepredictedimpactsrapidlydropoffwithinafewmetersfurtherawayfromtheperimeterroad.

4‐8

Table 4‐1 Modeling Source Summary

Source Description/

Type ID

Applicable Modeling Averaging Period

Height

[m]

Diameter

[m]

SigmaY

[m]

SigmaZ

[m]

Length_X

[m] Configuration

Line Volume Height

[m]

PlumeWidth

[m]

Line Volume

Type

Wind Erosion from stockpiles/ AREA_CIRC

CAREA1 All averaging periods 0 71.5

2

Bull‐dozer/Grader operations over the entire storage pile surface/ AREA_CIRC

FAREA1 Annual Averaging period 2 71.5

2

Bull‐dozer/Grader/ AREA_POLY

PAREA1 Short term Averaging periods (24‐hour)

2

2

Paved Road Haul Trucks/ LINE_VOLUME

SLINE1 (HT000001 ‐HT000018)

All averaging periods

Adjacent 5.7 8.44 Surface Based

Unpaved Road Articulated Dump Truck & Front End Loader/ LINE_VOLUME

SLINE2 (L0000069 ‐ L0000075)

Short term Averaging periods (24‐hour)

Adjacent 5.18 9.05 Surface Based

Unpaved Road Articulated Dump Truck & Front End Loader/ AREA_CIRC

UAREA1

For the long‐term averaging period, the emissions were spread‐out over the entire area of the storage pile.

2 71.5

2

Conveyor Drop 1/ VOLUME

VOL1 All averaging periods 5

1.163 1.163 5.0009



1.163 1.163 5.0009



1.163 1.163 5.0009

On‐Road Haul Truck Dump/ VOLUME

VOL4 All averaging periods 2.438

0.567 0.567 2.4381

Articulated Dump Truck Loading/ VOLUME

VOL5 All averaging periods 3.048

0.425 0.567 1.8275

Note: A base elevation of zero was used for all sources; emission rates were not included because an hourly emission rate source file that has more than one emission rate per source was used for each run. Lake Environmental AERMOD View uses single abbreviated source IDs to represent multiple volume sources (SLINE1 and SLINE2). Because the temperature of the sources are nearly ambient, fugitive dust emission plumes are modeled as not being buoyant.


4‐9

Table 4‐2 AERMOD Modeling Results Summary for Petcoke Material Handling

Material Pollutant Averaging

Period Source Group Figure

Maximum Predicted

Concentration (µg/m3)

Coordinates (meters)

X Y

Petcoke

PM10

24‐hour

(NAAQS = 150 µg/m3)

All 4.3, 4.3a

5297 70.71 84.26

Dozer 4.3b 4899 70.71 84.26

Drops 4.3c 69.6 ‐70.71 ‐84.26

Paved Roads 4.3d 450.3 110 0

Travel on Pile Surface

4.3e 276.7 37.62 103.37

Wind Erosionfrom Stockpiles

4.3f 9.6 103.4 37.6

PM2.5 24‐hour (NAAQS = 35 µg/m3)

All 4.4, 4.4a

390.5 70.71 84.26

Dozer 4.4b 317.5 70.71 84.26

Drops 4.4c 10.5 ‐70.71 ‐84.26

Paved Roads 4.4d 110.5 110 0


4.4e 27.7 37.62 103.37


4.4f 1.4 103.4 37.6

PM2.5

Annual

(NAAQS = 12 µg/m3)

All 4.5, 4.5a

21.4 108.3 19.1

Dozer 4.5b 6.1 84.26 70.71

Drops 4.5c 0.8 ‐70.71 ‐84.26

Paved Roads 4.5d 14.1 108.3 19.1


4.5e 0.9 84.26 70.71


4.5f 0.1 37.62 103.37

4.4.2 Coal Material Handling Modeling Results ThecoalmaterialhandlingmodelingresultsandcorrespondingfiguresthatgraphicallysummarizethemodelingresultsaredescribedinTable4‐3.EachmodelingscenarioisrepresentedbyacorrespondingfigurethatisdescribedinthetableandincludedinAppendixC.Figuresdepictingthepredictedimpactsofallsources(summedtogether)arealsoincludedinthissection.

Asshowninthetableandsimilartothemodelingresultsforpetcoke,AERMODpredictedforcoalmaterialhandlingoperationsthatforthe24‐houraveragingperiod,amongallthesourcegroups,bulldozer/graderoperationswouldresultinthemaximumconcentrationofbothPM10andPM2.5(atthesamereceptorineachcase).Predictedmaximumconcentrationsarelowerthanthoseforpetcoke(byasmuchasafactorof4,dependingonthespecificemissionsource),butstillsubstantiallylargerthanNAAQS.AERMODalsopredictedthatfortheannualaveragingperiod,pavedroademissionswoulddominatethetotalpredictedconcentration.


