基于多参数特征比值构建大气颗粒物污染类型快速识别方法

Method of quickly identifying the type of particulate pollution based on multiparameter feature ratio

识别颗粒物污染类型是全面厘清污染成因和进行动态源解析的基础。针对北方工业城市包头市的大气污染特征及空气质量监测数据,确定了沙尘型、扬尘型、二次生成与累积型和其他型4种污染类型。根据包头市所处环境空气功能区,选择二级质量浓度限值对污染物质量浓度数据进行归一化处理,进而计算多种污染物特征比值和污染类型的判别阈值,从而快速判别出包头市4种颗粒物污染类型的对应时段。结果表明:基于多参数特征比值构建大气颗粒物污染类型快速识别方法能很好地区分扬尘型和沙尘型污染,对沙尘型污染识别的准确率可达80%,且识别出扬尘型污染日较高风速的气象条件有利于扬尘形成;二次生成与累积型和其他型污染日与历史特征雷达图筛选的偏二次型和燃煤型污染日重合率达到89%。沙尘型污染日的颗粒物质量浓度对2019年包头市PM10超标的贡献率最高,累积型与二次生成型对PM2.5的贡献率最高,因此控制二次生成与累积型污染可以有效改善当地的细颗粒污染。基于多参数特征比值构建大气颗粒物污染类型快速识别方法简化了颗粒物的重污染类型识别过程,可快速识别超标天的污染类型,为颗粒物污染成因的快速分析提供了科学依据。

Quickly identifying the air pollution type is a basic process for revealing the pollution cause of the formation and conducting the dynamic source apportionment.In this study,we propose a method for quantitatively identifying the air pollution type at a rapid rate and then validate the reasonableness of this method by choosing Baotou City with clear and specific pollution characteristics.Firstly,four particulate pollution types including sand dust,fugitive dust,second generation and accumulation,and other type were confirmed based on the air pollution characteristics and quality monitoring data of Baotou,an industrial city in northern China.Then,the second standard of ambient air pollutants in China was used to calculate the characteristic ratio and threshold of pollution factors by considering the ambient air function area of Baotou,which helped quickly identify the periods of four particulate pollution types.Finally,based on the data of environmental monitoring on ambient air during 2019,it was validated that the recognition accuracy could reach 80%for the identification of sand dust type and the fugitive dust type days matched the meteorological characteristics correspondingly,which means this method could well distinguish sand dust and fugitive dust type.And the second generation and accumulation and the other type reach an 89 percent of coincidence rate by comparing with the results given by using of historical characteristic radar chart method.The contribution of sand dust type to exceedance of the second standard of PM10 in China was the highest while the second generation and accumulation type contributed most to PM2.5 in 2019,showing that local fine particle pollution can be effectively reduced by controlling the pollution of second generation and accumulation type.We found that this method not only simplifies the processes of identifying types and periods but also quickly identifies the pollution types that exceed standard days,which provides a scientific reference for rapid analysis of causes of particulate pollution.