A comprehensive risk assessment of metals in riverine surface sediments across the rural-urban interface of a rapidly developing watershed. (February 2019) - Wang, Zhenfeng; Zhou, Jiayu; Zhang, Chi; Qu, Liyin; Mei, Kun; Dahlgren, Randy A.; Zhang, Minghua; Xia, Fang
Abstract: Metal contamination in aquatic environments is a severe global concern to human health and aquatic ecosystems. This study used several risk assessment indices, to evaluate metal (Cu, Zn, Pb, Cd and Cr) environmental risk of riverine surface sediments across the rural-urban interface of the rapidly developing Wen-Rui Tang River watershed in eastern China. Risk assessments were determined for 38 sites based on the potential ecological risk index (RI), consensus-based sediment quality guidelines (SQGs) and risk assessment code (RAC). Land-use cluster analysis showed that sediments were severely contaminated, especially for Cd, whose concentrations were ∼100 times higher than background levels and had a high proportion in the bioaccessible fraction. According to RI, E r Cd was identified with extremely high risk potential, resulting in the highest ecological risk of Cluster 4 (industrial). Similarly, risk within Cluster 4 (industrial) was also ranked highest by SQGs assessment due to the high proportion of industrial land use. Zinc was determined with high risk due to its high concentration compared to its effect range medium (ERM) value. Discrepancies in predicting environmental risks from metals among the three indices were mainly attributed to the contrasting definitions of these metrics. Environmental risk uncertainty derived from spatial variation was further estimated by Monte Carlo simulation and ranked as: Zn > Cd > Cr > Pb > Cu. This comprehensive environmental risk assessment provides important information to guide remediation strategies for management of metal contamination at the watershed scale. Graphical abstract: Highlights: Heavy metals in Wen-Rui Tang watershed showed considerable ecological risk. Risk assessment diverged for different metals among the selected risk metrics. Greater uncertainty for Zn risk assessment was identified by Monte Carlo simulation.