Li Qiang, Wang Peifang, Wang Chao, Hu Bin, Wang Xun
Key Laboratory of Integrated Regulation and Resources Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China.
Key Laboratory of Integrated Regulation and Resources Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China.
Environ Res. 2022 Dec;215(Pt 1):114132. doi: 10.1016/j.envres.2022.114132. Epub 2022 Aug 20.
Perfluorinated compounds (PFCs) can pose adverse effect on aquatic species and community structure. However, little is known about how the characteristics of molecules of PFCs affect their chronic toxic potencies to aquatic species, and the species sensitivity distributions (SSDs) and ecological risk assessments of PFCs are hampered by limited available data of chronic toxicity. In the present study, a novel procedure is proposed to obtain the ecological risk of PFCs using existing exposure concentrations of PFCs and SSDs integrated with the chronic toxicity prediction through robust QSAR models. The results showed that the energy of the lowest unoccupied molecular orbital (E) exhibited the strongest correlation with the chronic toxicities of 15 PFCs (R > 0.844, F > 16.206, p < 0.05). SSDs of 15 PFCs on eight species were first constructed, and the SSD fitting parameters were significantly correlated with E (R > 0.610, F > 19.471, p < 0.05). The QSAR-SSDs support the evaluation of hazardous criteria of PFCs for which data are lacking. Given environmental exposure distributions (EEDs) of the national presence of PFCs in aquatic systems in China, the QSAR-SSDs models allow the development of the ecological risk assessment for PFCs. This way, it was concluded that negligible environmental risk (defined as 5% of the species being potentially exposed to concentrations able to cause effects in < 5% of the case) could be expected from exposure to PFCs in surface waters in China. This method may be helpful for providing an evidence-based approach to guide the risk management for PFCs in aquatic environment.
全氟化合物(PFCs)会对水生物种和群落结构产生不利影响。然而,关于PFCs分子特性如何影响其对水生物种的慢性毒性效力,人们所知甚少,而且PFCs的物种敏感性分布(SSDs)和生态风险评估因慢性毒性的可用数据有限而受到阻碍。在本研究中,提出了一种新方法,利用PFCs的现有暴露浓度和SSDs,并通过稳健的定量构效关系(QSAR)模型结合慢性毒性预测来获得PFCs的生态风险。结果表明,最低未占分子轨道能量(E)与15种PFCs的慢性毒性表现出最强的相关性(R>0.844,F>16.206,p<0.05)。首次构建了15种PFCs对8个物种的SSDs,且SSD拟合参数与E显著相关(R>0.610,F>19.471,p<0.05)。QSAR-SSDs有助于评估缺乏数据的PFCs的危害标准。鉴于中国水生系统中PFCs的全国环境暴露分布(EEDs),QSAR-SSDs模型可用于开展PFCs的生态风险评估。据此得出结论,在中国地表水中接触PFCs预计可产生可忽略不计的环境风险(定义为5%的物种可能接触到能在<5%的情况下产生影响的浓度)。该方法可能有助于提供一种循证方法,以指导水生环境中PFCs的风险管理。