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Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern United States using

Receptor and Deterministic Models

Ralph Morris and Jaegun Jung, ENVIRON Intl. Corp.

Eric Fujita, Desert Research InstitutePatricia Brewer, National Park Service

2009 CMAS ConferenceOctober 19-21, 2009

Chapel Hill, North Carolina

CMAS 2009 2

Organic Carbon Mass (OCM) is an Important Component of Total PM2.5

Mass and Visibility Impairment in the Southeastern U.S.

• Time series of annual PM2.5 at Great Smoky Mountains NP 1988-2006

• OCM second highest PM2.5 component to Ammonium Sulfate

CMAS 2009 3

Projected Improvements in PM2.5 Mass and Visibility Impairment in

Southeastern U.S. primarily due to Reductions in Ammonium Sulfate

• Estimated percent change in particle extinction from 2000-2005 to 2018 for Worst 20% days at VISTAS Class I areas

Average change in extinction components from 2002 baseline to 2018 projectedat VISTAS sites using 2018g4a/2002gt2a RRFs

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bSO4

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CMAS 2009 4

VISTAS Organic Carbon Source Apportionment Study

•Visibility Improvement State and Tribal Association of the Southeast (VISTAS) undertook a multi-pronged study to understand the source of OCM in the southeastern U.S.– Enhanced PM monitoring at 5 sites

Organic Tracers 14C dating

– Receptor OCM/EC source apportionment modeling Chemical Mass Balance (CMB) and PMF

– Deterministic OCM/EC source apportionment modeling Particulate Source Apportionment Technology (PSAT) in

CAMx

CMAS 2009 5

VISTAS OCM Source Apportionment Study

• Total Carbon (TC) consists of OCM and EC– Most of TC is OCM– Primary emitted and

secondarily formed in the atmosphere (SOA)

– Anthropogenic and biogenic sources

– Past CMB studies identified three largest components as: Vegetative Burning Mobile Sources Unexplained Carbon

– Unexplained Carbon presumed to be secondary in origin

– Large seasonal and spatial variability in the TC

Millbrook

FL

GA

SC

NC

KY

VA

WV

AL MS

TN

• Five monitoring sites with enhanced measurements– 4 Class I areas plus Raleigh, NC (Millbrook)

CMAS 2009 6

VISTAS TC Source Apportionment Modeling

• CMB Receptor TC SA Modeling for 2004/2005 (Fujita et al., 2009):– Gasoline Vehicle

Exhaust– Diesel Vehicle Exhaust– Hardwood Combustion– Softwood Combustion– Meat Cooking– Vegetative Detritus– Unexplained Carbon

(UC)

• CAMx/PSAT TC SA Modeling for 2002 (Morris et al., 2009):– Gasoline Combustion– Diesel Combustion– Biomass Burning– Other Point Sources– Other Area Sources– Anthropogenic SOA

(SOAA)– Biogenic SOA (SOAB)

CMAS 2009 7

CAMx PSAT TC Source Apportionment Modeling

TC Source Apportionment

• SMOKE emissions modeling to separate TC source categories

• CAMx photochemical grid model

• Particulate Source Apportionment Technology (PSAT) to obtain TC source contributions for primary EC and OCM emissions

• Standard model output to obtain SOAA and SOAB contributions

• Model performance evaluation

• VISTAS 2002 36 km Continental U.S. Database– CMAQ and CAMx

CMAS 2009 8

• Model Performance Evaluation for OCM– Monthly Fractional

Bias (FB) for OCM shows large underprediction bias

– OCM underprediction bias greatest for urban-oriented STN network and during summer

– Identification of the source of OCM underprediction bias one of objectives of VISTAS TC source apportionment study

CAMx CMAQ IMPROVE_OC_MFB (%)

