Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong,China |
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| Authors: | Jian Zhou Dongsheng Ma Jiayong Pan Wenming Nie Kai Wu |
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| Institution: | (1) State Key Laboratory for Mineral Deposit Research, Nanjing University, Nanjing, 210093, People’s Republic of China;(2) Department of Earth Sciences, Nanjing University, Nanjing, 210093, People’s Republic of China;(3) Department of Geoscience and Resource Information, East China Institute of Technology, Fu Zhou, 344000, People’s Republic of China |
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| Abstract: | Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in
surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the
water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both
surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis
and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water
samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment
samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples
are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples
is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical
analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making
this statistical discussion more convincing. |
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