The MCRA model for probabilistic single-compound and cumulative risk assessment of pesticides. (May 2015)

• Record Type: Journal Article
• Authors: van der Voet, Hilko; de Boer, Waldo J.; Kruisselbrink, Johannes W.; Goedhart, Paul W.; van der Heijden, Gerie W.A.M.; Kennedy, Marc C.; Boon, Polly E.; van Klaveren, Jacob D.
• Is Part Of: Food and chemical toxicology. Volume 79(2015)
• Page Start: 5
• Page End: 12
• Publication Date: 2015-05
• Subjects: Monte Carlo Risk Assessment -- Combined exposure -- EFSA Guidance -- Agricultural use -- Model validation -- DEEM model; 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.2014.10.014
• Languages: English
• ISSNs: 0278-6915

Abstract

Graphical Abstracts: Highlights: We present the MCRA software for modelling pesticide probabilistic risk assessment. Mixtures of pesticides are handled in advanced cumulative risk assessment models. Dietary and non-dietary exposures can be combined in aggregate risk assessments. Both variability and uncertainty of exposure are modelled. The software was validated using synthetic data and by comparisons to other models. Abstract: Pesticide risk assessment is hampered by worst-case assumptions leading to overly pessimistic assessments. On the other hand, cumulative health effects of similar pesticides are often not taken into account. This paper describes models and a web-based software system developed in the European research project ACROPOLIS. The models are appropriate for both acute and chronic exposure assessments of single compounds and of multiple compounds in cumulative assessment groups. The software system MCRA (Monte Carlo Risk Assessment) is available for stakeholders in pesticide risk assessment atmcra.rivm.nl . We describe the MCRA implementation of the methods as advised in the 2012 EFSA Guidance on probabilistic modelling, as well as more refined methods developed in the ACROPOLIS project. The emphasis is on cumulative assessments. Two approaches, sample-based and compound-based, are contrasted. It is shown that additional data on agricultural use of pesticides may give more realistic risk assessments. Examples are given of model and software validation of acute and chronic assessments, using both simulated data and comparisons against the previous release of MCRA and against the standard software DEEM-FCID used by the Environmental Protection Agency in the USA. It is shown that the EFSA Guidance pessimistic model may not always give an appropriate modelling of exposure.