STOFFENMANAGER® and ART are widely used knowledge-based exposure models that produce qualitative exposure estimates. While these models have been evaluated at the ‘operational analysis’ level, there is a need for robust internal and external evaluations to better understand why the models tend to underestimate high exposures and overestimate low exposures. This paper is important for identifying models and types of models where improvements are needed – and the critical need for more, high-quality data to support these improvements. It also points to the need for further discussion around the best use of the different types of models to meet specific objectives (e.g. regulatory versus epidemiological) when the level of knowledge and availability of data differ.
Please refer to the link below for the full paper. Professor Arnold is one of the co-authors.
Antti Joonas Koivisto, Michael Jayjock, Kaarle J Hämeri, Markku Kulmala, Patrick Van Sprang, Mingzhou Yu, Brandon E Boor, Tareq Hussein, Ismo K Koponen, Jakob Löndahl, Lidia Morawska, John C Little, Susan Arnold, Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool, Annals of Work Exposures and Health, 2021;, wxab057, https://doi.org/10.1093/annweh/wxab057