overview of the manitou experimental forest observatory: site

Atmos Chem Phys 14 6345ndash6367 2014wwwatmos-chem-physnet1463452014doi105194acp-14-6345-2014copy Author(s) 2014 CC Attribution 30 License

Overview of the Manitou Experimental Forest Observatory sitedescription and selected science results from 2008 to 2013

J Ortega1 A Turnipseed1 A B Guenther1a T G Karl 1b D A Day2 D Gochis1 J A Huffman34 A J Prenni5cE J T Levin5 S M Kreidenweis5 P J DeMott5 Y Tobo5d E G Patton1 A Hodzic1 Y Y Cui6 P C Harley1eR S Hornbrook1 E C Apel1 R K Monson7 A S D Eller8f J P Greenberg1 M C Barth 1 P Campuzano-Jost2B B Palm2 J L Jimenez2 A C Aiken9 M K Dubey9 C Geron10 J Offenberg11 M G Ryan1213 P J Fornwalt13S C Pryor14g F N Keutsch15 J P DiGangi15h A W H Chan16i A H Goldstein1617 G M Wolfe1819 S Kim1jL Kaser20k R Schnitzhofer20 A Hansel20 C A Cantrell1l R L Mauldin 1l and J N Smith121

1National Center for Atmospheric Research PO Box 3000 Boulder CO 80307 USA2University of Colorado Department of Chemistry and Biochemistry and CIRES Boulder CO 80309 USA3Max Planck Institute for Chemistry PO Box 3060 55020 Mainz Germany4University of Denver Department of Chemistry amp Biochemistry Denver CO 80208 USA5Department of Atmospheric Science Colorado State University Fort Collins CO 80523 USA6Department of Earth and Atmospheric Sciences Saint Louis University MO 63103 USA7School of Natural Resources and the Environment and Laboratory for Tree Ring Research University of Arizona TucsonAZ 85721 USA8Cooperative Institute for Research in Environmental Sciences (CIRES) University of Colorado Boulder CO 80309 USA9Los Alamos National Laboratory Earth and Environmental Sciences Division Los Alamos NM 87545 USA10US Environmental Protection Agency Office of Research and Development National Risk Management ResearchLaboratory Air pollution Prevention and Control Division Research Triangle Park NC 27711 USA11United States Environmental Protection Agency Office of Research and Development National Exposure ResearchLaboratory Research Triangle Park NC 27711 USA12National Resource Ecology Laboratory Colorado State University Fort Collins CO 80523 USA13United States Department of Agriculture Forest Service Rocky Mountain Research Station 240 West Prospect Rd FortCollins CO 80526 USA14Department of Geological Sciences Indiana University Bloomington IN 47405 USA15Department of Chemistry University of Wisconsin Madison WI 53706 USA16Department of Environmental Science Policy and Management University of California Berkeley CA 94720 USA17Department of Civil and Environmental Engineering University of California Berkeley CA 94720 USA18Atmospheric Chemistry and Dynamics Laboratory Goddard Space Flight Center 8800 Greenbelt Road GreenbeltMD 20771 USA19Joint Center for Earth Systems Technology University of Maryland Baltimore County Baltimore County MD 21250 USA20Institute for Ion Physics and Applied Physics University of Innsbruck Innsbruck Austria21Department of Applied Physics University of Eastern Finland 70211 Kuopio Finlandanow at Pacific Northwest National Laboratory Atmospheric Sciences Division PO Box 999 Richland WA 99352 USAbnow at University of Innsbruck Institute for Meteorology and Geophysics (IMGI) Innrain 52 6020 Innsbruck Austriacnow at Air Resources Division National Park Service Lakewood CO 80225 USAdnow at National Institute of Polar Research Tachikawa Tokyo 190-8518 Japanenow at Department of Plant Physiology Estonian University of Life Sciences Tartu 51014 Estoniafnow at Department of Biological Sciences Macquarie University Sydney NSW 2109 Australiagnow at Department of Earth and Atmospheric Sciences Cornell University Ithaca NY 14853 USAhnow at NASA Langley Research Center Chemistry and Dynamics Branch Hampton VA 23681 USAinow at Department of Chemical Engineering and Applied Chemistry University of Toronto Canadajnow at Department of Earth System Science University of California Irvine Irvine CA 92697 USAknow at National Center for Atmospheric Research PO Box 3000 Boulder CO 80307 USAlnow at Department of Atmospheric and Oceanic Sciences University of Colorado Boulder CO 80309 USA

Published by Copernicus Publications on behalf of the European Geosciences Union

6346 J Ortega et al Overview of the Manitou Experimental Forest Observatory

Correspondence toJ N Smith (jimsmithucaredu)

Received 23 November 2013 ndash Published in Atmos Chem Phys Discuss 20 January 2014Revised 30 April 2014 ndash Accepted 12 May 2014 ndash Published 26 June 2014

Abstract The Bio-hydro-atmosphere interactions of En-ergy Aerosols Carbon H2O Organics amp Nitrogen (BEA-CHON) project seeks to understand the feedbacks and inter-relationships between hydrology biogenic emissions carbonassimilation aerosol properties clouds and associated feed-backs within water-limited ecosystems The Manitou Exper-imental Forest Observatory (MEFO) was established in 2008by the National Center for Atmospheric Research to addressmany of the BEACHON research objectives and it now pro-vides a fixed field site with significant infrastructure MEFOis a mountainous semi-arid ponderosa pine-dominated forestsite that is normally dominated by clean continental air but isperiodically influenced by anthropogenic sources from Col-orado Front Range cities This article summarizes the pastand ongoing research activities at the site and highlightssome of the significant findings that have resulted from thesemeasurements These activities include

ndash soil property measurements

ndash hydrological studies

ndash measurements of high-frequency turbulence parame-ters

ndash eddy covariance flux measurements of water energyaerosols and carbon dioxide through the canopy

ndash determination of biogenic and anthropogenic volatileorganic compound emissions and their influence on re-gional atmospheric chemistry

ndash aerosol number and mass distributions

ndash chemical speciation of aerosol particles

ndash characterization of ice and cloud condensation nuclei

ndash trace gas measurements and

ndash model simulations using coupled chemistry and meteo-rology

In addition to various long-term continuous measurementsthree focused measurement campaigns with state-of-the-artinstrumentation have taken place since the site was estab-lished and two of these studies are the subjects of this specialissue BEACHON-ROCS (Rocky Mountain Organic CarbonStudy 2010) and BEACHON-RoMBAS (Rocky MountainBiogenic Aerosol Study 2011)

1 Introduction

11 Motivation

Development of Earth system models is driven by the needto improve the predictability of atmospheric chemical andphysical processes over timescales ranging from minutesto decades Accurate model predictions are contingent onprocess-level understanding and detailed numerical descrip-tions of the coupling between water energy and biogeochem-ical cycles across temporal and spatial scales (Denman et al2007 Alo and Wang 2008 Heald et al 2009) A number ofstudies have discussed some of these processes and associ-ated feedbacks (eg Barth et al 2005 Carslaw et al 2010Mahowald et al 2011) but more detailed observations andcoordinated modeling efforts are required for improved rep-resentation in Earth system models

The Bio-hydro-atmosphere interactions of EnergyAerosols Carbon H2O Organics amp Nitrogen (BEACHON)project was initiated by the National Center for AtmosphericResearch (NCAR) as well as research collaborators from theuniversity community to investigate ecosystemndashatmosphereexchange of trace gases and aerosols and their potentialfeedbacks between biogeochemical and water cyclesBEACHON is now an ongoing component of atmosphericresearch sponsored by the National Science FoundationThis interdisciplinary research program integrates local andregional model simulations with remote sensing regionalnetwork observations and canopy- to regional-scale fieldmeasurements BEACHON includes investigations of at-mospheric ecological and hydrological processes includingconcentration and flux measurements of energy CO2H2O volatile organic compounds aerosols nitrogen com-pounds hydrological parameters and feedback processesthat are relevant to atmospheric chemistry Rocky Mountainecosystems are important for providing water and otherresources in the western United States but contain only alimited number of long-term monitoring sites This region ispredominantly arid or semi-arid resulting in biogeochemicalcycles that are water limited Since the area contains someof the fastest growing population centers water limitations(combined with a climate that is projected to be warmerand potentially drier) pose significant societal vulnerabilities(Vorosmarty et al 2010) The regionrsquos remote complexterrain leads to highly variable ecosystem characteristicsand it is unclear how this variability affects hydrological andatmospheric processes across larger geographical areas Theneed for long-term landndashecosystemndashatmosphere observation

Atmos Chem Phys 14 6345ndash6367 2014 wwwatmos-chem-physnet1463452014

J Ortega et al Overview of the Manitou Experimental Forest Observatory 6347

networks has been identified by international researchprograms as a key need for advancing Earth system science(Guenther et al 2011)

To address these challenges the BEACHON project incollaboration with the United States Department of Agricul-ture (USDA) Forest Service established the Manitou Experi-mental Forest Observatory (MEFO) in 2008 in an area repre-sentative of a middle-elevation (sim 2000ndash2500 m asl) semi-arid ponderosa pine ecosystem that is common throughoutthe Rocky Mountain West but not adequately characterizedThe BEACHON project and establishment of this site weredesigned to meet the following objectives

ndash collect long-term measurements of meteorology watercarbon dioxide (CO2) energy fluxes aerosol size dis-tributions and fluxes trace gas and cloud condensationnuclei concentrations

ndash monitor soil moisture precipitation snowpack stablewater isotopes and other hydrological variables to pro-vide input and lateral boundary conditions for Earth sys-tem models and as a basis for making more accuratewater resource predictions for this and other semi-aridregions

ndash provide infrastructure for collaborative research amonggovernment laboratories universities and private com-panies

ndash carry out intensive measurement campaigns

ndash provide training for undergraduate and graduate stu-dents and promote multidisciplinary research

This article describes the Manitou Experimental Forest Ob-servatory presents ongoing research at the site and highlightssome initial findings More specific scientific results and pub-lications can be found in the publication list (Table S2 in theSupplement) and within the individual articles as part of thisspecial issue ofAtmospheric Chemistry and Physics

12 Site description and meteorological overview

The Manitou Experimental Forest (391006 N1050942 W Fig 1a b) in the Front Range of theColorado Rocky Mountains has been managed as a researchfacility by the USDA Forest Servicersquos Rocky Mountain Re-search Station since 1938 It contains approximately 6760 haand exemplifies the Colorado Front Range wildlandndashurbaninterface where semi-arid montane forest ecosystems arein close proximity to larger urban centers These interfaceareas which also contain a number of small residentialcommunities are prone to wild fires from lightning aswell as human causes Two particularly large nearby fires(the 560 km2 Hayman fire in 2002 and the 74 km2 WaldoCanyon fire in 2012) were among the most ecologically andeconomically damaging in the statersquos history Although the

primary study areas were not burned areas within severalkilometers to the south and west of the site were affectedby the 2002 fire The landscape has thus been dramaticallyaffected in both appearance and in the vegetationrsquos ability toslow soil erosion from surface runoff during monsoon rainsFire-damaged portions of the forest can change aspects ofthe atmospheric chemistry measured at the site throughchanges in gas- and aerosol-phase emissions from nearbyfire-scarred vegetation and soil Wildfires are ubiquitous inthe semi-arid forested American West of which this areacan be considered representative

This forestrsquos elevation ranges from 2280 to 2840 m asland vegetation is primarily composed of forests of ponderosapine Douglas fir mixed conifer and aspen The forest standssurrounding the observatory are relatively young uneven-aged stands dominated by ponderosa pine In 2009 coresamples from a survey of 38 representative ponderosa pineshowed that the median tree age was 495 years (with aver-age minimum and maximum ages of 625 27 and 201 yearsrespectively)

Soils underlying the tower site and the surrounding areaare classified as deep well-drained sandy loams and sandygravelly loams originating from alluvial deposits weath-ered from underlying arkosic sandstone formations as wellas nearby granite formations (Soil Conservation Service1992) Although numerous outcroppings of partially weath-ered sandstone exist around the site the average depth tobedrock is estimated to be between 1 and 18 m (36ndash60 in)below ground surface The soil ranges from slightly acidicto moderately alkaline (pH 61ndash78) with little organic mat-ter content (1ndash4 ) and rooting depths reported to be in ex-cess of 13 m (40 in) Soil permeability on undisturbed soilsis moderately rapid (approx 50ndash150 mm hminus1) Rapid runoffand sediment transport occurs on compacted road surfacesand other areas void of significant ground vegetation Thetower site is on an alluvial bench formed by the erosion ofunderlying granite It is situated in a broad shallow valley ap-proximately 1 km west of an intermittent creek which flowstowards the north The terrain slope is asymmetric across thisvalley with the east side of the valley being steeper and thewest side being more gradual (gradient between 3 and 8 )

The National Weather Service has been monitoring pre-cipitation at MEFO since 1940 (Station Woodland Park 8NNW Coop ID 059210) and US Forest Service staff havebeen collecting meteorological data including air and soiltemperature precipitation and wind speed since 1998 Theclimate is cool (mean temperature is 19C in July andminus2Cin January) and dry with an average annual precipitationfor 2010ndash2013 of 4305 mm (1694 in) Approximately 50 of the precipitation falls as rain during the summer season(JunendashSeptember) primarily during afternoon thunderstormscharacterized by brief but intense periods of rainfall andlightning Winter snowfall is typically light and a persistentsnowpack rarely develops

wwwatmos-chem-physnet1463452014 Atmos Chem Phys 14 6345ndash6367 2014


A B

C

D E

i

300 m

MEFO

N

Woodland Park

CO

NM AZ

UT

WY

MT

Denver ~90 km

Colorado Springs ~40 km

0 8 16 km

ND

SD

NE

KS

ii

iii N

Figure 1 Manitou Experimental Forest Observatory (MEFO)(A)Map showing general area within Colorado and its relationship toneighboring states(B) Site location relative to the Front Range ur-ban corridor including Denver and Colorado Springs(C) Close-up aerial photograph showing the open-canopy ponderosa pine-dominated forest with the (i) micrometeorological tower (ii) chem-istry tower and (iii) water manipulation experiment(D) Close-uppicture of the chemistry tower(E) Close-up picture of microme-teorological tower The two towers shown in C are approximately300 m apart Maps in(A) and(B) were produced using ArcGIS soft-ware (ESRI Inc Redlands CA)

Like much of Colorado the site has a high frequencyof sunny days during most of the year During midday inJuly 2011 approximately 90 of the days had PAR val-ues (photosynthetically active radiation between 400 and700 nm) above the canopy that exceeded 2100 micromol mminus2 sminus1and part of every day reached a PAR value of at least

2000 micromol mminus2 sminus1 Frequent afternoon thunderstorms cantemporarily reduce the solar insolation but rarely for morethan 3 h Figure 2 shows the diel cycles of net longwave andshortwave radiation latent heat flux sensible heat flux andnet CO2 flux (calculated using the eddy covariance method)from four representative months during 2011 Each point rep-resents the 30 min average for that time period The net ra-diation is calculated from the difference between the down-welling radiation and the upwelling radiation from the ra-diometers at the top (28 m) of the chemistry tower It is in-teresting to note the net carbon uptake in the spring (April)and autumn (October) during the day and the large nighttimerespiration flux in July

