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
Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands.
Biometris, Wageningen University and Research Centre (WUR), Wageningen, The Netherlands.
Food Chem Toxicol. 2015 May;79:5-12. doi: 10.1016/j.fct.2014.10.014. Epub 2014 Oct 28.
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.
最坏情况假设导致农药风险评估过于悲观,从而阻碍了风险评估。另一方面,类似农药对健康的累积影响往往未被考虑在内。本文介绍了欧洲研究项目ACROPOLIS中开发的模型和基于网络的软件系统。这些模型适用于单一化合物以及累积评估组中多种化合物的急性和慢性暴露评估。软件系统MCRA(蒙特卡罗风险评估)可在mcra.rivm.nl上供农药风险评估的利益相关者使用。我们按照2012年欧洲食品安全局(EFSA)概率建模指南中的建议描述了MCRA对这些方法的实施,以及ACROPOLIS项目中开发的更精细方法。重点是累积评估。对比了基于样本和基于化合物的两种方法。结果表明,有关农药农业使用的更多数据可能会给出更现实的风险评估。给出了急性和慢性评估的模型及软件验证示例,使用了模拟数据,并与MCRA的先前版本以及美国环境保护局使用的标准软件DEEM - FCID进行了比较。结果表明,EFSA指南中的悲观模型可能并不总是能对暴露进行恰当建模。