TY - JOUR
T1 - Sensitivity-based research prioritization through stochastic characterization modeling
AU - Wender, Ben A.
AU - Prado-Lopez, Valentina
AU - Fantke, Peter
AU - Ravikumar, Dwarakanath
AU - Seager, Thomas P.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
U2 - 10.1007/s11367-017-1322-y
DO - 10.1007/s11367-017-1322-y
M3 - Journal article
VL - 23
SP - 324
EP - 332
JO - International Journal of Life Cycle Assessment
JF - International Journal of Life Cycle Assessment
SN - 0948-3349
IS - 2
ER -