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深圳市大气PM2.5来源解析
引用本文:孙天乐,邹北冰,黄晓锋,申航印,戴静,何凌燕.深圳市大气PM2.5来源解析[J].中国环境科学,2019,39(1):13-20.
作者姓名:孙天乐  邹北冰  黄晓锋  申航印  戴静  何凌燕
作者单位:1. 北京大学深圳研究生院环境与能源学院城市人居环境科学与技术重点实验室, 广东 深圳 518055; 2. 深圳市环境监测中心站, 广东 深圳 518049
基金项目:国家自然科学基金资助项目(91744202;41622304);深圳市科技计划(JCYJ20170412150626172)
摘    要:为识别和量化深圳市大气PM2.5的污染来源,2014年3,6,9,12月分别在5个站点采集PM2.5的膜样品并进行质量浓度及组分分析,利用正向矩阵因子解析(PMF)模型对其主要来源和时空变化规律进行了解析.结果表明,2014年深圳市PM2.5年均浓度为35.7 μg/m3,其中机动车源、二次硫酸盐生成、二次有机物生成和二次硝酸盐生成是最主要的来源,质量浓度贡献比例分别为27%、21%、12%和10%;地面扬尘、生物质燃烧源、远洋船舶源、工业源、海洋源、建筑尘和燃煤源贡献比例达2%~6%.各个源贡献的时空变化特征表明,二次硫酸盐生成、生物质燃烧源、二次有机物生成、工业源、远洋船舶源和海洋源显示出明显的区域源特征,机动车源、二次硝酸盐生成、燃煤源、地面扬尘和建筑尘具有显著的本地源特征.

关 键 词:源解析  正向矩阵因子解析(PMF)  细颗粒物(PM2.5)  深圳  
收稿时间:2018-06-05

Source apportionment of PM2.5 pollution in Shenzhen
SUN Tian-le,ZOU Bei-bing,HUANG Xiao-feng,SHEN Hang-yin,DAI Jing,HE Ling-yan.Source apportionment of PM2.5 pollution in Shenzhen[J].China Environmental Science,2019,39(1):13-20.
Authors:SUN Tian-le  ZOU Bei-bing  HUANG Xiao-feng  SHEN Hang-yin  DAI Jing  HE Ling-yan
Institution:1. School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen 518055, China; 2. Shenzhen Environment Monitoring Center, Shenzhen 518049, China
Abstract:In order to identify main sources and their characteristics of PM2.5 in atmosphere, filter samples of PM2.5 were collected at five receptors in Shenzhen during March, June, September and December in 2014. Mass concentrations and chemical compositions were analyzed, then the positive matrix factorization (PMF) model was applied for source apportionment. The results showed the annual mean concentration of PM2.5 reached 35.7μg/m3 in Shenzhen in 2014, with vehicle emissions, secondary sulfate, secondary organic aerosol (SOA) and secondary nitrate identified as the major sources, contributing 27%, 21%, 12%, and 10% to PM2.5, respectively. Fugitive dust, biomass combustion, ship emissions, industrial emissions, marine emissions, building dust and coal burning each contributed 2%~6%.The tempo-spatial variations of sources revealed that secondary sulfate, biomass combustion, SOA, industrial emissions, ship emissions and marine emissions had obvious regional pollution characteristics; however, vehicle emissions, secondary nitrate, coal burning, fugitive dust and building dust showed obvious local emission characteristics.
Keywords:source apportionment  positive matrix factorization (PMF)  fine particle matter(PM2  5)  Shenzhen  
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