受体模型在湖泊沉积物中PAHs、PFASs和OCPs源解析比较

何卓识; 李超灿; 张靖天; 马春子; 张含笑; 许秋瑾; 张新波; 霍守亮

doi:10.3969/j.issn.1674-991X.2018.03.031

受体模型在湖泊沉积物中PAHs、PFASs和OCPs源解析比较

doi: 10.3969/j.issn.1674-991X.2018.03.031

^1. 中国环境科学研究院,北京 100012
^2. 天津城建大学环境与市政工程学院,天津 300384

详细信息

作者简介:
何卓识(1987—),女,工程师,硕士,主要研究方向为区域水环境质量演变, zhuoshihe@163.com

通讯作者:
许秋瑾 E-mail: xuqj@craes.org.cn

中图分类号: X524
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出版历程
- 收稿日期: 2018-01-15
- 刊出日期: 2018-05-20

Analysis and comparison of PAHs, PFASs and OCPs sources in lake sediments by receptor model

^1. Chinese Research Academy of Environmental Science, Beijing 100012, China
^2. School of Environmental and Municipal Engineering, Tianjin Chenjian University, Tianjin 300384, China

More Information

Corresponding author: Qiujing XU E-mail: xuqj@craes.org.cn

摘要

摘要: 受体模型是一类主要用于空气污染溯源的源解析方法,在沉积物中的应用研究较少。正定矩阵因子分析模型(positive matrix factorization,PMF)、Unmix模型和主成分分析-多元线性回归模型(principal component analysis-multiple linear regression,PCA-MLR)是3种应用较成熟的大气源解析模型。以江苏省、安徽省的湖泊沉积物为研究对象,分别使用3种模型对采集沉积物样品中不同种类的半挥发性有机污染物多环芳烃(polycyclic aromatic hydrocarbons,PAHs)、全氟化合物(perfluoroalkyl substances,PFASs)、有机氯农药(organochlorine pesticides,OCPs)进行源解析,并通过对比3种模型结果的来源、贡献和拟合效果,探索模型在沉积物中污染物源解析中的应用。结果表明:不同模型对3类污染物的溯源均呈现出一致的解析结果,并且不同模型计算所得的模拟值与实测值拟合结果良好,在沉积物中污染物源解析得到较好应用。源解析结果表明:研究区沉积物中PAHs的来源主要有3种,分别为交通排放源,煤炭燃烧,天然气、柴油燃烧源;PFASs来源主要有3种,分别是氟化物加工助剂、树脂涂层、金属电镀工业源,纺织、贵金属、涂料工业排放源,纸质食品包装工业源;OCPs来源主要是滴滴涕和六氯环己烷(hexachlorocyclohexane,BHC)的历史残留,以及少量的异狄氏剂醛、氯丹和硫丹的贡献。PMF模型可以根据输入数据的不确定性赋予数据相应的权重。Unmix模型可以筛选出源信息较为明确的物质进入模型中。PCA-MLR模型可以定量的说明聚类分析的结果。应用多种模型进行污染物源解析可以使模型优缺点互补,消除单一模型局限性,更准确地完成沉积物中的污染物源解析。
- 受体模型 /
- 源解析 /
- 沉积物 /
- 半挥发性有机污染物
Abstract: Receptor models were typically used in air pollution studies and few publications are available for receptor models that consider the details of parameters and procedures in evaluating the trace organic pollutants in sediments. PMF, Unmix and PCA-MLR are three receptor modes which have been widely used in source apportionment analysis in air pollution study. The sediment samples were collected from seven lakes in Jiangsu and Anhui provinces. Three models were applied to analyze the source apportionment of different semi volatile organic pollutants, polycyclic aromatic hydrocarbons (PAHs), perfluoroalkyl substances (PFASs) and organochlorine pesticides (OCPs). The aims of this study were to explore the applications of the three receptor models in the sediment pollution, based on a comparison of their modeling results. The three models exhibit consistent results, and the simulated values and measured values fit well, indicating that these models are well applied in the source apportionment of sediment pollutants. The results show that PAHs in the sediment in the study area are mainly from three sources, including vehicle exhaust, coal combustion and kerosene combustion. There are three main sources of PFASs in the sediment, including fluoropolymer processing aid, fluororesin coating and metal plating, textile treatments, precious metals and coatings industry, and food paper packing. The source of OCPs is mainly pesticide residues, including DDTs, hexachlorocyclohexane(BHC), and some endrin aldehyde, chlordane and sulfudan. Among the three receptor models, PMF can give corresponding weight to the data based on the uncertainty of the input data, Unmix has advantage of selecting indicators associated to specific sources into the model, while PCA-MLR can quantify the results of cluster analysis. Using multiple models to analyze the source apportionment of sediment pollutant can make the models complementary and the results more accurate, avoiding the limitation of a single model.
- receptor models /
- source apportionment /
- sediment /
- semi volatile organic pollutants

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