Numerous studies have been conducted here by re-searchers from a wide range of federal agencies aca-demic institutions and non-governmental organizationsEarly research focused on range management including re-vegetation of abandoned fields grazing management in na-tive and seeded pastures watershed management in gullycontrol stream sedimentation surface runoff bacterial pol-lution and infiltration (Gary et al 1985) Recent research ismore diverse and includes a long-term (gt 30 years) study onthe flammulated owl (Linkhart et al 2006 2007) studiesassessing the impacts of forest restoration and fuel reduc-tion techniques (Battaglia et al 2010 Massman et al 2010Rhoades et al 2012) silviculture studies (Lezberg et al2008) and wildfire recovery studies (Fornwalt et al 2010)Additional information about the site (including long-termweather tree growth data and a bibliography of publications)can be found athttpwwwfsusdagovmanitou

13 Measurements at the Manitou Experimental ForestObservatory (MEFO) under the auspices ofBEACHON

In 2008 with cooperation with the USDA Forest ServiceNCAR established the infrastructure at the site and namedit the Manitou Experimental Forest Observatory (MEFO)The site includes four mobile steel containers each having149 m2 of laboratory floor space numerous sampling portstemperature control and 20 kW power Two research towersthat extend through the canopy were constructed approxi-mately 300 m apart (Fig 1c) and are referred to here as themicrometeorology and chemistry towers Detailed informa-tion on these towersrsquo measurements is listed in Table S1 inthe Supplement A third (smaller) eddy covariance measure-ment tower was deployed in a large clearing or ldquoforest gaprdquofrom 2011 to 2012 The purpose of this smaller tower wasto make four-way radiation measurements surface skin tem-perature and sensible and latent heat flux measurements overthe grass and forb vegetation that is found beneath and in be-tween the ponderosa pine These measurements were takenat 1 and 3 m above ground level

The micrometeorology tower (Fig 1e) is a narrow 45 mtriangular tower (Rohn Products Peroria IL USA model



Figure 2 Average diel net radiation (downwelling minus upwelling) latent heat flux sensible heat flux and net CO2 flux for four representa-tive months All properties were measured from 28 m at the top of the chemistry tower in 2011 Each data point represents a 30 min averagefor that time period They axis limits are the same for each plot except for January where the scale is 12 of the other three months Theshaded area for net radiation and error bars for CO2 flux representplusmn1 standard deviation Error bars for sensible and latent heat fluxes havebeen omitted for clarity

45G 425 mm per side) designed to facilitate the analysis ofthe impact of canopy elements (needles branches trunks) onturbulent exchange between the surface canopy layers andthe overlying atmosphere The instruments on the microme-teorology tower operated nearly continuously from July 2009until July 2012 when they were removed as a precaution duethe proximity of the Waldo Canyon fire This tower had in-struments deployed at six different levels (2 8 16 22 30and 43 m) thus allowing several measurements within andabove the canopy (average canopy heightasymp 16 m) The 22 mlevel contained a four-component radiometer (Kipp and Zo-nen the Netherlands model CNR1) for measuring above-canopy incoming and outgoing shortwave and longwave ra-diation Instrumentation on the other five levels included

ndash sonic anemometers (Campbell Scientific Logan UTmodel CSAT3) to record the three orthogonal wind ve-locity components and temperature fluctuations

ndash NCAR-Vaisala (Vantaa Finland) aspirated hygrother-mometers to measure absolute temperature and relativehumidity

ndash open-path infrared gas analyzers (LiCOR Lincoln NEmodel 7500) to measure water vapor and carbon diox-ide

This multiseason data set is being used to

ndash quantify the importance of canopy-induced modifica-tions to turbulence in predicting whole-ecosystem ex-change in regional and global climate models

ndash partition water fluxes into transpiration and evaporationcomponents and

ndash investigate impacts of spatially heterogeneous canopydistributions on evapotranspiration using additional in-formation from the chemistry and understory towers

The chemistry tower is a 28 m walk-up-type tower that isequipped with meteorological sensors as well as a vari-ety of flux and gradient concentration measurements forgases and aerosols (Fig 1d) The platform on each level is178 mtimes 127 m and is suitable for heavier instruments thatrequire more space power and maintenance It can also sup-port gradient sampling systems which can move verticallyalong the tower This tower is also equipped with 2-D and3-D sonic anemometers as well as temperature and radia-tion probes for continuous meteorological measurements andfor calculating fluxes using the closed-path eddy covariancemethod Other continuous gas-phase measurements from thistower have included CO CO2 H2O vapor NO NO2 andSO2 The Waldo Canyon fire in June 2012 forced the removalof the trace gas instruments from the chemistry tower and allof the instruments from the micrometeorological tower For-tunately the fire did not directly affect the site and meteo-rological measurements from the chemistry tower have op-erated continuously (see Table S1 in the Supplement) Sincethe two towers had generated 3ndash4 years of data and someof the instruments were required for other projects and fieldsites it was decided to adjust the sampling strategy Futurecore measurements of trace gases (CO O3 SO2 NOx) andaerosol number size distributions will be operated four timesper year (for 4ndash6 weeks in duration) to capture the seasonalvariability of these key species

The suitability of these towers for making eddy covari-ance flux measurements in the surrounding landscape was



analyzed by Kaser et al (2013b) Briefly the flux footprintwas found to extend to 900 m for unstable boundary layerconditions and to 2500 m for stable conditions However be-cause there is more heterogeneity in the forest compositionand proximity to former burn areas inside the 2500 m radiusa practical limit of 1850 m beyond the tower was used as oneof the criteria for valid flux data A paved roadsim 500 m eastof the tower site caused data to be eliminated if wind direc-tion was from that sector

The only significant woody vegetation around the obser-vatory is ponderosa pine Measurements from this speciesinclude leaf- and branch-level photosynthesis respirationand biogenic volatile organic compound (BVOC) emissionsas well as sap flow using the compensation heat pulsemethod as described by Burgess et al (2001) Leaf-levelgas exchange was measured during maximum photosynthe-sis (0800ndash1300 MST) on sunlit needlessim 10 m above theground (Table 1) Each measurement was made on 6ndash10 ma-ture needles which were defined as needles that been on thebranch through at least one winter Gas exchange measure-ments were made using an LI-6400 portable gas exchangesystem (LI-COR Biosciences Lincoln NE) and photosyn-thesis stomatal conductance and transpiration calculationswere made using total leaf area (measurement as describedin Eller et al 2013) The effects of high solar insolationwarm temperatures and low humidity just prior to monsoonprecipitation are demonstrated by the low stomatal conduc-tance and photosynthesis values in July (Table 1)

A suite of hydrological measurements for total precipita-tion soil moisture leaf wetness and snow depth have beenmeasured nearly continuously since 2009 Aerosol measure-ments include 2 years (February 2010 to January 2012) ofparticle size distributions from 4 nm to 25 microm and 1 year ofCCN (cloud condensation nuclei) data during March 2010 toApril 2011 measured from one of the four mobile laborato-ries adjacent to the tower (Fig 1d) An additional month ofCCN measurements (May 2011) was made above the canopy(25 m above ground) from the chemistry tower (Levin etal 2012) BEACHON-ROCS (Rocky Mountain OrganicsStudy 2010) and BEACHON-RoMBAS (Rocky MountainBiogenic Aerosol Study 2011) were two large intensive mea-surement campaigns that occurred at the site Selected resultsfrom these two campaigns as well as the initial 2008 South-ern Rocky Mountain (SRM) study are discussed in this arti-cle and are summarized in Sect 5 A more detailed summaryof measurements at MEFO can be found in Table S1 in theSupplement Campaign data and long-term observations areavailable at the following websitehttpwww2acducareducampaigns

Other long-term data are available upon request from thecorresponding author

14 Meteorology at Manitou Experimental ForestObservatory

As mentioned in Sect 12 the observatory lies within anorthndashsouth drainage (draining to the north) leading to theformation of diurnal mountain-valley flows Nighttime flowabove the canopy (28 m) is dominated by drainage from thesouth as can be seen in Fig 3b and f Winds below the canopyare often westerly or southwesterly due to drainage flow fromsurrounding ridgelines (Fig 3d) This height-dependent noc-turnal pattern is dominant in all seasons Daytime wind di-rections are much more variable Although there is often asoutherly flow during the day other wind directions are alsoprevalent Synoptic winter winds lead to a higher frequencyof westerly and southwesterly flow (Fig 3a and e) Theseconditions tend to bring relatively unpolluted air to the sitefrom the west Stagnant high-pressure conditions lead to lo-cally induced upslope flow from either the northeast or south-east which are consistently observed during daylight hours(Fig 3c) These periods are important in understanding thelocal chemistry as these flows transport air from Front Rangecities (mainly Denver and Colorado Springs) Regardless ofthe daytime wind patterns southerly drainage flow usuallydevelops soon after the stable nocturnal boundary layer de-velops which is often accompanied by an increase in anthro-pogenic pollutants Wind measurements as well as modelingresults suggest that this is often due to air from the Denverarea during daytime upslope flow which then drains towardsthe north and past the site at night

2 Footprint hydrology in a water-limited ecosystem

21 Overview of hydrological measurements

Intensive hydrological measurements of total precipitation(rain and snow) soil moisture and snow depth as well as soiltemperatures have been collected at MEFO since the sum-mer of 2009 These complement the vertical flux measure-ments of water vapor for a complete accounting of the sitersquoswater budget The precipitation measurements also augmentthe long-term records maintained by the USDA Forest Ser-vice mentioned in Sect 12 A network of 11 tipping bucketrain gauges as well as an alter-shielded weighing-type to-tal precipitation gauge provide high time resolution year-round precipitation measurements in a network distributedwithin the chemistry tower flux footprint in order to charac-terize the high spatial variability of precipitation More de-tails about these measurements are given in Table S1 in theSupplement The 2010ndash2013 annual accumulation of hourlyprecipitation is shown in Fig 4a These time series are bias-corrected merged data products between the sitersquos sensorsin order to cover periodic data gaps The sitersquos annual pre-cipitation measurements for a given year are defined by anend date of 30 September of that year and a start date of 1



Table 1 Mean values for needle-level gas exchange measured on maturePinus ponderosaneedles at the Manitou Experimental ForestObservatory All calculations are based on total rather than projected leaf area Values in parentheses give the range of measurement dates(2011 day of year) Standard deviations are given in italics (n = 3)

May June July August September(136ndash149) (178ndash185) (230ndash233) (263ndash265)

Net photosynthesis (A) 29 09 32 35(micromol CO2 mminus2 sminus1) 06 06 08 02Stomatal conductance (gs) 28 7 29 30(mmol H2O mminus2 sminus1) 9 5 12 6Transpiration 049 035 100 064(mmol H2O mminus2 sminus1) 013 028 022 007

(a) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

50

100

150

200

250

300

350

(b) z = 28 m

90 180 270 360

0

500

1000

1500

2000

2500

(c) z = 2 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

(d) z = 2 m

90 180 270 360

0

200

400

600

800

1000

1200

Summer 2011

Daytime

Winter 2010-2011

Nighttime

(e) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

600

(f) z = 28 m

90 180 270 360

0

200

400

600

800

1000

1200

1400

1600

1800

2000

F0

0 0

0 0

D

BA

C

E

Summer 2010

Winter 2010-2011

Direction (degrees) Direction (degrees)

Figure 3Wind direction distributions (5 min averages binned every10) from the MEFO chemistry tower(a c and e)are daytime winddistributions (0900ndash1700 MST) whereas panels(b d and f) arefor nighttime hours (2000 until 0500 MST) Summer includes datafrom June to August 2010 Winter includes data from December2010 to February 2011 Measurement height is noted on the panels

October in the preceding year The patterns observed havebeen fairly consistent Periodic precipitation episodes occurthroughout the principal cool season of October through Mayfollowed by a brief dry season from late May through mid-June This is followed by a summer period of rather intenseprecipitation episodes associated with the regional incursionof the North American monsoon system Finally there is anextended dry period starting in late summer and extending

into early autumn The average annual accumulated precipi-tation for 2010ndash2013 was 4305 mm with a range of 392 mm(in 2012) to 513 mm (in 2010) It should be noted that 2012was among the driest years on record for most of Coloradoand the total precipitation for 2013 was similarly low Thelatter year began with very low winter and spring snowfalland stayed much drier than average until heavy Septemberrains increased the total accumulated precipitation to aboutthe same level observed in 2012 The maximum observedhourly rainfall recorded at the site from 2009 to 2013 was579 mm which occurred on 4 August 2010 Other thunder-storms with high rainfall rates (up to 25 mm per hour) arecommon during the summer monsoon

Seasonally transient snowpack is an important feature ofthe hydrologic cycle as the snowpack can provide a lastingwater source to the site during the spring melt period and canalso insulate the soil from freezing temperatures Snow depthmeasurements (Jenoptik Inc Jena Germany model SHM30laser snow depth sensor) began during the winter of 2010ndash2011 Persistent patchy or complete snowpack is limited toDecember January and February Periodic snowstorms mayalso input appreciable moisture during the months of Octo-ber November March and April although a snowpack rarelypersists for more than 7 days

Soil moisture probes (Decagon Devices Pullman WAUSA model EC-5) and temperature profiles (Campbell Sci-entific Logan UT USA model T107 thermistors) extendingfrom the near surface to approximately 1 m depth are madeat three different sites within the micrometeorology towerrsquosflux footprint The merged annual cycle of soil moisture fromall sites is shown in Fig 4b and the annual soil temperaturecycle is shown in Fig 4c The soil moisture cycle exhibitssome interesting and classic features of western landscapehydrology especially the tendency for persistent dryness andpulsed recharge of near-surface moisture particularly in thewarm season Deeper into the soil the moisture variabilityis significantly damped and there is evidence of persistentsoil moisture there regardless of extended summer dry pe-riods This deeper layer of persistent wet soil helps sustainsome of the total evaporative flux from the ponderosa pine



000

B Average annual soil moisture (2010-2012)

A Accumulated precipitation (2010-2013)

C Average annual soil temperature (2010-2012)

600

200

0

400

500

300

100

2010 2012

2011 2013

2010-2013

Monthly average precipitation


B Average annual soil moisture (2010-2012) 0-10 cm 20-50 cm 70-150 cm

0-10 cm 20-50 cm 70-150 cm


005

020

010

025

030

015

000

270

285

275

290

295

280

265

300

Pre

cip

itat

ion

(m

m)

Soil

mo

istu

re (

m3 m

-3)

Tem

pe

ratu

re (

K)

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

Figure 4 Hydrological measurement summary at the Manitou Ex-perimental Forest Observatory Annual accumulated precipitationfrom rain and snow(A) soil moisture at three depths(B) and soiltemperature at three different depths(C) Panel(A) includes datafrom hydrological years 2010ndash2013 whereas(B) and (C) includedata from 2010 to 2012

ecosystem during the summer There are extended periods ofwinter soil temperatures several degrees below 0C whichextends to approximately 70 cm below the surface These lowsoil temperatures indicate that significant amounts of soil wa-ter freeze (ie creates ldquosoil frostrdquo) occasionally during thewinter The presence of soil frost is further evidenced bythe sharp decline in recorded soil moisture values from De-cember through late February Suppressed soil moisture val-ues corresponding to sub-zero soil temperatures are a classicmeasurement artifact due to the significant change in soil di-electric permittivity as water undergoes phase change fromliquid to ice and back again at the freezing point This melt-water release and periodic melting of the transient snowpackimpart additional water pulses to the site As previously men-tioned MEFO typically experiences an early-summer dry pe-riod before the onset of the monsoon rains which is highlycorrelated with increased CO2 and BVOC fluxes The semi-arid climate creates very low midday stomatal conductance

in ponderosa pine during the early- and late-summer dry pe-riods (see Table 1) which protects the trees from water stressWhen the monsoon rains start these fluxes and stomatal con-ductance both increase substantially

