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Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils

Potentially toxic element (PTE) contamination in soils has serious impacts on ecosystems. However, there is no consensus in the field of assessment and monitoring of contaminated sites in China. In this paper, a risk assessment and pollution monitoring method for PTEs was proposed and applied to a m...

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Autores principales: Yang, Jie, Wang, Yunlong, Zuo, Rui, Zhang, Kunfeng, Li, Chunxing, Song, Quanwei, Du, Xianyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963655/
https://www.ncbi.nlm.nih.gov/pubmed/36833857
http://dx.doi.org/10.3390/ijerph20043163
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author Yang, Jie
Wang, Yunlong
Zuo, Rui
Zhang, Kunfeng
Li, Chunxing
Song, Quanwei
Du, Xianyuan
author_facet Yang, Jie
Wang, Yunlong
Zuo, Rui
Zhang, Kunfeng
Li, Chunxing
Song, Quanwei
Du, Xianyuan
author_sort Yang, Jie
collection PubMed
description Potentially toxic element (PTE) contamination in soils has serious impacts on ecosystems. However, there is no consensus in the field of assessment and monitoring of contaminated sites in China. In this paper, a risk assessment and pollution monitoring method for PTEs was proposed and applied to a mining site containing As, Cd, Sb, Pb, Hg, Ni, Cr, V, Zn, Tl, and Cu. The comprehensive scoring method and analytical hierarchical process were used to screen the priority PTEs for monitoring. The potential ecological risk index method was used to calculate the risk index of monitoring point. The spatial distribution characteristics were determined using semi-variance analysis. The spatial distribution of PTEs was predicted using ordinary kriging (OK) and radial basis function (RBF). The results showed that the spatial distribution of As, Pd, and Cd are mainly influenced by natural factors, while Sb and RI are influenced by both natural and human factors. OK has higher spatial prediction accuracy for Sb and Pb, and RBF has higher prediction accuracy for As, Cd, and RI. The areas with high ecological risk and above are mainly distributed on both sides of the creek and road. The optimized long-term monitoring sites can achieve the monitoring of multiple PTEs.
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spelling pubmed-99636552023-02-26 Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils Yang, Jie Wang, Yunlong Zuo, Rui Zhang, Kunfeng Li, Chunxing Song, Quanwei Du, Xianyuan Int J Environ Res Public Health Article Potentially toxic element (PTE) contamination in soils has serious impacts on ecosystems. However, there is no consensus in the field of assessment and monitoring of contaminated sites in China. In this paper, a risk assessment and pollution monitoring method for PTEs was proposed and applied to a mining site containing As, Cd, Sb, Pb, Hg, Ni, Cr, V, Zn, Tl, and Cu. The comprehensive scoring method and analytical hierarchical process were used to screen the priority PTEs for monitoring. The potential ecological risk index method was used to calculate the risk index of monitoring point. The spatial distribution characteristics were determined using semi-variance analysis. The spatial distribution of PTEs was predicted using ordinary kriging (OK) and radial basis function (RBF). The results showed that the spatial distribution of As, Pd, and Cd are mainly influenced by natural factors, while Sb and RI are influenced by both natural and human factors. OK has higher spatial prediction accuracy for Sb and Pb, and RBF has higher prediction accuracy for As, Cd, and RI. The areas with high ecological risk and above are mainly distributed on both sides of the creek and road. The optimized long-term monitoring sites can achieve the monitoring of multiple PTEs. MDPI 2023-02-10 /pmc/articles/PMC9963655/ /pubmed/36833857 http://dx.doi.org/10.3390/ijerph20043163 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Jie
Wang, Yunlong
Zuo, Rui
Zhang, Kunfeng
Li, Chunxing
Song, Quanwei
Du, Xianyuan
Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils
title Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils
title_full Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils
title_fullStr Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils
title_full_unstemmed Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils
title_short Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils
title_sort research on risk assessment and contamination monitoring of potential toxic elements in mining soils
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963655/
https://www.ncbi.nlm.nih.gov/pubmed/36833857
http://dx.doi.org/10.3390/ijerph20043163
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