Application of new statistical distribution approaches for environmental mixture risk assessment: A case study.

Aquatic toxicity Combined exposure Ecotoxicological Threshold of Toxicological Concern Mode of action

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
25 Nov 2019
Historique:
received: 19 03 2019
revised: 18 07 2019
accepted: 19 07 2019
pubmed: 30 7 2019
medline: 30 7 2019
entrez: 30 7 2019
Statut: ppublish

Résumé

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. 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). 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.

Identifiants

pubmed: 31357034
pii: S0048-9697(19)33429-1
doi: 10.1016/j.scitotenv.2019.07.316
pmc: PMC6839615
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

133510

Informations de copyright

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

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Auteurs

Aude Kienzler (A)

European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy. Electronic address: aude.kienzler@ec.europa.eu.

Stephanie Bopp (S)

European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy.

Marlies Halder (M)

European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy.

Michelle Embry (M)

Health and Environmental Science Institute, 740 15th Street NW, Suite 600, Washington, DC 20005, USA.

Andrew Worth (A)

European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy.

Classifications MeSH