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Evaluation for the heavy metal risk in fine particulate matter from the perspective of urban energy and industrial structure in China: A meta-analysis

机译:中国城市能源与产业结构视角下的细颗粒物重金属风险评价:Meta分析

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摘要

The distribution of the heavy metals (HMs) in fine particulate matter (PM2.5) with the evolution of the urban industrial structure is attracting much attention in developing countries. In this study, a meta-analysis was conducted to re-evaluate the pollution by 7 HMs (Pb, Cd, As, Cu, Mn, Cr and Ni) in the PM2.5 from 14 main cities in China. The standard mean difference (SMD) was served as the effect size. The most severe pollution by Pb, Cd, As, Cu, Mn, Cr and Ni was found in Foshan, Jinan, Wuhan, Foshan, Xi'an, Jinan and Shenzhen, respectively. The SMD5 of each HM from the 14 cities were merged using the random-effect model, indicating that As was the HM causing the most pollution, followed by Mn, Pb, Cd, Ni, Cu and Cr. The HM SMD5 as pollution indices were connected to city factors (energy, industry, traffic and environmental policy) using principal component analysis (PCA). General emission sources for HMs were assessed on the city scale, and it was concluded that coal consumption was still the main source for Pb, Cd, As, Cu and Mn pollution but electronic manufacturing industries were new sources responsible for Cr and Ni pollution. Thereinto, electronic manufacturing affected Ni pollution strongly, which was supported by the significance of the meta-regression analysis and the chemical speciation of Ni in PM2.5 compared to electronic waste. Thus, coal combustion mainly contributed to atmospheric HM pollution but there were also contributions from electronic manufacturing. Our results provide a novel method to assess the source and risk of atmospheric HMs accompanying urban industrial changes. (C) 2019 Elsevier Ltd. All rights reserved.
机译:随着城市产业结构的演变,细颗粒物(PM2.5)中的重金属(HMs)的分布引起了发展中国家的关注。在这项研究中,进行了荟萃分析,以重新评估来自中国14个主要城市的PM2.5中7种重金属(铅,镉,砷,铜,锰,铬和镍)的污染。标准均差(SMD)用作效应量。铅,镉,砷,铜,锰,铬和镍的污染最严重,分别位于佛山,济南,武汉,佛山,西安,济南和深圳。使用随机效应模型对来自14个城市的每个HM的SMD5进行了合并,表明As是造成最大污染的HM,其次是Mn,Pb,Cd,Ni,Cu和Cr。使用主成分分析(PCA)将HM SMD5作为污染指数与城市因素(能源,工业,交通和环境政策)联系起来。在城市范围内对重金属的一般排放源进行了评估,得出的结论是,煤炭消费仍然是铅,镉,砷,铜和锰污染的主要来源,而电子制造业是造成铬和镍污染的新来源。其中,电子制造业对镍污染的影响很大,与电子废物相比,元回归分析和PM2.5中Ni的化学形态的重要性支持了这一点。因此,煤炭燃烧主要导致大气中的HM污染,但电子制造也有贡献。我们的结果提供了一种新颖的方法来评估伴随城市工业变化的大气HM的来源和风险。 (C)2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Journal of Cleaner Production》 |2020年第2期|118597.1-118597.12|共12页
  • 作者

  • 作者单位

    Shanghai Univ Sch Environm & Chem Engn 99 Shangda Rd Shanghai 200444 Peoples R China;

    Shanghai Univ Sch Environm & Chem Engn 99 Shangda Rd Shanghai 200444 Peoples R China|Shanghai Univ Sch Econ 99 Shangda Rd Shanghai 200444 Peoples R China;

    Shanghai Univ Sch Econ 99 Shangda Rd Shanghai 200444 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    PM2.5; Heavy metals; Source apportionment; Meta-analysis; Chemical speciation;

    机译:PM2.5;重金属;来源分配;荟萃分析;化学形态;
  • 入库时间 2022-08-18 05:19:47

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