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Evaluation of CMAQ with FAQS Episode of August 11 th -20 th , 2000

Evaluation of CMAQ with FAQS Episode of August 11 th -20 th , 2000 . Yongtao Hu, M. Talat Odman, Maudood Khan and Armistead (Ted) Russell October 29th, 2003. Fall line Air Quality Study. 36-km . 12-km . 4-km . Air Quality Modeling System.

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Evaluation of CMAQ with FAQS Episode of August 11 th -20 th , 2000

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  1. Evaluation of CMAQ with FAQS Episode of August 11th-20th, 2000 Yongtao Hu, M. Talat Odman, Maudood Khan and Armistead (Ted) Russell October 29th, 2003 Georgia Institute of Technology

  2. Fall line Air Quality Study 36-km 12-km 4-km Georgia Institute of Technology

  3. Air Quality Modeling System • MM5 v3.5.3, Using ETA analysis data and ADP observational data with 4DDA, MRF PBL and OSU LSM • SMOKE v1.5b, Using FAQS2000 Inventory which is based on FAQS investigations and NET99, CEM data from EPA, Spatial Surrogates data based on Census 2000, BEIS3 with BELD3 data and MOBIL6 • CMAQ v4.2.2, Using SAPRC99 with MEBI solver, PPM for advections, Eddy Diffusion for vertical mixing, None of PinG Georgia Institute of Technology

  4. FAQS Episode of August 11th-20th, 2000 • Daily Peak 1-hour Ozone Observations on August 17th (ppb): • 173@Atlanta, 129@Augusta, 154@Macon, 129@Columbus CMAQ Daily Peak 1-hour Ozone on August 17th: 12-km vs. 4-km Georgia Institute of Technology

  5. CMAQ Evaluation • Basic Method: Compare the measurements of the pollutant concentration at site locations with the CMAQ concentration predictions of the matched model species at the corresponding grid cells • Statistical Measures: Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Normalized Bias (MNB), Mean Normalized Error (MNE), Normalized Mean Bias (NMB), Normalized Mean Error (NME), Fractional Bias (FB), Fractional Error (FE) Georgia Institute of Technology

  6. Ozone Performance by Using 40ppb Cutoff Daily Errors: 12-km vs. 4-km Daily Bias: 12-km vs. 4-km Georgia Institute of Technology

  7. Ozone Performance of the Sites in Georgia by Using 40ppb Cutoff Bias by Sites: 12-km vs. 4-km Errors by Sites: 12-km vs. 4-km Georgia Institute of Technology

  8. Measurements vs. Predictions: Ozone and NO Scatters Plot of Ozone in 12-km Scatters Plot of NO in 12-km Georgia Institute of Technology

  9. Ozone Was Overestimated at Night Ozone Time Series at Columbus, GA Midnight Surface Ozone in 12-km Georgia Institute of Technology

  10. Performance in Diurnal Periods by No Cutoff Georgia Institute of Technology

  11. Free Atmosphere VOCs,NOx Mixing Height Collapse O3 Residual Layer NO O3 NO Vdiff Mixed Boundary Layer Stable Boundary Layer Surface Layer Surface Layer NO Emis Sunrise Noon Sunset Midnight Diurnal Change of Mixing Height: Vertical Mixing in Night Time Ozone Sinking • Kzz cutoff in CMAQ ~ Default: 1.0 m2/s, we tested: 0.3,0.1,0.03 and 0.0001 m2/s. Georgia Institute of Technology

  12. An optimal Kzz cutoff may lie between 0.1 and 1.0 m2/s Nighttime 12-km NMB by using different Kzz (m2/s) cutoff in CMAQ Georgia Institute of Technology

  13. Underestimation of CO Emissions CO NMB by using different Kzz (m2/s) cutoff in CMAQ Georgia Institute of Technology

  14. Overestimation of Isoprene Emissions at Other Rural Locations Isoprene 36-km NMB by using different Kzz (m2/s) cutoff in CMAQ Georgia Institute of Technology

  15. Localized, aberrantly high ozone peaks during the day found by reducing Kzz cutoff Late Afternoon Surface Ozone in 12-km Ozone Time Series at Santa Rosa, FL Georgia Institute of Technology

  16. Dominate Landuse was used as the only landuse in the grid cell to derive Surface Met Parameters in MM5 MM5 OSU LSM Assign Water Dominate Grid Cell as Pure Water USGS Water Fractions in 12-km Georgia Institute of Technology

  17. Grid Concentrations (too high) Grid Emissions(significant) Grid Met Parameters (much lower Kzz) Emissions from roads, trees Strong cooling effect of water surface Land-based emissions are simulated as being trapped very near surface since of water cooling Georgia Institute of Technology

  18. Solutions to Artificial Surface Ozone Values • Aggregating surface meteorological parameters from the fractional landuse for each grid cell in the meteorological modeling. • Smoothing the Kzz in CMAQ for those grid cells over the mixed landuse with water by averaging the Kzz of this grid cell with its surrounding grid cells. Georgia Institute of Technology

  19. A 9-points averaging method was used in CMAQ to smooth Kzz Late Afternoon Surface Ozone in 12-km Ozone Time Series at Santa Rosa, FL Georgia Institute of Technology

  20. Summary • CMAQ had a good ozone performance for FAQS episode of August 11th-20th, 2000 at day time, but not at night time. • Analysis suggests that an optimal Kzz cutoff may lie between 0.1 and 1.0 m2/s. • A consistent bias between simulated and observed CO suggests that there is an underestimate in CO emissions. On the contrary, isoprene might be overestimated in rural locations • Artificially high surface ozone values were found resulting from the OSU land surface model applied in MM5. A method of using 9-point averaging was proposed to fix this problem. Georgia Institute of Technology

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