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Novel assessment method of heavy metal pollution in surface water: A case study of Yangping River in Lingbao City, China

  • Liu, Yingran (Faculty of Engineering, China University of Geosciences) ;
  • Yu, Hongming (Faculty of Engineering, China University of Geosciences) ;
  • Sun, Yu (The Fourth Geological Exploration Institute of Henan Geology and Mineral Bureau) ;
  • Chen, Juan (The Fourth Geological Exploration Institute of Henan Geology and Mineral Bureau)
  • Received : 2016.01.27
  • Accepted : 2016.09.06
  • Published : 2017.03.31

Abstract

The primary purpose of this research is to understand those elements that define heavy metals contamination and to propose a novel assessment method based on principal component analysis (PCA) in the Yangping River region of Lingbao City, China. This paper makes detailed calculations regarding such factors the single-factor assessment ($P_i$) and Nemerow's multi-factor index ($P_N$) of heavy metals found in the surface water of the Yangping River. The maximum values of $P_i$ (Cd) and $P_i$ (Pb) were determined to be 892.000 and 113.800 respectively. The maximum value of $P_N$ was calculated to be 639.836. The results of Pearson's correlation analysis, hierarchical cluster analysis, and PCA indicated heavy metal groupings as follows: Cu, Pb, Zn and As, Hg, Cd. The PCA-based pollution index ($P_{an}$) of samplings was subsequently calculated. The relative coefficient square was valued at 0.996 between $P_{an}$ and $P_N$, which indicated that $P_{an}$ is able to serve as a new heavy metal pollution index; not only this index able to eliminate the influence of the maximum value of $P_i$, but further, this index contains the principal component elements needed to evaluate heavy metal pollution levels.

Acknowledgement

Supported by : National Natural Science Foundation of China, National Youth Science Foundation of China

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