title: The MCRA model for probabilistic single-compound and cumulative risk assessment of pesticides.
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 at mcra.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.
authors.affiliation: Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands. Electronic address: hilko.vandervoet@wur.nl.
authors.forename: Hilko
authors.initials: H
authors.lastname: van der Voet
authors.affiliation: Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands.
authors.forename: Waldo J
authors.initials: WJ
authors.lastname: de Boer
authors.affiliation: Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands.
authors.forename: Johannes W
authors.initials: JW
authors.lastname: Kruisselbrink
authors.affiliation: Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands.
authors.forename: Paul W
authors.initials: PW
authors.lastname: Goedhart
authors.affiliation: Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands.
authors.forename: Gerie W A M
authors.initials: GW
authors.lastname: van der Heijden
authors.affiliation: Food and Environmental Research Agency (FERA), Sand Hutton, United Kingdom.
authors.forename: Marc C
authors.initials: MC
authors.lastname: Kennedy
authors.affiliation: National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
authors.forename: Polly E
authors.initials: PE
authors.lastname: Boon
authors.affiliation: National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
authors.forename: Jacob D
authors.initials: JD
authors.lastname: van Klaveren
mesh_terms: D054750:Ecotoxicology / Q000379:methods*; D004787:Environmental Pollution / Q000009:adverse effects*; D005062:European Union; D005506:Food Contamination / Q000517:prevention & control; D017408:Guidelines as Topic; D006801:Humans; D020407:Internet; D015233:Models, Statistical; D009010:Monte Carlo Method; D010573:Pesticide Residues / Q000633:toxicity*; D010575:Pesticides / Q000633:toxicity*; D018570:Risk Assessment / Q000592:standards; D012984:Software; D012986:Software Validation
chemical_list: D010573:Pesticide Residues; D010575:Pesticides
keywords: Agricultural use; Combined exposure; DEEM model; EFSA Guidance; Model validation; Monte Carlo Risk Assessment