Scientifically and efficiently ensuring good air quality for important events is an issue of concern to the government. In addition to analysis based on historical data, advanced prediction before an event is essential for the government having ample time to take effective actions to improve air quality during the event period. Taking “the 2022 Olympic Winter Games (OWG)” as a typical case, a chemical transport model coupled with a tracer-tagged module was used to evaluate the air quality and source apportionment of ambient pollutants in the OWG host cities under historical and predicted meteorological conditions. Driven by the downscaling of meteorological fields from an operational real-time climate forecast system, the potential ability of air quality forecasting three months ahead was investigated, which was meaningful for designing control strategies. Sensitive simulations indicated that under unfavorable meteorological conditions, such as those during February 2014, both Beijing and Zhangjiakou faced a high risk of experiencing haze episodes, even based on current anthropogenic emission intensity. The contribution of the joint prevention and control region to Beijing and Zhangjiakou would become larger under worse meteorological conditions, which favor heavy air pollution. The source apportionment results indicated that strengthened emission control in cities including Beijing, Zhangjiakou and south of Beijing (Baoding, Langfang, Tianjin, and Tangshan) is effective for reducing haze episodes in the host cities. There is still a long way to make accurate daily fine particulate matter predictions on a seasonal-scale in advance; however, it could capture the trends in air quality in host cities around the OWG period three months ahead. The comparison of observations and predictions confirmed and highlighted the role of regional emission controls on the realization of the “OWG blue”.
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