Probabilistic human health-risk assessment and influencing factors of aromatic hydrocarbon in groundwater near urban industrial complexes in Northeast China.

Organic pollutants are common in the environment, very difficult to remove, and pose a serious threat to human health. Probabilistic risk assessment advances conservative single-point estimation and brings a new perspective to risk assessment. From 2009 to 2019, we monitored the distribution of major pollutants in an industrial park in Northeastern China. The result showed the maximum concentration of benzene reached 73,680 μg/L in 2009, benzo[a]pyrene reached 36.80 ng/L in 2016. These concentrations are significantly above the levels set by Chinese regulatory agencies. The single-factor index increases year by year, and pollutants gradually spread from the pollution leakage source to surrounding areas. A new method was used to quantify the human health risk from groundwater organic pollution accurately, based on the triangular fuzzy numbers coupled with the Monte Carlo simulation. The Monte Carlo simulation was used to simulate the triangular fuzzy numbers. This simplified the operation between the triangular fuzzy numbers and their function successfully and obtained the risk as a set of values. The results indicated that non-carcinogenic risk was negligible in all age groups (children, adolescents, and adults). Conversely, when it comes to carcinogenic risks, adults were about 50-270 times the tolerable level of risk due to long exposure years and wide skin contact areas. Oral ingestion played an essential role in total exposure (>90%) compared to dermal contact. Control of exposure duration and intake should be prioritized when making decisions to reduce risk uncertainty. Monte Carlo simulation-triangular fuzzy numbers can effectively reduce the risk of uncertainty and reflect the complex conditions of the groundwater environment for small amounts of data or inaccurate data.

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Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.