4‐10

Table 4‐3 AERMOD Modeling Results Summary for Coal Material Handling

Material Pollutant Averaging

Period Source Group Figure

Maximum Predicted

Concentration (µg/m3)

Coordinates (meters)

X Y

Coal

PM10

24‐hour

(NAAQS = 150 µg/m3)

All 4.6, 4.6a

1509 70.71 84.26

Dozer 4.6b 1215 70.71 84.26

Drops 4.6c 111 ‐70.71 ‐84.26

Paved Roads 4.6d 450.3 110 0


4.6e 70 37.62 103.37


4.6f 8.4 103.37 37.62

PM2.5

24‐hour

(NAAQS = 35 µg/m3)

All 4.7, 4.7a

186 70.71 84.26

Dozer 4.7b 119.5 70.71 84.26

Drops 4.7c 16.8 ‐70.71 ‐84.26

Paved Roads 4.7d 110.5 110 0


4.7e 7 37.62 103.37


4.7f 1.26 103.37 37.62

PM2.5

Annual

(NAAQS = 12 µg/m3)

All 4.8, 4.8a

17.2 108.3 19.1

Dozer 4.8b 2.3 84.26 70.71

Drops 4.8c 1.3 ‐70.71 ‐84.26

Paved Roads 4.8d 14.1 108.3 19.1


4.8e 0.2 84.26 70.71


4.8f 0.08 37.62 103.37

4.4.3 Wind Erosion Modeling for the Petcoke and Coal Storage Piles ThespecificeffectsofwindoneachofapetcokeandcoalstoragepileweremodeledbyisolatingtheAERMODmodelingrunstoonlythePM10emissionratederivedfromthewinderosionfromstockpilesequations.Themodelingwasperformedfora1‐houraveragingperiod,correspondingtotheemissionalgorithmsthatassumethatmaterialblowsoffthepileduringthehourofthedaywiththehighestwindspeed.TheresultsaregraphicallyrepresentedinFigures4.9and4.10forpetcokeandcoaldust,respectivelyandareincludedinAppendixC.Thehighest1‐hourconcentrationsareoftheorderof200µg/m3,which,whenaveragedovera24‐hourperiod,wouldnotlikelyleadtoexceedanceofthePM10NAAQS.However,giventhehighwindsthataccompanythepredictedwinderosionevents,theamountofmaterialreleasedduringtheseeventscouldbesubstantialrelativetootheremissionsources.


4‐11

Figure 4‐3 Highest 24‐Hour Average PM10 Concentration Predictions for Petroleum Coke (All Sources)


4‐12

Figure 4‐4 Highest 24‐Hour Average PM2.5 Concentration Predictions for Petroleum Coke (All Sources)


4‐13

Figure 4‐5 Highest Annual Average PM2.5 Concentration Predictions for Petroleum Coke (All Sources)


4‐14

Figure 4‐6 Highest 24‐Hour Average PM10 Concentration Predictions for Coal (All Sources)


4‐15

Figure 4‐7 Highest 24‐Hour Average PM2.5 Concentration Predictions for Coal (All Sources)


4‐16

Figure 4‐8 Highest Annual Average PM2.5 Concentration Predictions for Coal (All Sources)


4‐17

Figure 4‐9 1‐Hour Averaging Period PM10 Emissions Wind Erosion of a Petcoke Storage Pile

Figure 4‐10 1‐Hour Averaging Period PM10 Emission Rate Wind Erosion of a Coal Storage Pile


