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CENRAP’S TECHNICAL WORK OVERVIEW

Explore improvements in emissions inventory, monitoring protocols, air quality modeling, and regional implementation strategies within CENRAP. Learn about key findings, model performances, and upcoming inventory updates.

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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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