Characterizing Freshwater Ecotoxicity of More Than 9000 Chemicals by Combining Different Levels of Available Measured Test Data with In Silico Predictions

Author:

Douziech Mélanie12ORCID,Oginah Susan Anyango3,Golsteijn Laura4,Hauschild Michael Zwicky35,Jolliet Olivier3ORCID,Owsianiak Mikołaj3,Posthuma Leo67ORCID,Fantke Peter35ORCID

Affiliation:

1. Agroscope Life Cycle Assessment Research Group Zurich Switzerland

2. Centre of Observations, Impacts, Energy, MINES Paris Tech PSL University Sophia Antipolis France

3. Quantitative Sustainability Assessment, Department of Environmental and Resource Engineering Technical University of Denmark Lyngby Denmark

4. PRé Sustainability Amersfoort The Netherlands

5. Centre for Absolute Sustainability Technical University of Denmark Lyngby Denmark

6. Department of Environmental Science, Radboud Institute for Biological and Environmental Science Radboud University Nijmegen The Netherlands

7. National Institute for Public Health and the Environment, Centre for Sustainability Environment and Health Bilthoven The Netherlands

Abstract

AbstractEcotoxicological impacts of chemicals released into the environment are characterized by combining fate, exposure, and effects. For characterizing effects, species sensitivity distributions (SSDs) estimate toxic pressures of chemicals as the potentially affected fraction of species. Life cycle assessment (LCA) uses SSDs to identify products with lowest ecotoxicological impacts. To reflect ambient concentrations, the Global Life Cycle Impact Assessment Method (GLAM) ecotoxicity task force recently recommended deriving SSDs for LCA based on chronic EC10s (10% effect concentration, for a life‐history trait) and using the 20th percentile of an EC10‐based SSD as a working point. However, because we lacked measured effect concentrations, impacts of only few chemicals were assessed, underlining data limitations for decision support. The aims of this paper were therefore to derive and validate freshwater SSDs by combining measured effect concentrations with in silico methods. Freshwater effect factors (EFs) and uncertainty estimates for use in GLAM‐consistent life cycle impact assessment were then derived by combining three elements: (1) using intraspecies extrapolating effect data to estimate EC10s, (2) using interspecies quantitative structure–activity relationships, or (3) assuming a constant slope of 0.7 to derive SSDs. Species sensitivity distributions, associated EFs, and EF confidence intervals for 9862 chemicals, including data‐poor ones, were estimated based on these elements. Intraspecies extrapolations and the fixed slope approach were most often applied. The resulting EFs were consistent with EFs derived from SSD‐EC50 models, implying a similar chemical ecotoxicity rank order and method robustness. Our approach is an important step toward considering the potential ecotoxic impacts of chemicals currently neglected in assessment frameworks due to limited test data. Environ Toxicol Chem 2024;43:1914–1927. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Publisher

Wiley

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Extrapolation factors for calculating ecotoxicity effects in LCA;The International Journal of Life Cycle Assessment;2024-09-10

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