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Understanding quantitative structure-property relationships uncertainty in environmental fate modeling
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
Radboud University.
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.ORCID iD: 0000-0001-9382-9296
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
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2013 (English)In: Environmental Toxicology and Chemistry, ISSN 0730-7268, E-ISSN 1552-8618, Vol. 32, no 5, 1069-1076 p.Article in journal (Refereed) Published
Abstract [en]

In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structure–property relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered QSPR predictions of the fate input parameters' melting point, water solubility, vapor pressure, organic carbon–water partition coefficient, hydroxyl radical degradation, biodegradation, and photolytic degradation. Uncertainty in POV and LRTP was dominated by the uncertainty in direct photolysis and the biodegradation half-life in water. However, the QSPRs developed specifically for PBDEs had a relatively low contribution to uncertainty. These findings suggest that the reliability of the ranking of PBDEs on the basis of POV and LRTP can be substantially improved by developing better QSPRs to estimate degradation properties. The present study demonstrates the use of uncertainty and sensitivity analyses in nontesting strategies and highlights the need for guidance when compounds fall outside the applicability domain of a QSPR.

Place, publisher, year, edition, pages
2013. Vol. 32, no 5, 1069-1076 p.
National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
URN: urn:nbn:se:lnu:diva-23272DOI: 10.1002/etc.2167ISI: 000317852700013OAI: oai:DiVA.org:lnu-23272DiVA: diva2:582480
Available from: 2013-01-04 Created: 2013-01-04 Last updated: 2016-11-15Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • modern-language-association-8th-edition
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Language
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