4‐18

4.5 Interpretation of Model Predictions PredictionofincrementalPM10andPM2.5concentrationsgreaterthantheNAAQSlevelsdoesnotnecessarilymeanthatairqualitystandardswillinpracticebeexceededas(1)fugitivedustemissionfactorsmayoverpredictactualemissions,(2)facilitiesmaynotemployallofthesourcesconsidered,and/orinthemannerconsidered,and(3)therehasbeennoaccountingofpotentialmitigationeffortsdesignedtocurbdustemissions.However,giventhemagnitudeofincrementalconcentrationspredictedforsomeemissionsources,thepotentialexistsforNAAQSstobeexceeded,especiallyatlocationsclosetobulkmaterialprocessingandstoragefacilities.Predictedconcentrationsaregenerallypredictedtodecreaserapidlywithdistancefromthefacility,characteristicofthedispersionofemissionsfromaground‐levelsource.Basedonmodelingassumptions,theprocessesmostlikelytoaffectairqualityarebulldozing/gradingoperations,pavedroademissions,andunpavedroad(bulkmaterialsurface)emissions.Predictedimpactsfromthepavedroademissionsourcearethesameforpetroleumcokeandcoalbecausetheestimatesareindependentofmaterialproperties,dependingprincipallyontheamountoffinedustpresentontheroadsavailabletobemobilizedbyvehiculartraffic.TheAP42‐basedvalueforroadsiltloadingisbasedonolderdatacollectedfromindustrialfacilitiesandmaygreatlyoverestimatevaluesatfacilitiesthatemploystreetsweepersanddustsuppression(watering).Forthebulldozing/gradingandunpavedroad(bulkmaterialsurface)sources,modelingestimatesforthepetroleumcokematerialaresubstantiallylargerthanthoseforcoal,aresultofthemuchhighersiltcontentofthepetcokematerialthatleadstohigherpredictedemissions.Uncertaintyassociatedwiththeemissionsestimatesmaybesubstantial,asreflectedbylowemissionfactorratingsintheAP42database.

4.6 Comparison to Background Air Quality in Chicago Chicago,likemanyurbanareas,hasmanyemissionsourcesofparticulatematterthatcontributetosignificantbackgroundconcentrationsofPM2.5andPM10.Datafromthe2012IllinoisAirQualityReport(http://www.epa.state.il.us/air/air‐quality‐report/2012/air‐quality‐report‐2012.pdf)indicatebackgroundconcentrationsareclosetothelevelsoftheNationalAmbientAirQualityStandards(NAAQS).MonitoredannualaveragePM2.5concentrationsareoftheorderof12µg/m3,orapproximatelythesameastheallowableNAAQSof12µg/m3(Figure4‐11).Measured24‐houraveragePM2.5concentrationsreachashighas30µg/m3,orabout86%oftheNAAQSof35µg/m3(Figure4‐12).Thehighest24‐houraveragePM10concentrationof106µg/m3measuredin2012represents71%ofthe150µg/m3NAAQS(Figure4‐13).Inallcases(andparticularlyforPM2.5),incrementalparticulatematterconcentrationsduetoemissionsfrombulkmaterialprocessingandstoragefacilitiesmustbesmallinordertoavoidlocalizedexceedancesoftheNAAQS.ThemodelpredictionsofTable4‐2and4‐3,however,indicatethepotentialimpactsofbulkmaterialfacilitiesmaybesubstantial.GiventhelevelsofpotentialimpactsandthelimitedgapbetweenbackgroundlevelsandNAAQS,itmaybedifficultforbulkmaterialfacilitiestoavoidlocalizedexceedancesofairqualitystandardsevenifdiligentmitigationmeasuresareemployed.


4‐19

Figure 4‐11 Annual Average PM2.5 Concentrations at Monitoring Locations in Chicago

Figure 4‐12 24‐Hour Average PM2.5 Concentrations at Monitoring Locations in Chicago

0

10

20

30

40

Washington High School Mayfair Pump Station Springfield Pump Station Com Ed Maintenance

Co

nce

ntr

atio

n (

µg/

m3)

PM2.5 24‐Hour 2010‐12 Design Value ConcentrationsChicago Air Quality Monitoring Stations

National Ambient Air Quality Standard = 35 µg/m3


4‐20

Figure 4‐13 24‐Hour Average PM10 Concentrations at Monitoring Locations in Chicago

0

20

40

60

80

100

120

140

160

Highest 2nd Highest 3rd Highest

Co

nce

ntr

atio

n (

µg/

m3)

Highest 24‐Hour Concentrations of PM10 in 2012Washington High School Monitoring Station

National Ambient Air Quality Standard = 150 µg/m3

5‐1

Section 5

Conclusions

CalculationsindicatethatfugitivedustemissionsfrombulkmaterialstorageandhandlingfacilitiesmaybesubstantialenoughtoleadtolocalizedexceedancesoftheNationalAmbientAirQualityStandardsforPM10andPM2.5.Thestudydoesnotaccountforuseofmitigationmethodstoreducefugitivedustemissions.Varyingcharacteristicsofbulkmaterialsarelikelytoleadtodifferencesinemissionsamongfacilities.Inparticular,modelequationspredictgreateremissionsformaterialswithhighsiltcontents.Thus,ofthematerialsexaminedinthisstudy,thehighestoverallemissionsandairqualityimpactsarepredictedforthepetroleumcokematerial.

