Characteristics, Ecological Risks and Source Analysis of Soil Heavy Metal Pollution in the Huangshi Lion Mountain Mining Area

To reveal the enrichment characteristics, spatial patterns, ecological risks, and sources of heavy metals in surface soil of the Lion Mountain mining area, 38 topsoil samples were analyzed for Cu, Fe, Mn, Pb, and Zn. Using pollution-index evaluation, Hakanson ecological-risk assessment, inverse distance weighting (IDW), Z-score/IQR outlier diagnosis, Voronoi verification, and PCA source identification, we found that Cu, Pb, Zn, and Mn exceeded the Hubei provincial background, while Fe was about twice its background but remained in the uncontaminated to moderate contamination grade. Cu had the highest screening exceedance rate (36.84%), while Pb dominated the ecological risk despite a sub-screening mean Pi, driven by an extreme Pb outlier. The regional Nemero index was 7.76 (severe contamination) in the full dataset and 2.49 (moderate contamination) after excluding the outlier. The comprehensive ecological risk index was 25.87 under the Hubei background and 42.05 under the local background, both at Slight risk, with Pb as the dominant contributor. PCA suggested that Cu-Fe-Zn were likely controlled by the mineralization parent material, Pb likely represented an anthropogenic signal requiring further verification, and Zn had dual sources. These findings show that a single extreme value can dominate regional contamination grading without altering the underlying spatial structure, providing a methodological reference for the integrated framework of statistical outlier diagnosis, spatial clustering verification, and interpolation sensitivity assessment in mining-area soil studies.

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Publication Details

Journal
Sustainability
Published
2026-10-19
DOI
https://doi.org/10.3390/su182010603
Primary Topic
Heavy metals in environment
Type
article
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article

Characteristics, Ecological Risks and Source Analysis of Soil Heavy Metal Pollution in the Huangshi Lion Mountain Mining Area

Xing Gu, Minghui Xie, Xianping Luo, Huading Shi et al.
Sustainability
Heavy metals in environment
article

Characteristics, Ecological Risks and Source Analysis of Soil Heavy Metal Pollution in the Huangshi Lion Mountain Mining Area

Xing Gu, Minghui Xie, Xianping Luo, Huading Shi, Ruojun Huang
article en

Abstract

To reveal the enrichment characteristics, spatial patterns, ecological risks, and sources of heavy metals in surface soil of the Lion Mountain mining area, 38 topsoil samples were analyzed for Cu, Fe, Mn, Pb, and Zn. Using pollution-index evaluation, Hakanson ecological-risk assessment, inverse distance weighting (IDW), Z-score/IQR outlier diagnosis, Voronoi verification, and PCA source identification, we found that Cu, Pb, Zn, and Mn exceeded the Hubei provincial background, while Fe was about twice its background but remained in the uncontaminated to moderate contamination grade. Cu had the highest screening exceedance rate (36.84%), while Pb dominated the ecological risk despite a sub-screening mean Pi, driven by an extreme Pb outlier. The regional Nemero index was 7.76 (severe contamination) in the full dataset and 2.49 (moderate contamination) after excluding the outlier. The comprehensive ecological risk index was 25.87 under the Hubei background and 42.05 under the local background, both at Slight risk, with Pb as the dominant contributor. PCA suggested that Cu-Fe-Zn were likely controlled by the mineralization parent material, Pb likely represented an anthropogenic signal requiring further verification, and Zn had dual sources. These findings show that a single extreme value can dominate regional contamination grading without altering the underlying spatial structure, providing a methodological reference for the integrated framework of statistical outlier diagnosis, spatial clustering verification, and interpolation sensitivity assessment in mining-area soil studies.

SustainabilityVol. 18(20)
Jiangxi University of Water Resources and Electric Power (CN), Minzu University of China (CN), Ministry of Ecology and Environment (CN), Chinese Research Academy of Environmental Sciences (CN)
Openalex Percentile: Top 25%
Heavy metals in environment
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