1. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CCOS 2000 Model Intercomparison: Summary of Model Evaluation November 18, 2003, Progress Report to CARB Gail Tonnesen, Zion Wang, Mohammad Omary, Chao-Jung Chien, Bo Wang, Youjun Qin, Glen Kaukola, Tiegang Cao, University of California, Riverside Bourns College of Engineering Center for Environmental Research and Technology

2. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Study Plan Evaluate 3 Models for 2 Mechanisms: CAMx version 3 CMAQ version 4.2.2 SAQM CBM-IV (CB4) gas phase chemistry SAPRC99 gas phase chemistry

3. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Meteorology Processed the MM5 files using: –MCIP for CMAQ –mm5camx Met Cases Used: –ETA –MRF, several versions –Sensitivity case with reduced wind speed

4. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Emissions Inventories Raw Emissions files from Alpine Geophysics Processed using ARB software, ported to Linux. Emissions Sensitivity cases included: –Fire emissions –Corrections to mobile sources –Corrections to Point Sources

5. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside All models under predicted O3 Focused primarily on CAMx sensitivity simulations which had highest O3. Ran multiple iterations using Emission updates and Meteorology updates. Including fire emissions had largest effect. Small changes (few ppb O3) for other sensitivities

6. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Performance results at website www.cert.ucr.edu/aqm/ccos Click on site to bring up O3, CO and NOx plots at monitoring sites.

7. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CAMx Evaluation July 30

8. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CAMx Evaluation July 31

9. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CAMx Evaluation August 1

10. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CAMx Evaluation August 2 Peak O3 150 ppb in Kern Co., early in Day Adding fire emissions gave us 142 ppb O3 at 10 AM near Bakersfield Not a good case to model because of contribution of fires.

11. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Compare CAMx SAPRC99 vs CB4

12. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CAMx SAPRC99 minus CB4 SAPRC99 has higher O3 than CB4 throughout the domain. SAPRC99 has higher peak O3, 119 vs 113 ppb consistent with previous results. CB4 has updated (1/03) emissions but this appears to have minor effect. (However do not have new mobile yet.)

13. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Compare CAMx SAPRC99 ETA vs MRF ETA has lower O3 in urban areas. ETA has greater variation in O3, i.e., curve is “less flat”. Peak O3 is shifted 2 cells but virtually unchanged on 7/30.

14. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Other Sensitivity Case Boundary Conditions –O3 BC sensitivity increased O3 by2 to 5 ppb in Bay Area and northern domain. N2O5 Hydrolysis –Increased O3 by 5 to 8 ppb in SQV

15. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Conclusions Models are insensitive to changes in emissions inputs (within the uncertainty range used here). Models are sensitive to wind speed. Fire create large uncertainty. Fate of NOx is a key uncertainty in SJV: –N2O5 hydrolysis and “re-noxification” will lead to higher model O3 for SJV.

16. Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside Recommend Future Work Vertical mixing sensitivity: –Reduce Kz_min –1:1 mapping for MM5 and air quality model Fire Sensitivity simulations Run models with aerosols to include heterogeneous chemistry effects. Evaluate other episodes.