Sensitivity-based research prioritization through stochastic characterization modeling

Publication: Research - peer-reviewJournal article – Annual report year: 2017

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Product developers using life cycle toxicity characterization models to understand the potential impacts of chemical emissions face serious challenges related to large data demands and high input data uncertainty. This motivates greater focus on model sensitivity toward input parameter variability to guide research efforts in data refinement and design of experiments for existing and emerging chemicals alike. This study presents a sensitivity-based approach for estimating toxicity characterization factors given high input data uncertainty and using the results to prioritize data collection according to parameter influence on characterization factors (CFs). Proof of concept is illustrated with the UNEP-SETAC scientific consensus model USEtox.
Original languageEnglish
JournalInternational Journal of Life Cycle Assessment
Number of pages9
ISSN0948-3349
DOIs
StateAccepted/In press - 29 Apr 2017
CitationsWeb of Science® Times Cited: No match on DOI
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