Thevariouscategoriesofemissionsourcesarepredictedtohavedifferinglevelsofimpactstoambientair.Thefollowingarepredictedimpactsfromvarioussourceshandlingpetcokeandcoal:

Dropoperationsfromconveyorpointsandbulkmaterialtransfersarepredictedtoleadtomodestincreasesinambientdustconcentrations.Thefencelineincrementsof111µg/m3for24‐houraveragePM10and16.8µg/m3for24‐houraveragePM2.5predictedforcoal(Table4‐3),whencombinedwithbackground,couldcontributetoexceedancesofNationalAmbientAirQualityStandards(NAAQSs).

Travelonthesurfaceofthestoragepilebyoff‐roadconstructionvehicles(anarticulatedtruckandafront‐endloader)arepredictedtoresultinaworst‐caseincremental24‐houraveragePM10fencelineconcentrationofpetcokeof277µg/m3thatbyitselfexceedstheNAAQS.

Haultruckstravelingonthepavedaccessroadarepredictedtocausehighlocalizedimpacts,withtheworst‐caseincremental24‐houraveragefencelineconcentrationsof450µg/m3(PM10)and110µg/m3(PM2.5)eachaboutthreetimestheleveloftheNAAQS.ThemodeledannualaveragePM2.5concentrationof14µg/m3isalsopredictedtoexceedtheNAAQS.Thedustlevelontheindustrialroads,akeyparameterusedinthecalculations,maybeoverestimatedforlocalroadsandcurrentpractices.Locationofthehaulroadadjacenttothefencelinealsocontributestotheelevatedimpacts.

Bulldozingoperationsareresponsibleforthehighestincremental24‐houraveragefencelineconcentrationsof4,899µg/m3(PM10)and317µg/m3(PM2.5)forthepetcokematerial(Table4‐2),eachapproximatelyanorderofmagnitudegreaterthantheNAAQSs,Aworst‐caseincrementof6µg/m3totheannualPM2.5concentration(Table4‐2)isroughlyhalftheleveloftheNAAQS.

Winderosionofthestoragepilesurfaceleadstothelowestpredictedincrementstoambientdustconcentrations(Table4‐2andTable4‐3).Thisinpartresultsfromtheepisodicnatureofwinderosion,whichisassumedtooccuronlyonceperdayduringthehourofthehighest(andmostdispersive)windspeed.Figure4‐9andFigure4‐10,whichdepictpotential1‐houraveragedustconcentrationsduetostoragepilewinderosion,indicatesubstantialshort‐termimpactsarepossible,especiallyincasesinwhichmaterialisblownoffthepileinstantaneously.

Section 5 Conclusions

5‐2

Theestimatesmayreflectconservativeassumptionsregardingvehicleutilizationandfacility‐relatedactivities.Giventhestudy’sinherentuncertaintiesandassumptions,thestudyresultsarebestinterpretedasindicatingapotentialforbulkmaterialprocessingandstoragefacilitiestoadverselyaffectairquality.Useofbestmanagementpracticescanmitigatemostfugitivedustimpacts,butpotentiallocalizedexceedancesofNationalAmbientAirQualityStandardsmaystillresult,andairqualitymonitoringmaybeausefultooltobetterevaluatefacilityimpacts.

A‐1

Appendix A

Petroleum Coke Data

1 of 8

February 25, 2014Date:STAT Analysis Corporation

Project: PPT DOCClient: CDM Smith Inc.

Lab Order: 13120303Work Order Sample Summary

Lab Sample ID Client Sample ID Collection DateTag Number Date Received

13120303-001A PPTDOC-KCBX-South 12/13/2013 10:00:00 AM 12/13/201313120303-002A PPTDOC-KCBX-North 12/13/2013 10:15:00 AM 12/13/2013

2 of 8

Project: PPT DOC

Client Sample ID: PPTDOC-KCBX-South

Collection Date: 12/13/2013 10:00:00 AMMatrix: Solid

Analyses Result Qualifier Units Date AnalyzedRL

Client: CDM Smith Inc.Lab Order: 13120303

Lab ID: 13120303-001A

DF

Print Date: February 25, 2014

Tag Number:

STAT Analysis Corporation2242 West Harrison St., Suite 200, Chicago, IL 60612-3766Tel: (312) 733-0551 Fax: (312) 733-2386 [email protected]

