摘要
为探讨成都市冬季大气PM2.5元素的污染特征及来源,于2010年和2018年冬季采集大气PM2.5样品,利用X射线荧光光谱法分析得到18种元素的含量,并运用富集因子法和主成分分析法分析其来源。结果表明:成都市冬季大气PM2.5质量浓度处于较高的污染水平,2010年和2018年冬季PM2.5质量浓度分别为225.5μg·m-3、115.3μg·m-3。2010年冬季成都元素质量浓度为21.2μg·m-3;而2018年PM2.5中元素质量浓度为15.0μg·m-3。富集因子分析表明,Sb、S、Cl、Zn、Pb、Cu等元素显著富集,成都2018年冬季PM2.5中Cl、Cu、Zn、Ba和Pb的富集程度较2010年有明显减轻。主成分分析表明,成都冬季PM2.5中元素的主要来源是燃煤和生物质燃烧、交通源、扬尘以及工业源。成都2018年冬季相对于2010年在PM2.5质量浓度以及PM2.5中的大部分元素富集程度都有一定程度的下降,但PM2.5污染水平依然较高。
In order to investigate the pollution characteristics and sources of inorganic elements in winter atmospheric PM2.5 of Chengdu.PM2.5 samples were collected in winter of 2010 and 2018,and the mass concentration of elements in PM2.5 was determined by X-ray fluorescence spectrometry.The source of elements was analyzed by enrichment factor and principal component analysis.The results showed that the atmospheric PM2.5 concentration in Chengdu was at a high pollution level in winter.The mass concentration of PM2.5 in Chengdu in 2010 and 2018 was 225.5 and 115.3μg·m-3.The mass concentration of elements in Chengdu was 21.2μg·m-3 in winter of 2010 and 15.0μg·m-3 in PM2.5 of 2018.The enrichment factor analysis showed that Sb,S,Cl,Zn,Pb,Cu were heavily enriched.The enrichment degree of Cl,Cu,Zn,Ba and Pb in PM2.5 in winter 2018 of Chengdu was significantly lower than that in 2010 and there were still different degrees of enrichment.It showed that the main sources of PM2.5 in Chengdu were coal combustion and biomass combustion,traffic sources,dust lifting and industrial sources.Compared with the mass concentration of PM2.5 and most of the elements in 2010,they in 2018 decreased to a certain extent,but the level of PM2.5 pollution was still high.
作者
郭佳灵
李友平
刘欢
李敏
刘漫琦
Guo Jialing;Li Youping;Liu Huan;Li Min;Liu Manqi(College of Environmental Science and Engineering,China West Normal University,Nanchong Sichuan 637009,China)
出处
《环境与发展》
2020年第6期143-146,148,共5页
Environment & Development
基金
化学合成与污染控制四川省重点实验室项目(SCPC2014-4-2)
西华师范大学英才科研基金项目(17YC138)。
关键词
PM2.5
元素
富集因子
主成分分析
成都
PM2.5
Inorganic elements
Enrichment factor
Principal component analysis
Chengdu