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CMAS 2009 9

Comparison of CMB & PSAT TC Apportionment•Convert CAMx/PSAT OCM into OC using

source-specific OCM/OC ratios – e.g., 1.4 for gasoline and 2.2 for SOA

•Combined OC with EC to make TC

•Compare seasonal average PSAT & CMB TC

•Map PSAT and CMB source categories:Source Category CMB CAMx/PSAT Gasoline Combustion Gasoline Vehicle Exhaust Gasoline Combustion Diesel Combustion Diesel Vehicle Exhaust Diesel Combustion Vegetative Burning Hardwood and Softwood Combustion Biomass Burning Other Meat Cooking and Vegetative Detritus Other (Area) Sources Point None Point Sources Biogenic SOA UCm SOAB Anthropogenic SOA UCf SOAA

CMB UC split between modern (UCm) and fossil (UCf) Carbon using 14C data

CMAS 2009 10

• TC Gasoline Contributions, CMB vs. PSAT for Winter and Summer– PSAT gasoline

contributions much lower than CMB

– Variability in PSAT 24-hour gasoline TC contributions shown

– Largest difference at suburban MILL site

– CMB gasoline TC ~5 times greater than PSAT

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ROMA SHEN MACA GRSM MILL

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CAMx

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Gasoline Winter

Gasoline Summer

CMAS 2009 11

• TC Diesel Contributions, CMB vs. PSAT for Winter and Summer– PSAT seasonal average

always lower than CMB– PSAT 24-hour variability

overlaps with CMB goodness of fit

– On average CMB Diesel TC contributions factor of ~2 greater than PSAT

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Diesel Winter

Diesel Summer

CMAS 2009 12

• TC Vegetative Burning Contributions, CMB vs. PSAT Winter and Summer– Comparable seasonal

average TC contributions from fires

– Lots of variability in the 24-hour PSAT Vegetative Burning TC contributions

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Fires Winter

Fires Winter

CMAS 2009 13

• Modern vs. Fossil TC comparisons: 14C vs. CMB vs. PSAT for Mammoth Cave, KY– CMB and PSAT

frequently overstating the fraction of Fossil Carbon

– CMB best fit with 14C data if assume UC is modern (i.e., SOAB)

C14 - Winter

CMB - Winter

CAMx - Winter

Fossil

Modern

Unexplained

C14 - Spring

CMB - Spring

CAMx - Spring

Fossil

Modern

Unexplained

C14 - Summer

CMB - Summer

CAMx - Summer

Fossil

Modern

Unexplained

C14 - Fall

CMB - Fall

CAMx - Fall

Fossil

Modern

Unexplained

CMAS 2009 14

CMB vs. PSAT TC Apportionment Comparisons• Gasoline: CMB TC ~5 times greater than PSAT

• Diesel: CMB TC ~2 times greater than PSAT• Fires: CMB and PSAT TC comparable• Other Area: CMB and PSAT comparable• Other Point: No comparable source category in

CMB• Both CMB w/ 14C and PSAT estimate that SOA is

dominated by SOAB– Exception is suburban Millbrook site that has some higher

SOAA• Several confounding aspects to the comparison:

– CMB frequently overstates amount of fossil carbon– 36 km grid cell size in CAMx PSAT diluting TC signal at

MILL– PSAT point source has no counterpart in CMB

Maybe partially embedded in gasoline or diesel CMB contributions

CMAS 2009 15

Summary CMB vs. PSAT TC Contributions• 5-Site and 4-Site average CMB vs. PSAT TC

contributions– Why CMB gasoline (~5x) and diesel (~2x) greater

than CAMx/PSAT?– Why CMB/14C SOAB (~1.5-2x) greater than

CAMx/PSAT?– Why does CMB not attribute TC to stationary

sources (points)?

