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Published on: September 13, 2019
Toxicity of 10 organic micropollutants and their mixture: Implications for aquatic risk assessment
Ying Shao1, Zhongli Chen2, Henner Hollert3
1Institute for Environmental Research (Biology V), RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany; Department of Cell Toxicology, UFZ - Helmholtz Centre for Environmental Research GmbH, Permoserstraße 15, 04318 Leipzig, Germany.
Abstract:
Micropollutants, as a serious water pollution issue, raise considerable toxicological concerns, particularly when present as components of complex mixtures. Due to the interactions of environmental pollution components (contaminant), the micropollutant problem is increasingly complex, thus, water quality of organic chemical contamination assessed substance-by-substance might lead to underestimation in aquatic environmental risk assessment. To assess the aquatic environmental risk of micropollutants mixture, a total of 10 organic micropollutants were selected and analysed by an approach of integration of literature data, laboratory experiments and prediction techniques. The experiment results showed that all 10 micropollutants were capable of causing toxicity in zebrafish embryos, aquatic invertebrates and algae with the LC50 (50% lethal concentration) values from 1.14 mg/L to 14.37 mg/L. Triclosan, carbamazepine, diazinon and diuron were the most hazardous compounds in the Danube River and the Rhine River. The artificial mixture presented a strong antagonistic relationship, which demonstrated an independent action (IA) model of the mixture. Based on the observed toxicity data, the risk quotients (RQs) of environmental mixtures of the Danube River and the Rhine River were extrapolated. It can be concluded that the micropollutant mixture may pose a potential risk for aquatic ecosystems with the present environmentally measured concentrations in the Danube River and Rhine River. Mixture risk assessment results suggested that the toxicity of studied chemicals might be induced by dissimilar actions, which is in agreement with the mixture toxicity prediction of the IA model. The observed findings could be useful to establish an overview of the pressures, vision, measures and expectations for hazardous substances pollution, which can help in making to informed decisions to reduce the concentration and bioactive fraction of pollutants.
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