TREXMO: A Translation Tool to Support the Use of Regulatory Occupational Exposure Models.

Savic N; Racordon D; Buchs D; Gasic B; Vernez D

doi:10.1093/annhyg/mew042

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Journal article

TREXMO: A Translation Tool to Support the Use of Regulatory Occupational Exposure Models.

Savic N 1.Institute for Work and Health (IST), University of Lausanne and University of Geneva, Rte de la Corniche 2, 1066 Epalinges-Lausanne, Switzerland; nenad.savic@chuv.ch.
Racordon D 2.Computer Science Department, University of Geneva, Building A, 7 rte de Drize, 1227 Carouge, Geneva, Switzerland;
Buchs D 2.Computer Science Department, University of Geneva, Building A, 7 rte de Drize, 1227 Carouge, Geneva, Switzerland;
Gasic B 3.Chemicals and Occupational Health Unit, State Secretariat for Economic Affairs (SECO), Holzikofenweg 36, 3003 Bern, Switzerland.
Vernez D 1.Institute for Work and Health (IST), University of Lausanne and University of Geneva, Rte de la Corniche 2, 1066 Epalinges-Lausanne, Switzerland;

2016-07-01

Published in:

The Annals of occupational hygiene. - 2016

English Occupational exposure models vary significantly in their complexity, purpose, and the level of expertise required from the user. Different parameters in the same model may lead to different exposure estimates for the same exposure situation. This paper presents a tool developed to deal with this concern-TREXMO or TRanslation of EXposure MOdels. TREXMO integrates six commonly used occupational exposure models, namely, ART v.1.5, STOFFENMANAGER(®) v.5.1, ECETOC TRA v.3, MEASE v.1.02.01, EMKG-EXPO-TOOL, and EASE v.2.0. By enabling a semi-automatic translation between the parameters of these six models, TREXMO facilitates their simultaneous use. For a given exposure situation, defined by a set of parameters in one of the models, TREXMO provides the user with the most appropriate parameters to use in the other exposure models. Results showed that, once an exposure situation and parameters were set in ART, TREXMO reduced the number of possible outcomes in the other models by 1-4 orders of magnitude. The tool should manage to reduce the uncertain entry or selection of parameters in the six models, improve between-user reliability, and reduce the time required for running several models for a given exposure situation. In addition to these advantages, registrants of chemicals and authorities should benefit from more reliable exposure estimates for the risk characterization of dangerous chemicals under Regulation, Evaluation, Authorisation and restriction of CHemicals (REACH).

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