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Multivariate statistical approach to identify heavy metal sources in agricultural soil around an abandoned Pb–Zn mine in Guangxi Zhuang Autonomous Region, China

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Abstract

A study of agricultural lands around an abandoned Pb–Zn mine in a karst region was undertaken to (1) assess the distribution of heavy metals in the agricultural environment, in both dry land and paddy field; (2) discriminate between natural and anthropogenic contributions; and (3) identify possible sources of any pollution discovered. Ninety-two samples of cultivated soils were collected around the mine and analyzed for eight heavy metals, pH, fluoride (F−), cation exchange capacity, organic matter, and grain size. The eight heavy metals included Cd, Cr, Cu, Ni, Pb, Zn, As, and Hg. The average concentrations (mg/kg) obtained were as follows: Cd 16.76 ± 24.49, Cr 151.5 ± 18.24, Cu 54.28 ± 18.99, Ni 57.5 ± 14.43, Pb 2,576.2 ± 1,096, Zn 548.7 ± 4,112, As 29.1 ± 6.36, and Hg 1.586 ± 1.46. In a site where no impact from mining activities was detected, the mean and median of Cd, Cu, Ni, Pb, Zn, As, and Hg concentrations in investigated topsoils were higher than the mean and median of heavy metal concentrations in reference soils. An ensemble of basic and multivariate statistical analyses was performed to reduce the multidimensional space of variables and samples. Two main sets of heavy metals were revealed as indicators of natural and anthropogenic influences. The results of principal component analysis (PCA) and categorical PCA demonstrated that Cd, Cu, Pb, Zn, and Hg are indicators of anthropogenic pollution, whereas Cr, As and Ni concentrations are mainly associated with natural sources in the environment. The contamination from Pb–Zn mining operations, coupled with the special karst environment, was a key contributing factor to the spatial distribution of the eight heavy metals in the surrounding soil. The values of heavy metals in the soil samples suggested the necessity of conducting a rigorous assessment of the health and environmental risks posed by these residues and taking suitable remedial action as necessary.

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Acknowledgments

This work was supported by the National Basic Research Program of China (2004CB418507), the National Natural Science Fund of China (40861024), and the Guangxi Scientific and Technological Brainstorm Project, Science and Technology (Guikegong 0779011). The assistance in sample analysis from the Guangxi Test Center of Geology and Mine is also greatly appreciated. The authors would like to thank the reviewers for their valuable comments which highly improved the manuscript. Appreciation should be directed to Dr. Donald G. Barnes, a visiting professor of Guangxi University and an anonymous reviewer who offered valuable comments and detailed revisions for the manuscript.

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  1. Guangxi Environmental Monitoring Center, Nanning, 530028, China

    Liang-Mei Huang, Chao-Bing Deng, Ning Huang & **ao-Jia Huang

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  1. Liang-Mei Huang
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Correspondence to Liang-Mei Huang.

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Huang, LM., Deng, CB., Huang, N. et al. Multivariate statistical approach to identify heavy metal sources in agricultural soil around an abandoned Pb–Zn mine in Guangxi Zhuang Autonomous Region, China. Environ Earth Sci 68, 1331–1348 (2013). https://doi.org/10.1007/s12665-012-1831-8

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