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AERMOD Evaluation for Non-Guideline Applications

AERMOD Evaluation for Non-Guideline Applications. Roger W. Brode U.S. EPA, OAQPS Air Quality Modeling Group Research Triangle Park, NC. Region 4 Modelers Workshop March 17, 2009 Atlanta, GA. Requirements of Operational Regulatory Dispersion Models vs. ER Models.

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AERMOD Evaluation for Non-Guideline Applications

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  1. AERMOD Evaluation for Non-Guideline Applications Roger W. Brode U.S. EPA, OAQPS Air Quality Modeling Group Research Triangle Park, NC Region 4 Modelers Workshop March 17, 2009 Atlanta, GA

  2. Requirements of Operational Regulatory Dispersion Models vs. ER Models • Regulatory models need to predict the peak of the concentration distribution, unpaired in time and space, for comparison to AQ standards • Emergency response models, and models used for risk and exposure assessments, require skill at predicting concentration distributions paired in time and space • Growing need for integrated exposure and risk-based approaches to health and environmental impact assessments places higher demands on dispersion model skill that will be difficult to meet

  3. Example of Operational Regulatory Dispersion Model Evaluation

  4. Previous Example Showing Results Paired in Time and Space

  5. Example of Operational Regulatory Dispersion Model Evaluation – Urban Case

  6. Previous Example Showing Results Paired in Time and Space

  7. Surface Roughness Sensitivity

  8. Example from NO2 NAAQS Review • AERMOD was applied for exposure assessment of the Atlanta area to support current NO2 NAAQS review • Majority of NO2 impacts attributed to mobile sources • Initial model-to-monitor comparisons showed AERMOD concentrations significantly exceeding monitored NO2 concentrations at 3 Atlanta area monitors • Initial assessment was that low surface roughness used to process airport data was not representative of roughness typical of source locations, and suggestion was to re-process airport data with 1m roughness

  9. Example from NO2 NAAQS Review • Based on a broader assessment of modeling analysis, recommendations were made to • Acquire and process SEARCH met data as more representative of surface characteristics for mobile sources • Apply OLMGROUP option within Ozone Limiting Method (OLM) to better account for NO to NO2 conversion • Modify source characteristics for mobile source emissions to better account for vehicle induced turbulence • Next slide shows a land cover map with locations of Jefferson Street SEARCH site (JST) and Atlanta Hartsfield airport site (ATL)

  10. Wind Rose Comparison for SEARCH and ATL-NWS Data for 2002 JST 82 calms ATL 856 calms 2002

  11. Model-to-Monitor Comparison - Before

  12. Model-to-Monitor Comparison - After

  13. Q-Q plot of modeled concentrations using SEARCH (JST) vs. NWS (ATL) data

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