Schinkel Jody, Warren Nicholas, Fransman Wouter, van Tongeren Martie, McDonnell Patricia, Voogd Eef, Cherrie John W, Tischer Martin, Kromhout Hans, Tielemans Erik
TNO Quality and Safety, PO Box 360, 3700 AJ, Zeist, The Netherlands.
J Environ Monit. 2011 May;13(5):1374-82. doi: 10.1039/c1em00007a. Epub 2011 Mar 14.
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.
高级接触工具（ART）的机理模型提供了不同场景下接触水平的相对排名。本文所述校准的目标有三个：研究机理模型得分相对于接触测量值是否准确排名；使机理模型能够估计实际接触水平而非相对得分；并提供一种量化模型不确定性的方法。严格的数据质量指南应用于整理后的数据。线性混合效应模型用于评估ART模型相对得分与测量值之间的关联。引入了随机场景和公司方差成分以反映模型不确定性。针对不同形式的接触（磨料粉尘、粉尘、蒸汽和雾）进行了分层分析。总共超过2000个高质量测量值可用于机理模型的校准。校准表明，校准后ART的机理模型能够以90%的置信度估计给定场景下的几何平均（GM）接触水平，根据接触形式的不同，其值在测量GM的两到六倍之间。