22 Water manipulation effects on ponderosa pine

Projected water limitations and higher temperatures areexpected to put additional climate-induced physiologicalstresses on semi-arid forest ecosystems (Allen et al 2010)To test hypotheses related to future climates manipulationexperiments must be carefully designed to ensure that dataare representative of larger ecosystems responses (Beier etal 2012) With these considerations in mind another studyat MEFO during 2010ndash2011 was designed to quantify theeffect of different water treatments on the photosynthesisand respiration rates as well as BVOC emissions from ma-ture trees (at least 10 m in height) Up to 50 of the in-coming precipitation (snow and rain) was systematically di-verted from the root zones (10 mtimes 10 m area) around tar-geted trees using an array of troughs (see iii in Fig 1c) Theintercepted water was collected in barrels and then addedto nearby trees resulting in a water continuum delivered tothe various trees from 05 to 15 times the total precipita-tion such that the total amount of water delivered to the en-tire plot remained constant Physiological parameters (egsapflow photosynthesis and BVOC emissions) were mea-sured on all trees within the experimental plot Similar tothe speciation seen in ambient air branch-level measure-ments showed that the BVOCs emitted in the highest concen-trations were methanol 2-methyl-3-buten-2-ol and monoter-penes Initial observations showed that seasonality in plantphysiological processes and weather dynamics interact toproduce complex controls over climate-dependent emissionsof these compounds with a strong dependence on soil mois-ture and precipitation If the climate in this region shifts toa drier summer regime total BVOCs emitted from needlesof this forest are likely to decrease which will have implica-tions for modeling both gas- and liquid-phase regional chem-istry Studies such as this exemplify the interdisciplinary re-search questions addressed by the BEACHON project andare necessary to address the ecological system processes forinclusion in Earth system models as discussed in Sect 11

3 Volatile organic compounds oxidants and aerosolproperties

31 Volatile organic compound observations

Volatile organic compounds (VOCs) at MEFO are a mixtureof biogenic and anthropogenic compounds The summertimeVOC signals are dominated by biogenic emissions primar-ily methanol ethanol acetone monoterpenes (C10H16 ab-breviated as MT) and 2-methyl-3-buten-2-ol (C5H10O ab-breviated as 232-MBO or MBO) Isoprene (C5H8) is also



Flux [mg m-2 hr-1 m-1]

Hei

ght

[m]

Figure 5 Average daytime and nighttime vertical fluxes ofmonoterpenes (C10H16) and 2-methyl-3-buten-2-ol (232MBOC5H10O) during August 2010 The average daytime inte-grated flux ratio of MBO monoterpenes is 165 Fluxes withinplusmn01 mg mminus2 hminus1 mminus1 are shown within the shaded gray area toindicate the detection limit Error bars indicate the standard devia-tion of all measurements for that period and chemical species

observed during summer but to a much lesser extent (sim 10ndash20 of 232-MBO concentrations) Anthropogenic VOCconcentrations are lower than the biogenic compounds andare typically transported into the area from the ColoradoSprings or Denver metropolitan areas

A variety of techniques have been used to measure VOCsfrom different levels on the chemistry tower individual pon-derosa pine branches and the ground A quadrupole proton-transfer-reaction mass spectrometer (PTR-MS Ionicon An-alytik Innsbruck Austria) measured a suite of selectedVOCs (including methanol acetonitrile acetaldehyde ace-tone+ propanal 232-MBO+ isoprene benzene monoter-penes and sesquiterpenes) during portions of each of the2008ndash2012 growing seasons Under normal operating con-ditions 232-MBO undergoes a dehydration reaction in thePTR-MS drift tube leading to a molecular ion ofmz = 69This is the same ion as protonated isoprene which is whythey are reported as the sum of both species Tower-basedmeasurements alternated between a six-point gradient sys-tem (16 5 85 12 177 and 251 m above ground) and aneddy covariance (EC) flux system at the top level (251 m)In addition a time-of-flight (TOF) PTR-MS (University ofInnsbruck Austria) was deployed for EC and concentrationmeasurements above the ponderosa pine canopy in 2010 and2011 (Kaser et al 2013a b) A selective reagent ion (SRI)PTR-TOF-MS (Ionicon Analytik Innsbruck Austria) instru-ment was used in 2011 to selectively distinguish 232-MBOfrom isoprene concentrations by using NO+ as the reagention (Karl et al 2012) This configuration was also used for 1week in 2012 to continue these measurements for determin-ing EC fluxes of 232-MBO and isoprene (Karl et al 2014)Figure 5 shows the August 2010 vertical flux profiles for 232-MBO and total MT calculated from gradient measurementsusing the methodology described in Karl et al (2004) It isevident that MBO emissions follow a light-dependent patternand that the fluxes increase with height up to 12 m MT emis-

sion patterns were vertically more uniformly distributed sug-gesting that the understory (forest litter bark and trunks) alsocontributed to the total emissions Using site-specific leaf cu-vette measurements as model inputs MEGAN 21 estimatesshowed good agreement with the measured average daytime232-MBO+ isoprene fluxes of 184 mg mminus2 hminus1 After thelarge rain and hail storm on 4 August 2010 (which produced579 mm precipitation in an hour see Sect 21) monoterpenefluxes increased to 47 mg mminus2 hminus1 which is a factor 5ndash10higher than what is normally observed (05ndash1 mg mminus2 hminus1)

(Kaser et al 2013b) Figure 6a shows the sum of MT andMBO+isoprene concentrations and fluxes starting on thisday (4 August) and ending 1 week later (11 August) Theincreases in both emissions and fluxes which continue forsim 2 days after the rain event are evident The missing fluxdata on the first day (and periodically throughout the mea-surement period) are due to turbulence characteristics thatare not amenable to EC calculations as described in Sect 13The PTR-MS showed that ambient concentrations of severalother BVOC (including cymene camphor nopinone pinon-aldehyde and sesquiterpenes) were also elevated after thisvegetation disturbance

The trace organic gas analyzer (TOGA Apel et al 2010)was deployed during the BEACHON-ROCS campaign tomeasure concentrations of isoprene 232-MBO speciatedMT and over 25 other targeted compounds Results showedthat the MT speciation is dominated byα-pineneβ-pineneand1-3-carene (approximately 25 each) Other quantifiedmonoterpenes include camphene (7 ) limonene (12 )myrcene (5 ) and ocimene (1 ) Figure 6b (1ndash4) showsAugust 2010 ambient diel concentrations of four selectedVOCs reported by TOGA The concentrations of the bio-genic compounds MBO and MT are much higher than thoseof a typical anthropogenic compound (eg toluene) at thissite and the concentrations have different diurnal signaturesDuring the day as the boundary layer grows and OH ispresent MT concentrations are diminished even though theiremissions are the greatest during this time At night thesuppressed boundary layer height combined with decreasedlosses from O3 and OH reactions leads to elevated MT con-centrations that generally increase from 1800 to midnightand remain elevated until 0600ndash0700 MBO emissions fromponderosa pine are strongly light dependent (Harley et al1998 Kaser et al 2013b) resulting in maximum emissionsand ambient concentrations during midday with a secondarypeak in the early morning associated with initiation of emis-sions before the morning breakup of the nocturnal boundarylayer The combination of all three instruments used duringBEACHON-ROCS provided a unique opportunity to com-pare VOC measurement techniques under real-world condi-tions The results were encouraging as the instruments agreedwithin sim 20 for monoterpenes andsim 10 for 232-MBO+ isoprene withR2 values of 085ndash097 (Kaser et al 2013a)

Consistent with ambient concentration measurementsbranch- and needle-level BVOC emission measurements



A1 232-MBO (blue) and MT (red) fluxes

A2 232-MBO (blue) and MT (red) concentrations

5-Aug 6-Aug 7-Aug 8-Aug 9-Aug 10-Aug 11-Aug

4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

d Sum of Monoterpenes (pptv)

1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0

c Toluene (pptv)B-1 Isoprene (pptv) B-2 Toluene (pptv)

B-3 232-MBO (pptv) B-4 Total MT (pptv)

Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]

Figure 6 (A) (adapted from Kaser et al 2013b) shows the sumof MT and MBO+isoprene measurements as reported by the PTR-TOF-MS from 251 m on the chemistry tower from 4 August(DOY = 216) to 11 August 2010 (DOY= 223) A1 shows theabove-canopy fluxes while A2 shows the corresponding concen-trations in ppbv(B) shows diurnal profiles of (B-1) isoprene (B-2)toluene (B-3) MBO and (B-4) sum of monoterpenes during all ofAugust 2010 as measured using TOGA Box boundaries indicateinterquartile range median is indicated as the line through the boxand whisker lengths indicate the total measurement range

confirm the dominance of MBO in the emission profileduring daylight hours MBO typically comprises gt 85 ofthe emitted reactive BVOC mass Similar to ambient ob-servationsα-pineneβ-pinene1-3-carene camphene andlimonene dominate the MT emissions but a large numberof other terpenoids are also emitted including sabinenemyrcene ocimeneα-terpineneβ-phellandrene cymeneterpinolenep-cymenene and the oxygenated monoterpeneslinalool terpineol and methyl chavicol In many cases espe-cially in high light conditions linalool was a major compo-nent of the leaf-level emissions A number of sesquiterpenesdominated byβ-farnesene also appear in emission samplesFor model inputs BVOC speciation is an important consid-eration as different compounds (such as MT isomers withthe same chemical formula) have different reaction rate con-stants with OH O3 and NO3 so their reaction products path-ways and atmospheric lifetimes can vary considerably Addi-tional soil BVOC flux measurements have been made usingenclosures and a micrometeorological gradient technique atthe site (Greenberg et al 2012) These results suggested thatemissions from the litter were negligible contributing less

than 1 of above-canopy emissions for all BVOCs mea-sured

A newly developed thermal desorption aerosol gaschromatographndashaerosol mass spectrometer (TAG-AMS) wasdeployed and used to analyze semi-volatile VOCs (sim C14ndashC25) on a bihourly timescale The sample collection ther-mal desorption and chromatography systems have been de-scribed previously by Zhao et al (2013) however the 2011BEACHON-RoMBAS campaign was one of the first to cou-ple it to the AMS as a detector (Williams et al 2014)More than 70 semi-volatile gas-phase species were observedand quantified in the ambient atmosphere during the cam-paign Source apportionment was used to identify the originof these gas-phase species Some were anthropogenic com-pounds (such as poly-aromatic hydrocarbons (PAH) oxy-genated PAH and alkanes) but 23 species were identifiedto be terpenoid compounds of biogenic origin from a localsource determined from positive matrix factorization (PMF)

In addition to direct VOC emissions and transportedspecies it is also important to consider oxidation prod-ucts These compounds can influence tropospheric ozone for-mation and oxidative capacity of the atmosphere and con-tribute to secondary organic aerosol Concentrations andfluxes of two important oxygenated VOCs formaldehyde(HCHO) and glyoxal (CHOCHO) were measured during the2010 BEACHON-ROCS campaign (DiGangi et al 20112012) using fiber-laser-induced fluorescence (FILIF Hot-tle et al 2009) and laser-induced phosphorescence (Huis-man et al 2008) Ambient formaldehyde concentrationsranged between a minimum ofsim 05 ppb in the early morn-ing hours (0400 MST) and maximum values of 2ndash25 ppb inthe evening (sim 2000 MST) Ambient glyoxal concentrationsranged between a minimum ofsim 18 ppt in the early morn-ing hours (0600 MST) and maximum values of 30ndash55 pptin the evening (sim 1700 MST) The glyoxal formaldehyderatio maintained a stable diurnal cycle ratio with valuesof sim 15ndash2 in the early morning and at night and ris-ing to sim 25ndash3 in the middle of the days In addition toour knowledge these canopy-scale HCHO eddy flux mea-surements are the first reported for any site These resultscoupled with enclosure measurements that showed minimaldirect emissions suggest a surprisingly large HCHO pro-duction source within the canopy air space The middayHCHO fluxes were positive (upward) ranging from 37 to131 microg mminus2 hminus1 (see Fig 7b) and were correlated with tem-perature and radiation within the canopy The missing HCHOsource is thus consistent with oxidation of VOCs with light-and temperature-dependent emission profiles The strengthof HCHO fluxes cannot be accounted for by the oxidation ofmeasured MBO and terpenes (also see Sect 32) A detailedanalysis regarding HCHO sources and oxidation is discussedin DiGangi et al (2011)



A

B

Figure 7 Average modeled and measured diurnal cycles of(A)within-canopy peroxy radical mixing ratios and(B) above-canopyformaldehyde fluxes The measured and modeled results for bothcompounds include the hourly averages from the August 2010BEACHON-ROCS intensive measurement campaign Model calcu-lations of HCHO fluxes and peroxy radicals are described in Di-Gangi et al (2011) and Wolfe et al (2014) respectively

32 Peroxy and hydroxyl radical observations

Numerous studies (eg Stone et al 2012) have highlighteddiscrepancies between modeled and measured radical con-centrations in forested environments suggesting a lack ofunderstanding of the chemical processes driving secondarypollutant formation While most research has focused on re-gions dominated by isoprene emissions results from severalinvestigations indicate gaps in our understanding of BVOCoxidation in MBO- and monoterpene-dominated areas sim-ilar to MEFO (Kurpius and Goldstein 2003 Day et al2008 Farmer and Cohen 2008 Wolfe et al 2011 Maoet al 2012) Both the 2010 BEACHON-ROCS and 2011BEACHON-RoMBAS campaigns included measurements ofthe hydroxyl radical (OH) and peroxy radicals (HO2 andRO2 see Table S1 in the Supplement) using the techniquesdescribed by Edwards et al (2003) Hornbrook et al (2011)and Mauldin et al (2001) This provided a unique oppor-tunity to test our understanding of the chemical reactionsthat link BVOC oxidation with production of ozone and sec-ondary organic aerosol (SOA) precursors

Discrepancies between modeled and measured HOx (ieOH+ HO2) in regions with high BVOC levels have been pri-marily attributed to ldquomissingrdquo sources of OH (Thornton etal 2002 Lelieveld et al 2008 Hofzumahaus et al 2009Peeters et al 2009) In the boundary layer OH is producedboth via ldquoprimaryrdquo sources such as photolysis of ozone inthe presence of water vapor and via radical cycling reactions

such as reaction of HO2 with NO

O3 + hν rarr O(1D) + O2 (R1)

O(1D) + H2O rarr 2OH (R2)

HO2 + NO rarr OH+ NO2 (R3)

In a detailed analysis of OH observations Kim et al (2013)demonstrate that radical recycling via Reaction (R3) is likelythe dominant source of OH within the MEFO canopy A0-D box model underpredicts HOx concentrations relativeto observations implying unidentified sources of HO2 Us-ing the same box model in a study focused on peroxy radi-cal observations Wolfe et al (2014) confirm this result andidentify several potential additional sources of both HO2 andRO2 Notably it is suggested that oxidation of unmeasuredhighly reactive BVOC could explain a significant portion ofthe missing peroxy radical source Such a source could alsoexplain the high HCHO fluxes observed during the samecampaign (DiGangi et al 2011 see Sect 31) Figure 7acompares the hourly averaged measured and modeled totalperoxy radical mixing ratios for BEACHON-ROCS (August2010) As described in Wolfe et al (2014) the differencebetween measured and modeled values corresponds to a to-tal ldquomissingrdquo peroxy radical production rate of as much as130 ppt minminus1 For comparison Fig 7b shows measured andmodeled HCHO fluxes (DiGangi et al 2011) The additionalHCHO production needed to reconcile modeled and mea-sured formaldehyde fluxes is on the order of 65 ppt minminus1

at midday Uncertainties in measurements and model resultscontribute to a significant overall uncertainty in these pro-duction rate estimates (approximatelyplusmn50 ) Nonethelessthe similarity between these results ndash obtained via two es-sentially independent methods ndash supports the conclusion thatVOC oxidation within the canopy is much stronger than pre-dicted by canonical chemical mechanisms

