典型文献
Significant contribution of secondary particulate matter to recurrent air pollution:Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China
文献摘要：
Particulate matter(PM)pollution in high emission regions will affect air quality,human health and climate change on both local and regional scales,and thus attract worldwide attention.In this study,a comprehensive study on PM2.5 and its chemical composition were performed in Yuncheng(the most polluted city of Fen-Wei Plain of China)from November 28,2020 to January 24,2021.The average concentration of PM2.5 was 87.8±52.0μg/m3,which were apparently lower than those observed during the same periods of past five years,at-tributable to the clean air action plan implemented in this region.NO3-and organic carbon(OC)were the dominant particulate components,which on average contributed 22.6％and 16.5％to PM2.5,respectively.The fractions of NO3-,NH4+,OC and trace metals increased while those of crustal materials and elemental carbon decreased with the degradation of PM2.5 pollution.Six types of PM2.5 sources were identified by the PMF model,including sec-ondary inorganic aerosol(35.3％),coal combustion(28.7％),vehicular emission(20.7％),elec-troplating industry(8.6％),smelt industry(3.9％)and dust(2.8％).Locations of each identified source were pinpointed based on conditional probability function,potential source contri-bution function and concentration weighted trajectory,which showed that the geographical distribution of the sources of PM2.5 roughly agreed with the areas of high emission.Overall,this study provides valuable information on atmospheric pollution and deems beneficial for policymakers to take informed action to sustainably improve air quality in highly polluted region.
文献关键词：
中图分类号：
作者姓名：
Yu Liu;Xiaojuan Xu;Xiaoyang Yang;Jun He;Wenjie Zhang;Xingang Liu;Dongsheng Ji;Yuesi Wang
作者机构：
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China;Atmosphere Sub-Center of Chinese Ecosystem Research Network,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100191,China;State Key Laboratory of Environmental Criteria and Risk Assessment,Chinese Research Academy of Environmental Sciences,Beijing 100012,China;Natural Resources and Environment Research Group,Department of Chemical and Environmental Engineering,University of Nottingham Ningbo China,Ningbo 315100,China;State Key Laboratory of Water Environment Simulation,School of Environment,Beijing Normal University,Beijing 100875,China
文献出处：
引用格式：
[1]Yu Liu;Xiaojuan Xu;Xiaoyang Yang;Jun He;Wenjie Zhang;Xingang Liu;Dongsheng Ji;Yuesi Wang-.Significant contribution of secondary particulate matter to recurrent air pollution:Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China)[J].环境科学学报（英文版）,2022(04):422-433
A类：
Yuncheng,troplating,smelt,Locations,deems
B类：
Significant,contribution,secondary,particulate,matter,recurrent,air,pollution,Evidence,from,situ,observation,most,polluted,city,Fen,Wei,Plain,China,Particulate,emission,regions,will,affect,quality,human,health,climate,change,both,local,regional,scales,thus,attract,worldwide,attention,In,this,study,comprehensive,PM2,its,chemical,composition,were,performed,November,January,average,concentration,was,which,apparently,lower,than,those,observed,during,same,periods,past,five,years,tributable,clean,plan,implemented,NO3,carbon,OC,dominant,components,contributed,respectively,fractions,NH4+,trace,metals,increased,while,crustal,materials,elemental,decreased,degradation,Six,types,sources,identified,by,PMF,model,including,inorganic,aerosol,coal,combustion,vehicular,elec,industry,each,pinpointed,conditional,probability,function,potential,weighted,trajectory,showed,that,geographical,distribution,roughly,agreed,areas,Overall,provides,valuable,information,atmospheric,beneficial,policymakers,take,informed,sustainably,improve,highly
AB值：
0.578907
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
