A Coupled MM5-CMAQ Modeling System for Assessing Effects of Restriction Measures on PM10 Pollution in Olympic City of Beijing, China
Cheng, S. Y.
Chen, D. S.
MetadataShow full item record
In this paper, a coupled MM5-CMAQ modeling system was employed to investigate the PM10 pollution issue in Beijing, China, with a focus on assessing the effects of different restriction policies implemented during and after the 2008 Olympic Games. The simulations under designed scenarios were implemented over a 2-level nested grid domain for comparing the difference of PM10 concentrations under restriction and no-restrictions situations. The restriction measures include alternate-day vehicle driving, construction activities, trans-boundary emissions from neighboring provinces, and vehicle restrictions during the post-Olympic period. Meteorological contributions to the air quality improvement were also examined. The results show that significant improvement of air quality in Beijing during the 2008 Games was attributed largely to these restriction measures, although favorable weather conditions play an important role. Also, during the post-Olympic period, daily vehicle restrictions implemented temporarily under extreme weather conditions played a crucial role in alleviating Beijing's air pollution. Beijing not only needs to take continuing efforts to addresses its own PM10 problem, but also has a clear self-interest in demanding better environmental performance from neighboring provinces. It is suggested that Beijing would work collectively with neighboring provinces to develop a long-term multi-region initiative and strategy aimed at emission reduction for providing the citizens in this region a healthy and clean air in the long run.
Zhou, Y., S. Y. Cheng, L. Liu, and D. S. Chen. 2012. "A Coupled MM5-CMAQ Modeling System for Assessing Effects of Restriction Measures on PM10 Pollution in Olympic City of Beijing, China." Journal of Environmental Informatics 19(2): 120-127. Copyright 2012 by the International Society for Environmental Information Sciences. http://www.iseis.org