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Distribution and source analysis of heavy metal pollutants in sediments of a rapid developing urban river system

Xia, Fang, Qu, Liyin, Wang, Ting, Luo, Lili, Chen, Han, Dahlgren, Randy A., Zhang, Minghua, Mei, Kun, Huang, Hong
Chemosphere 2018 v.207 pp. 218-228
anthropogenic activities, aquatic ecosystems, aquatic environment, business enterprises, cadmium, chromium, copper, fractionation, heavy metals, human health, industrial sites, industrialization, land use, lead, manufacturing, models, multivariate analysis, pollutants, remediation, rivers, sediment contamination, sediments, watersheds, zinc, China
Heavy metal pollution of aquatic environments in rapidly developing industrial regions is of considerable global concern due to its potential to cause serious harm to aquatic ecosystems and human health. This study assessed heavy metal contamination of sediments in a highly industrialized urban watershed of eastern China containing several historically unregulated manufacturing enterprises. Total concentrations and solid-phase fractionation of Cu, Zn, Pb, Cr and Cd were investigated for 39 river sediments using multivariate statistical analysis and geographically weighted regression (GWR) methods to quantitatively examine the relationship between land use and heavy metal pollution at the watershed scale. Results showed distinct spatial patterns of heavy metal contamination within the watershed, such as higher concentrations of Zn, Pb and Cd in the southwest and higher Cu concentration in the east, indicating links to specific pollution sources within the watershed. Correlation and PCA analyses revealed that Zn, Pb and Cd were dominantly contributed by anthropogenic activities; Cu originated from both industrial and agricultural sources; and Cr has been altered by recent pollution control strategies. The GWR model indicated that several heavy metal fractions were strongly correlated with industrial land proportion and this correlation varied with the level of industrialization as demonstrated by variations in local GWR R² values. This study provides important information for assessing heavy metal contaminated areas, identifying heavy metal pollutant sources, and developing regional-scale remediation strategies.