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Abstract Exposure to asbestos fibres is linked to numerous adverse health effects, and the use of asbestos is currently banned in many countries. Still, asbestos is present in numerous buildings and installations, which need to be removed in the (near) future. Exposure measurements give good insight in exposure levels, but collecting measurements for all possible situations is costly and time-consuming, as working conditions and materials vary greatly. Therefore, the mechanistic model Asbestos Removal Exposure Assessment Tool (AREAT) was developed to estimate exposure to respirable asbestos fibres released during asbestos abatement processes. The model was developed using scientific literature, an in-house dataset containing measurements of asbestos abatements in the Netherlands, and knowledge with regard to previously developed (generic) exposure models. The model consists of several exposure determinants such as substance emission potential, activity emission potential, control measures and dilution in air, taking into account near- and far-field sources of exposure. Through an algorithm, AREAT calculates dimensionless scores based on model inputs, which are translated to estimated fibre concentrations by a mixed effect model which was applied on the dataset. The model has also been validated against additional data. The AREAT model is integrated in an assessment tool called SMART-NS, in which users describe the asbestos removal scenario based on a series of questions with regards to the asbestos containing material, removal method and controls in place. Exposure levels are then estimated based on either validated safe working procedures, available exposure measurements or modelled exposure levels by means of the AREAT model. Based on the estimated exposure level a control regime is prescribed.
Franken et al. (Sat,) studied this question.