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Douziech M, Oldenkamp R, van Zelm R, King H, Hendriks AJ, Ficheux AS, Huijbregts MAJ. Confronting variability with uncertainty in the ecotoxicological impact assessment of down-the-drain products. ENVIRONMENT INTERNATIONAL 2019; 126:37-45. [PMID: 30776748 DOI: 10.1016/j.envint.2019.01.080] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 01/24/2019] [Accepted: 01/29/2019] [Indexed: 05/07/2023]
Abstract
The use of down-the-drain products and the resultant release of chemicals may lead to pressures on the freshwater environment. Ecotoxicological impact assessment is a commonly used approach to assess chemical products but is still influenced by several uncertainty and variability sources. As a result, the robustness and reliability of such assessments can be questioned. A comprehensive and systematic assessment of these sources is, therefore, needed to increase their utility and credibility. In this study, we present a method to systematically analyse the uncertainty and variability of the potential ecotoxicological impact (PEI) of chemicals using a portfolio of 54 shampoo products. We separately quantified the influence of the statistical uncertainty in the prediction of physicochemical properties and freshwater toxicity as predicted from Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) respectively, and of various sources of spatial and technological variability as well as variability in consumer habits via 2D Monte Carlo simulations. Overall, the variation in the PEIs of shampoo use was mainly the result of uncertainty due to the use of toxicity data from three species only. All uncertainty sources combined resulted in PEIs ranging on average over seven orders of magnitude (ratio of the 90th to the 10th percentile) so that an absolute quantification of the ecological risk would not be meaningful. In comparison, variation in shampoo composition was the most influential source of variability, although less than compared to uncertainty, leading to PEIs ranging over three orders of magnitude. Increasing the number of toxicity data by increasing the number of species, either through additional measurements or ecotoxicological modelling (e.g. using Interspecies Correlation Equations), should get priority to improve the reliability of PEIs. These conclusions are not limited to shampoos but are applicable more generally to the down-the-drain products since they all have similar data limitations and associated uncertainties relating to the availability of ecotoxicity data and variability in consumer habits and use.
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Affiliation(s)
- Mélanie Douziech
- Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500, GL, Nijmegen, the Netherlands.
| | - Rik Oldenkamp
- Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500, GL, Nijmegen, the Netherlands; Environment Department, University of York, York, United Kingdom
| | - Rosalie van Zelm
- Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500, GL, Nijmegen, the Netherlands
| | - Henry King
- Safety & Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire MK441LQ, United Kingdom
| | - A Jan Hendriks
- Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500, GL, Nijmegen, the Netherlands
| | - Anne-Sophie Ficheux
- Laboratoire d'Evaluation du Risque Chimique pour le Consommateur (LERCCo), Université Européenne de Bretagne e Université de Bretagne Occidentale (UEB-UBO), UFR Sciences et Techniques, 6 Av. Victor Le Gorgeu, CS93837, 29238 Brest Cedex 3, France
| | - Mark A J Huijbregts
- Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500, GL, Nijmegen, the Netherlands
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Tao M, Li D, Song R, Suh S, Keller AA. OrganoRelease - A framework for modeling the release of organic chemicals from the use and post-use of consumer products. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 234:751-761. [PMID: 29245149 DOI: 10.1016/j.envpol.2017.11.058] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Revised: 11/15/2017] [Accepted: 11/16/2017] [Indexed: 05/03/2023]
Abstract
Chemicals in consumer products have become the focus of recent regulatory developments including California's Safer Consumer Products Act. However, quantifying the amount of chemicals released during the use and post-use phases of consumer products is challenging, limiting the ability to understand their impacts. Here we present a comprehensive framework, OrganoRelease, for estimating the release of organic chemicals from the use and post-use of consumer products given limited information. First, a novel Chemical Functional Use Classifier estimates functional uses based on chemical structure. Second, the quantity of chemicals entering different product streams is estimated based on market share data of the chemical functional uses. Third, chemical releases are estimated based on either chemical product categories or functional uses by using the Specific Environmental Release Categories and EU Technological Guidance Documents. OrganoRelease connects 19 unique functional uses and 14 product categories across 4 data sources and provides multiple pathways for chemical release estimation. Available user information can be incorporated in the framework at various stages. The Chemical Functional Use Classifier achieved an average accuracy above 84% for nine functional uses, which enables the OrganoRelease to provide release estimates for the chemical, mostly using only the molecular structure. The results can be can be used as input for methods estimating environmental fate and exposure.
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Affiliation(s)
- Mengya Tao
- Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA, 93106, United States.
| | - Dingsheng Li
- Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA, 93106, United States.
| | - Runsheng Song
- Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA, 93106, United States.
| | - Sangwon Suh
- Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA, 93106, United States.
| | - Arturo A Keller
- Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA, 93106, United States.
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