1. Georgia Environmental Protection Division IMPACTS OF MODELING CHOICES ON RELATIVE RESPONSE FACTORS IN ATLANTA, GA Byeong-Uk Kim, Maudood Khan, Amit Marmur, and James Boylan 6 th Annual CMAS Conference Chapel Hill, NC October 2, 2007

2. Georgia Environmental Protection Division Objective Investigate the effects of modeling choices on Relative Response Factors (RRFs) in Atlanta, GA –Horizontal grid resolution: 4 km and 12 km –Chemical Transport Model: CMAQ and CAMx

3. Georgia Environmental Protection Division Approach Exercising typical SIP modeling –Model Performance Evaluation (MPE) Measures and methods following the EPA’s guidance document (EPA, 2007) –Modeled Attainment Test Relative Response Factors Additional analyses –MPE with graphical measures Partial implementation of PROMPT (Kim and Jeffries, 2006) –Investigation of day-by-day and site-by-site variation of model predictions

4. Georgia Environmental Protection Division Modeled Attainment Test Future Attainment Status is determined by Future Design Value (DVf) –DVf should be less than 0.85 ppm. DVf = RRF x DVb Where, DVb is Baseline Design Value and RRF is Relative Response Factor defined as

5. Georgia Environmental Protection Division 8-Hour Ozone Attainment Status in GA

6. Georgia Environmental Protection Division Modeling System Setup Base case modeling period –May 21, 2002 ~ Sep 13, 2002 UTC (3 spin- up days ) MM5 (v 3.x) –Pleim-Xiu model for Land-Surface interaction –Asymmetric Convective Mixing SMOKE (v 2.x) –VISTAS Base G version 2 inventory CMAQ and CAMx –Inputs made to be close to each model for a same grid configuration. Georgia

7. Georgia Environmental Protection Division 12 km 4 km 7x7 array for 4-km runs

8. Georgia Environmental Protection Division MPE with statistical metrics

9. Georgia Environmental Protection Division Time series

10. Georgia Environmental Protection Division Time series

11. Georgia Environmental Protection Division Time series O3O3 O3O3 Mon Tue Wed Thur Fri Sat Sun

12. Georgia Environmental Protection Division Time series NO 2 ETH Mon Tue Wed Thur Fri Sat Sun

13. Georgia Environmental Protection Division Time series O3O3 O3O3 Mon Tue Wed Thur Fri Sat Sun

14. Georgia Environmental Protection Division NO 2 ETH Mon Tue Wed Thur Fri Sat Sun

15. Georgia Environmental Protection Division CAMx CAMx-CMAQ 2002-06-12 Spatial distribution (12km) Daily Max 8-hr O 3 2002-07-232002-07-24 ppb

16. Georgia Environmental Protection Division Relative Response Factors Two possible methods to calculate RRFs Max value in “nearby” grid cell arrays Value at each monitoring site grid cell Spatially averaged RRFs vary from 0.891 to 0.897 by modeling choices If DV b = 100 ppb, 0.001 difference in RRF will result in 0.1 ppb in DV f. RRFs from max O 3 nearby grid cell arrays

17. Georgia Environmental Protection Division Conclusion (1) Reasonable performance with respect to statistical metrics by all four models, CMAQ and CAMx with 4-km and 12-km grids –4-km emissions had 11% lower NOx in non-attainment areas –4-km MM5 runs showed poor nighttime performance. Higher biases during nighttime by CMAQ and during daytime by CAMx –Gross overestimation of ozone by CAMx for several days Lower biases from 4-km simulations –Probably due to emission discrepancies in 4-km inputs compared with 12-km emissions. No significant daytime NOx biases

18. Georgia Environmental Protection Division Conclusion (2) Stable or insensitive RRFs –Due to higher absolute concentrations predicted by CAMx, CAMx might show quite lower RRFs than CMAQ. –Max-Value based RRFs fell within 0.863 ~ 0.914 for all simulations. Effect of RRF calculation methods –Despite of noticeable differences between 4-km and 12-km modeling inputs, Max-Value based RRFs does not reflect this fact significantly. –Cell-Value based RRF distinguished grid configuration differences. –For all 11 monitoring sites, maximum RRF difference due to model choices were 0.036 and 0.033 by Max-Value based and Cell-Value based RRF calculation.

19. Georgia Environmental Protection Division Future Work Process Analysis to explain large variation of predicted ozone concentrations with similar modeling inputs Detail study on the relationship between model performance including day-by-day and site-by-site meteorological model performance and RRFs

20. Georgia Environmental Protection Division Acknowledgement ENVIRON International Corporation –Ralph Morris for CMAQ-to-CAMx utilities

21. Georgia Environmental Protection Division Byeong-Uk Kim, Ph.D. Georgia Environmental Protection Division 4244 International Parkway, Suite 120 Atlanta, GA 30354 Byeong_Kim@dnr.state.ga.us 404-362-2526 Contact Information