Report Date: February 25, 2014

Accreditation Numbers: IEPA ELAP 100445; ORELAP IL300001; AIHA 101160; NVLAP LabCode 101202-

Grain Size D422 Analyst: SUBPrep Date:Clay Sized Particles * 1/24/2014%17.1Gravel Sized Particles * 1/24/2014%32.0Sand Sized Particles * 1/24/2014%43.6Silt Sized Particles * 1/24/2014%7.3

Qualifiers: J - Analyte detected below quantitation limitsB - Analyte detected in the associated Method Blank

S - Spike Recovery outside accepted recovery limitsR - RPD outside accepted recovery limits

ND - Not Detected at the Reporting Limit

E - Value above quantitation range* - Non-accredited parameter H - Holding time exceededHT - Sample received past holding time

RL - Reporting / Quantitation Limit for the analysis

3 of 8

D60 (mm) D30 (mm) D10 (mm) Cu Cc

2.7 0.2

SAMPLE ID: PPTDOC-KCBX-South

43.6 7.3 17.1

% + 3" % Gravel % Sand % Silt

GRAIN SIZE ANALYSIS (ASTM D422)

System:

Black coarse to fine sand-sized particles, and coarse to fine gravel-sized particles, some fines, moist

% Clay

Soil Classification:

100.0

3/4" 100.0

58.0

3/8" 100.0

37.2

#4

32.1

#200 24.4

#40

Percent Passing

#20 47.8

#60

Visual Soil Description:

0.0 32.0

#140 28.0

#10

Sieve Size

1"

68.0

0

10

20

30

40

50

60

70

80

90

100

0.0010.0100.1001.00010.000100.0001000.000

PE

RC

EN

T F

INE

R

GRAIN SIZE - mm

1.5

"1

.0"

3/4

"

3/8

"

No

. 1

0

No

. 4

0

No

. 1

00

No

. 2

00

No

. 4

4 of 8

Project: PPT DOC

Client Sample ID: PPTDOC-KCBX-North

Collection Date: 12/13/2013 10:15:00 AMMatrix: Solid

Analyses Result Qualifier Units Date AnalyzedRL

Client: CDM Smith Inc.Lab Order: 13120303

Lab ID: 13120303-002A

DF

Print Date: February 25, 2014

Tag Number:

STAT Analysis Corporation2242 West Harrison St., Suite 200, Chicago, IL 60612-3766Tel: (312) 733-0551 Fax: (312) 733-2386 [email protected]

Report Date: February 25, 2014

Accreditation Numbers: IEPA ELAP 100445; ORELAP IL300001; AIHA 101160; NVLAP LabCode 101202-

Grain Size D422 Analyst: SUBPrep Date:Clay Sized Particles * 1/24/2014%5.6Gravel Sized Particles * 1/24/2014%22.6Sand Sized Particles * 1/24/2014%59.3Silt Sized Particles * 1/24/2014%12.4

Qualifiers: J - Analyte detected below quantitation limitsB - Analyte detected in the associated Method Blank

S - Spike Recovery outside accepted recovery limitsR - RPD outside accepted recovery limits

ND - Not Detected at the Reporting Limit

E - Value above quantitation range* - Non-accredited parameter H - Holding time exceededHT - Sample received past holding time

RL - Reporting / Quantitation Limit for the analysis

5 of 8

D60 (mm) D30 (mm) D10 (mm) Cu Cc

1.12 0.27 0.0400 28.00 1.63

SAMPLE ID: PPTDOC-KCBX-North

59.3 12.4 5.6

% + 3" % Gravel % Sand % Silt

GRAIN SIZE ANALYSIS (ASTM D422)

System:

Black coarse to fine sand-sized particles, some coarse to medium gravel-sized particles, little fines, moist

% Clay

Soil Classification:

100.0

3/4" 100.0

65.7

3/8" 100.0

48.1

#4

32.4

#200 18.0

#40

Percent Passing

#20 57.1

#60

Visual Soil Description:

0.0 22.6

#140 21.3

#10

Sieve Size

1"

77.4

0

10

20

30

40

50

60

70

80

90

100

0.0010.0100.1001.00010.000100.0001000.000

PE

RC

EN

T F

INE

R

GRAIN SIZE - mm

1.5

"1

.0"

3/4

"

3/8

"

No

. 1

0

No

. 4

0

No

. 1

00

No

. 2

00

No

. 4

6 of 8

7 of 8

8 of 8

B‐1

Appendix B

Slag Data

C‐1

Appendix C

Modeling Results Figures

Appendix C Modeling Results Figures

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