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利用SPAMS研究西安市重污染天气细颗粒物污染特征及来源
引用本文:闫璐璐,刘焕武,黄学敏,高健,张文杰.利用SPAMS研究西安市重污染天气细颗粒物污染特征及来源[J].环境科学研究,2018,31(11):1841-1848.
作者姓名:闫璐璐  刘焕武  黄学敏  高健  张文杰
作者单位:1.西安建筑科技大学环境与市政工程学院, 陕西 西安 710054
基金项目:国家自然科学基金项目(No.91544226)
摘    要:为了对西安市冬季重污染过程中的细颗粒物进行动态源解析,于2016年12月5-22日,利用SPAMS(单颗粒气溶胶质谱仪)在西安市城市运动公园开展连续观测.将观测期分为4个阶段,结合气象条件对不同阶段细颗粒物的污染特征进行分析比较.依据质谱特征,将所采集到的颗粒分为EC(元素碳)、OC(有机碳)、ECOC(混合碳)、HM(重金属)、LEV(左旋葡聚糖)、SiO3(矿尘)、K(钾)、Na(钠)、HOC(有机大分子)及Other(其他)类.结果表明:观测期间所采集到的OC类颗粒物数量最多,在重污染阶段OC、K和EC类颗粒物占颗粒总数的70%以上,是重污染天气的主要组成颗粒.在雾霾消散期,OC、LEV和SiO3类颗粒是主要类型颗粒物.根据颗粒物的化学类型及离子特征,利用PMF(正交矩阵因子分解)模型法得到6种污染源贡献率分别为27.7%(燃煤源)、22.3%(二次污染源)、20.4%(交通源)、10.4%(生物质燃烧源)、9.7%(工艺过程源)、6.5%(扬尘源)及3.0%(其他未知源).研究显示:在重污染阶段,燃煤源与交通源占比大幅上升,与二次污染源共同造成了此次重污染天气;在雾霾消散期,扬尘源及生物质燃烧源成为大气细颗粒物的主要污染源. 

关 键 词:单颗粒气溶胶质谱    细颗粒物    正交矩阵因子分解模型    来源解析
收稿时间:2018/1/30 0:00:00
修稿时间:2018/4/11 0:00:00

Characteristics and Source Apportionment of Fine Particles in Xi'an Using a Single Particle Aerosol Mass Spectrometer (SPAMS) during Heavy Pollution
YAN Lulu,LIU Huanwu,HUANG Xuemin,GAO Jian and ZHANG Wenjie.Characteristics and Source Apportionment of Fine Particles in Xi'an Using a Single Particle Aerosol Mass Spectrometer (SPAMS) during Heavy Pollution[J].Research of Environmental Sciences,2018,31(11):1841-1848.
Authors:YAN Lulu  LIU Huanwu  HUANG Xuemin  GAO Jian and ZHANG Wenjie
Institution:1.School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710054, China2.Xi'an Environmental Monitoring Station, Xi'an 710119, China3.Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Abstract:To study dynamically the source apportionment of fine particles in Xi''an during a heavy pollution period a single particle aerosol mass spectrometer (SPAMS) was applied in Xi''an City Sport Park for a continuous observation from 5th to 22nd December, 2016. The pollution characteristics of the fine particles in four different periods were analyzed and compared with different meteorological conditions. According to the mass spectral characteristics, the fine particles were divided into 10 classes of chemical composition:EC (element carbon), OC (organic carbon), ECOC (mixed carbon), HM (heavy metal), LEV (levoglucosan), SiO3, K, Na, HOC (heavy organic carbon) and other. The positive matrix factorization (PMF) method was used to identify the source apportionment of the collected fine particles, and the results from PMF indicated that there were six major sources and other unknown sources (3.0%) of the fine particles. The six major sources were coal combustion (27.7%), secondary formation (22.3%), traffic emission (20.4%), biomass burning (10.4%), industrial emission (9.7%) and dust pollution (6.5%). The results showed that during this observation, OC was the main component of fine particles in Xi''an. In heavy pollution periods, OC,K and EC accounted for more than 70% of the total collected particles, and LEV and SiO3 were the main component of particles in clean days. Coal combustion, traffic emission and secondary formation were the major sources during heavy pollution period, while dust pollution and biomass burning dominated in clean days.
Keywords:single particle aerosol mass spectrometer  fine particles  positive matrix factorization  source apportionment
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