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Risk assessment and source identification of heavy metals in agricultural soil: a case study in the coastal city of Zhejiang Province, China

  • Zhouqiao Ren
  • Rui Xiao
  • Zhonghao Zhang
  • Xiaonan Lv
  • Xufeng FeiEmail author
Original Paper
  • 110 Downloads

Abstract

Heavy metal contamination is a serious environmental problem, especially in developing countries such as China. In this study, we collected 1928 soil samples from the southeastern coastal area of China and analyzed the pollution concentration and potential ecological risk from heavy metals including arsenic (As), cadmium (Cd), chromium (Cr), lead (Pb), and mercury (Hg). The mean concentrations of Cr, Hg, and Pb were lower than their corresponding background values, whereas As and Cd were 1.31 and 1.59 times their background values, respectively. The calculation of the mean Pollution Index (PI) for these heavy metals were, in decreasing order Cd (1.59), As (1.31), Cr (0.94), Pb (0.89), and Hg (0.78) and the Nemerow Integrated Pollution Index revealed that almost one-fifth of the soil in the study area was moderately polluted. According to the ecological risk index, about 12% of the soil was at a moderate or high ecological risk, and Cd and Hg presented the highest ecological risk. The GeogDetector software was used to quantitatively assess the potential sources of these metals. The GeogDetector results showed that the soil heavy metals have various sources, including: natural processes had significant impacts on all heavy metals analyzed in this study; farmland types influenced the concentrations of As and Cr significantly; industrial activities significantly increased As, Cr, and Hg; transportation-related activities increased As, Cd, and Hg; and agricultural application of fertilizer and pesticides, had significant impacts on As, Cd, and Pb levels. Based on the results of the interaction detector, natural processes and agricultural activities were determined to be the main sources of heavy metals in the study area.

Keywords

Heavy metal Source analysis Pollution assessment GeogDetector model 

Notes

Acknowledgements

This work was partially supported by the National Key R&D Program (2018YFD0200500 and 2017YFD0200600) and the National Natural Science Foundation of China (No. 41801302). They have no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zhouqiao Ren
    • 1
    • 2
  • Rui Xiao
    • 3
  • Zhonghao Zhang
    • 4
  • Xiaonan Lv
    • 1
    • 2
  • Xufeng Fei
    • 1
    • 2
    Email author
  1. 1.Zhejiang Academy of Agricultural SciencesHangzhouChina
  2. 2.Key Laboratory of Information Traceability of Agriculture ProductsMinstry of Agriculture and Rural AffairsBeijingChina
  3. 3.School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
  4. 4.Institute of Urban Studies, School of Environmental and Geographical SciencesShanghai Normal UniversityShanghaiChina

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