Optimizing critical source control of five priority-regulatory trace elements from industrial wastewater in China: Implications for health management
2018
Wu, Wenjun | Wang, Jinnan | Yu, Yang | Jiang, Hongqiang | Liu, Nianlei | Bi, Jun | Liu, Miaomiao
Anthropogenic emissions of toxic trace elements (TEs) have caused worldwide concern due to their adverse effects on human health and ecosystems. Based on a stochastic simulation of factors' probability distribution, we established a bottom-up model to estimate the amounts of five priority-regulatory TEs released to aquatic environments from industrial processes in China. Total TE emissions in China in 2010 were estimated at approximately 2.27 t of Hg, 310.09 t of As, 318.17 t of Pb, 79.72 t of Cd, and 1040.32 t of Cr. Raw chemicals, smelting, and mining were the leading sources of TE emissions. There are apparent regional differences in TE pollution. TE emissions are much higher in eastern and central China than in the western provinces and are higher in the south than in the north. This spatial distribution was characterized in detail by allocating the emissions to 10 km × 10 km grid cells. Furthermore, the risk control for the overall emission grid was optimized according to each cell's emission and risk rank. The results show that to control 80% of TE emissions from major sources, the number of top-priority control cells would be between 200 and 400, and less than 10% of the total population would be positively affected. Based on TE risk rankings, decreasing the population weighted risk would increase the number of controlled cells by a factor of 0.3–0.5, but the affected population would increase by a factor of 0.8–1.5. In this case, the adverse effects on people's health would be reduced significantly. Finally, an optimized strategy to control TE emissions is proposed in terms of a cost-benefit trade-off. The estimates in this paper can be used to help establish a regional TE inventory and cyclic simulation, and it can also play supporting roles in minimizing TE health risks and maximizing resilience.
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