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Species Sensitivity Distributions for Use in Environmental Protection, Assessment, and Management of Aquatic Ecosystems for 12 386 Chemicals

机译:物种敏感性分布用于环境保护,评估和管理水生生态系统的1286种化学品

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The present study considers the collection and use of ecotoxicity data for risk assessment with species sensitivity distributions (SSDs) of chemical pollution in surface water, which are used to quantify the likelihood that critical effect levels are exceeded. This fits the European Water Framework Directive, which suggests using models to assess the likelihood that chemicals affect water quality for management prioritization. We derived SSDs based on chronic and acute ecotoxicity test data for 12 386 compounds. The log-normal SSDs are characterized by the median and the standard deviation of log-transformed ecotoxicity data and by a quality score. A case study illustrates the utility of SSDs for water quality assessment and management prioritization. We quantified the chronic and acute mixture toxic pressure of mixture exposures for 22 000 water bodies in Europe for 1760 chemicals for which we had both exposure and hazard data. The results show the likelihood of mixture exposures exceeding a negligible effect level and increasing species loss. The SSDs in the present study represent a versatile and comprehensive approach to prevent, assess, and manage chemical pollution problems. Environ Toxicol Chem 2019;38:905-917. (c) 2019 SETAC
机译:本研究考虑了与地表水中化学污染的物种敏感性分布(SSD)的风险评估的收集和使用,用于量化临界效果水平的可能性。这适合欧洲水框架指令,这表明使用模型来评估化学品影响水质以获得管理优先级的可能性。我们基于慢性和急性生态毒性测试数据来衍生SSD,用于12,386化合物。 Log-Normal SSD的特征在于中位数和对数转换的生态毒性数据的标准偏差以及质量分数。案例研究说明了SSD用于水质评估和管理优先级的实用性。我们量化了欧洲> 22 000个水体的混合物曝光的慢性和急性混合物的毒性压力,为1760年进行了接触和危险数据。结果表明,混合曝光超过忽略效果水平和增加物种损失的可能性。本研究中的SSD代表了防止,评估和管理化学污染问题的多功能和综合方法。环境毒素科学2019; 38:905-917。 (c)2019 Setac

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