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Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn


Multivariate Analysis of Heavy Metal Contamination in Soil of Baiyangdian Wetland in China

Journal of Environmental Accounting and Management 2(4) (2014) 313--323 | DOI:10.5890/JEAM.2014.12.003

Liya Su; Jingling Liu

State Key Joint Laboratory of Water Environmental Simulation and Pollution Control & School of Environment, Beijing Normal University, 100875, Beijing, China

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Abstract

Soil pollution has become an important environmental issue due to changes in the land use pattern over the last few decades. However, up to now, except Cd and Pb, little attention was paid on more heavy metals in Baiyangdian soil. This article applied multivariate statistical techniques with element concentration analysis and correlation analysis for source identification of heavy metals in the soil of Baiyangdian. The application of multivariate statistical techniques combined with element concentration analysis and correlation analysis has been proved to be an effective tool for source identification of heavy metals in Baiyangdian soil. Firstly, based on the comparison of heavy metals concentrations of soil with background values of Chinese soils, the examined elements were classified into two main groups: natural and anthropogenic sources. Then principal component analysis and cluster analysis, coupled with correlation analysis, were used to gain additional insight into the origins of different elements in soil. Three main sources for these studied elements, as well as some subdivided sources, were therefore identified. Hg, Pb and As are attributed to commercial and domestic sources; Cd and Cu are mainly derived from industrial sources and Cr and Zn associated with traffic sources.

Acknowledgments

The present investigation was supported by the Fundamental Research Funds for the Central Universities (2013YB16) and Major Science and Technology Program for Water Pollution Control and Treatment (2012ZX07203-006). We thank Ms. Yongli Li, Mr. Bao Zhang, Zhiguo Cao in Beijing Normal University for their help with collecting samples. We also wish to thank two anonymous reviewers for useful comments which helped improve this paper.

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