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

Loading...

PPT – Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern United States using Receptor and Deterministic Models PowerPoint presentation | free to view - id: 2082a9-ZDc1Z



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

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

Description:

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

Number of Views:48
Avg rating:3.0/5.0
Slides: 22
Provided by: skc9
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

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


1
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

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

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

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

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

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)

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

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

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

CMB UC split between modern (UCm) and fossil
(UCf) Carbon using 14C data
10
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
11
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
12
Fires Winter
  • 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

Fires Winter
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)

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

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)?

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

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)
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)

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.

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

21
Acknowledgements
  • Acknowledge Dr. Eric Fujitas 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
About PowerShow.com