Analysis of the role of anthropogenic influence on the oxi-dation of BVOCs especially via the influence of NOx on thefate of RO2 is of great current interest (Orlando and Tyndall2012) and MEFO is well suited for such studies (see alsoSect 41) Figure 8a shows the measured HO2 HO2+ RO2NO and NO2 concentrations during a representative day inBEACHON-ROCS (24 August 2010) and Fig 8c shows thecorresponding wind speed and direction On this day ups-lope conditions (which can bring polluted urban air and areoften seen at this site) were not observed as the wind wasgenerally out of the south or southwest where there is rela-tively little anthropogenic influence During the mid-morningas the boundary layer developed an increase in NOx (Fig 8a)can be seen which was likely due to downward transport ofa residual layer The anthropogenic influence on the fate ofRO2 is evident as the loss mechanism was initially domi-nated by the RO2+ NO channel (Fig 8b) but during mid-day as NOx concentrations decreased (due to the residualmorning boundary layer breaking up and southwesterly flowto the site) the RO2+ HO2 channel became the major loss



0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)

Figure 8 Examination of RO2 fate and its relation to anthro-pogenic influence on 24 August 2010 during BEACHON-ROCSThe first(A) shows median concentrations of NO NO2 HO2 andHO2+ RO2 over the course of this day Wind speed and direction(C) show the wind shifting from out of the south to out of the south-east just prior to noon (MST) indicating an anthropogenic influencefrom the Colorado Springs area This transition is also reflected inthe NO increase in panel A The middle(B) shows the calculatedRO2 loss percentage from reaction with NO or HO2 based on mea-sured NO and HO2 concentrations and on rate constants obtainedfrom the IUPAC database Each symbol in(B) represents the me-dian value from 30 min time bins Figure adapted from DiGangi etal (2012)

mechanism While the patterns of these transitions do notappreciably affect the concentrations of biogenic and anthro-pogenic VOCs the changes in the role of the different reac-tion channels are consistent with the measured HCHO andglyoxal concentrations (DiGangi et al 2012) and measuredand modeled HO2+ RO2 concentrations indicated in Fig 7This competition between NOx and HO2 for reaction withthe peroxy radicals (RO2) affects the composition of multi-generational reaction products formed during gas-phase radi-cal cycling and thus dictates to a large extent the productionof ozone and organic aerosol precursors

33 Aerosol properties and composition

Particle size distribution measurements (covering diametersfrom 4 nm to 25 microm) were conducted for nearly 2 years atMEFO starting in February 2010 and ending in January 2012The instruments used for these measurements consist of thefollowing components

ndash optical particle counter (200ndash2500 nm) Lasair model1002 from Particle Measurement Systems (BoulderCO USA)

ndash regular scanning mobility particle sizer (SMPS 30ndash300 nm) custom sheath air and HV control unit com-bined with TSI model 3081 differential mobility ana-

lyzer (DMA) and TSI model 3760 condensation particlecounter (CPC TSI Inc Shoreview MN USA) and

ndash nano-SMPS (4ndash30 nm) custom sheath air and HV con-trol unit combined with TSI model 3085 DMA and TSImodel 3025a CPC

Particle size distributions started at midnight at exact 5 minintervals for a total of 288 size distributions per day Fre-quent ldquosmall particle eventsrdquo characterized by high concen-trations of 4ndash20 nm particles were observed especially dur-ing the summer season The origin of these small particles islikely atmospheric nucleation (Kulmala et al 2007) whichis thought to be caused by reactions of gas-phase sulfuricacid with atmospheric bases such as ammonia and aminesas well as oxidized organic compounds (Kirkby et al 2011Almeida et al 2013) An example of three typical small par-ticle events during July 2011 is shown in Fig 9a where theonset of each event is seen just prior to noon (MST) Theseevents are common at MEFO in the summer occurring 3ndash5times per week during late morning or early afternoon andtypically coincide with changes in wind speed and directionFigure 9b shows wind speed and wind direction at the topof the chemistry tower and sulfate aerosol mass loadingsmeasured by an aerosol mass spectrometer (described be-low) On each of these mornings the wind speed is fairly low(sim 1 m sminus1) at 0800 MST with wind direction shifting fromthe south to a more northerly or northeasterly direction indi-cating upslope transport from the Denver area Thermal des-orption chemical ionization mass spectrometer (TDCIMS)measurements during these nucleation events demonstratedthat sub-20 nm particles were composed ofsim 60 sulfate bymass whereas during non-event periods sulfate contributedless than 40 of the mass to these small particles (Cui et al2014) In both event and non-event periods the bulk aerosolmass is not significantly affected by this sulfate mass as themajority of the total aerosol mass is dominated by larger par-ticles The correlation with wind direction and the increase insulfate aerosol indicates that these events are anthropogeni-cally induced The scarcity of particles smaller than 10 nmon 29 July suggests that nucleation is occurring away fromthe site either aloft (Mirme et al 2010 Schobesberger etal 2013) or in the mixed layer shortly (sim 60 min or less)upwind of the site

A fast mobility particle sizer (FMPS Model 3091 TSIInc Shoreview MN USA) was used during BEACHON-RoMBAS to measure size-dependent particle fluxes (Pryoret al 2013) While the mean flux of both Aitken and nu-cleation mode particles was downwards upward fluxes werefrequently observed Based on quadrant and timescale analy-ses using the University of Helsinki Multicomponent Aerosol(UHMA) model (Korhonen et al 2004) Pryor et al (2013)found that the upward fluxes of nucleation mode (lt 30 nmdiameter) particles were most strongly influenced by up-ward transport of particle-rich air from the canopy resultingfrom the growth of recently nucleated particles as well as


J Ortega et al Overview of the Manitou Experimental Forest Observatory 6357W

ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm

] July 27 July 28 July 29

A

B

Mountain Standard Time

000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]

Figure 9 Three representative days of particle size distributions(A) wind speed wind direction and sulfate aerosol mass(A) during27ndash29 July 2011 In(A) the mobility diameter is on they axis timeis on thex axis and the color bar indicates particle number concen-tration (dN dlogDp) in cmminus3 In (B) the sulfate aerosol mass ismultiplied by 4 and is listed on the secondy axis along with windspeed

coagulation processes Downward fluxes of the Aitken modeparticles were more commonly linked to breakdown of thenocturnal inversion and entrainment of particle-depleted airfrom above the canopy

Average particle number concentrations at this site areusually less than 2times 103 cmminus3 which is typical for ru-ral continental environments and concentrations rarelyexceed 104 cmminus3 During the August 2011 BEACHON-RoMBAS study chemical speciation and mass loadings ofnon-refractory PM1 aerosol were measured using a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS Aerodyne Research Inc Billerica MA DeCarloet al 2006) Average mass loadings during the campaignwere 25 microg mminus3 (Fig 10) Also included in this figure isblack carbon aerosol as measured with a single-particle sootphotometer (Droplet Measurement Technologies BoulderCO model SP2) Approximately 75 of the total PM1aerosol mass was comprised of organic aerosol (OA) withthe rest composed primarily of ammonium sulfate Nitrateconcentrations were low and were shown to be primarilycomposed of organic nitrates (Fry et al 2013) Black carbon(BC) aerosol mass was on the order of a few percent of the to-tal submicron mass and more variable often increasing anddecreasing by an order of magnitude on hourly timescalesTransport from urban areas fires and local traffic likely ex-plain this variability Figure 10b shows the size-resolvedcomposition for the same species and time period Ammo-nium and sulfate size distributions were centered at 300ndash400 nm while organics and nitrate aerosol size distributionswere centered atsim 250 nm The distinct size distributions ofthe chemical components indicate that these aerosols are notcompletely internally mixed Figure 10c shows the month-long daily distributions which indicate a subtle diurnal cycle

in organic aerosol peaking at night but with considerableday-to-day variability The peak in average sulfate (and asso-ciated ammonium) atsim 1600ndash1900 is primarily due to theinfluence of certain days when sulfate increased during lateafternoon to early evening with corresponding SO2 increases(see spikes in Fig 10a) The diurnal BC trends showed twopeaks The larger of these was in the evening (sim 2000)coincident with the regular prolonged impact of the urbanplume in the afternoon and through the evening and wasalso seen in other anthropogenic species (eg NOx CO)The smaller shorter duration morning peak (sim 0600 MST)was also correlated with NOx and CO The reason for thismorning BC increase could be due to the breakup of the shal-low nocturnal boundary layer causing mixing down of morepollution-rich residual layer air or an increase of local emis-sion sources into a shallow morning boundary layer It shouldbe noted that the diameter measured from BC aerosol is themass equivalent diameter (Dme) that was obtained by assum-ing a density of 18 g cmminus3 as recommended by Moteki etal (2010) The aerodynamic diameter is estimated to be atleast 18 times larger than theDme shown in Fig 10b andcould be larger than this if the BC were internally mixed withother non-BC compounds (eg organic coatings) or smallerif the particles had irregular shapes (DeCarlo et al 2004)

PM25 collection on quartz fiber filters during the samecampaign were analyzed for a variety of specific SOC(secondary organic carbon) and carbon isotopic measure-ments as described in Geron (2011) and Lewandowski etal (2013) These results estimated that 05 microgC mminus3 couldbe attributed to specific SOC precursors Hemiterpene pre-cursor compounds (isoprene+ MBO) represented approxi-mately half of the observed SOC with monoterpenes con-tributing nearly the same amount to the total SOC Iso-topic measurements of these same filter samples found thatthe 14C ratio was 071plusmn 011 (range 052 to 088) indicat-ing that roughly three-quarters of the particulate carbon ob-served during BEACHON-RoMBAS was of modern non-petrogenic origin The fraction of modern carbon (70 ) atthis site is less than values observed in eastern US forestsFor example Geron (2009) reported mean summertime val-ues of 83 and with maximum values reaching 97 forthose forests Similarly during summer months near forestsin the eastern United States Lewis et al (2004) observed val-ues betweensim 80 and 95 Organic tracer results (includingoxidation products of isoprene MT and 232-MBO) indicatethat the lower fraction of contemporary carbon is primarilydue to lower total biogenic emissions and lower organic massloadings and not due to more traffic or other urban influences(Kleindienst et al 2007) The modern carbon results fromMEFO can also be compared to measurements at nine In-teragency Monitoring for Protection of Visual Environments(IMPROVE) network sites The values from the urban sitesin this network averaged approximately 50 (Bench et al2007)



Figure 10 Aerosol mass spectrometer (AMS) and single-particlesoot photometer (SP2) results of bulk PM1 aerosol compositionduring July and August 2011 Black carbon (BC) is measuredby the SP2 and all others (organics nitrate sulfate and ammo-nium) are from the AMS(a) shows the time series of mass load-ings(b) shows the average size-resolved aerosol distributions and(c) shows the diurnal trends of each of the individual species aver-aged over the study period The box plot boundaries in(c) representthe standard deviations and the whisker lengths indicate the 25thand 75th percentiles of the measurements The center line througheach box indicates the median Note that most of the aerosol is com-posed of organic species and that in all panels black carbon masshas been multiplied by 6 and the other (sulfate nitrate and ammo-nium) speciesrsquo masses have been multiplied by 3 The diameters forthe BC measurements are estimated using an assumed density of18 g cmminus3 as indicated in the text (Sect 33)

Gas- and aerosol-phase organic nitrate concentrationswere quantified with thermal dissociation laser-included flu-orescence (TD-LIF Day et al 2002 Rollins et al 2010)during summer 2011 (Fry et al 2013) Gas-phase organicnitrate classes showed diurnal cycles peaking midday atsim 200 ppt (total alkyl and multifunctional nitrates)sim 300 ppt(total peroxy acyl nitrates) whereas total particle-phase or-ganic nitrates peaked at night and early morning hours For-mation rates of gas-phase organic nitrates within the shallownocturnal boundary layer were comparable to daytime ratesof formation It was observed that total gas- and particle-phase organic nitrates had equilibrium-like responses to di-urnal temperature changes suggesting some reversible par-titioning although thermodynamic modeling could not ex-plain all of the repartitioning Additionally the diurnal cy-cle of gasndashparticle partitioning supported modeled-predictednighttime formation of lower volatility products compared

to daytime from NO3 radical-initiated oxidation of monoter-penes Aerosol-phase organic nitrates were also measured byAMS and showed good agreement with TD-LIF (Fry et al2013)

Hundreds of acids in the gas and aerosol phases werequantified in real-time during summer 2011 using a newlydeveloped technique the micro-orifice volatilization im-pactor high-resolution time-of-flight chemical ionizationmass spectrometer (MOVI-HRToF-CIMS Yatavelli et al2012 2014) It allowed for direct measurement of the gasndashparticle partitioning of individual and bulk organic acidsComparisons to absorptive partitioning modeling demon-strated that bulk organic acids seemed to follow absorp-tive partitioning responding to temperature changes ontimescales of lt 1ndash2 h suggesting there were no major kineticlimitations to species evaporation It was shown that speciescarbon number and oxygen content together with ambienttemperature controlled the volatility of organic acids and aregood predictors for partitioning Moreover the relationshipbetween observed and model partitioning with carbon num-ber and oxygen content pointed toward the likely importanceof different classes of multifunctional organic acids that com-prised the bulk of the acid groups (eg hydroxy acids hy-droperoxy acids or polyacids but not keto acids)

A newly identified 232-MBO-derived organosulfate wasidentified in aerosol samples during BEACHON-RoMBASalthough at levels lower than reported for a previous Cali-fornian study (Zhang et al 2012) The difference was ten-tatively attributed to the lower acidity of the pre-existingaerosol at BEACHON as acidity is thought to greatly en-hance the formation of this organosulfate This species hasthe potential to be used as a tracer of SOA formation from232-MBO

Part of BEACHON-RoMBAS included the collection oftime- and size-resolved biological aerosol properties To ourknowledge this is the most extensive and comprehensiveset of these measurements and data available One key ob-servation during the study was that rainfall events inducedlarge increases in ambient fluorescent biological aerosol par-ticle (FBAP) concentrations within the forest canopy (Huff-man et al 2013 Prenni et al 2013) with concentrationsremaining elevated for extended periods of time (gt 12 h) dueto increased humidity and surface wetness The largest ob-served increases of more than an order of magnitude rela-tive to dry conditions occurred in the size range of 2ndash6 micromMicroscopic observations showed that these particles weredominated by biological cells at sizes with characteristicsof bacterial aggregates and fungal spores (Huffman et al2013) Concentration increases that occurred during the rainevents likely resulted from mechanical ejection of biologicalparticles from surfaces (Constantinidou et al 1990 Jonesand Harrison 2004) while a second larger mode (which oc-curred after the rain) was likely actively emitted from biotaon vegetated surfaces near the site (Elbert et al 2007 Huff-man et al 2013) Contrary to the expectation that large



particles will be washed out during precipitation these datashowed a significant increase in concentration and net up-ward flux of primary supermicron particles after rain whichdemonstrates a direct and important link of airborne parti-cles to the hydrological cycle Longer term measurementscontinued for 10 months (July 2011ndashJune 2012) trackingthe seasonal FBAP cycle at the site and observing trendswith season precipitation and other meteorological param-eters (Schumacher et al 2013)

