1. Evaluation of the VISTAS 2002 CMAQ/CAMx Annual Simulations T. W. Tesche & Dennis McNally -- Alpine Geophysics, LLC Ralph Morris -- ENVIRON Gail Tonnesen -- UC Riverside Patricia Brewer -- VISTAS Technical Coordinator James Boylan – Georgia Dept of Natural Resources Models-3 CMAS Conference 18-20 October 2004 Chapel Hill, NC

2. Outline VISTAS objectives Model set-up for initial Phase II runs Highlights of CMAQ/CAMx evaluations –Operational, Comparative, Diagnostic, Mechanistic Some findings from diagnostic studies Suggestions

3. VISTAS AQ Modeling Objectives Phase I: –Evaluate suite of models for episodic and annual simulation of Regional Haze & PM2.5 on 36/12 km US grid Phase II: –Select and evaluate preferred model(s) for 2002 annual period via detailed model performance and sensitivity evaluations –Evaluate emission control strategies for regional haze, particularly for VISTAS region. –Support VISTAS states responsible for upcoming PM 2.5 attainment demonstrations.

4. Model Set-up for Initial 2002 Annual Run 36/12 km grid, 19 layers CMAQ v4.3 and CAMx v4.0 MM5 (Pleim-Xiu_ACM8 36/12 km) 2002 Emissions for VISTAS states (WRAP and CENRAP updates; NEI 1999 V2 for rest of U.S.) CMAQ (CB4, SORGAM); CAMx (CB4, SOAP) BCs from 2001 Seasonal GEOS-CHEM Models run in 4 quarters with 15 day spin-up VISTAS Phase II Modeling Protocol followed For reports, results, presentations…. http://pah.cert.ucr.edu/vistas/vistas2/reports

5. Operational Evaluation Focus on –Visibility-related PM species –Identify needed improvements before final 2002 basecase simulations begin (next week…!) Use suite of 15 metrics and graphical tools Evaluate by month and monitoring network Multiple evaluation teams –ENVIRON, UCR, Alpine, VISTAS-TAWG, GA-DNR

6. Monitors in VISTAS 12 km MPE Domain Yorkville, GA

7. Sulfate Fractional Bias and Error: CMAQ (note scale: 0-100%) IMPROVE Data for VISTAS States: 12 km grid

8. Nitrate Fractional Bias and Error: CMAQ (note scale: 0-200%) IMPROVE Data for VISTAS States: 12 km grid

9. Data for VISTAS States: 12 km grid Bias as Function of Concentration: CMAQ

10. Good:SO4 and EC Good-Fair: PM2.5 and PM10 Fair:NH4 Fair-Poor OC and CM Poor NO3 and Soils Operational Evaluation Summary for CMAQ & CAMx

11. Comparative Evaluation Inter-compare CMAQ V4.3 and CAMx V.4 Use identical SMOKE/MM5 inputs & VISTAS evaluation protocol Examine reasons for similar and divergent behavior –Gas phase and aerosol species –Wet and dry deposition patterns Conduct sensitivity experiments to elucidate similar and divergent behavior in CMAQ and CAMx

12. CMAQ/CAMx Fractional Error: 12 km

13. CMAQ/CAMx Fractional Bias: 12 km EC/CM “Flip-Flop”

14. In general: CMAQ and CAMx respond consistently for most gas-phase and PM species Winter: Large over-predictions of NO3 and CM Summer: Large under-predictions of NO3 (but concentrations are quite small) All Seasons: Soils over-predicted; OC under- predicted (understated primary OC emissions?) Comparative Evaluation Summary

15. Diagnostic Evaluation Examine PM and gas-phase species by network Evaluate effects of grid resolution, model response by sub-region, and range of time scales Examine differences in CMAQ/CAMx response Synthesize CMAQ/CAMx model evaluation results to elucidate possible sources of model bias and error (e.g. formulation, inputs, …)

16. CMAQ NO3 Fractional Bias: 12 km

17. Seasonal & Annual Average Aerosol Bias and Error: CMAQ IMPROVE Data for VISTAS States: 12 km grid

18. Spatial Mean Nitrate: VISTAS vs. MANE-VU VISTAS: Jan ‘02MANE-VU Jan ‘02 VISTAS: May ‘02MANE-VU May ‘02 CMAQ

19. Spatial Mean Sulfate: VISTAS vs. MRPO VISTAS: Jan ‘02MRPO Jan ‘02 VISTAS: May ‘02MRPO May ‘02 CMAQ

20. Spatial Mean EC Dry Deposition CMAQ-Jan ’02CAMx-Jan ’02 CMAQ-Jul ’02 CAMx-Jul ‘02 CMAQ dep > CAMx dep for EC

21. Spatial Mean CM Dry Deposition CMAQ-Jan ’02CAMx-Jan ’02 CMAQ-Jul ’02CAMx-Jul ‘02 CMAQ dep << CAMx dep for EC

22. SEARCH Hourly Sulfate at Yorkville, GA: Jan ‘02

23. SEARCH Hourly Nitrate at Yorkville, GA: Jan ‘02

24. Yorkville NO3, Temp & Mixing Ratio Time Series (Jan ’02) NO 3 Mixing Ratio Temperature

25. SEARCH Hourly Nitrogen Species at Yorkville, GA: Jan ‘02 NO HNO 3 NO y NO 2

26. Bias in Hourly VISTAS Domain-Wide MM5 Fields: Jan ‘02

27. - CMAQ and CAMx consistent for most species across all domains and time scales. - EC/CM bias ‘flip-flop’ due to different dry deposition algorithms in CMAQ/CAMx -OC bias differences in CMAQ/CAMx, in part, attributed to -Different SOA chemistry formulations -Different environmental chamber data sets and parameterizations. Diagnostic Evaluation Summary

28. Mechanistic Evaluation: CB4 vs SAPRC99 for Jan ’02 & Jul ’01 Episodes Very Similar Base Case Performance for SO4, NO3 and OC: –Differences between 36 and 12 km grid larger than differences between CB4 and SAPRC –SAPRC exhibits slightly improved performance for ozone compared to CB4 Generally Similar Response to 30% Controls, except: –SO4 sensitivity to NOx controls SAPRC approximately twice as sensitive Tied to H 2 O 2 and O 3 sensitivity to NOx controls –O3 sensitivity to VOC SAPRC more sensitive than CB4

29. Three Suggestions Devote greater emphasis to the diagnostic component of MPE (consider range of time and space scales, super-site data sets) Utilize the extensive 2002 aircraft data base for aloft model evaluation (probe ‘regional transport’ issue) Employ corroborative models to explore key uncertainties in –Input data base development –Base case model performance –Reliability of model response to emission controls