4.7 Article

Ranking the risks of eighty pharmaceuticals in surface water of a megacity: A multilevel optimization strategy

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SCIENCE OF THE TOTAL ENVIRONMENT
卷 878, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.scitotenv.2023.163184

关键词

Pharmaceuticals; Risk assessment; Multilevel strategy; QSAR-ICE; Structural equation modeling

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This study assessed the risks of 80 pharmaceuticals in surface water of Beijing using a multilevel environmental risk optimization strategy, revealing that antiviral drugs were the dominant pharmaceuticals. Certain pharmaceuticals posed low risks and could be prioritized for screening as priority pollutants in water environments. The results also highlighted the indirect influence of human land use and climate conditions on pharmaceutical risks.
Pharmaceuticals in freshwater posed ecological risks to aquatic ecosystem, however, most risk assessments of pharmaceuticals were conducted at screening level, which were limited by the availability of the toxicity data. In this study, risks of 80 pharmaceuticals including 35 antibiotics, 13 antiviral drugs, 13 illicit drugs, and 19 antidepressants in surface water of Beijing were assessed with a proposed multilevel environmental risk optimization strategy. Target pharmaceuticals were detected in surface water samples with the detection frequency from 1.7 % to 100 % and the total concentrations from 31.1 ng/L to 2708 ng/L. Antiviral drugs were the dominant pharmaceuticals. Preliminary screening-level risk assessment indicated that 20 pharmaceuticals posed low to high risks with risk quotient from 0.14 (chloroquine diphosphate) to 27.8 (clarithromycin). Thirteen pharmaceuticals were recognized with low to high risks by an optimized risk assessment method. Of them, the refined probabilistic risk assessment of joint probability curves coupling with a quantitative structure activity relationship-interspecies correlation estimation (QSARICE) model was applied. Clarithromycin, erythromycin and ofloxacin were identified to pose low risks with maximum risk products (RP) of 1.23 %, 0.41 % and 0.35%, respectively, while 10 pharmaceuticals posed de minimis risks. Structural equation modeling disclosed that human land use and climate conditions influenced the risks of pharmaceuticals by indirectly influencing the concentrations of pharmaceuticals. The results indicated that the multilevel strategy cou-pling with QSAR-ICE model was appropriate and effective for screening priority pollutants, and the strategy can be used to prioritize pharmaceuticals and other emerging contaminants in the aquatic environment.

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