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渝东南典型城区冬季一次罕见的PM_(2.5)污染过程及溯源分析 被引量:1

Characteristics and Potential Source Contribution of PM_(2.5) During a Continuing Pollution Process in Typical Urban Area of Southeast Chongqing
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摘要 2020年12月底,以生态旅游业为主的重庆市渝东南地区出现了一次较为罕见的PM_(2.5)污染过程,持续时间长且污染程度重。以渝东南地区武隆区为例,应用污染特征雷达图、后向轨迹模型及潜在源污染贡献估算等方法分析了本次PM_(2.5)污染的特征及来源,结果表明:(1)在污染前期主要受扬尘、燃煤和机动车等污染排放影响,污染源直接排放贡献较大;中、后期污染受二次颗粒物影响显著,扬尘影响也较为明显。(2)污染期间的气流轨迹均为短距离输送,轨迹主要来自东北方向(65%)。(3)除自身污染排放贡献外,渝东北地区和主城都市区是武隆区PM_(2.5)污染的主要潜在源区,对武隆区传输贡献占比超50%。 At the end of December 2020,a relatively rare PM_(2.5) pollution process occurred in the southeast of Chongqing,which is dominated by eco-tourism,with a long duration and heavy pollution degree.Taking Wulong District in southeast Chongqing as an example,the characteristics and sources of PM_(2.5) pollution were analyzed by using radar chart of pollution characteristics,backward trajectory model and potential source contribution.The results showed that the emissions of dust,coal burning and motor vehicles were the main sources of PM_(2.5) at the early stage of pollution process,and the contributions of primary sources were higher than others.However,PM_(2.5) was significantly affected by the secondary particulate formation and dust source in the middle and later stages.The air trajectories were short transported distances from the northeast direction(65%)and the northwest direction(35%)during the pollution period.Furthermore,besides the contribution of local pollution sources,the northeast of Chongqing and major urban areas were the main potential sources of PM_(2.5),accounting for more than 50%during the pollution period.
作者 张凤 李振亮 ZHANG Feng;LI Zhenliang(Chongqing Academy of Eco-Environmental Science,Chongqing 401147,China;Environmental Monitoring Station of Wulong District,Chongqing 500156,China;Key Laboratory for Urban Atmospheric Environment Integrated Observation&Pollution Prevention and Control of Chongqing,Chongqing 401147,China)
出处 《中国环境监测》 CAS CSCD 北大核心 2023年第5期95-104,共10页 Environmental Monitoring in China
基金 国家重点研发计划专项(2018YFC0214005) 重庆市科研机构绩效激励引导专项(cstc2019jxjl20006)。
关键词 细颗粒物 污染特征 轨迹聚类 潜在源贡献 PM_(2.5) pollution characteristics trajectory clustering potential source contribution
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