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Multivariate statistical and lead isotopic analyses approach to identify heavy metal sources in topsoil from the industrial zone of Beijing Capital Iron and Steel Factory

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Abstract

Heavy metals are considered toxic to humans and ecosystems. In the present study, heavy metal concentration in soil was investigated using the single pollution index (PIi), the integrated Nemerow pollution index (PIN), and the geoaccumulation index (Igeo) to determine metal accumulation and its pollution status at the abandoned site of the Capital Iron and Steel Factory in Beijing and its surrounding area. Multivariate statistical (principal component analysis and correlation analysis), geostatistical analysis (ArcGIS tool), combined with stable Pb isotopic ratios, were applied to explore the characteristics of heavy metal pollution and the possible sources of pollutants. The results indicated that heavy metal elements show different degrees of accumulation in the study area, the observed trend of the enrichment factors, and the geoaccumulation index was Hg > Cd > Zn > Cr > Pb > Cu ≈ As > Ni. Hg, Cd, Zn, and Cr were the dominant elements that influenced soil quality in the study area. The Nemerow index method indicated that all of the heavy metals caused serious pollution except Ni. Multivariate statistical analysis indicated that Cd, Zn, Cu, and Pb show obvious correlation and have higher loads on the same principal component, suggesting that they had the same sources, which are related to industrial activities and vehicle emissions. The spatial distribution maps based on ordinary kriging showed that high concentrations of heavy metals were located in the local factory area and in the southeast-northwest part of the study region, corresponding with the predominant wind directions. Analyses of lead isotopes confirmed that Pb in the study soils is predominantly derived from three Pb sources: dust generated during steel production, coal combustion, and the natural background. Moreover, the ternary mixture model based on lead isotope analysis indicates that lead in the study soils originates mainly from anthropogenic sources, which contribute much more than the natural sources. Our study could not only reveal the overall situation of heavy metal contamination, but also identify the specific pollution sources.

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Acknowledgements

This research was financially supported by the National High Technology Research and Development Program of China (973 Program: No. 2014CB238906), the National Natural Science Foundation of China (No. 41425014; 41625006), China Postdoctoral Science Foundation Funded Project (No. 2015 M582578), and the Feature Institute Program of the Chinese Academy of Sciences (Comprehensive Technical Scheme and Integrated Demonstration for Remediation of Soil and Groundwater in Typical Area).

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Authors and Affiliations

  1. State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China

    Guangxu Zhu & Huayun Xiao

  2. Center for Environmental Remediation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Guangxu Zhu, Qingjun Guo, Tongbin Chen & Jun Yang

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  1. Guangxu Zhu
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  2. Qingjun Guo
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  3. Huayun Xiao
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  4. Tongbin Chen
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  5. Jun Yang
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Correspondence to Guangxu Zhu or Qingjun Guo.

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Responsible editor: Zhihong Xu

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Zhu, G., Guo, Q., Xiao, H. et al. Multivariate statistical and lead isotopic analyses approach to identify heavy metal sources in topsoil from the industrial zone of Beijing Capital Iron and Steel Factory. Environ Sci Pollut Res 24, 14877–14888 (2017). https://doi.org/10.1007/s11356-017-9055-9

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