安徽省沿江地区PM2.5污染日分类及特征

Classification and Characteristics of PM2.5 Pollution Days along the Yangtze River in Anhui Province

  • 摘要: 为探究安徽省沿江地区PM2.5污染成因,利用2015—2023年PM2.5浓度、地面气象要素观测数据、ERA5再分析和GDAS1资料,基于后向轨迹经过地区的PM2.5污染状况和天气形势,对污染日进行分类和特征分析。结果表明:该地区年均污染日46.2 d,污染日总数和轻、中度污染日数均呈显著减少趋势。污染日可分为外源输入型、静稳累积型两类。前者数量少,在重度以上污染日中占比多,与南下冷空气密切相关,其带来的PM2.5输入是造成该地区重污染的重要原因。后者数量多,在轻、中度污染日中占比多,多与均压场、辐合风场、反气旋等天气形势相关,无冷空气活动,以本地PM2.5累积为主,造成的污染相对较轻。

     

    Abstract: To explore the causes of PM2.5 pollution in the areas along the Yangtze River in Anhui Province, this study utilized PM2.5 concentration, ground meteorological element observation data, ERA5 reanalysis, and GDAS1 data from 2015 to 2023. Based on the PM2.5 pollution status and synoptic situations in the traversed areas of backward trajectories, pollution days were classified and their characteristics analyzed. The results showed that the average annual number of pollution days in this region was 46.2 days, with the total number of pollution days and the number of light and moderate pollution days both showing a significant decreasing trend. Pollution days can be divided into two categories: external input type and static and stable accumulation type. The former, though less frequent, accounted for a larger proportion of severe and above pollution days, and was closely related to the southward movement of cold air; the input of PM2.5 it brought was a major cause of heavy pollution in this region. The latter was more numerous and dominated light and moderate pollution days, often associated with synoptic situations such as uniform pressure fields, convergent wind fields, and anticyclones. With no cold air activity, it was primarily characterized by local PM2.5 accumulation, resulting in relatively light pollution.

     

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