Advanced REACH Tool (ART): Calibration of the mechanistic model

Jody Schinkel*, Nicholas Warren, Wouter Fransman, Martie Van Tongeren, Patricia McDonnell, Eef Voogd, John W. Cherrie, Martin Tischer, Hans Kromhout, Erik Tielemans

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    57 Citations (Scopus)


    The mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper are threefold: to study whether the mechanistic model scores are accurately ranked in relation to exposure measurements; to enable the mechanistic model to estimate actual exposure levels rather than relative scores; and to provide a method of quantifying model uncertainty. Stringent data quality guidelines were applied to the collated data. Linear mixed effects models were used to evaluate the association between relative ART model scores and measurements. A random scenario and company component of variance were introduced to reflect the model uncertainty. Stratified analyses were conducted for different forms of exposure (abrasive dust, dust, vapours and mists). In total more than 2000 good quality measurements were available for the calibration of the mechanistic model. The calibration showed that after calibration the mechanistic model of ART was able to estimate geometric mean (GM) exposure levels with 90% confidence for a given scenario to lie within a factor between two and six of the measured GM depending upon the form of exposure.

    Original languageEnglish
    Pages (from-to)1374-1382
    Number of pages9
    JournalJournal of Environmental Monitoring
    Issue number5
    Publication statusPublished - 1 May 2011

    ASJC Scopus subject areas

    • Management, Monitoring, Policy and Law
    • Public Health, Environmental and Occupational Health


    Dive into the research topics of 'Advanced REACH Tool (ART): Calibration of the mechanistic model'. Together they form a unique fingerprint.

    Cite this