Literature DB >> 31704412

An integrated approach to quantifying ecological and human health risks from different sources of soil heavy metals.

Hui-Hao Jiang1, Li-Mei Cai2, Han-Hui Wen3, Guo-Cheng Hu4, Lai-Guo Chen4, Jie Luo1.   

Abstract

Heavy metals (HMs) in soil cause adverse effects on ecosystem and human health. Quantifying ecological risk and human health risk (HHR) from sources can determine priority sources and help to mitigate the risks. In this research, geostatistics and positive matrix factorization (PMF) were used to identify and quantify the sources of soil HMs; and then ecological risk and HHR from different sources under woodland, construction land and farmland were quantitatively calculated by combining the potential ecological risk index (RI) and HHR assessment models with PMF model. Taking Jiedong District as an example, four sources were quantitatively apportioned, which were agricultural practices (23.08%), industrial activities (29.10%), natural source (22.87%) and traffic emissions (24.95%). For ecological risk, industrial activities were the greatest contributor, accounting for about 49.71%, 48.11% and 47.15% under construction land, woodland and farmland, respectively. For non-carcinogenic risk, agricultural practices were the largest source under woodland and farmland, while industrial activities were the largest source under construction land. As for carcinogenic risk, no matter which kind of land use, agricultural practices were the largest source. In addition, the health risks of children, including non-carcinogenic and carcinogenic risks, were higher than those of adults, and the trends in health risks for children and adults were similar. The integrated approach was useful to evaluate ecological risk and HHR quantification from sources under different land use, thereby providing valuable suggestions for reducing pollution and protecting human health from the sources.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Heavy metals; Land use; Priority sources; Risks quantification; Source apportionment

Mesh:

Substances:

Year:  2019        PMID: 31704412     DOI: 10.1016/j.scitotenv.2019.134466

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  10 in total

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Journal:  J Environ Health Sci Eng       Date:  2022-01-10

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Authors:  Wanjiang She; Linghui Guo; Jiangbo Gao; Chi Zhang; Shaohong Wu; Yuanmei Jiao; Gaoru Zhu
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Authors:  Hatice Kubra Gul; Gulen Gullu; Parisa Babaei; Afsoun Nikravan; Perihan Binnur Kurt-Karakus; Guray Salihoglu
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Authors:  Xiaohui Chen; Mei Lei; Shiwen Zhang; Degang Zhang; Guanghui Guo; Xiaofeng Zhao
Journal:  Int J Environ Res Public Health       Date:  2022-06-16       Impact factor: 4.614

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Authors:  Lu Gan; Jiangping Wang; Mengyun Xie; Bokai Yang
Journal:  Sci Rep       Date:  2022-10-12       Impact factor: 4.996

  10 in total

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