34 Cloud condensation nuclei and ice nuclei

One of the primary goals of the BEACHON project was todetermine the potential for biogenic emissions to serve asCCN and ice nuclei (IN) which can impact cloud proper-ties and precipitation (eg Barth et al 2005) It has beenrecently suggested that fungal spores may have large influ-ences on SOA formation in the Amazonian forest (Poumlhlker etal 2012) and as discussed below these biologically influ-enced particles can influence both CCN and IN Changes incloud properties and precipitation can in turn influence bio-genic emissions closing the loop on a potentially importantfeedback between the carbon and water cycles (Poumlschl et al2010 Morris et al 2014)

To better understand the influence of biogenic secondaryorganic aerosol on aerosol hygroscopicity and the seasonalvariability of CCN a continuous 14-month study (March2010ndashMay 2011) was performed at MEFO (Levin et al2012) This was followed by additional measurements dur-ing the summer 2011 BEACHON-RoMBAS intensive cam-paign which allowed for direct comparison between aerosolhygroscopicity and aerosol chemical composition measure-ments (Levin et al 2014) Aerosol hygroscopicity was de-scribed using the dimensionless hygroscopicity parameterκ (Petters and Kreidenweis 2007) showing an annual av-eragedκ value of 016plusmn 008 This value is similar toκvalues measured in remote forested regions such as inFinland (Cerully et al 2011) and the Brazilian Amazon(Gunthe et al 2009) and is lower than the commonly as-sumed continental value ofκ = 03 (Andreae and Rosen-feld 2008) Aerosol composition derived from the hygro-scopicity measurements at MEFO indicated a predominanceof organic species in the aerosol leading to the lowκ mea-surement values Direct comparison of organic mass fractionmeasured by aerosol mass spectrometry and filter measure-ments (discussed in Sect 33) during BEACHON-RoMBASagreed well with the composition derived from the hygro-scopicity measurements Organic mass fractions were foundto be largest (up to 90 ) in the smallest particles (20ndash30 nm as measured by the TDCIMS) This fraction decreasedwith increasing particle diameter as measured by the AMS(Fig 10b Levin et al 2014) and is consistent with thesmallest particles being composed primarily of oxidized or-ganic species from forest emissions Results from the year-long measurements showed thatκ was slightly higher dur-

ing the winter months when biogenic emissions (which arestrongly temperature dependent) are suppressed The com-bination of these results suggests that secondary organicaerosol derived from biogenic emissions impact aerosol hy-groscopicity and CCN number concentrations throughout theyear

In addition to the CCN measurements IN have also beencharacterized Ice-nucleating particles induce ice formationin clouds and are thought to be critical in initiating precipi-tation from mixed-phase clouds (DeMott et al 2010) Dur-ing BEACHON-RoMBAS IN number concentrations werecharacterized at temperatures betweenminus34 andminus9C Inaddition the particle sizes that induced freezing at tempera-tures greater thanminus20C were characterized via the dropletfreezing technique These particles as well as IN were bothpositively correlated with number concentrations of FBAP(Huffman et al 2013 Prenni et al 2013 Tobo et al 2013)Similar to the precipitation-induced increases observed inbiological particle concentrations IN also increased duringrain The most dramatic example of this increase occurred on2 August 2011 when a thunderstorm produced 196 mm ofprecipitation (maximum rainfall rate of 30 mm hminus1) Duringthis storm IN concentrations atminus25C increased from 2 tonearly 200 Lminus1 (Prenni et al 2013) Correlation between INand FBAP across the temperature range coupled with DNAanalysis of a portion of the residual IN suggests that a signifi-cant fraction of the IN near the ground surface is composed ofbiological particles particularly during and after rain events(Huffman et al 2013 Prenni et al 2013 Tobo et al 2013)When lofted to altitudes where mixed-phase clouds persistthese biologically influenced IN can influence subsequentprecipitation providing yet another feedback between bio-genic emissions and the hydrologic cycle and further linkingthe biosphere hydrosphere and atmosphere

4 Atmospheric processes at an urbanndashrural interface

41 Atmospheric chemistry

As mentioned in Sect 22 the MEFO site is primarily influ-enced by clean continental air but is periodically impactedby polluted air advected from the Colorado Front Range ur-ban areas This makes the site a suitable location to investi-gate interactions between biogenic and anthropogenic emis-sions and a variety of interesting questions can be addressedFor example how are the oxidation pathways of locally emit-ted BVOC influenced by oxidant levels (NO3 OH and O3)

during clean and polluted conditions In addition to what ex-tent does the transport of SO2 oxidants and VOCs from ur-ban areas affect particle nucleation and growth Model simu-lations can be initialized and parameterized using long-termand campaign-specific measurements of aerosols VOCstrace gases and meteorology Results from these simulationscan then be compared to observations Local emissions are



dominated by 232-MBO and monoterpenes but these canbe augmented by transport of anthropogenic species fromthe Front Range cities Typical summertime ozone concen-trations are 50ndash60 ppb during the afternoon and decreaseto sim 10ndash20 ppb at night Nitrogen oxides (NOx) are gener-ally dominated by NO2 with typical valuessim 05 to 40 ppbalthough occasional urban influences can cause the concen-tration to increase to 8ndash10 ppb NO concentrations are muchlower ndash typically less than 05 ppb and rarely exceed 10 ppbSince the area is relatively rural with low NOx concentra-tions ozone is not titrated away at night as would typicallyhappen in an urban environment Average SO2 concentra-tions are quite low year-round averaging less than 02 ppbbut concentrations can occasionally spike tosim 20 ppb Theaverage August 2011 CO concentration was 123 ppb (stan-dard deviation of 27 ppb) These values increase when urbanair is transported to the site but rarely exceed 150 ppb Peri-odic CO measurements at other times of year have shownsimilar consistent results These direct measurements pro-vide valuable insight into the range of atmospheric condi-tions that the site experiences and can be used as initial in-puts and provide constraints in modeling efforts The rela-tively clean conditions combined with periodic well-definedurban perturbations make it an ideally situated location forstudying atmospheric processes at the rural-urban interfaceAn example of this was demonstrated in Fig 8 (adapted fromDiGangi et al 2012) which shows the ambient concentra-tions of HO2 RO2 NO and NO2 in panel a and the corre-sponding wind speed and direction in panel c during a rep-resentative BEACHON-ROCS day (24 August 2010) In theearly morning both HO2 and RO2 are very low (lt 20 ppt)accompanied by low wind speeds During the day the windspeed increases and becomes southeasterly with an accompa-nying increase in NO (likely from the Colorado Springs areasim 40 km SE of the site) Atsim 1030 there is an abrupt changein wind direction with air coming from the SW (where thereis little anthropogenic influence) accompanied by a sharp de-crease in NO concentrations Concentrations of HO2+ RO2then reach maximum values during the early afternoon atwhich point the HO2 concentrations become maximized andthe loss mechanism for RO2 is through the RO2+ HO2 chan-nel (Fig 8b) These observations demonstrate that the fateof RO2 radicals at the site is dominated by reaction withHO2 under clean-air conditions and by reaction with NOwhen influenced by urban air The transitions between thetwo regimes can be quite sharp making the site well suitedfor studying these types of transitions

42 Coupled weather and chemistry modeling

Three-dimensional coupled meteorology and chemistry sim-ulations of MEFO and the surrounding region have been con-ducted using the Weather Research and Forecasting modelwith chemistry (WRF-Chem Grell et al 2005 Fast etal 2006) These model runs include gas-phase and aerosol

Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude

Figure 11 Residence time analysis (RTA) from WRF-Chem esti-mates the amount of time that air masses originate from the vari-ous locations in the region These simulations estimate 48 h back-trajectories at MEFO (27 July to 26 August 2011) Three ma-jor Front Range cities (Denver Colorado Springs and Pueblo) areshown and open circles indicate the citiesrsquo primary coal-fired powerplants The left panel indicates that the majority of the low NO2 con-centration results (0ndash50th percentile) are from air masses that orig-inate from the west The right panel shows that the highest 10 ofNO2 concentrations originate from the Front Range cities and areadvected to the site

chemistry as well as aerosol effects on radiation and cloudsSimulations were performed at 4 km horizontal grid spacingand compared to ground measurements during the intensiveBEACHON-ROCS and BEACHON-RoMBAS measurementperiods These modeling studies focused particularly on or-ganic aerosol (OA) formation from forest BVOC emissionsand the influence of anthropogenic pollutants transported tothe site To study OA formation the WRF-Chem model wasconfigured as described in Fry et al (2013) using the SOAmodule based on Hodzic and Jimenez (2011) for anthro-pogenic precursors and Shrivastava et al (2011) for biogenicprecursors To study the influence of anthropogenic pollutionon aerosol formation the WRF-Chem model was configuredas described in Cui et al (2014) Back-trajectory calculationsbased on WRF-Chem simulations confirm that these pollu-tants are advected from the Front Range urban area (Fig 11)Elevated concentrations of NO2 (and SO2 not shown) mea-sured onsite coincide with the arrival of polluted air massesfrom Denver or Colorado Springs whereas low concentra-tions are associated with cleaner air advected from the westThe effect of anthropogenic pollution on predicted OA com-position suggests a fraction of modern carbon that is on theorder of that measured Figure 12 shows that 30 or moreof OA is influenced by anthropogenic species through ei-ther the formation of secondary organic aerosols by night-time NO3 chemistry increased OH and O3 oxidation or thedirect transport of anthropogenic OA to the site NO3 chem-istry contributes to larger SOA concentrations at night whenthe boundary layer is shallow (Fry et al 2013) but the over-all contribution to the actual aerosol column relevant to ra-diative forcing is small (a 1 microg mminus3 mass concentration rep-resents a 100 microg mminus2 column density in a 100 m nighttime


J Ortega et al Overview of the Manitou Experimental Forest Observatory 6361TO

A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA

+ Biogenic SOA from NO3

+ Biogenic SOA from OH O3 Primary OA

30

25

20

15

10

05

00

Modeled and measured total organic aerosol (TOA) July 16-August 25 2011

Figure 12 Modeled and measured average diurnal profiles of to-tal organic aerosol (TOA) mass concentrations at MEFO duringBEACHON-RoMBAS 2011 Aerosol mass spectrometry (AMS)observations are shown as black circles (with 1σ variability shownin gray) Predicted TOA is indicated in yellow (with variabilityshown by the yellow bars) The predicted TOA is the sum ofthe contributions primary OA (red) biogenic secondary organicaerosol (SOA) from OH and O3 chemistry (green) biogenic SOAfrom NO3 nighttime chemistry (purple) and anthropogenic SOA(yellow) Each plot (starting with green) is additive (equal to thatprocess plus the sum of the processes below it) for example thepurple plot shows the contributions from primary OA biogenicSOA from OH and O3 and biogenic SOA+ NO3 Biogenic SOA(both day and night) are the largest contributors to TOA but an-thropogenic species (yellow) also make a significant contribution

boundary layer) Daytime aerosol mass loadings contributemuch more to the regional aerosol mass due to the combina-tion of the higher mass loadings and fully developed bound-ary layer (2 microg mminus3 corresponds to 4000 microg mminus2 in a 2 kmdaytime boundary layer a 40-fold increase column height)

Small particle events (see Sect 33) were correlated withelevated SO2 concentrations Figure 13 shows the onset andsubsequent growth of particles at the site during one of theseevents (29 July 2011) as observed (panel a) and the corre-sponding WRF-Chem simulation (panel b) Model results in-dicate that initial particle formation is triggered by anthro-pogenic SO2 whereas subsequent particle growth is drivenby condensation of BVOC oxidation products (Cui et al2014) as discussed in Sect 33 Growth rates were calculatedusing the number mean diameter defined by (Matsui et al2011)

NMD =

sumi Dpi times Nisum

i Ni

(1)

whereDpi andNi are the diameter (nm) and number concen-tration respectively The model simulations estimated thatthe average particle growth rates during these events (from4 to 40 nm mobility diameter) were 34 nm hminus1 The ob-served values calculated from SMPS measurements (aver-age= 20 nm hminus1) are less than the simulated values but inreasonable agreement with other reports from forested re-

Figure 1329 July 2011 particle size distributions observed(a) andmodeled with WRF-Chem(b) White areas in(a) indicate that nocounts were observed for that diameter particle at that time(c)shows the observed (black) and predicted (red) CCN concentrationsaveraged over the 10ndash15 August 2011 time period The blue circlesare the simulations when nucleation is not included which demon-strates the importance of particle nucleation for CCN formation

gions in Indiana USA (25 nm hminus1 Pryor et al 2010) andFinland (29 nm hminus1 Jaatinen et al 2009) It should also benoted that there is considerable variability in reported growthrates and this value is highly dependent upon the chosen di-ameter range

The impact of biogenic aerosols on clouds and precipita-tion was also investigated as part of the BEACHON projectFigure 13c shows the effect of new particle formation oncloud condensation nuclei (CCN) concentrations at the siteduring 5 days in August 2011 The observed CCN con-centrations are compared with the predicted values com-puted with and without accounting for new particle forma-tion in the model These results show that modeled CCNconcentration predictions (at 05 supersaturation) signifi-cantly underpredict the actual measured concentrations un-less nucleation is taken into account This demonstrates theimportance of aerosol nucleation to accurately parameterizeaerosolndashcloud interactions In future climate scenarios it hasbeen hypothesized that warmer temperatures (and potentiallyhigher biogenic emissions) could have a negative climatefeedback (Paasonen et al 2013) This is because more ox-idation products from BVOC emissions will be available forcondensation resulting in higher CCN concentrations andconsequently increased cloud cover Other regional modelingefforts utilizing BEACHON-ROCS and RoMBAS data arestill underway to explore a variety of bio-hydro-atmosphererelationships



5 Key findings from 2008ndash2011 field campaigns

The Manitou Experimental Forest Observatory has hostedthree multi-investigator intensive measurement campaignseach designed to focus on specific aspects of bio-hydro-atmosphere interactions Measurements made during theBEACHON-SRM08 (Southern Rocky Mountains 2008)study provided an initial characterization of the site pro-vided data (specifically aerosol number and mass concentra-tions CCN and hygroscopicity) for evaluation of regional-scale model simulations examining aerosolndashcloud interac-tions and enabled the identification of key scientific ques-tions that could be addressed during subsequent field cam-paigns The 2010 BEACHON-ROCS (Rocky Mountain Or-ganic Carbon) study focused on BVOC oxidation and as-sociated implications for oxidant cycling and distributionsThe results showed that while there are compounds in theambient air not typically measured by standard techniquesthere is evidence that missing OH sinks are associated withoxidation products of known BVOC rather than primaryemissions of unknown BVOC The study also demonstratedthat considerable BVOC oxidation takes place within thecanopy air space The following year (2011) the BEACHON-RoMBAS (Rocky Mountain Biogenic Aerosol Study) tookplace to characterize a multitude of aerosol processes at thesite and incorporate the findings from the gas-phase measure-ments of BEACHON-ROCS into modeling efforts Amongthe many measurements performed were IN CCN particlesize distributions chemical speciation of bulk aerosol andsmall (lt 30 nm) particles gas- and particle-phase partition-ing black carbon elemental organic carbon (EC OC) ra-tios gas-phase nitrate and NOx and supermicron biologi-cal particles This campaign also included many of the samegas-phase measurements from 2010 to further characterizeBVOC emissions oxidant levels and oxidation productsMany of the long-term seasonal observations (see Table S1in the Supplement) have been valuable in characterizing thesite and for interpreting measurements taken during the in-tensive measurement campaigns Table S2 in the Supplementlists the publication results from the past 5 years based onMEFO observations Future investigations and data analysisfrom past measurements are expected to result in further pub-lications additional observations and more collaborative re-search This is not intended to be an exhaustive list but ratherprovide context for the research site and further informationfor past present and future researchers

