A Comparative Performance Evaluation of the AURAMS and CMAQ Air Quality Modelling Systems

1. A Comparative Performance Evaluation of the AURAMS and CMAQ Air Quality Modelling Systems Steven C. Smyth, Weimin Jiang, Helmut Roth, and Fuquan Yang ICPET, National Research Council of Canada, Ottawa, Ontario Michael D. Moran and Paul A. Makar MSC, Environment Canada, Toronto, Ontario Véronique S. Bouchet and Hugo Landry CMC, Environment Canada, Dorval, Québec

2. Outline • Introduction • AURAMS vs. CMAQ – Differences in science, input file preparation, etc. • O3, total PM2.5, and speciated PM2.5 performance comparison • Summary and Conclusions 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

3. Introduction • Many aspects of the AURAMS and CMAQ simulations were “aligned” to reduce some of the common sources of differences: • same input meteorology from Environment Canada’s GEM model • same raw emissions inventories processed by SMOKE • same biogenic emissions model • same grid resolution • Confidence that the differences in model results are caused by the AQ models themselves rather than by meteorological and/or emissions inputs 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

4. Modelling Systems • CMAQ v4.6 • SAPRC-99 chemical mechanism; AERO4; NRC PMx post-processor • AURAMS v1.3.1b • AUnified Regional Air-quality Modelling System • AQ modelling system with size- and composition-resolved PM • Designed to be a “one” atmosphere or “unified” model in order to address a variety of interconnected tropospheric air pollution problems ranging from ground level O3 to PM to acid rain 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

5. AURAMS v1.3.1b (cont.) • 9 PM species/components: sulphate (SU), nitrate (NI), ammonium (AM), black carbon (EC), primary organic aerosols (PC), secondary organic aerosols (OC), crustal material (CM), sea-salt (SE), and particle bound water (WA) • 12 PM size distribution bins: 0.01 to 40.96 µm in diameter • Bins 1 thru 8 – PM2.5 • Bins 9 and 10 – PMC; where PM10-PM2.5 = PMC • Bins 11 and 12 – PM greater than 10 µm in diameter • Gas phase chemistry – modified version of ADOM-II • Includes sea-salt emissions but not chemistry at this time • Zero-gradient lateral boundary conditions 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

6. Domains and Simulation period • AURAMS -Polar Stereographic; true scale at 60°N; 150 x 106 grid; 42-km resolution • CMAQ -Lambert conformal conic; standard parallels of 50°N and 70°N; 139 x 99 grid; 42-km resolution • 01:00 July 1, 2002 to 00:00 July 30, 2002 UTC 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

7. Model Inputs - Meteorology • GEM v3.2 • AURAMS meteorological pre-processor • GEM-MCIP (based on MCIP v3.1) • Overlapping grid cell comparison of surface fields – NMEs of 0.25% for pressure; 0.4% for temperature; 3.8% for specific humidity (HU) 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

8. Model Inputs - Emissions • SMOKE v2.2 • Canadian Emissions • 2000 CAC inventory • U.S. Emissions • 2001 CAIR • Mexican Emissions • 1999 inventory • Biogenic Emissions • BEISv3.09 • AURAMS – online • CMAQ – offline using SMOKE 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

9. Model Inputs - Emissions (cont.) • Point source processing • AURAMS – plume-rise of major point sources calculated within CTM • CMAQ – meteorological data used to calculate plume rise within SMOKE • Emissions files • AURAMS: grams/sec • representative week of emissions for each month of simulation • 3 emissions files (non-mobile, mobile, minor-point) in RPN format • 1 emissions file (major-point sources) in ASCII format • CMAQ: gaseous - moles/sec; PM - grams/sec • daily emissions files • single comprehensive file in I/O API format 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

10. Measurement Data • O3 - hourly measurements from: the EC NAPS network (190 sites) and U.S. EPA AQS network (1087 sites) • PM2.5 - hourly measurements from: NAPS (92 sites) and AQS (262 sites) • Speciated PM2.5 - daily averaged measurements from: NAPS (17 sites) and U.S. EPA STN network (205 sites) O3 Measurement Sites PM Measurement Sites 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

11. O3 Performance • AURAMS lower bias • Similar levels of error • CMAQ over prediction mainly due to inability in predicting daily lows 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

12. O3 Performance (cont.) • Both AURAMS and CMAQ over-predict daily peaks • AURAMS much better at predicting daily lows • Both models show correct diurnal patterns and overall trends in concentration level 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

13. Total PM2.5 Performance • AURAMS lower bias • Similar levels of error 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

14. Total PM2.5 Performance (cont.) • Both models under-predict PM2.5 • Forest-fires not included in emissions contributes to under-prediction in both models • Much more PM2.5 sea-salt in AURAMS 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

15. PM2.5 Species Performance • AURAMS better bias for SO4 and NH4; similar levels of error • CMAQ better correlation 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

16. PM2.5 Species Performance (cont.) • CMAQ better bias for EC; similar levels of error • AURAMS much better performance for TOA • Due to difference in SOA algorithms • Poor TOA correlation for both models impacts overall correlation for total PM2.5 (AURAMS – 0.074; CMAQ = 0.151) 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

17. PM2.5 Species – Temporal Comparison SO4 NO3 NH4 EC POA SOA Other PM2.5 Sea-salt 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

18. PM2.5 Species – Spatial Comparison 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

19. PM2.5 Species – Spatial Comparison (cont.) • Similar spatial and temporal patterns for most species • Sea-salt aerosols vastly different • Concentration levels quite different 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

20. PM Composition • PM2.5 sea-salt contributes over half to AURAMS total PM2.5 mass for all grid cells; only 5% in CMAQ • For land grid cells only, PM2.5 sea-salt contributes 15% in AURAMS and 2% in CMAQ • If sea-salt is excluded from model results, total PM2.5 performance still better in AURAMS results PM composition avg. over all grid cells PM composition avg. over land grid cells only 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

21. Discussion and Summary • Similar levels of error for O3, total PM2.5, and most PM2.5 species • AURAMS better bias for all species except PM2.5 nitrate and elemental carbon • Enhanced AURAMS bias due to cancellation of positive and negative biases • Sea-salts contribute much more to overall PM composition in AURAMS than CMAQ • Does not impact overall conclusions regarding relative PM2.5 performance of the models • Spatial and temporal patterns similar, but overall concentration levels quite different 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

22. Acknowledgements • Radenko Pavlovic and Sylvain Ménard of Environment Canada • transfer of AURAMS code and help in understanding and compiling various AURAMS related material • Wanmin Gong of EC • help in identifying problem in AURAMS land-use file • Pollution Data Division of EC • 2000 Canadian raw emissions inventories • U.S. EPA and CMAS • U.S. emissions data, SMOKE, CMAQ, MCIP • Colorado State University • VIEWS database for measurement data • Meteorological Service of Canada • NAtChem database for measurement data • Environment Canada and the Program of Energy Research and Development (PERD) for funding support 6th Annual Models-3 Conference, Chapel Hill, NC, October 1-3, 2007

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