5 Sites Average (w/ MILL) 4 Site Average (Class I Areas) Source Category

CMB (µg/m3)

CAMx (µg/m3)

Diff (%)

CMB/ CAMx

CMB (µg/m3)

CAMx (µg/m3)

Diff (%)

CMB/ CAMx

Points -- 0.115 -- -- -- 0.105 -- -- Gasoline 0.428 0.082 -80.9% 5.7 0.368 0.078 -78.7% 5.2 Diesel 0.593 0.303 -48.9% 2.0 0.539 0.289 -46.4% 1.9 Fires 0.618 0.540 -12.5% 1.4 0.540 0.473 -12.4% 1.4

Others 0.157 0.118 -24.8% 1.4 0.109 0.117 7.3% 1.0 SOAA 0.117 0.027 -76.6% 4.1 0.013 0.026 92.5% 0.5

SOAB 1.064 0.630 -40.8% 2.2 0.723 0.604 -16.4% 1.5

Total 2.977 1.816 -39.0% 1.6 2.292 1.693 -26.1% 1.4

CMAS 2009 16

Gasoline/Diesel TC Contributions

•CAMx/PSAT gasoline and diesel TC emissions– MOBILE6 on-road mobile sources

LDGV dominate gasoline HDDT large component of diesel

– NONROAD non-road mobile source emissions Large component of diesel Locomotive, marine vessels and airplanes

separately

•EPA’s MOBILE6 and NONROAD being replaced by new EPA/OTAQ MOVES model– Preliminary MOVES vs. MOBILE6 comparisons

just becoming available

CMAS 2009 17

Motor Vehicle Emissions Simulator (MOVES)MOVES estimating 2.5-3.0 times more PM2.5

emissions from on-road mobile sources than MOBILE6 for three test cities

(Source: Beardsley and Dolce, 2009)

CMAS 2009 18

Kansas City 2004-2005 Vehicle Measurement Study•KC motor vehicle measurements used in MOVES

•Also found high emission levels of Semi-Volatile Organic Compounds (SVOC) from LDGV– SVOC compounds not typically collected in vehicle

exhaust VOC measurement studies e.g., alkanes with 12 carbons or more, PAH compounds

– SVOC emissions from LDGV 1.5 times the TC emissions SVOC can condense to form an SOAA that would increase

amount of TC from LDGVs Unclear where condensed LDGV SVOC emissions would be

in the CMB source apportionment (gasoline and/or UC)

CMAS 2009 19

Secondary Organic Aerosol (SOA)

• SOA an area of current research and development

• Significant progress over last 5 years– MEGAN biogenic emissions model– CMAQ SOAmods (2005), CAMx V4.5 (2008) and

CMAQ V4.7 (2008) Added SOAB from isoprene and sesquiterpene and other

processes not treated in previous versions

• Several researchers are attributing more SOAA to aromatic VOC precursors (e.g., Toluene) than in current models– e.g., UofWI, NOAA, Kleindienst, etc.

CMAS 2009 20

VISTAS Source Apportionment Conclusions• Comparison of CMB and CAMx/PSAT TC source

apportionment provides insight into both methods and identifies areas for further research to improve our OCM modeling capability

• Current emission inventories underestimate particulate Carbon emissions from gasoline and diesel combustion– New MOVES on-road and non-road mobile source emissions

factor model will make up much of the shortfall– KC vehicle study SVOC emissions may also help with gasoline

OCM and/or SOAA shortfall – CMB gasoline contribution may also be overstated

Where are the stationary source TC contributions in the CMB analysis?

• SOA due to biogenic emissions is an area of current research– Implementation of SOA basis set treatment in CAMx will allow

more flexibility in treating SOA from SVOC emissions and biogenic VOCs

CMAS 2009 21

Acknowledgements

•Acknowledge Dr. Eric Fujita’s colleagues at Desert Research Institute who performed sampling and CMB/PMF modeling– David Campbell, Johann Engelbrecht and

Barbara Zielinska

•Acknowledge Woods Hole Oceanographic who made 14C measurements that were documented by Roger Tanner of TVA

•This study was sponsored by VISTAS and acknowledge John Hornback and Ron Methier of SESARM for their support