4.7 Article

Prediction of high-risk areas of soil heavy metal pollution with multiple factors on a large scale in industrial agglomeration areas

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 808, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.151874

关键词

Heavy metal; Industrial agglomeration areas; Geodetector; High-risk areas; Prediction; Interaction

资金

  1. National Key Research and Development Programof China [2018YFC1800203]
  2. National Key Research and Development Program of China [2018YFF0213401]

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Industrialization has increased the risk of heavy metal pollution in soil. This study explored the factors and interactions affecting the distribution of heavy metals in a typical area, and predicted high-risk areas of heavy metal pollution in the Xiangjiang River basin. High-risk areas were primarily concentrated in the upper and middle reaches, with significant overlapping of multiple heavy metals in certain regions.
Heavy metals in soil are a great threat to ecosystems and human health. The rapid development of industrialization has created a serious risk of heavy metal pollution in soil. The study took the industrial-intensive Dahetan subbasin as the typical area. The factors and interactions that affected the distribution of soil heavy metals (Cd, Hg, As, Pb and Cr) in the typical area were explored based on the Geodetector model. The analysis results were extended to predict high-risk areas of heavy metal pollution in the soil in the Xiangjiang River basin. The results showed that Cd, As and Pb were significantly affected by local industrial and mining activities, and Hg and Cr were primarily affected by natural fac-tors, such as pH and soil type. Compared to a single factor, the interaction between factors had a greater impact on the concentration of heavy metals. The high-risk areas of soil heavy metal pollution in the Xiangjiang River basin were primarily concentrated in the upper reaches and middle reaches.Significant overlapping of high-risk areas of mul -tiple heavy metals occurred in the west, middle and south of the basin. The spatial visualization of the high-risk areas was realized, and the influence of several factors was integrated via layer superposition. This study proposes a new idea to predict the high-risk areas of soil pollution in large-scale areas to provide a reference for the regional prevention and control of soil pollution.

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