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A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems
AbstractA harmonized comparative performance evaluation of A Unified Regional Air-quality Modelling System (AURAMS) v1.3.1b and Community Multiscale Air Quality (CMAQ) v4.6 air-quality modelling systems was conducted on the same North American grid for July 2002 using the same emission inventories, emissions processor, and input meteorology.Comparison of AURAMS- and CMAQ-predicted O3 concentrations against hourly surface measurement data showed a lower normalized mean bias (NMB) of 20.7% for AURAMS versus 46.4% for CMAQ. However, AURAMS and CMAQ had more similar normalized mean errors (NMEs) of 46.9% and 54.2%, respectively. Both models did similarly well in predicting daily 1-h O3 maximums; however, AURAMS performed better in calculating daily minimums. CMAQ's poorer performance for O3 is partly due to its inability to correctly predict nighttime lows.Total PM2.5 hourly surface concentration was under-predicted by both AURAMS and CMAQ with NMBs of −10.4% and −65.2%, respectively. However, as with O3, both models had similar NMEs of 68.0% and 70.6%, respectively. In general, AURAMS performance was better than CMAQ for all major PM2.5 species except nitrate and elemental carbon. Both models significantly under-predicted total organic aerosols (TOAs), although the mean AURAMS concentration was over four times larger than CMAQ's. The under-prediction of TOA was partly due to the exclusion of forest-fire emissions. Sea-salt aerosol made up approximately 50.2% of the AURAMS total PM2.5 surface concentration versus only 6.2% in CMAQ when averaged over all grid cells. When averaged over land cells only, sea-salt still contributed 13.9% to the total PM2.5 mass in AURAMS versus 2.0% in CMAQ.
A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems
AbstractA harmonized comparative performance evaluation of A Unified Regional Air-quality Modelling System (AURAMS) v1.3.1b and Community Multiscale Air Quality (CMAQ) v4.6 air-quality modelling systems was conducted on the same North American grid for July 2002 using the same emission inventories, emissions processor, and input meteorology.Comparison of AURAMS- and CMAQ-predicted O3 concentrations against hourly surface measurement data showed a lower normalized mean bias (NMB) of 20.7% for AURAMS versus 46.4% for CMAQ. However, AURAMS and CMAQ had more similar normalized mean errors (NMEs) of 46.9% and 54.2%, respectively. Both models did similarly well in predicting daily 1-h O3 maximums; however, AURAMS performed better in calculating daily minimums. CMAQ's poorer performance for O3 is partly due to its inability to correctly predict nighttime lows.Total PM2.5 hourly surface concentration was under-predicted by both AURAMS and CMAQ with NMBs of −10.4% and −65.2%, respectively. However, as with O3, both models had similar NMEs of 68.0% and 70.6%, respectively. In general, AURAMS performance was better than CMAQ for all major PM2.5 species except nitrate and elemental carbon. Both models significantly under-predicted total organic aerosols (TOAs), although the mean AURAMS concentration was over four times larger than CMAQ's. The under-prediction of TOA was partly due to the exclusion of forest-fire emissions. Sea-salt aerosol made up approximately 50.2% of the AURAMS total PM2.5 surface concentration versus only 6.2% in CMAQ when averaged over all grid cells. When averaged over land cells only, sea-salt still contributed 13.9% to the total PM2.5 mass in AURAMS versus 2.0% in CMAQ.
A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems
Smyth, Steven C. (author) / Jiang, Weimin (author) / Roth, Helmut (author) / Moran, Michael D. (author) / Makar, Paul A. (author) / Yang, Fuquan (author) / Bouchet, Véronique S. (author) / Landry, Hugo (author)
Atmospheric Environment ; 43 ; 1059-1070
2008-11-13
12 pages
Article (Journal)
Electronic Resource
English
Air quality , Particulate matter , Ozone , AURAMS , CMAQ
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