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

Author

Listed:
  • Jie Yang

    (State Key Laboratory of Petroleum Pollution Control, Beijing 102206, China
    College of Water Sciences, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Groundwater Pollution Control and Remediation, Ministry of Education, Beijing 100875, China)

  • Yunlong Wang

    (College of Water Sciences, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Groundwater Pollution Control and Remediation, Ministry of Education, Beijing 100875, China)

  • Rui Zuo

    (College of Water Sciences, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Groundwater Pollution Control and Remediation, Ministry of Education, Beijing 100875, China)

  • Kunfeng Zhang

    (State Key Laboratory of Petroleum Pollution Control, Beijing 102206, China)

  • Chunxing Li

    (State Key Laboratory of Petroleum Pollution Control, Beijing 102206, China)

  • Quanwei Song

    (State Key Laboratory of Petroleum Pollution Control, Beijing 102206, China)

  • Xianyuan Du

    (State Key Laboratory of Petroleum Pollution Control, Beijing 102206, China)

Abstract

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.

Suggested Citation

  • Jie Yang & Yunlong Wang & Rui Zuo & Kunfeng Zhang & Chunxing Li & Quanwei Song & Xianyuan Du, 2023. "Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils," IJERPH, MDPI, vol. 20(4), pages 1-21, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:3163-:d:1064999
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    References listed on IDEAS

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    1. Hassan Amjad & Shanawar Hamid & Yasir Niaz & Muhammad Ashraf & Umair Yasir & Amna Chaudhary & Ali Arsalan & Mian Waqar Daud, 2019. "Efficiency Assessment Of Wastewater Treatment Plant: A Case Study Of Pattoki, District Kasur, Pakistan," Earth Sciences Pakistan (ESP), Zibeline International Publishing, vol. 3(2), pages 01-04, October.
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