New approaches to uncertainty analysis for use in aggregate and cumulative risk assessment of pesticides. (May 2015)

• Record Type: Journal Article
• Authors: Kennedy, Marc C.; van der Voet, Hilko; Roelofs, Victoria J.; Roelofs, Willem; Glass, C. Richard; de Boer, Waldo J.; Kruisselbrink, Johannes W.; Hart, Andy D.M.
• Is Part Of: Food and chemical toxicology. Volume 79(2015)
• Page Start: 54
• Page End: 64
• Publication Date: 2015-05
• Subjects: Common assessment group -- Probabilistic modelling -- Occupational exposure -- Consumer exposure -- Multiple pesticides; Toxicology -- Periodicals; Food poisoning -- Periodicals; Food Poisoning -- Periodicals; Toxicology -- Periodicals; Toxicologie -- Périodiques; Intoxications alimentaires -- Périodiques; Food poisoning; Toxicology; Periodicals; Electronic journals; 615.9
• DOI: 10.1016/j.fct.2015.02.008
• Languages: English
• ISSNs: 0278-6915

Abstract

Graphical Abstract: Highlights: Uncertainty in aggregate and cumulative pesticide exposure are considered. A general strategy is presented to prioritise and handle uncertainties. Examples including dietary and non-dietary exposures are illustrated using MCRA. A new method is described to combine pesticide usage and monitoring data. Alternative approaches to quantify uncertainty and variability in 2DMC are discussed. Abstract: Risk assessments for human exposures to plant protection products (PPPs) have traditionally focussed on single routes of exposure and single compounds. Extensions to estimate aggregate (multi-source) and cumulative (multi-compound) exposure from PPPs present many new challenges and additional uncertainties that should be addressed as part of risk analysis and decision-making. A general approach is outlined for identifying and classifying the relevant uncertainties and variabilities. The implementation of uncertainty analysis within the MCRA software, developed as part of the EU-funded ACROPOLIS project to address some of these uncertainties, is demonstrated. An example is presented for dietary and non-dietary exposures to the triazole class of compounds. This demonstrates the chaining of models, linking variability and uncertainty generated from an external model for bystander exposure with variability and uncertainty in MCRA dietary exposure assessments. A new method is also presented for combining pesticide usage survey information with limited residue monitoring data, to address non-detect uncertainty. The results show that incorporating usage information reduces uncertainty in parameters of the residue distribution but that in this case quantifying uncertainty is not a priority, at least for UK grown crops. A general discussion of alternative approaches to treat uncertainty, either quantitatively or qualitatively, is included.