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dc.contributor.authorKIENZLER AUDEen_GB
dc.contributor.authorBOPP STEPHANIEen_GB
dc.contributor.authorHALDER MARIA ELISABETHen_GB
dc.contributor.authorEMBRY MICHELLEen_GB
dc.contributor.authorWORTH ANDREWen_GB
dc.date.accessioned2019-10-26T02:18:58Z-
dc.date.available2019-10-25en_GB
dc.date.available2019-10-26T02:18:58Z-
dc.date.created2019-10-22en_GB
dc.date.issued2019en_GB
dc.date.submitted2018-12-13en_GB
dc.identifier.citationSCIENCE OF THE TOTAL ENVIRONMENT vol. 693 no. 133510 p. 1-10en_GB
dc.identifier.issn0048-9697 (online)en_GB
dc.identifier.urihttps://publications.jrc.ec.europa.eu/repository/handle/JRC114791-
dc.description.abstractObjectives: There is growing evidence that single substances present below their individual thresholds of effect may still contribute to combined effects. In component-based mixture risk assessment (MRA), the risks can be addressed using information on the mixture components. This is, however, often hampered by limited availability of ecotoxicity data. Here, the possible use of ecotoxicological threshold concentrations of no concern (i.e. 5th percentile of statistical distribution of ecotoxicological values) is investigated to fill data gaps in MRA. Methods: For chemicals without available aquatic toxicity data, ecotoxicological threshold concentrations of no concern have been derived from Predicted No Effect Concentration (PNEC) distributions and from chemical toxicity distributions, using the EnviroTox tool, with and without considering the chemical mode of action. For exposure, chemical monitoring data from European rivers have been used to illustrate four realistic co-exposure scenarios. Based on those monitoring data and available ecotoxicity data or threshold concentrations when no data were available, Risk Quotients for individual chemicals were calculated, to then derive a mixture Risk Quotient (RQmix). Results: A risk was identified in two of the four scenarios. Threshold concentrations contribute from 24 to 95% of the whole RQmix; thus they have a large impact on the predicted mixture risk. Therefore they could only be used for data gap filling for a limited number of chemicals in the mixture. The use of mode of action information to derive more specific threshold values could be a helpful refinement in some cases.en_GB
dc.description.sponsorshipJRC.F.3-Chemicals Safety and Alternative Methodsen_GB
dc.format.mediumOnlineen_GB
dc.languageENGen_GB
dc.publisherELSEVIER SCIENCE BVen_GB
dc.relation.ispartofseriesJRC114791en_GB
dc.titleApplication of new statistical distribution approaches for environmental mixture risk assessment: A case studyen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1016/j.scitotenv.2019.07.316 (online)en_GB
JRC Directorate:Health, Consumers and Reference Materials

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