Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis

Zhou, Wentao; Li, Zhen; Liu, Yunjia; Shen, Chongyang; Tang, Huaizhi; Huang, Yuanfang

doi:10.1016/j.jhazmat.2024.135868

Journal of Hazardous Materials

2024

DOI: 10.1016/j.jhazmat.2024.135868

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Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis

Wentao Zhou,

Zhen Li,

Yunjia Liu

et al.

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Cited by 3 publications

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Soil health assessment of dressing and smelting slag field based on heavy metal pollution-buffer-fertility three aspects

Fan,

Liang

2025

Journal of Hazardous Materials

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Soil health assessment of dressing and smelting slag field based on heavy metal pollution-buffer-fertility three aspects

Fan,

Liang

2025

Journal of Hazardous Materials

View full text Add to dashboard Cite

Identifying spatial drivers of soil heavy metal pollution risk integrating positive matrix factorization, machine learning, and multi-scale geographically weighted regression

Pan,

Sha,

Han

et al. 2025

Journal of Hazardous Materials

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Speciation Characteristics and Risk Assessment of Heavy Metals in Cultivated Soil in Pingshui Village, Zhaoping County, Hezhou City, Guangxi

Ma,

Wen,

Liu

et al. 2024

Applied Sciences

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In order to comprehensively understand the content, source, speciation characteristics, and risk of heavy metals in cultivated soil of Pingshui Village, Zhaoping County, Hezhou City, this study conducted measurements on the total amounts of Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg in 34 soil samples within the study area. Correlation analysis and principal component analysis were employed to investigate their sources. An improved BCR sequential extraction procedure was utilized to analyze the occurrence forms of eight heavy metals in soil samples. Ecological risks were evaluated using the geo-accumulation index (Igeo), potential ecological risk index (RI), and risk assessment code (RAC). The findings revealed that: (1) The soil heavy metals in the study area exhibited varying degrees of enrichment, primarily attributed to anthropogenic activities. (2) There was no significant difference in the speciation characteristics of the eight heavy metals in the soil of each sampling site in the study area, and the main components were all residual fraction, and the mild acid-soluble fraction of Cd and Zn accounted for a relatively high proportion in individual sampling sites, which should be paid attention to. (3) Through the results of three risk assessment methods, it is concluded that the heavy metal pollution of soil in the study area is serious, and continuous attention should be paid to the corresponding pollution prevention measures.

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Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis

Cited by 3 publications

References 57 publications

Soil health assessment of dressing and smelting slag field based on heavy metal pollution-buffer-fertility three aspects

Soil health assessment of dressing and smelting slag field based on heavy metal pollution-buffer-fertility three aspects

Identifying spatial drivers of soil heavy metal pollution risk integrating positive matrix factorization, machine learning, and multi-scale geographically weighted regression

Speciation Characteristics and Risk Assessment of Heavy Metals in Cultivated Soil in Pingshui Village, Zhaoping County, Hezhou City, Guangxi

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