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Ecotoxicology

, Volume 25, Issue 2, pp 380–388 | Cite as

Multivariate analysis combined with GIS to source identification of heavy metals in soils around an abandoned industrial area, Eastern China

  • Jie ZhouEmail author
  • Ke Feng
  • Zongping Pei
  • Fang Meng
  • Jian Sun
Article

Abstract

Heavy metals in soils polluted by industrial production are a meaningful topic worldwide. The purpose of this study is to understand the pollution status and spatial distribution of heavy metals in soils. The result can help decision-makers apportion possible soil heavy metals sources and formulate effective pollution control policies. In this paper, 155 soil samples (0–20 cm) were collected and analyzed for eight heavy metals (Cd, Hg, As, Cu, Pb, Cr, Zn, and Ni) from an abandoned industrial area of Tong County, located in Jiangsu Province of Eastern China. The multivariate analysis (including Igeo, Ei/RI, EF, PCA, and CA) and geostatistics (GIS) were used to assess the enrichment level and pollution level of soil heavy metals and identify their sources. The results indicated that eight heavy metals in soils had moderate variations, with CVs ranging from 19.63 to 63.34 %. The pollution level of Igeo of soil heavy metals decreased in the order of Cd~Zn > Cu > Hg~As~Pb~Cr~Ni. The enrichment level of soil heavy metals decreased in the order of Cd > Zn > Hg > Cu > Pb > Ni > As > Cr. According to the Ei, except Cd and Hg were in the significant and moderate ecological risk levels respectively, other soil heavy metals were in the clean or light ecological risk levels, the level of potential ecological risk (RI) of the whole industrial area was moderate. Finally, the source identification of soil heavy metals indicated that Cd and Zn were primarily controlled by human activities, and Hg and Cu were controlled by natural and anthropogenic sources, and As, Pb, Cr, and Ni were mainly controlled by soil parent materials.

Keywords

Heavy metal Soil pollution Multivariate analysis Spatial distribution Source identification 

Notes

Acknowledgments

This study was supported by the Special Fund from Ministry of Environmental Protection for Soil Pollution Control and Remediation Technology (Grant No. SL231015846). The authors thank Environmental Monitoring Department of Tong County for providing the laboratory to experiment, and thank anonymous reviewers for their helpful comments.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Jie Zhou
    • 1
    Email author
  • Ke Feng
    • 2
  • Zongping Pei
    • 3
  • Fang Meng
    • 1
  • Jian Sun
    • 1
  1. 1.College of Chemistry & Chemical EngineeringYangzhou UniversityYangzhouChina
  2. 2.College of Environmental Science & EngineeringYangzhou UniversityYangzhouChina
  3. 3.School of Environmental Science & Spatial InformaticsChina University of Mining & TechnologyXuzhouChina

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