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Improvements in Emissions and Modeling of OC and SVOC from Onroad

Improvements in Emissions and Modeling of OC and SVOC from Onroad. Mark Janssen – LADCO, Mike Koerber – LADCO, Chris Lindjem – EVIRON, Eric Fujita – DRI 8 th Annual - CMAS Conference October 19 th – 21 st , 2009. Overview.

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Improvements in Emissions and Modeling of OC and SVOC from Onroad

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  1. Improvements in Emissions and Modeling of OC and SVOC from Onroad Mark Janssen – LADCO, Mike Koerber – LADCO, Chris Lindjem – EVIRON, Eric Fujita – DRI 8th Annual - CMAS Conference October 19th – 21st, 2009

  2. Overview • Develop mobile source emissions inventory adjustment factors (e.g., MOVES-like) • Apply adjustment factors and assess effect on air quality modeling • Provide guidance to states on upcoming PM2.5 SIP activities

  3. PM2.5 Design Value: Daily Standard 2006-2008

  4. ERTACEastern Regional Technical Advisory Committee • Eastern Inventory Folks Work to Repair Problematic Sources • Rail – Link Level National Inventory • Area Source Comparability • Organic Carbon • EGU Temporalization and EGU Growth • Agricultural Ammonia Process Based

  5. PM2.5 Model Performance Monthly Average Mean Bias Midwest States

  6. Sources of Organic Carbon Cite: LADCO’s 2004 Urban Organics Study

  7. Potential Adjustments to MOBILE6 LDGV and LDGT PM adjustment Mass adjustment Temperature adjustment HDDV HC and PM adjustment Speed adjustment LDGV and LDGT HC adjustment Inclusion of semi-volatile hydrocarbons LDGV HC, CO, NOx adjustment Consideration of high emitting vehicles MOVES-like

  8. 1. PM Temperature Adjustment

  9. ºF MOVES v. MOBILE6 (NMIM) Courtesy: Marc Houyoux, USEPA

  10. 2. HDDV Emissions v. Speed PM Emissions HC Emissions

  11. Onroad Framework • CONCEPT Emissions Model • Link Level VMT, Speed, Mix • Improved Temporalization(VMT, Speed, Mix) • Detroit 68% Onroad NOX HDDV, significant Weekend Dropoff.

  12. 3. Semi-Volatile Organic Carbon (SVOC) Emissions Samples taken during Kansas City study (Note: only 9 of about 50 samples were analyzed!!!)

  13. 4. High Emitter Analysisfor Detroit and Atlanta • Results from ENVIRON study funded by EPRI • Used RSD data for: • Atlanta: Continuous Atlanta Fleet Evaluation (CAFÉ), Release 18. • Detroit: ESP and McClintock: 2007 High Emitter Remote Sensing Project

  14. Air Quality Modeling: Overview Model: CAMx Base Year: 2005 Scenarios: * Base (Mobile 6.2) * Base w/ Adj. 1-2 * Base w/ Adj. 1-3 * Base w. Adj. 1-4 (not done) 12 km 36 km

  15. Results: Adj. 1-2 Absolute change in 2005 base case JANUARYaverage PM2.5 concentrations (Adj. 1-2 v. Base)

  16. Results: Adj. 3 Absolute change in 2005 base case JULYaverage PM2.5 concentrations (Adj. 1-3 v. Adj. 1-2)

  17. Results: Adj. 1-3 Cleveland Detroit Indianapolis Chicago Blue = Base (MOBILE6), Green = Adj.1-2, Purple = Adj. 1-3

  18. Source Apportionment Results Organic Carbon Monitoring Data Organic Carbon x 1.6 Modeling Data

  19. Conclusions • Emissions inventory adjustments had little effect on modeled PM2.5 (organic carbon) concentrations • SIP inventories expected to rely on MOVES • PM model performance still problematic • Source apportionment analyses suggest that important sources of organic carbon include… Biogenic emissions Biomass combustion “Mobile” sources Local point sources (in industrialized areas) • Given inventory and modeling shortcomings, States may need to consider other information (e.g., monitoring data) to support SIP development

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