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http://dx.doi.org/10.4491/eer.2016.015

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)
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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.
Keywords
Heavy metals contamination; Hierarchical cluster analysis (HCA); Pollution evaluation; Principal component analysis (PCA); Yangping River;
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