Ferrier Helen, Shaw George, Nieuwenhuijsen Mark, Boobis Alan, Elliott Paul
Department of Environmental Science and Technology, Imperial College London, SW7 2BP, London, UK.
Food Addit Contam. 2006 Jun;23(6):601-15. doi: 10.1080/02652030600573244.
The assessment of consumer exposure to pesticides is an important part of pesticide regulation. Probabilistic modelling allows analysis of uncertainty and variability in risk assessments. The output of any assessment will be influenced by the characteristics and uncertainty of the inputs, model structure and assumptions. While the use of probabilistic models is well established in the United States, in Europe problems of low acceptance, sparse data and lack of guidelines are slowing the development. The analyses in the current paper focused on the dietary pathway and the exposure of UK toddlers. Three single food, single pesticide case studies were used to parameterize a simple probabilistic model built in Crystal Ball. Data on dietary consumption patterns were extracted from National Diet and Nutrition Surveys, and levels of pesticide active ingredients in foods were collected from Pesticide Residues Committee monitoring. The effect of uncertainty on the exposure estimate was analysed using scenarios, reflecting different assumptions related to sources of uncertainty. The most influential uncertainty issue was the distribution type used to represent input variables. Other sources that most affected model output were non-detects, unit-to-unit variability and processing. Specifying correlation between variables was found to have little effect on exposure estimates. The findings have important implications for how probabilistic modelling should be conducted, communicated and used by policy and decision makers as part of consumer risk assessment of pesticides.
评估消费者接触农药的情况是农药监管的重要组成部分。概率建模有助于分析风险评估中的不确定性和变异性。任何评估的结果都会受到输入数据的特征和不确定性、模型结构及假设的影响。虽然概率模型在美国的使用已得到充分确立，但在欧洲，接受度低、数据稀少以及缺乏指导方针等问题正阻碍其发展。本文的分析聚焦于饮食途径以及英国幼儿的接触情况。通过三个单一食物、单一农药的案例研究，对在Crystal Ball中构建的一个简单概率模型进行参数化。饮食消费模式的数据取自国家饮食与营养调查，食品中农药活性成分的含量则从农药残留委员会的监测中收集。利用反映与不确定性来源相关的不同假设的情景，分析了不确定性对接触估计值的影响。最具影响力的不确定性问题是用于表示输入变量的分布类型。对模型输出影响最大的其他因素包括未检出值、单位间变异性和加工过程。研究发现，指定变量之间的相关性对接触估计值影响不大。这些研究结果对于政策制定者和决策者在进行、交流和使用概率建模作为农药消费者风险评估的一部分方面具有重要意义。
