Probabilistic ecological risk assessment of heavy metals in western Laizhou Bay, Shandong Province, China

Considering the serious land-based pollution and the weak water exchange ability of western Laizhou Bay, it is essential to conduct an ecological risk assessment of the pollutants in this area. In this study, the ecological risk caused by heavy metals deposited in the surface sediments and those resuspended in the seawater of western Laizhou Bay was evaluated using probabilistic approaches. First, the concentrations of seven heavy metals, namely As, Cd, Cr, Cu, Hg, Pb, and Zn, in the surface sediments and seawater of western Laizhou Bay were detected during the spring and autumn of 2016. The concentrations of As, Cd, Cr, Cu, and Pb were found to be at levels comparable to those in the other global coastal systems, while those of Hg and Zn were lower than those in other coastal areas. Next, an ecological risk assessment of heavy metals in the surface sediments was performed using a typical potential ecological risk index and refined by using a Monte Carlo simulation. The results suggested low risk for the heavy metals detected in the sediments of western Laizhou Bay, with the exception of Hg in September 2016, which showed a probability (0.03%) of moderate risk. Meanwhile, the aquatic ecological risk assessment of the heavy metals was performed by applying a combination of hazard quotient (HQ) and joint probability curve. While the ecological risk of Cd, Hg, and Pb was found to be acceptable, the HQs for Cr, Cu, and Zn were greater than 1, and the overall risk probability of their adverse effects was higher than 0.05, suggesting certain ecological risk. Specifically, in the case of As, the overall risk probability was lower than 0.05, suggesting that its ecological risk was acceptable, although its HQ was greater than 1. Thus, by applying the probabilistic approaches, the ecological risk of the heavy metals in western Laizhou Bay was better characterized in this study, avoiding both overestimation and underestimation of ecological risk.