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首页> 中文期刊> 《气象学报：英文版》 >Dominant Synoptic Patterns and Their Relationships with PM2.5 Pollution in Winter over the Beijing–Tianjin–Hebei and Yangtze River Delta Regions in China

Dominant Synoptic Patterns and Their Relationships with PM2.5 Pollution in Winter over the Beijing–Tianjin–Hebei and Yangtze River Delta Regions in China

         
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This paper concerns about the episodes of PM2.5 pollution that frequently occur in China in winter months.The severity of PM2.5 pollution is strongly dependent on the synoptic-scale atmospheric conditions.We combined PM2.5 concentration data and meteorological data with the Hybrid Single Particle Lagrangian Integrated Trajectory model(HYSPLIT4)to investigate the dominant synoptic patterns and their relationships with PM2.5 pollution over the Beijing–Tianjin–Hebei(BTH)and Yangtze River Delta(YRD)regions in the winters of 2014–17.The transport of PM2.5 from the BTH to YRD regions was examined by using cluster analysis and HYSPLIT4.It is found that the level of PM2.5 pollution over the BTH region was higher than that over the YRD region.The concentration of PM2.5 in the atmosphere was more closely related to meteorological factors over the BTH region.The episodes of PM2.5 pollution over the BTH region in winter were related to weather patterns such as the rear of a high-pressure system approaching the sea,a high-pressure field,a saddle pressure field,and the leading edge of a cold front.By contrast,PM2.5 pollution episodes in the YRD region in winter were mainly associated with the external transport of cold air,a high-pressure field,and a uniform pressure field.Cluster analysis shows that the trajectories of PM2.5 were significantly different under different weather patterns.PM2.5 would be transported from the BTH to the YRD within 48 h when the PM2.5 pollution episodes were associated with three different kinds of weather patterns:the rear of a highpressure system approaching the sea,the high-pressure field,and the leading edge of a cold front over the BTH region.This suggests a possible method to predict PM2.5 pollution episodes based on synoptic-scale patterns.

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