Objectives: For regulatory risk assessment under REACH a tiered approach is proposed in which the first tier models should provide a conservative exposure estimate that can discriminate between scenarios of concern and those which are not. The Stoffenmanager is mentioned as first tier approach in the REACH guidance. In an attempt to investigate the validity of the Stoffenmanager algorithms a cross-validation study was performed.
Methods: Exposure estimates using the Stoffenmanager algorithms were compared with exposure measurement results (n=254). Correlations between observed and predicted exposures, bias and precision were calculated. Stratified analyses were performed for the scenarios “handling of powders and granules” (n=82), “handling solids resulting in comminuting” (n=60), “handling of low-volatile liquids” (n=40) and for “handling of volatile liquids” (n=72).
Results: The relative bias of the 4 algorithms ranged between -9% and -77% with a precision of approximately 1.7. The 90-percentile estimate of 1 out of 4 algorithms was not conservative enough. Based on these statistics and analyses of residual plots the underlying algorithm was adapted. Subsequently, the calibration and the cross-validation dataset were merged to one dataset (n=952) used for calibrating the adapted Stoffenmanager algorithms. This new calibration resulted in new exposure algorithms for the 4 scenarios.
Conclusions: The Stoffenmanager is capable of discriminating among exposure levels mainly between scenarios in different companies. The 90-percentile estimates of the Stoffenmanager are verified to be sufficiently conservative. Therefore, the Stoffenmanager could be a useful Tier 1 exposure assessment tool for REACH.
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