6 Conclusions

Observations at the Manitou Experimental Forest Obser-vatory have provided important data for understandingterrestrialndashatmosphere interactions in a semi-arid ponderosapine forest that is typical of the Colorado Front Range urbanndashrural interface Studies of biogenic emissions and their influ-

ence on gas-phase chemistry aerosol properties and cloudcondensation nuclei have led to a number of interesting con-clusions ndash some of which have been summarized hereinHigh-frequency turbulence measurements coupled with cor-responding CO2 water and energy fluxes at the site are nowbeing incorporated into the land-surface schemes of climatemodels to more accurately represent canopy influences Theunique observational data are available for other model pa-rameterization and evaluation studies The infrastructure ex-ists to enable additional measurements and future scientificmeasurement campaigns as well as for testing new instru-ments measurement intercomparisons graduate and under-graduate student development and other studies involvingterrestrialndashatmospheric exchange processes MEFO is a col-laborative facility that is maintained through a cooperativeagreement between NCAR and the USDA Forest Service andis available to the scientific community for training modeldevelopment and evaluation and scientific discovery

The Supplement related to this article is available onlineat doi105194acp-14-6345-2014-supplement

AcknowledgementsThe authors would like to acknowledgegenerous field support from Richard Oakes (USDA ForestService Manitou Experimental Forest Site Manager) Authorsfrom Colorado State University were supported through NSFgrant ATM-0919042 Authors from the University of Coloradowere supported by NSF grant ATM-0919189 and United StatesDepartment of Energy grant DE-SC0006035 Authors from theNational Center for Atmospheric Research were supported byNSF grant ATM-0919317 and US Department of Energy grantDE-SC00006861 T Karl was also supported by the EC SeventhFramework Programme (Marie Curie Reintegration programldquoALP-AIRrdquo grant no 334084) S C Pryor (Indiana University)was supported by NSF ATM-1102309 Authors from the Universityof Innsbruck were supported by the Austrian Science Fund (FWF)under project number L518-N20 L Kaser was also supportedby a DOC-fFORTE fellowship of the Austrian Academy ofScience Authors from the University of Wisconsin-Madison weresupported by NSF grant ATM-0852406 the BEACHON projectand NASA-SBIR Phase I amp II funding Contributions from LosAlamos National Laboratory (LANL) were funded by the UnitedStates Department of Energyrsquos Atmospheric System Research(project F265 KP1701 M K Dubey as principal investigator)A C Aiken also thanks LANL ndash Laboratory Directed Research andDevelopment for a directorrsquos postdoctoral fellowship award Theauthors would also like to acknowledge substantial participationand input from the Max Planck Institute for Chemistry (MPICMainz Germany) which was funded by the Max Planck Society(MPG) and the Geocycles Cluster Mainz (LEC Rheinland-Pfalz)J A Huffman acknowledges internal faculty support from theUniversity of Denver The United States Environmental ProtectionAgency (EPA) through its Office of Research and Developmentcollaborated in the research described here The manuscript hasbeen subjected to peer review and has been cleared for publicationby the EPA Mention of trade names or commercial products



does not constitute endorsement or recommendation for useThe National Center for Atmospheric Research is sponsored bythe National Science Foundation Any opinions findings andconclusions or recommendations expressed in the publication arethose of the authors and do not necessarily reflect the views of theNational Science Foundation or the US Environmental ProtectionAgency

Edited by R Holzinger

References

Allen C D Macalady A K Chenchouni H Bachelet D Mc-Dowell N Vennetier M Kitzberger T Rigling A Bres-hears D D Hogg E H Gonzalez P Fensham R ZhangZ Castro J Demidova N Lim J H Allard G Run-ning S W Semerci A and Cobb N A global overview ofdrought and heat-induced tree mortality reveals emerging cli-mate change risks for forests Forest Ecol Manag 259 660ndash684 doi101016jforeco200909001 2010

Almeida J Schobesberger S Kurten A Ortega I KKupiainen-Maatta O Praplan A P Adamov A Amorim ABianchi F Breitenlechner M David A Dommen J Don-ahue N M Downard A Dunne E Duplissy J EhrhartS Flagan R C Franchin A Guida R Hakala J HanselA Heinritzi M Henschel H Jokinen T Junninen H Ka-jos M Kangasluoma J Keskinen H Kupc A Kurten TKvashin A N Laaksonen A Lehtipalo K Leiminger MLeppa J Loukonen V Makhmutov V Mathot S McGrathM J Nieminen T Olenius T Onnela A Petaja T Ric-cobono F Riipinen I Rissanen M Rondo L RuuskanenT Santos F D Sarnela N Schallhart S Schnitzhofer RSeinfeld J H Simon M Sipila M Stozhkov Y StratmannF Tome A Trostl J Tsagkogeorgas G Vaattovaara P Vi-isanen Y Virtanen A Vrtala A Wagner P E WeingartnerE Wex H Williamson C Wimmer D Ye P L Yli-JuutiT Carslaw K S Kulmala M Curtius J Baltensperger UWorsnop D R Vehkamaki H and Kirkby J Molecular under-standing of sulphuric acid-amine particle nucleation in the atmo-sphere Nature 502 359ndash363 doi101038nature12663 2013

Alo C A and Wang G L Hydrological impact of the po-tential future vegetation response to climate changes pro-jected by 8 GCMs J Geophys Res-Biogeo 113 G03011doi1010292007jg000598 2008

Andreae M O and Rosenfeld D Aerosol-cloud-precipitation interactions Part 1 The nature and sourcesof cloud-active aerosols Earth Sci Rev 89 13ndash41doi101016jearscirev200803001 2008

Apel E C Emmons L K Karl T Flocke F Hills A JMadronich S Lee-Taylor J Fried A Weibring P WalegaJ Richter D Tie X Mauldin L Campos T Weinheimer AKnapp D Sive B Kleinman L Springston S Zaveri R Or-tega J Voss P Blake D Baker A Warneke C Welsh-BonD de Gouw J Zheng J Zhang R Rudolph J JunkermannW and Riemer D D Chemical evolution of volatile organiccompounds in the outflow of the Mexico City Metropolitan areaAtmos Chem Phys 10 2353ndash2375 doi105194acp-10-2353-2010 2010

Barth M McFadden J P Sun J L Wiedinmyer C ChuangP Collins D Griffin R Hannigan M Karl T Kim S WLasher-Trapp S Levis S Litvak M Mahowald N MooreK Nandi S Nemitz E Nenes A Potosnak M RaymondT M Smith J Still C and Stroud C Coupling between landecosystems and the atmospheric hydrologic cycle through bio-genic aerosol pathways B Am Meterol Soc 86 1738ndash1742doi101175bams-86-12-1738 2005

Battaglia M A Rocca M E Rhoades C C and Ryan MG Surface fuel loadings within mulching treatments in Col-orado coniferous forests Forest Ecol Manag 260 1557ndash1566doi101016jforeco201008004 2010

Beier C Beierkuhnlein C Wohlgemuth T Penuelas J Em-mett B Korner C de Boeck H J Christensen J HLeuzinger S Janssens I A and Hansen K Precipitationmanipulation experiments ndash challenges and recommendationsfor the future Ecol Lett 15 899ndash911 doi101111j1461-0248201201793x 2012

Bench G Fallon S Schichtel B Malm W and McDade CRelative contributions of fossil and contemporary carbon sourcesto PM25 aerosols at nine Interagency Monitoring for Protectionof Visual Environments (IMPROVE) network sites J GeophysRes-Atmos 112 D10205 doi1010292006jd007708 2007

Burgess S S O Adams M A Turner N C Beverly C R OngC K Khan A A H and Bleby T M An improved heat pulsemethod to measure low and reverse rates of sap flow in woodyplants Tree Physiol 21 589ndash598 2001

Carslaw K S Boucher O Spracklen D V Mann G W RaeJ G L Woodward S and Kulmala M A review of natu-ral aerosol interactions and feedbacks within the Earth systemAtmos Chem Phys 10 1701ndash1737 doi105194acp-10-1701-2010 2010

Cerully K M Raatikainen T Lance S Tkacik D Tiitta PPetaumljauml T Ehn M Kulmala M Worsnop D R LaaksonenA Smith J N and Nenes A Aerosol hygroscopicity and CCNactivation kinetics in a boreal forest environment during the 2007EUCAARI campaign Atmos Chem Phys 11 12369ndash12386doi105194acp-11-12369-2011 2011

Constantinidou H A Hirano S S Baker L S and Upper C DAtmospheric dispersal of ice nucleation-active bacteria The roleof rain Phytopathology 80 934ndash937 1990

Cui Y Y Hodzic A Smith J N Ortega J Brioude J Mat-sui H Turnipseed A Winkler P and de Foy B Modelingultrafine particle growth at a pine forest site influenced by an-thropogenic pollution during BEACHON-RoMBAS 2011 At-mos Chem Phys Discuss 14 5611ndash5651 doi105194acpd-14-5611-2014 2014

Day D A Wooldridge P J and Cohen R C Observations ofthe effects of temperature on atmospheric HNO3 6ANs6PNsand NOx evidence for a temperature-dependent HOx source At-mos Chem Phys 8 1867ndash1879 doi105194acp-8-1867-20082008

Day D A Wooldridge P J Dillon M B Thornton J A andCohen R C A thermal dissociation laser-induced fluorescenceinstrument for in situ detection of NO2 peroxy nitrates alkylnitrates and HNO3 J Geophys Res-Atmos 107 ACH 4-1ndashACH 4-14 doi1010292001jd000779 2002

DeCarlo P F Kimmel J R Trimborn A Northway M J JayneJ T Aiken A C Gonin M Fuhrer K Horvath T Docherty



K S Worsnop D R and Jimenez J L Field-deployablehigh-resolution time-of-flight aerosol mass spectrometer AnalChem 78 8281ndash8289 doi101021ac061249n 2006

DeMott P J and Prenni A J New Directions Need fordefining the numbers and sources of biological aerosolsacting as ice nuclei Atmos Environ 44 1944ndash1945doi101016jatmosenv201002032 2010

DeMott P J Prenni A J Liu X Kreidenweis S M PettersM D Twohy C H Richardson M S Eidhammer T andRogers D C Predicting global atmospheric ice nuclei distribu-tions and their impacts on climate P Natl USA 107 11217ndash11222 doi101073pnas0910818107 2010

Denman K L Brasseur G Chidthaisong A Ciais P Cox PM Dickinson R E Hauglustaine D Heinze C Holland EJacob D Lohmann U Ramachandran S da Silva Dias P LWofsy S C and Zhang X Couplings Between Changes in theClimate System and Biogeochemistry in Climate Change 2007The Physical Science Basis Contribution of Working Group Ito the Fourth Assessment Report of the Intergovernmental Panelon Climate Change edited by Solomon S Qin D ManningM Chen Z Marquis M Averyt K B Tignor M and MillerH L Cambridge University Press Cambridge United Kingdomand New York NY USA 2007

DiGangi J P Boyle E S Karl T Harley P Turnipseed AKim S Cantrell C Maudlin III R L Zheng W Flocke FHall S R Ullmann K Nakashima Y Paul J B Wolfe GM Desai A R Kajii Y Guenther A and Keutsch F NFirst direct measurements of formaldehyde flux via eddy covari-ance implications for missing in-canopy formaldehyde sourcesAtmos Chem Phys 11 10565ndash10578 doi105194acp-11-10565-2011 2011

DiGangi J P Henry S B Kammrath A Boyle E S Kaser LSchnitzhofer R Graus M Turnipseed A Park J-H WeberR J Hornbrook R S Cantrell C A Maudlin III R L KimS Nakashima Y Wolfe G M Kajii Y Apel EC GoldsteinA H Guenther A Karl T Hansel A and Keutsch F N Ob-servations of glyoxal and formaldehyde as metrics for the anthro-pogenic impact on rural photochemistry Atmos Chem Phys12 9529ndash9543 doi105194acp-12-9529-2012 2012

Edwards G D Cantrell C A Stephens S Hill B GoyeaO Shetter R E Mauldin R L Kosciuch E Tanner D Jand Eisele F L Chemical ionization mass spectrometer instru-ment for the measurement of tropospheric HO2 and RO2 AnalChem 75 5317ndash5327 doi101021ac034402b 2003

Elbert W Taylor P E Andreae M O and Poumlschl U Contribu-tion of fungi to primary biogenic aerosols in the atmosphere wetand dry discharged spores carbohydrates and inorganic ions At-mos Chem Phys 7 4569ndash4588 doi105194acp-7-4569-20072007

Eller A S D Harley P and Monson R K Potential contribu-tion of exposed resin to ecosystem emissions of monoterpenesAtmos Environ 77 440ndash444 2013

Farmer D K and Cohen R C Observations of HNO3 6AN6PN and NO2 fluxes evidence for rapid HOx chemistry withina pine forest canopy Atmos Chem Phys 8 3899ndash3917doi105194acp-8-3899-2008 2008

Fast J D Gustafson W I Easter R C Zaveri R A BarnardJ C Chapman E G Grell G A and Peckham S E Evo-lution of ozone particulates and aerosol direct radiative forcing

in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model J Geophys Res-Atmos 111 D21305doi1010292005jd006721 2006

Fornwalt P J Kaufmann M R and Stohlgren T J Impactsof mixed severity wildfire on exotic plants in a Colorado pon-derosa pine-Douglas-fir forest Biol Invasions 12 2683ndash2695doi101007s10530-009-9674-2 2010

Fry J L Draper D C Zarzana K J Campuzano-Jost P DayD A Jimenez J L Brown S S Cohen R C Kaser LHansel A Cappellin L Karl T Hodzic Roux A TurnipseedA Cantrell C Lefer B L and Grossberg N Observations ofgas- and aerosol-phase organic nitrates at BEACHON-RoMBAS2011 Atmos Chem Phys 13 8585ndash8605 doi105194acp-13-8585-2013 2013

Gary H L A summary of research at the Manitou ExperimentalForest in Colorado 1937ndash1983 US Department of AgricultureForest Service Publication Rocky Mountain Forest and RangeExperiment Station Fort Collins CO 1985

Geron C Carbonaceous aerosol over a Pinus taeda forest inCentral North Carolina USA Atmos Environ 43 959ndash969doi101016jatmosenv200810053 2009

Geron C Carbonaceous aerosol characteristics over a Pinus taedaplantation Results from the CELTIC experiment Atmos Envi-ron 45 794ndash801 doi101016jatmosenv201007015 2011

Greenberg J P Asensio D Turnipseed A Guenther A BKarl T and Gochis D Contribution of leaf and needle litter towhole ecosystem BVOC fluxes Atmos Environ 59 302ndash311doi101016jatmosenv201204038 2012

Grell G A Peckham S E Schmitz R McKeen S A Frost GSkamarock W C and Elder B Fully coupled ldquoonlinerdquo chem-istry within the WRF model Atmos Environ 39 6957ndash6975doi101016jatmosenv200504027 2005

Guenther A Kulmala M Turnipseed A Rinne J Suni T andReissell A Integrated land ecosystem-atmosphere processesstudy (iLEAPS) assessment of global observational networksBoreal Environ Res 16 321ndash336 2011

