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CENRAP’S TECHNICAL WORK OVERVIEW

CENRAP’S TECHNICAL WORK OVERVIEW. National RPO Technical Meeting June 9, 2005 Annette Sharp. CENRAP 2002 Emissions Inventory. Improvements in Ammonia, Agricultural Dust, Planned Burning, and Mobile Sources (VMT) CENRAP-wide Gulf of Mexico Offshore Emissions State Specific Improvements

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CENRAP’S TECHNICAL WORK OVERVIEW

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  1. CENRAP’S TECHNICAL WORK OVERVIEW National RPO Technical Meeting June 9, 2005 Annette Sharp

  2. CENRAP 2002 Emissions Inventory • Improvements in Ammonia, Agricultural Dust, Planned Burning, and Mobile Sources (VMT) CENRAP-wide • Gulf of Mexico Offshore Emissions • State Specific Improvements • Next Version Due out July 31, 2005

  3. CENRAP 2018 Emissions Inventory • EGAS5 • IPM – EGU • MOBILE6

  4. CENRAP Monitoring • IMPROVE/IMPROVE Protocol Monitors in CENRAP • Deployment of Nephelometers • Ammonia Monitors • Carbon Speciation?

  5. CENRAP Implementation and Control Strategy • Inter-RPO Cost-Benefit Analysis • SIP Development – SIP Development Steering Committee; 3 EPA Regions Participating • Control Strategies – PM2.5 menu from STAPPA/ALAPCO, MWRPO, VISTAS, CAIR or not to CAIR

  6. CENRAP Modeling: Supporting Analysis from Two Air Quality Models

  7. Air Quality Modeling • Base A 2002 36-km annual CMAQ/CAMx base case simulation • Reporting and results on CENRAP modeling website: • http://pah.cert.ucr.edu/aqm/cenrap/cmaq.shtml • Base B 2002 36-km annual and 12-km episodes are ongoing • Inventory updates and other improvements

  8. Fractional Bias –SO4CAMx

  9. Fractional Bias –SO4 CMAQ

  10. Fractional Error/Fractional BiasCMAQ

  11. Fractional Error/ Fractional BiasCAMx

  12. Model Performance • Comparable model performance between CMAQ and CAMx • neither model is performing better than the other across all species. • SO4 performance is fairly good across all models • NO3 performance is poor • Both models overestimate in the winter and underestimate in the summer.

  13. Model Performance 2 • Total Carbon Mass- poor • Over estimate in winter and underestimate in summer • Slightly better performance for CAMx over CMAQ • Both models having the poorest performance for periods with the highest observed concentrations • Soil & Coarse Matter- exhibit little skill • Over estimate in winter and underestimate in summer • Modeled without fugitive dust transport factors in CMAQ and used an 0.25 factor for CAMx • Soil performance supports the use of FDTFs • However, coarse matter performance did not suggest that FDTFs are supportable • Base B simulations will be using FDTFs

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