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 which are of concern and those which are not. The Stoffenmanager is mentioned as a 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 (n¼254). Correlations between observed and predicted exposures, bias and precision were calculated. Stratified analyses were performed for the scenarios "handling of powders and granules" (n¼82), "handling solids resulting in comminuting" (n¼60), "handling of low-volatile liquids" (n¼40) and "handling of volatile liquids" (n¼72).Results The relative bias of the four algorithms ranged between À9% and À77% with a precision of approximately 1.7. The 90th percentile estimate of one out of four 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 into one dataset (n¼952) used for calibrating the adapted Stoffenmanager algorithms. This new calibration resulted in new exposure algorithms for the four scenarios. Conclusions The Stoffenmanager is capable of discriminating among exposure levels mainly between scenarios in different companies. The 90th 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.

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.

As it is often difficult to obtain sufficient numbers of measurements to adequately characterise exposure levels, occupational exposure models may be useful tools in the exposure assessment process. This study aims to refine and validate the inhalable dust algorithm of the Advanced REACH Tool (ART) to predict airborne exposure of workers in the pharmaceutical industry. The ART was refined to reflect pharmaceutical situations. Largely task based workplace exposure data (n ¼ 192) were collated from a multinational pharmaceutical company with exposure levels ranging from 5 Â 10 À5 to 12 mg m À3 . Bias, relative bias and uncertainty around geometric mean exposure estimates were calculated for 16 exposure scenarios. For 12 of the 16 scenarios the ART geometric mean exposure estimates were lower than measured exposure levels with on average, a one-third underestimation of exposure (relative bias À32%). For 75% of the scenarios the exposure estimates were, within the 90% uncertainty factor of 4.4, as reported for the original calibration study, which may indicate more uncertainty in the ART estimates in this industry. While the uncertainty was higher than expected this is likely due to the limited number of measurements per scenario, which were largely derived from single premises.

The ART is an expert tool and extensive training is recommended prior to use. Improvements of the guidance documentation, consensus procedures, and improving the training methods could improve the reliability of ART. Nevertheless, considerable variability can be expected between assessors using ART to estimate exposure levels for a given scenario.

The aim of this study was to assess exposure to pesticides for a longitudinal epidemiological study on adverse reproduction effects among greenhouse workers. Detailed information on pesticide use among greenhouse workers was obtained on a monthly basis through self-administered questionnaires and subsequent workplace surveys. Questionnaires were filled in for a whole year. Dermal exposure rankings were developed for each task using the observational method Dermal Exposure Assessment Method (DREAM). Exposure scores were calculated for each worker for each month during the year, taking into account frequency, duration and exposure intensity for each task. A total number of 116 different active ingredients were used in the population, whereas a mean number of 15 active ingredients were applied per greenhouse. DREAM observations provided insight into the exposure intensity of 12 application techniques and three mixing and loading activities. Relatively high DREAM scores were obtained for scattering, fogging, dusting, and mixing and loading of powders. Observations with DREAM indicated that application with a horizontal ground-boom, motor driven boom, and bulb shower resulted in low dermal exposure. Exposure scores showed substantial variation between workers and over the year. It can be concluded that exposure variation between-and within greenhouses is very large, both in terms of chemical composition and exposure intensity. This may be a significant contributor to the inconsistent results of studies evaluating health effects of pesticide exposure.