Institute for Chemical and Bioengineering, ETH Zurich Swiss Federal Institute of Technology, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland.
National Institute for Public Health and the Environment (RIVM), P.O. Box 1, Bilthoven, 3720 BA, The Netherlands.
Environ Int. 2015 Jun;79:8-16. doi: 10.1016/j.envint.2015.03.006. Epub 2015 Mar 10.
Current practice of chemical risk assessment for consumer product ingredients still rarely exercises the aggregation of multi-source exposure. However, focusing on a single dominant source/pathway combination may lead to a significant underestimation of the risk for substances present in numerous consumer products, which often are used simultaneously. Moreover, in most cases complex multi-route exposure scenarios also need to be accounted for. This paper introduces and evaluates the performance of the Probabilistic Aggregate Consumer Exposure Model (PACEM) applied in the context of a tiered approach to exposure assessment for ingredients in cosmetics and personal care products (C&PCPs) using decamethylcyclopentasiloxane (D5) as a worked example. It is demonstrated that PACEM predicts a more realistic, but still conservative aggregate exposure within the Dutch adult population when compared to a deterministic point estimate obtained in a lower tier screening assessment. An overall validation of PACEM is performed by quantitatively relating and comparing its estimates to currently available human biomonitoring and environmental sampling data. Moderate (by maximum one order of magnitude) overestimation of exposure is observed due to a justified conservatism built into the model structure, resulting in the tool being suitable for risk assessment.
目前,消费品成分的化学风险评估实践仍然很少考虑多源暴露的综合评估。然而,仅关注单一主导源/途径组合可能会导致对存在于众多消费品中的物质的风险评估严重低估,而这些物质通常是同时使用的。此外,在大多数情况下,还需要考虑复杂的多途径暴露情况。本文介绍并评估了概率综合消费者暴露模型(PACEM)在化妆品和个人护理产品(C&PCP)成分暴露评估分层方法背景下的性能,并用十甲基环五硅氧烷(D5)作为实例进行了说明。结果表明,与低层次筛选评估中获得的确定性单点估计相比,PACEM 预测荷兰成年人群体的综合暴露更符合实际情况,但仍具有保守性。通过定量关联和比较其估计值与当前可用的人体生物监测和环境采样数据,对 PACEM 进行了全面验证。由于模型结构中内置了合理的保守性,暴露的适度高估(最高可达一个数量级),使得该工具适用于风险评估。