SIMULATING URBAN AIR TOXICS OVER CONTINENTAL AND URBAN SCALES.

1. SIMULATING URBAN AIR TOXICS OVER CONTINENTAL AND URBAN SCALES. W. T. Hutzell1, D. J. Luecken1 and J. K. S. Ching21Atmospheric Modeling Division, U. S. Environmental Protection Agency2Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration

2. Background • US EPA’s NATA assesses health risks from chronic exposure to Hazardous Air Pollutants. • 1996 results were criticized the modeling for HAPs produced by photochemistry. • Suggested improvements included using a model that better accounts for photochemistry. • Alternatives included models that simulate ozone and particulate matter. • ORD determined to investigate using CMAQ for assessing risks.

3. Method • Modify the CB-IV mechanism in the CMAQ modeling system. • Add twenty HAPs that exist primarily in the gas phase. • Simulate concentrations over a calendar year. • Provide predictions to OAQPS for comparison to other methods. • Evaluate the predictions against observation.

4. HAPs added • New species include reactive tracers for emissions of HCHO, CH3CHO and acrolein.

5. Simulation Details • Domain covered the continental US and spanned from surface to 100 mb. • Horizontal grid size was 36X36 km2 • Emissions came form the combined 1999 NEI and Air Toxics database. • Meteorology represented 2001 based on MM5 simulations.

6. Evaluation Method • Observations used • 2001 Pilot Study and other programs archived in EPA’s AQS database. • 1, 3 and 24 hour averaging periods. • We present evaluations of model predictions for the 24 hour averages. Compounds Evaluated HCHO CH3CHO 1,3-Butadiene Benzene Perchloroethylene Chloroform

7. Evaluation Statistics • Normalized Mean Bias (NMB) • Normalized Root Mean Squared Error (NRMS) • Correlation Coefficient (r) • Fractional difference in Coefficients of Variation (CV)

8. Summary Statistics

9. Regional Comparison

10. r=0.89 r=0.63 r=0.48 HCHO: Time Series Comparisons

11. Benzene: Time Series Comparisons r=0.67 r=0.76 r=0.48

12. Continental Evaluation • CMAQ under-predicts observations by about a factor of two. • Predictions have less precision than accuracy, i.e., NRMS>NMB. • Results rely on location. • Performance may depend how the grid cell represent meteorology and emissions near a monitor. • Comparing CV and time series can support the conclusion.

13. Finer scale simulations • Two nested simulations conducted within the continental domain. • Grid cells were 12X12 km2 and 4X4 km2. • Nests focused on Philadelphia, PA over 2001. • Each nest was driven by its own MM5 simulations at 12X12 km2 or 4X4 km2.

14. Evaluation of finest and coarsest resolutions • EPA’s AQS database provided five sites in New Jersey. • We compared 36X36 km2 and 4X4 km2. • The goal was to answer the question. • Does using smaller or finer-scale grid cells better match observations?

15. Summary Statistics

16. r=0.33 r=0.33 r=0.42 r=0.38 HCHO: Time Series Comparisons

17. r=0.58 r=0.62 r=0.48 r=0.40 Benzene: Time Series Comparisons

18. r=0.07 r=0.16 r=0.09 r=0.33 1,3-Butadiene: Time Series Comparisons

19. Comparison between 36X36 km2 and 4X4 km2 predictions. • Finer resolution has a better accuracy than coarsest resolution. • Precision and correlation does not significantly improve. • Improvements appear linked to matching the observed CV. • Performance depends season. • Timing of simulated emissions and meteorology factors into matching observations. • Seasonal performance and timing issues may explain little improvement in NRMS error and correlation coefficients. Disclaimer: The research presented here was performed under the memorandum of understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies of views.