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.

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The aim of this work was to identify the key mechanisms governing transport of organic chemical substances from consumer articles to cotton wipes. The results were used to establish a mechanistic model to improve assessment of dermal contact exposure. Four types of PVC flooring, 10 types of textiles and one type of inkjet printed paper were used to establish the mechanisms and model. Kinetic extraction studies in methanol demonstrated existence of matrix diffusion and indicated the presence of a substance surface layer on some articles. Consequently, the proposed substance transfer model considers mechanical transport from a surface film and matrix diffusion in an article with a known initial total substance concentration. The estimated chemical substance transfer values to cotton wipes were comparable to the literature data (relative transfer ∼ 2%), whereas relative transfer efficiencies from spiked substrates were high (∼ 50%). For consumer articles, high correlation (r(2)=0.92) was observed between predicted and measured transfer efficiencies, but concentrations were overpredicted by a factor of 10. Adjusting the relative transfer from about 50% used in the model to about 2.5% removed overprediction. Further studies are required to confirm the model for generic use.

On 18 farms for rose culture in greenhouses in The Netherlands, dermal exposure of hands and forearms to abamectin (avermectin B1), dodemorph (4-cyclododecyl-2,6-dimethylmorpholinium acetate) and bupirimate (5-butyl-2-(ethylamino)-6-methyl-4-pyrimidinyl dimethylsulphate) was measured during crop activities. Dermal exposure during cutting (75 workers) amounted to 13 micrograms/h, 1.8 mg/h, and 2.2 mg/h for abamectin, dodemorph and bupirimate, respectively. Dermal exposure to abamectin and dodemorph during sorting (21 workers) and bundling (30 workers) was comparable with that during cutting. From the dependence of dermal exposure on the amount of dislodgeable foliar residue (DFR) a transfer factor was estimated to be 1,200, 4,550, and 2,400 cm2/h for abamectin, dodemorph and bupirimate, respectively. For sorting and bundling these factors were of the same order of magnitude. The results suggested that work rate was also a determinant of dermal exposure. The within-farm variance of dermal exposure during cutting appeared to account for approximately 30% of the unexplained part of the variation remaining after regression on DFR and application technique. The final unexplained part in the variation of dermal exposure during cutting was amongst others due to the variation between the different farms in which the measurements were performed. A health risk evaluation of the observed levels of dermal exposure after re-entry of greenhouses led to the conclusion that a health hazard may exist, especially after application of high rates of relatively toxic pesticides which easily penetrate the skin.

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Crop activities lead to dermal exposure of workers to pesticides. The efficacy of hand washing as a control measure is unknown. The efficacy of water and soap was studied for some pesticides and exposure situations. Pre-washing contamination levels in field studies were calculated from foliar residues by models using transfer factors. Between 24.5% and 50.7% of the calculated prewashing contamination was removed in two field studies with three pesticides, with coefficients of variation between 43% and 72%. In a human volunteer study, on average 45.8% and 85.7% was removed for two pesticides (coefficients of variation 6% and 7%). No influence of 'washing vigour' was found and efficacy did not depend on pre-washing contamination levels. The combination of field studies and laboratory experiments was successful, partly compensating for weaknesses in both approaches.

The ECETOC TRA model (presently version 3.1) is often used to estimate worker inhalation and dermal exposure in regulatory risk assessment. The dermal model in ECETOC TRA has not yet been validated by comparison with independent measured exposure levels. This was the goal of the present study. Measured exposure levels and relevant contextual information were gathered via literature search, websites of relevant occupational health institutes and direct requests for data to industry. Exposure data were clustered in so-called exposure cases, which are sets of data from one data source that are expected to have the same values for input parameters in the ECETOC TRA dermal exposure model. For each exposure case, the 75th percentile of measured values was calculated, because the model intends to estimate these values. The input values for the parameters in ECETOC TRA were assigned by an expert elicitation and consensus building process, based on descriptions of relevant contextual information.From more than 35 data sources, 106 useful exposure cases were derived, that were used for direct comparison with the model estimates. The exposure cases covered a large part of the ECETOC TRA dermal exposure model. The model explained 37% of the variance in the 75th percentiles of measured values. In around 80% of the exposure cases, the model estimate was higher than the 75th percentile of measured values. In the remaining exposure cases, the model estimate may not be sufficiently conservative.The model was shown to have a clear bias towards (severe) overestimation of dermal exposure at low measured exposure values, while all cases of apparent underestimation by the ECETOC TRA dermal exposure model occurred at high measured exposure values. This can be partly explained by a built-in bias in the effect of concentration of substance in product used, duration of exposure and the use of protective gloves in the model. The effect of protective gloves was calculated to be on average a factor of 34 in this data set, while factors of five to ten were used in the model estimations. There was also an effect of the sampling method in the measured data on the exposure levels. Exposure cases where sampling was done via an interception method, such as gloves, on average showed a factor of six higher 75th percentiles of measured values than exposure cases where sampling was done via a removal method, such as hand washing. This may partly be responsible for the apparent underestimation of dermal exposure by the model at high exposure values. However, there also appeared to be a relation between expected exposure level (as indicated by the model estimate) and the choice of sampling method.In this study, solid substances used in liquid products were treated as liquids with negligible volatility. The results indicate that the ECETOC TRA dermal exposure model performs equally well for these substances as for liquids. There were suggestions of a difference in performance of the model between solids and liquids.For several parts of the ECETOC TRA der...