Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern United States using Receptor and Deterministic Models - PowerPoint PPT Presentation


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Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern United States using Receptor and Deterministic Models


4 Class I areas plus Raleigh, NC (Millbrook) 6. VISTAS TC Source Apportionment Modeling ... 36 km grid cell size in CAMx PSAT diluting TC signal at MILL ... – PowerPoint PPT presentation

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Title: Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern United States using Receptor and Deterministic Models

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 Institute
  • Patricia Brewer, National Park Service
  • 2009 CMAS Conference
  • October 19-21, 2009
  • Chapel Hill, North Carolina

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

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

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
  • Particulate Source Apportionment Technology
    (PSAT) in CAMx

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
  • Large seasonal and spatial variability in the TC
  • Five monitoring sites with enhanced measurements
  • 4 Class I areas plus Raleigh, NC (Millbrook)

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.,
  • Gasoline Combustion
  • Diesel Combustion
  • Biomass Burning
  • Other Point Sources
  • Other Area Sources
  • Anthropogenic SOA (SOAA)
  • Biogenic SOA (SOAB)

CAMx PSAT TC Source Apportionment Modeling
  • TC Source Apportionment
  • SMOKE emissions modeling to separate TC source
  • 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
  • Model performance evaluation
  • VISTAS 2002 36 km Continental U.S. Database
  • CMAQ and CAMx

  • 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

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

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

Gasoline Summer
Diesel Winter
  • 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

Diesel Summer
Fires Winter
  • TC Vegetative Burning Contributions, CMB vs. PSAT
    Winter and Summer
  • Comparable seasonal average TC contributions from
  • Lots of variability in the 24-hour PSAT
    Vegetative Burning TC contributions

Fires Winter
  • 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)

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
  • 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

Summary CMB vs. PSAT TC Contributions
  • 5-Site and 4-Site average CMB vs. PSAT TC
  • Why CMB gasoline (5x) and diesel (2x) greater
    than CAMx/PSAT?
  • Why CMB/14C SOAB (1.5-2x) greater than
  • Why does CMB not attribute TC to stationary
    sources (points)?

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
  • EPAs MOBILE6 and NONROAD being replaced by new
    EPA/OTAQ MOVES model
  • Preliminary MOVES vs. MOBILE6 comparisons just
    becoming available

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)
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
  • SVOC emissions from LDGV 1.5 times the TC
  • 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)

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.

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
  • 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

  • Acknowledge Dr. Eric Fujitas colleagues at
    Desert Research Institute who performed sampling
    and CMB/PMF modeling
  • David Campbell, Johann Engelbrecht and Barbara
  • 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