Gunthe S S King S M Rose D Chen Q Roldin P FarmerD K Jimenez J L Artaxo P Andreae M O Martin ST and Poumlschl U Cloud condensation nuclei in pristine tropi-cal rainforest air of Amazonia size-resolved measurements andmodeling of atmospheric aerosol composition and CCN activityAtmos Chem Phys 9 7551ndash7575 doi105194acp-9-7551-2009 2009

Harley P Fridd-Stroud V Greenberg J Guenther A andVasconcellos P Emission of 2-methyl-3-buten-2-ol by pinesA potentially large natural source of reactive carbon tothe atmosphere J Geophys Res-Atmos 103 25479ndash25486doi10102998jd00820 1998

Heald C L Wilkinson M J Monson R K Alo C A Wang GL and Guenther A Response of isoprene emission to ambientCO2 changes and implications for global budgets Glob ChangeBiol 15 1127ndash1140 doi101111j1365-2486200801802x2009

Hodzic A and Jimenez J L Modeling anthropogenically con-trolled secondary organic aerosols in a megacity a simplifiedframework for global and climate models Geosci Model Dev4 901ndash917 doi105194gmd-4-901-2011 2011

Hofzumahaus A Rohrer F Lu K D Bohn B Brauers TChang C C Fuchs H Holland F Kita K Kondo Y Li



X Lou S R Shao M Zeng L M Wahner A and Zhang YH Amplified Trace Gas Removal in the Troposphere Science324 1702ndash1704 doi101126science1164566 2009

Hornbrook R S Crawford J H Edwards G D Goyea OMauldin III R L Olson J S and Cantrell C A Measure-ments of tropospheric HO2 and RO2 by oxygen dilution modu-lation and chemical ionization mass spectrometry Atmos MeasTech 4 735ndash756 doi105194amt-4-735-2011 2011

Hottle J R Huisman A J Digangi J P Kammrath A Gal-loway M M Coens K L and Keutsch F N A Laser InducedFluorescence-Based Instrument for In-Situ Measurements of At-mospheric Formaldehyde Environ Sci Technol 43 790ndash795doi101021es801621f 2009

Huffman J A Prenni A J DeMott P J Poumlhlker C Mason RH Robinson N H Froumlhlich-Nowoisky J Tobo Y DespreacutesV R Garcia E Gochis D J Harris E Muumlller-Germann IRuzene C Schmer B Sinha B Day D A Andreae M OJimenez J L Gallagher M Kreidenweis S M Bertram AK and Poumlschl U High concentrations of biological aerosol par-ticles and ice nuclei during and after rain Atmos Chem Phys13 6151ndash6164 doi105194acp-13-6151-2013 2013

Huisman A J Hottle J R Coens K L DiGangi J PGalloway M M Kammrath A and Keutsch F N Laser-induced phosphorescence for the in situ detection of glyoxalat part per trillion mixing ratios Anal Chem 80 5884ndash5891doi101021ac800407b 2008

Jaatinen A Hamed A Joutsensaari J Mikkonen S Birmili WWehner B Spindler G Wiedensohler A Decesari S MirceaM Facchini M C Junninen H Kulmala M Lehtinen K EJ and Laaksonen A A comparison of new particle formationevents in the boundary layer at three different sites in EuropeBoreal Environ Res 14 481ndash498 2009

Jones A M and Harrison R M The effects of meteo-rological factors on atmospheric bioaerosol concentra-tions ndash a review Sci Total Environ 326 151ndash180doi101016jscitotenv200311021 2004

Karl T Potosnak M Guenther A Clark D Walker J Her-rick J D and Geron C Exchange processes of volatile organiccompounds above a tropical rain forest Implications for model-ing tropospheric chemistry above dense vegetation J GeophysRes-Atmos 109 D18306 doi1010292004jd004738 2004

Karl T Hansel A Cappellin L Kaser L Herdlinger-BlattI and Jud W Selective measurements of isoprene and 2-methyl-3-buten-2-ol based on NO+ ionization mass spectrom-etry Atmos Chem Phys 12 11877ndash11884 doi105194acp-12-11877-2012 2012

Karl T Kaser L and Turnipseed A Eddy covariance measure-ments of isoprene and 232-MBO based on NO+ time-of-flightmass spectrometry Int J Mass Spectrom 365ndash366 15ndash192014

Kaser L Karl T Schnitzhofer R Graus M Herdlinger-BlattI S DiGangi J P Sive B Turnipseed A Hornbrook R SZheng W Flocke F M Guenther A Keutsch F N Apel Eand Hansel A Comparison of different real time VOC measure-ment techniques in a ponderosa pine forest Atmos Chem Phys13 2893ndash2906 doi105194acp-13-2893-2013 2013a

Kaser L Karl T Guenther A Graus M Schnitzhofer RTurnipseed A Fischer L Harley P Madronich M GochisD Keutsch F N and Hansel A Undisturbed and disturbed

above canopy ponderosa pine emissions PTR-TOF-MS mea-surements and MEGAN 21 model results Atmos Chem Phys13 11935ndash11947 doi105194acp-13-11935-2013 2013b

Kim S Wolfe G M Mauldin L Cantrell C Guenther A KarlT Turnipseed A Greenberg J Hall S R Ullmann K ApelE Hornbrook R Kajii Y Nakashima Y Keutsch F N Di-Gangi J P Henry S B Kaser L Schnitzhofer R GrausM Hansel A Zheng W and Flocke F F Evaluation of HOxsources and cycling using measurement-constrained model cal-culations in a 2-methyl-3-butene-2-ol (MBO) and monoterpene(MT) dominated ecosystem Atmos Chem Phys 13 2031ndash2044 doi105194acp-13-2031-2013 2013

Kirkby J Curtius J Almeida J Dunne E Duplissy J EhrhartS Franchin A Gagne S Ickes L Kurten A Kupc A Met-zger A Riccobono F Rondo L Schobesberger S Tsagko-georgas G Wimmer D Amorim A Bianchi F Breitenlech-ner M David A Dommen J Downard A Ehn M Fla-gan R C Haider S Hansel A Hauser D Jud W Junni-nen H Kreissl F Kvashin A Laaksonen A Lehtipalo KLima J Lovejoy E R Makhmutov V Mathot S Mikkila JMinginette P Mogo S Nieminen T Onnela A Pereira PPetaja T Schnitzhofer R Seinfeld J H Sipila M StozhkovY Stratmann F Tome A Vanhanen J Viisanen Y VrtalaA Wagner P E Walther H Weingartner E Wex H Win-kler P M Carslaw K S Worsnop D R Baltensperger Uand Kulmala M Role of sulphuric acid ammonia and galac-tic cosmic rays in atmospheric aerosol nucleation Nature 476429ndashU477 doi101038nature10343 2011

Kleindienst T E Jaoui M Lewandowski M Offenberg J HLewis C W Bhave P V and Edney E O Estimates of thecontributions of biogenic and anthropogenic hydrocarbons tosecondary organic aerosol at a southeastern US location AtmosEnviron 41 8288ndash8300 doi101016jatmosenv2007060452007

Korhonen H Lehtinen K E J and Kulmala M Multicompo-nent aerosol dynamics model UHMA model development andvalidation Atmos Chem Phys 4 757ndash771 doi105194acp-4-757-2004 2004

Kulmala M Riipinen I Sipila M Manninen H E PetajaT Junninen H Dal Maso M Mordas G Mirme A VanaM Hirsikko A Laakso L Harrison R M Hanson I Le-ung C Lehtinen K E J and Kerminen V M Toward directmeasurement of atmospheric nucleation Science 318 89ndash92doi101126science1144124 2007

Kurpius M R and Goldstein A H Gas-phase chemistry domi-nates O-3 loss to a forest implying a source of aerosols and hy-droxyl radicals to the atmosphere Geophys Res Lett 30 1371doi1010292002gl016785 2003

Lelieveld J Butler T M Crowley J N Dillon T J Fis-cher H Ganzeveld L Harder H Lawrence M G MartinezM Taraborrelli D and Williams J Atmospheric oxidationcapacity sustained by a tropical forest Nature 452 737ndash740doi101038nature06870 2008

Levin E J T Prenni A J Petters M D Kreidenweis S M Sul-livan R C Atwood S A Ortega J DeMott P J and Smith JN An annual cycle of size-resolved aerosol hygroscopicity at aforested site in Colorado J Geophys Res-Atmos 117 D06201doi1010292011jd016854 2012



Levin E J T Prenni A J Palm B B Day D A Campuzano-Jost P Winkler P M Kreidenweis S M DeMott P JJimenez J L and Smith J N Size-resolved aerosol composi-tion and its link to hygroscopicity at a forested site in ColoradoAtmos Chem Phys 14 2657ndash2667 doi105194acp-14-2657-2014 2014

Lewandowski M Piletic I R Kleindienst T E Offenberg J HBeaver M R Jaoui M Docherty K S and Edney E O Sec-ondary organic aerosol characterisation at field sites across theUnited States during the spring-summer period Int J EnvironAn Ch 93 1084ndash1103 doi1010800306731920138035452013

Lewis C W Klouda G A and Ellenson W D Radiocar-bon measurement of the biogenic contribution to summertimePM-25 ambient aerosol in Nashville TN Atmos Environ 386053ndash6061 doi101016jatmosenv200406011 2004

Lezberg A L Battaglia M A Shepperd W D and Schoet-tle A W Decades-old silvicultural treatments influence sur-face wildfire severity and post-fire nitrogen availability ina ponderosa pine forest Forest Ecol Manag 255 49ndash61doi101016jforeco200708019 2008

Linkhart B D and Reynolds R T Lifetime reproduction ofFlammulated Owls in Colorado J Raptor Res 40 29ndash37doi1033560892-1016(2006)40[29lrofoi]20co2 2006

Linkhart B D and Reynolds R T Return rate fidelityand dispersal in a breeding population of flammulated owls(Otus flammeolus) Auk 124 264ndash275 doi1016420004-8038(2007)124[264rrfadi]20co2 2007

Mahowald N Ward D S Kloster S Flanner M G HealdC L Heavens N G Hess P G Lamarque J F andChuang P Y Aerosol Impacts on Climate and Biogeochem-istry Annu Rev Env Resour 36 45ndash74 doi101146annurev-environ-042009-094507 2011

Mao J Ren X Zhang L Van Duin D M Cohen R C ParkJ-H Goldstein A H Paulot F Beaver M R Crounse JD Wennberg P O DiGangi J P Henry S B Keutsch FN Park C Schade G W Wolfe G M Thornton J A andBrune W H Insights into hydroxyl measurements and atmo-spheric oxidation in a California forest Atmos Chem Phys 128009ndash8020 doi105194acp-12-8009-2012 2012

Massman W J Frank J M and Mooney S J Advancing inves-tigation and physical modeling of first-order fire effects on soilsFire Ecology 6 36ndash54 doi104996fireecology0601036 2010

Matsui H Koike M Kondo Y Takegawa N Wiedensohler AFast J D and Zaveri R A Impact of new particle forma-tion on the concentrations of aerosols and cloud condensationnuclei around Beijing J Geophys Res-Atmos 116 D19208doi1010292011jd016025 2011

Mauldin R L Eisele F L Cantrell C A Kosciuch E RidleyB A Lefer B Tanner D J Nowak J B Chen G WangL and Davis D Measurements of OH aboard the NASA P-3during PEM-Tropics B J Geophys Res-Atmos 106 32657ndash32666 doi1010292000jd900832 2001

Mirme S Mirme A Minikin A Petzold A Hotilderrak U Ker-minen V -M and Kulmala M Atmospheric sub-3 nm par-ticles at high altitudes Atmos Chem Phys 10 437ndash451doi105194acp-10-437-2010 2010

Morris C E Conen F Huffman J A Phillips V Poumlschl U andSands D C Bioprecipitation A feedback cycle linking Earth

history ecosystem dynamics and land use through biological icenucleators in the atmosphere Global Change Biol 20 341ndash351doi101111gcb12447 2013

Moteki N Kondo Y and Nakamura S Method to measure re-fractive indices of small nonspherical particles Application toblack carbon particles J Aerosol Sci 41 513ndash521 2010

Orlando J J and Tyndall G S Laboratory studies of organic per-oxy radical chemistry an overview with emphasis on recent is-sues of atmospheric significance Chem Soc Rev 41 8213ndash8213 2012

Paasonen P Asmi A Petaja T Kajos M K Aijala M Jun-ninen H Holst T Abbatt J P D Arneth A Birmili Wvan der Gon H D Hamed A Hoffer A Laakso L Laakso-nen A Leaitch W R Plass-Dulmer C Pryor S C RaisanenP Swietlicki E Wiedensohler A Worsnop D R KerminenV M and Kulmala M Warming-induced increase in aerosolnumber concentration likely to moderate climate change NatGeosci 6 438ndash442 doi101038ngeo1800 2013

Peeters J Nguyen T L and Vereecken L HOx radical regen-eration in the oxidation of isoprene Phys Chem Chem Phys11 5935ndash5939 101039b908511d 2009

Petters M D and Kreidenweis S M A single parameter repre-sentation of hygroscopic growth and cloud condensation nucleusactivity Atmos Chem Phys 7 1961ndash1971 doi105194acp-7-1961-2007 2007

Poumlhlker C Wiedemann K T Sinha B Shiraiwa M Gun-the S S Smith M Su H Artaxo P Chen Q ChengY F Elbert W Gilles M K Kilcoyne A L D MoffetR C Weigand M Martin S T Poeschl U and AndreaeM O Biogenic Potassium Salt Particles as Seeds for Sec-ondary Organic Aerosol in the Amazon Science 337 1075ndash1078 doi101126science1223264 2012

Poumlschl U Martin S T Sinha B Chen Q Gunthe S SHuffman J A Borrmann S Farmer D K Garland R MHelas G Jimenez J L King S M Manzi A MikhailovE Pauliquevis T Petters M D Prenni A J Roldin PRose D Schneider J Su H Zorn S R Artaxo P andAndreae M O Rainforest Aerosols as Biogenic Nuclei ofClouds and Precipitation in the Amazon Science 329 1513ndash1516 doi101126science1191056 2010

Prenni A J Tobo Y Garcia E DeMott P J Huffman J AMcCluskey C S Kreidenweis S M Prenni J E Pohlker Cand Poschl U The impact of rain on ice nuclei populations ata forested site in Colorado Geophys Res Lett 40 227ndash231doi1010292012gl053953 2013

Pryor S C Barthelmie R J and Hornsby K E Size-resolvedparticle fluxes and vertical gradients over and in a sparse pineforest Aerosol Sci Tech 47 1248ndash1257 2013

Pryor S C Spaulding A M and Barthelmie R J New particleformation in the Midwestern USA Event characteristics me-teorological context and vertical profiles Atmos Environ 444413ndash4425 doi101016jatmosenv201007045 2010

Rhoades C C Battaglia M A Rocca M E and RyanM G Short- and medium-term effects of fuel reduc-tion mulch treatments on soil nitrogen availability in Col-orado conifer forests Forest Ecol Manag 276 231ndash238doi101016jforeco201203028 2012

Rollins A W Smith J D Wilson K R and Cohen RC Real Time In Situ Detection of Organic Nitrates in At-



mospheric Aerosols Environ Sci Technol 44 5540ndash5545doi101021es100926x 2010

Schobesberger S Vaananen R Leino K Virkkula A BackmanJ Pohja T Siivola E Franchin A Mikkila J ParamonovM Aalto P P Krejci R Petaja T and Kulmala M Airbornemeasurements over the boreal forest of southern Finland duringnew particle formation events in 2009 and 2010 Boreal EnvironRes 18 145ndash163 2013

