Sensitivity Analysis, Dominant Factors, and Robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 Occupational Exposure Models

Abstract

Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.

The general ventilation multipliers calculated by using a standard Near-Field/Far-Field model

“…[5,12] In general, the ventilation multiplier Considering that Stoffenmanager and the ART are classified as higher tier exposure assessment tools, [5,17] both are recommended by ECHA for regulatory exposure assessment, [22] and that Stoffenmanager has alone over 32,000 users, [3] the errors is general ventilation multipliers should not be ignored. The studies [5,[22][23][24][25][26][27][28][29][30] concerning the tools evaluation, validation, applicability, and sensitivity analysis should be revised and corrected before the tools are used in regulatory risk assessment or before implementing them to tools combining different exposure models, such as a Translation Tool to Support the Use of Regulatory Occupational Exposure Models (TREXMO; [31] see also letter to the editors, [31][32][33] ) SUN decision support system, [34] or risk governance tools developed in caLIBERAte. [35] In our opinion, the regulatory exposure modeling should rely only on mathematical models following general physical principles, such as conservation of mass, rather than conceptual models based on non-physical models or exposure determinants.…”

Evaluation of the ECETOC TRA model for workplace inhalation exposure to ethylbenzene in Japan

“…5 [ 2 _ T D $ D I F F ] Further work is underway to clarify acceptance of the changes to PROC 7 from PROC 10 in this study.…”

Health Risk Assessment of Photoresists Used in an Optoelectronic Semiconductor Factory

“…We selected Stoffenmanager® from the available mechanistic models, based on our review of past validations and sensitivity studies that compared common mechanistic tools. Overall, estimates by the Stoffenmanager approach yield more accurate estimates than those from the other models of the same tier and remain conservative when compared to higher tier models, which sometimes underestimate the exposure (Koppisch, Schinkel, Gabriel, Fransman, & Tielemans, ; Landberg, Axmon, Westberg, & Tinnerberg, ; Riedmann, Gasic, & Vernez, ; Schinkel et al., ; Spinazzè et al., ). Navigation of Stoffenmanager quantitative exposure estimation module is briefly outlined in the Supporting Information.…”

“…One potential variation in the prior specification could arise from between‐user variations in assigning parameters for Stoffenmanager. Past reliability surveys have found that among parameters used in Stoffenmanager and similar models, the parameter “type of activity/handling” tends to be the most sensitive, yet it also tends to have larger user variations in selection (Landberg et al., ; Riedmann et al., ; Schinkel et al., ). We varied “handling type” by one order above and one order below the original setting, to characterize the impact of prior sensitivity according to Stoffenmanager reliability (Fig.…”