Human health ambient water quality criteria for 13 heavy metals and health risk assessment in Taihu Lake

Highlights

• The concentrations of 13 heavy metals in Taihu Lake were analyzed.

• Aquatic vegetables intake was first included in deriving human health AWQC.

• The human health AWQC for 13 heavy metals in Taihu Lake were derived.

• Human health risk assessment for 13 heavy metals were conducted in Taihu Lake.

Abstract

Heavy metals are widely concerning because of their toxicity, persistence, non-degradation and bioaccumulation ability. Human health ambient water quality criteria (AWQC) are specific levels of chemicals that can occur in water without harming human health. At present, most countries do not consider the effects of aquatic vegetables in deriving human health AWQC. Therefore, the intake of aquatic vegetables (Brasenia schreberi) was added to the derivation of human health AWQC and a health risk assessment for 13 heavy metals in Taihu Lake. The human health AWQC (consumption of water, fish and aquatic vegetables) values of 13 heavy metals ranged from 0.04 (Cd) to 710.87 μg/L (Sn), and the intake of B. schreberi had a very significant effect on the human health AWQC for Cu, with a more than 62-fold difference. The hazard quotients of As (2.8), Cd (1.6), Cr (1.4) and Cu (4.86) were higher than the safe level (HQ= 1), indicating that As, Cd, Cr and Cu in Taihu Lake posed a significant health risk. Sensitivity analysis showed that the contribution rate of B. schreberi intake to the human health risk from Cu was 91.6%, and all results indicated that the risk of Cu in B. schreberi to human health should be of particular concern. This study adds the consideration of aquatic vegetable consumption to the traditional method of human health AWQC derivation and risk assessments for the first time, and this approach can promote the development of risk assessments and water quality criteria.

Graphical abstract

Keywords

Heavy metals / Human health ambient water quality criteria / Taihu Lake / Health risk assessment / Contribution rate

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Acknowledgements

This work was supported by the National Science and Technology Project of Water Pollution Control and Abatement of China (Grant No. 2017ZX07301002-02), the Project of Chinese Research Academy of Environmental Sciences (Grant No. 2020YSKY-007) and the National Natural Science Foundation of China (Grant No. 41521003).

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-021-1475-6 and is accessible for authorized users.

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