Integrated assessment of potentially toxic elements in soil of the Kangdian metallogenic province: A two-point machine learning approach

Wantao Yang,Liankai Zhang,Bingbo Gao,Xiaojie Liu,Xingwu Duan, Chenyi Wang, Ya Zhang, Qiang Li,Lingqing Wang

Ecotoxicology and Environmental Safety(2024)

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摘要
The accumulation of potentially toxic elements in soil poses significant risks to ecosystems and human well-being due to their inherent toxicity, widespread presence, and persistence. The Kangdian metallogenic province, famous for its iron-copper deposits, faces soil pollution challenges due to various potentially toxic elements. This study explored a comprehensive approach that combinescombines the spatial prediction by the two-point machine learning method and ecological-health risk assessment to quantitatively assess the comprehensive potential ecological risk index (PERI), the total hazard index (THI) and the total carcinogenic risk (TCR). The proportions of copper (Cu), cadmium (Cd), manganese (Mn), lead (Pb), zinc (Zn), and arsenic (As) concentrations exceeding the risk screening values (RSVs) were 15.03%, 5.1%, 3.72%, 1.24%, 1.1%, and 0.13%, respectively, across the 725 collected samples. Spatial prediction revealed elevated levels of As, Cd, Cu, Pb, Zn, mercury (Hg), and Mn near the mining sites. Potentially toxic elements exert a slight impact on soil, some regions exhibit moderate to significant ecological risk, particularly in the southwest. Children face higher non-carcinogenic and carcinogenic health risks compared to adults. Mercury poses the highest ecological risk, while chromium (Cr) poses the greatest health hazard for all populations. Oral ingestion represents the highest non-oncogenic and oncogenic risks in all age groups. Adults faced acceptable non-carcinogenic risks. Children in the southwest region confront higher health risks, both non-carcinogenic and carcinogenic, from mining activities. Urgent measures are vital to mitigate Hg and Cr contamination while promoting handwashing practices is essential to minimize health risks.
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关键词
Potentially toxic elements,Ecological-health risk assessment,Spatial prediction,The two-point machine learning,Metallogenic province
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