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Assessing predictive uncertainty in comparative toxicity potentials of triazoles
Author(s) -
Golsteijn Laura,
Iqbal M. Sarfraz,
Cassani Stefano,
Hendriks Harrie W.M.,
Kovarich Simona,
Papa Ester,
Rorije Emiel,
Sahlin Ullrika,
Huijbregts Mark A.J.
Publication year - 2014
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.2429
Subject(s) - sorption , environmental science , monte carlo method , environmental chemistry , uncertainty analysis , biological system , chemistry , statistics , mathematics , biology , organic chemistry , adsorption
Comparative toxicity potentials (CTPs) quantify the potential ecotoxicological impacts of chemicals per unit of emission. They are the product of a substance's environmental fate, exposure, and hazardous concentration. When empirical data are lacking, substance properties can be predicted. The goal of the present study was to assess the influence of predictive uncertainty in substance property predictions on the CTPs of triazoles. Physicochemical and toxic properties were predicted with quantitative structure–activity relationships (QSARs), and uncertainty in the predictions was quantified with use of the data underlying the QSARs. Degradation half‐lives were based on a probability distribution representing experimental half‐lives of triazoles. Uncertainty related to the species' sample size that was present in the prediction of the hazardous aquatic concentration was also included. All parameter uncertainties were treated as probability distributions, and propagated by Monte Carlo simulations. The 90% confidence interval of the CTPs typically spanned nearly 4 orders of magnitude. The CTP uncertainty was mainly determined by uncertainty in soil sorption and soil degradation rates, together with the small number of species sampled. In contrast, uncertainty in species‐specific toxicity predictions contributed relatively little. The findings imply that the reliability of CTP predictions for the chemicals studied can be improved particularly by including experimental data for soil sorption and soil degradation, and by developing toxicity QSARs for more species. Environ Toxicol Chem 2014;33:293–301. © 2013 SETAC

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