Schumacher C J Poumlhlker C Aalto P Hiltunen V Petaumljauml TKulmala M Poumlschl U and Huffman J A Seasonal cyclesof fluorescent biological aerosol particles in boreal and semi-arid forests of Finland and Colorado Atmos Chem Phys 1311987ndash12001 doi105194acp-13-11987-2013 2013

Shrivastava M Fast J Easter R Gustafson Jr W I Zaveri RA Jimenez J L Saide P and Hodzic A Modeling organicaerosols in a megacity comparison of simple and complex rep-resentations of the volatility basis set approach Atmos ChemPhys 11 6639ndash6662 doi105194acp-11-6639-2011 2011

Soil Conservation Service Soil Survey of Pike National ForestEastern Part Colorado Parts of Douglas El Paso Jefferson andTeller Counties United States Department of Agriculture ForestService and Soil Conservation Service 106 pp 1992

Stone D Whalley L K and Heard D E Tropospheric OHand HO2 radicals field measurements and model comparisonsChem Soc Rev 41 6348ndash6404 101039c2cs35140d 2012

Thornton J A Wooldridge P J Cohen R C Martinez MHarder H Brune W H Williams E J Roberts J M Fehsen-feld F C Hall S R Shetter R E Wert B P and Fried AOzone production rates as a function of NOx abundances andHOx production rates in the Nashville urban plume J GeophysRes 107 4146ndash4163 doi1010292001JD000932 2002

Tobo Y Prenni A J DeMott P J Huffman J A McCluskey CS Tian G Poumlhlker C Poumlschl U Kreidenweis S M Biolog-ical aerosol particles as a key determinant of ice nuclei popula-tions in a forest ecosystem J Geophys Res-Atmos 118 10100ndash10110 doi101002jgrd50801 2013

Vorosmarty C J McIntyre P B Gessner M O Dudgeon DPrusevich A Green P Glidden S Bunn S E Sullivan CA Liermann C R and Davies P M Global threats to hu-man water security and river biodiversity Nature 467 555ndash561doi101038nature09440 2010

Williams B J Jayne J T Lambe A T Hohaus T Kimmel JR Sueper D Brooks W WilliamsL R Trimborn A MMartinez R E HayesP L Jimenez J L Kreisberg N MHering S V Worton D R Goldstein A H and Worsnop DR The First Combined Thermal Desorption Aerosol Gas Chro-matograph ndash Aerosol Mass Spectrometer (TAG-AMS) AerosolSci Tech 48 358370 doi1010800278682620138751142014

Wolfe G M Thornton J A Bouvier-Brown N C Goldstein AH Park J-H McKay M Matross D M Mao J Brune WH LaFranchi B W Browne E C Min K-E WooldridgeP J Cohen R C Crounse J D Faloona I C Gilman JB Kuster W C de Gouw J A Huisman A and KeutschF N The Chemistry of Atmosphere-Forest Exchange (CAFE)Model ndash Part 2 Application to BEARPEX-2007 observationsAtmos Chem Phys 11 1269ndash1294 doi105194acp-11-1269-2011 2011

Wolfe G M Cantrell C Kim S Mauldin III R L Karl THarley P Turnipseed A Zheng W Flocke F Apel E CHornbrook R S Hall S R Ullmann K Henry S B Di-Gangi J P Boyle E S Kaser L Schnitzhofer R HanselA Graus M Nakashima Y Kajii Y Guenther A andKeutsch F N Missing peroxy radical sources within a summer-time ponderosa pine forest Atmos Chem Phys 14 4715ndash4732doi105194acp-14-4715-2014 2014

Yatavelli R L N Lopez-Hilfiker F Wargo J D Kimmel JR Cubison M J Bertram T H Jimenez J L Gonin MWorsnop D R and Thornton J A A Chemical IonizationHigh-Resolution Time-of-Flight Mass Spectrometer Coupled toa Micro Orifice Volatilization Impactor (MOVI-HRToF-CIMS)for Analysis of Gas and Particle-Phase Organic Species AerosolSci Tech 46 1313ndash1327 doi1010800278682620127122362012

Yatavelli R L N Stark H Thompson S L Kimmel J R Cubi-son M J Day D A Campuzano-Jost P Palm B B HodzicA Thornton J A Jayne J T Worsnop D R and Jimenez JL Semicontinuous measurements of gasndashparticle partitioning oforganic acids in a ponderosa pine forest using a MOVI-HRToF-CIMS Atmos Chem Phys 14 1527ndash1546 doi105194acp-14-1527-2014 2014

Zhang H F Worton D R Lewandowski M Ortega J Ru-bitschun C L Park J H Kristensen K Campuzano-Jost PDay D A Jimenez J L Jaoui M Offenberg J H Klein-dienst T E Gilman J Kuster W C de Gouw J Park CSchade G W Frossard A A Russell L Kaser L JudW Hansel A Cappellin L Karl T Glasius M GuentherA Goldstein A H Seinfeld J H Gold A Kamens RM and Surratt J D Organosulfates as Tracers for SecondaryOrganic Aerosol (SOA) Formation from 2-Methyl-3-Buten-2-ol(MBO) in the Atmosphere Environ Sci Technol 46 9437ndash9446 doi101021es301648z 2012

Zhao Y L Kreisberg N M Worton D R Teng A P HeringS V and Goldstein A H Development of an In Situ Ther-mal Desorption Gas Chromatography Instrument for QuantifyingAtmospheric Semi-Volatile Organic Compounds Aerosol SciTech 47 258ndash266 doi101080027868262012747673 2013



Correspondence toJ N Smith (jimsmithucaredu)

Received 23 November 2013 ndash Published in Atmos Chem Phys Discuss 20 January 2014Revised 30 April 2014 ndash Accepted 12 May 2014 ndash Published 26 June 2014

Abstract The Bio-hydro-atmosphere interactions of En-ergy Aerosols Carbon H2O Organics amp Nitrogen (BEA-CHON) project seeks to understand the feedbacks and inter-relationships between hydrology biogenic emissions carbonassimilation aerosol properties clouds and associated feed-backs within water-limited ecosystems The Manitou Exper-imental Forest Observatory (MEFO) was established in 2008by the National Center for Atmospheric Research to addressmany of the BEACHON research objectives and it now pro-vides a fixed field site with significant infrastructure MEFOis a mountainous semi-arid ponderosa pine-dominated forestsite that is normally dominated by clean continental air but isperiodically influenced by anthropogenic sources from Col-orado Front Range cities This article summarizes the pastand ongoing research activities at the site and highlightssome of the significant findings that have resulted from thesemeasurements These activities include

ndash soil property measurements

ndash hydrological studies

ndash measurements of high-frequency turbulence parame-ters

ndash eddy covariance flux measurements of water energyaerosols and carbon dioxide through the canopy

ndash determination of biogenic and anthropogenic volatileorganic compound emissions and their influence on re-gional atmospheric chemistry

ndash aerosol number and mass distributions

ndash chemical speciation of aerosol particles

ndash characterization of ice and cloud condensation nuclei

ndash trace gas measurements and

ndash model simulations using coupled chemistry and meteo-rology

In addition to various long-term continuous measurementsthree focused measurement campaigns with state-of-the-artinstrumentation have taken place since the site was estab-lished and two of these studies are the subjects of this specialissue BEACHON-ROCS (Rocky Mountain Organic CarbonStudy 2010) and BEACHON-RoMBAS (Rocky MountainBiogenic Aerosol Study 2011)

1 Introduction

11 Motivation

Development of Earth system models is driven by the needto improve the predictability of atmospheric chemical andphysical processes over timescales ranging from minutesto decades Accurate model predictions are contingent onprocess-level understanding and detailed numerical descrip-tions of the coupling between water energy and biogeochem-ical cycles across temporal and spatial scales (Denman et al2007 Alo and Wang 2008 Heald et al 2009) A number ofstudies have discussed some of these processes and associ-ated feedbacks (eg Barth et al 2005 Carslaw et al 2010Mahowald et al 2011) but more detailed observations andcoordinated modeling efforts are required for improved rep-resentation in Earth system models

The Bio-hydro-atmosphere interactions of EnergyAerosols Carbon H2O Organics amp Nitrogen (BEACHON)project was initiated by the National Center for AtmosphericResearch (NCAR) as well as research collaborators from theuniversity community to investigate ecosystemndashatmosphereexchange of trace gases and aerosols and their potentialfeedbacks between biogeochemical and water cyclesBEACHON is now an ongoing component of atmosphericresearch sponsored by the National Science FoundationThis interdisciplinary research program integrates local andregional model simulations with remote sensing regionalnetwork observations and canopy- to regional-scale fieldmeasurements BEACHON includes investigations of at-mospheric ecological and hydrological processes includingconcentration and flux measurements of energy CO2H2O volatile organic compounds aerosols nitrogen com-pounds hydrological parameters and feedback processesthat are relevant to atmospheric chemistry Rocky Mountainecosystems are important for providing water and otherresources in the western United States but contain only alimited number of long-term monitoring sites This region ispredominantly arid or semi-arid resulting in biogeochemicalcycles that are water limited Since the area contains someof the fastest growing population centers water limitations(combined with a climate that is projected to be warmerand potentially drier) pose significant societal vulnerabilities(Vorosmarty et al 2010) The regionrsquos remote complexterrain leads to highly variable ecosystem characteristicsand it is unclear how this variability affects hydrological andatmospheric processes across larger geographical areas Theneed for long-term landndashecosystemndashatmosphere observation



















A B

C

D E

i

300 m

MEFO

N

Woodland Park

CO

NM AZ

UT

WY

MT

Denver ~90 km


0 8 16 km

ND

SD

NE

KS

ii

iii N





































(a) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

50

100

150

200

250

300

350

(b) z = 28 m

90 180 270 360

0

500

1000

1500

2000

2500

(c) z = 2 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

(d) z = 2 m

90 180 270 360

0

200

400

600

800

1000

1200

Summer 2011

Daytime

Winter 2010-2011

Nighttime

(e) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

600

(f) z = 28 m

90 180 270 360

0

200

400

600

800

1000

1200

1400

1600

1800

2000

F0

0 0

0 0

D

BA

C

E

Summer 2010

Winter 2010-2011









000




600

200

0

400

500

300

100

2010 2012

2011 2013

2010-2013




0-10 cm 20-50 cm 70-150 cm


005

020

010

025

030

015

000

270

285

275

290

295

280

265

300

Pre

cip

itat

ion

(m

m)

Soil

mo

istu

re (

m3 m

-3)

Tem

pe

ratu

re (

K)













Hei

ght

[m]













4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)


1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0



Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]








A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References




































































































































A B

C

D E

i

300 m

MEFO

N

Woodland Park

CO

NM AZ

UT

WY

MT

Denver ~90 km


0 8 16 km

ND

SD

NE

KS

ii

iii N





































(a) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

50

100

150

200

250

300

350

(b) z = 28 m

90 180 270 360

0

500

1000

1500

2000

2500

(c) z = 2 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

(d) z = 2 m

90 180 270 360

0

200

400

600

800

1000

1200

Summer 2011

Daytime

Winter 2010-2011

Nighttime

(e) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

600

(f) z = 28 m

90 180 270 360

0

200

400

600

800

1000

1200

1400

1600

1800

2000

F0

0 0

0 0

D

BA

C

E

Summer 2010

Winter 2010-2011









000




600

200

0

400

500

300

100

2010 2012

2011 2013

2010-2013




0-10 cm 20-50 cm 70-150 cm


005

020

010

025

030

015

000

270

285

275

290

295

280

265

300

Pre

cip

itat

ion

(m

m)

Soil

mo

istu

re (

m3 m

-3)

Tem

pe

ratu

re (

K)













Hei

ght

[m]













4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)


1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0



Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]








A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References















































































































































(a) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

50

100

150

200

250

300

350

(b) z = 28 m

90 180 270 360

0

500

1000

1500

2000

2500

(c) z = 2 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

(d) z = 2 m

90 180 270 360

0

200

400

600

800

1000

1200

Summer 2011

Daytime

Winter 2010-2011

Nighttime

(e) z = 28 m

0 90 180 270 360

o

f S

am

ple

s

0

100

200

300

400

500

600

(f) z = 28 m

90 180 270 360

0

200

400

600

800

1000

1200

1400

1600

1800

2000

F0

0 0

0 0

D

BA

C

E

Summer 2010

Winter 2010-2011









000




600

200

0

400

500

300

100

2010 2012

2011 2013

2010-2013




0-10 cm 20-50 cm 70-150 cm


005

020

010

025

030

015

000

270

285

275

290

295

280

265

300

Pre

cip

itat

ion

(m

m)

Soil

mo

istu

re (

m3 m

-3)

Tem

pe

ratu

re (

K)













Hei

ght

[m]













4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)


1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0



Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]








A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References




















































































































000




600

200

0

400

500

300

100

2010 2012

2011 2013

2010-2013




0-10 cm 20-50 cm 70-150 cm


005

020

010

025

030

015

000

270

285

275

290

295

280

265

300

Pre

cip

itat

ion

(m

m)

Soil

mo

istu

re (

m3 m

-3)

Tem

pe

ratu

re (

K)













Hei

ght

[m]













4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)


1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0



Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]








A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References





















































































































Hei

ght

[m]













4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)


1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0



Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]








A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References























































































































4

3

2

1

0

5

3 2

1 0

4

16

12

8

4

0

Flu

x [

mg

-2 h

r-1]

MB

O [

pp

b]

5

3

2

1

4

0

Flu

x [m

g m

-2 hr

-1] M

T [p

pb

]

3000

2500

2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)

b MBO (pptv)2000

1500

1000

500

0

0000 0600 1200 1800 0000

Time of Day (MST)


1000

800

600

400

200

0

a Isoprene (pptv)

200

150

100

50

0



Time (MST)

B-2 Toluene

B-4 Sum MT 20

15

10

00

05

10

08

06

04

02

00

000 0600 1200 1800 0000

200

150

100

50

0

000 0600 1200 1800 0000 Time (MST)

30

25

20

15

10

00

05

B-3 232-MBO

B-1 Isoprene

Iso

pre

ne[p

pb

] M

BO

[p

pb

]

To

luen

e[p

pt]

MT

[pp

b]








A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References




















































































































A

B






O3 + hν rarr O(1D) + O2 (R1)








0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References




















































































































0400 0800 1200 1600 2000 0000 0000

A

B

C

HO

2 a

nd

H

O2+

RO

2 (

pp

tv)

Co

ntr

ibu

tio

n (

)

Win

d d

ire

ctio

n (deg)

150

100

50

0

100

50

0 360

270

0

90

180

NO

2 (pp

bv)

NO

(pp

bv)

15

10

05

0

6

0

2

4

6

4

2

0

Win

d sp

ee

d (m

s-1)













ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References




















































































































ind

dir

ect

ion

[d

egre

es] Su

lfate ae

roso

l mass4

and

win

d sp

ee

d

1000

100

10

4 M

ob

ility

Dia

me

ter

[nm


A

B


000 400 800 1200 1600 2000 000 000 400 800 1200 1600 2000 000 400 800 1200 1600 2000

105

104

103

102

101

dN

dlo

gDp [cm

-3]































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References











































































































































Lati

tud

e

405

400

395

390

385

380 -105 -106 -104 -105 -106 -104

Longitude Longitude





A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References




















































































































A [m

g m

-3]

600 1200 1800 000 (MST)

+ Anthropogenic SOA



30

25

20

15

10

05

00





NMD =


i Ni

(1)









6 Conclusions









References






















































































































6 Conclusions









References






















































































































References



















































































































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