Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6342480 | Atmospheric Environment | 2012 | 14 Pages |
Abstract
The CMAQ modeling system has been used to simulate the air quality for North America and Europe for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII). The operational model performance of tropospheric ozone (O3), fine particulate matter (PM2.5) and total particulate matter (PM10) for the two continents has been assessed. The model underestimates daytime (8am-8pm LST) O3 mixing ratios by 13% in the winter for North America, primarily due to an underestimation of daytime O3 mixing ratios in the middle and lower troposphere from the lateral boundary conditions. The model overestimates winter daytime O3 mixing ratios in Europe by an average of 8.4%. The model underestimates daytime O3 by 4-5% in the spring for both continents, while in the summer daytime O3 is overestimated by 9.8% for North America and slightly underestimated by 1.6% for Europe. The model overestimates daytime O3 in the fall for both continents, grossly overestimating daytime O3 by over 30% for Europe. The performance for PM2.5 varies both seasonally and geographically for the two continents. For North American, PM2.5 is overestimated in the winter and fall, with an average Normalized Mean Bias (NMB) greater than â30%, while performance in the summer is relatively good, with an average NMB of â4.6%. For Europe, PM2.5 is underestimated throughout the entire year, with the NMB ranging from â24% in the fall to â55% in the winter. PM10 is underestimated throughout the year for both North America and Europe, with remarkably similar performance for both continents. The domain average NMB for PM10 ranges between â45% and â65% for the two continents, with the largest underestimation occurring in the summer for North American and the winter for Europe.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Atmospheric Science
Authors
K. Wyat Appel, Charles Chemel, Shawn J. Roselle, Xavier V. Francis, Rong-Ming Hu, Ranjeet S. Sokhi, S.T. Rao, Stefano Galmarini,