4.3 Article

Theoretical Background of Occupational-Exposure Models-Report of an Expert Workshop of the ISES Europe Working Group Exposure Models

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MDPI
DOI: 10.3390/ijerph19031234

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occupational-exposure modelling; mass-balance model; modifying-factor model; regulatory exposure modelling; workshop

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This article introduces an online workshop organized by ISES Europe to discuss theoretical background and challenges of occupational exposure models for chemicals. The workshop aims to address the main challenges in developing, validating, and using such models for regulatory purposes, and also explores the relationship between modeling and monitoring, as well as the need for common monitoring databases.
On 20 October 2020, the Working Group Exposure Models of the Europe Regional Chapter of the International Society of Exposure Science (ISES Europe) organised an online workshop to discuss the theoretical background of models for the assessment of occupational exposure to chemicals. In this report, participants of the workshop with an active role before and during the workshop summarise the most relevant discussion points and conclusions of this well-attended workshop. ISES Europe has identified exposure modelling as one priority area for the strategic development of exposure science in Europe in the coming years. This specific workshop aimed to discuss the main challenges in developing, validating, and using occupational-exposure models for regulatory purposes. The theoretical background, application domain, and limitations of different modelling approaches were presented and discussed, focusing on empirical modifying-factor or mass-balance-based approaches. During the discussions, these approaches were compared and analysed. Possibilities to address the discussed challenges could be a validation study involving alternative modelling approaches. The wider discussion touched upon the close relationship between modelling and monitoring and the need for better linkage of the methods and the need for common monitoring databases that include data on model parameters.

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