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Procode is a free of charge web-tool that allows automatic coding of occupational data (free-texts) by implementing Complement Naïve Bayes (CNB) as a machine-learning technique. The paper describes the algorithm, performance evaluation, and future goals regarding the tool's development. Almost 30 000 free-texts with manually assigned classification codes of French classification of occupations (PCS) and French classification of activities (NAF) were used to train CNB. A 5-fold cross-validation found that Procode predicts correct classification codes in 57-81 and 63-83% cases for PCS and NAF, respectively. Procode also integrates recoding between two classifications. In the first version of Procode, this operation, however, is only a simple search function of recoding links in existing crosswalks. Future focus of the project will be collection of the data to support automatic coding to other classification and to establish a more advanced method for recoding., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Stoffenmanager®v4.5 and Advanced REACH Tool (ART) v1.5, two higher tier exposure assessment tools for use under REACH, were evaluated by determining accuracy and robustness. A total of 282 exposure measurements from 51 exposure situations (ESs) were collected and categorized by exposure category. In this study, only the results of liquids with vapor pressure (VP) > 10 Pa category having a sufficient number of exposure measurements (n = 251 with 42 ESs) were utilized. In addition, the results were presented by handling/activity description and input parameters for the same exposure category. It should be noted that the performance results of Stoffenmanager and ART in this study cannot be directly compared for some ESs because ART allows a combination of up to four subtasks (and nonexposed periods) to be included, whereas the database for Stoffenmanager, separately developed under the permission of the legal owner of Stoffenmanager, permits the use of only one task to predict exposure estimates. Thus, it would be most appropriate to compare full-shift measurements against ART predictions (full shift including nonexposed periods) and task-based measurements against task-based Stoffenmanager predictions. For liquids with VP > 10 Pa category, Stoffenmanager®v4.5 appeared to be reasonably accurate and robust when predicting exposures [percentage of measurements exceeding the tool's 90th percentile estimate (%M > T) was 15%]. Areas that could potentially be improved include ESs involving the task of handling of liquids on large surfaces or large work pieces, allocation of high and medium VP inputs, and absence of local exhaust ventilation input. Although the ART's median predictions appeared to be reasonably accurate for liquids with VP > 10 Pa, the %M > T for the 90th percentile estimates was 41%, indicating that variance in exposure levels is underestimated by ART. The %M > T using the estimates of the upper value of 90% confidence interval (CI) of the 90th percentile estimate (UCI90) was considerably reduced to 18% for liquids with VP > 10 Pa. On the basis of this observation, users might be to consider using the upper limit value of 90% CI of the 90th percentile estimate for predicting reasonable worst case situations. Nevertheless, for some activities and input parameters, ART still shows areas to be improved. Hence, it is suggested that ART developers review the assumptions in relation to exposure variability within the tool, toward improving the tool performance in estimating percentile exposure levels. In addition, for both tools, only some handling/activity descriptions and input parameters were considered. Thus, further validation studies are still necessary., (Published by Oxford University Press on behalf of The British Occupational Hygiene Society 2018.)

Tier 1 occupational exposure assessment tools recommended for use under the Registration, Evaluation, Authorization, and restriction of CHemicals (REACH) were evaluated using newly collected measurement data. Evaluated tools included the ECETOC TRAv2 and TRAv3, MEASEv1.02.01, and EMKG-EXPO-TOOL. Fifty-three exposure situations (ESs) based on tasks/chemicals were developed from National Institute for Occupational Safety and Health field surveys. During the field surveys, high quality contextual information required for evaluating the tools was also collected. For each ES, applicable tools were then used to generate exposure estimates using a consensus approach. Among 53 ESs, only those related to an exposure category of liquids with vapor pressure (VP) > 10 Pa had sufficient numbers of exposure measurements (42 ESs with n = 251 for TRAv2 and TRAv3 and 40 ESs with n = 243 for EMKG-EXPO-TOOL) to be considered in detail. The results for other exposure categories (aqueous solutions, liquids with VP ≤ 10 Pa, metal processing, powders, and solid objects) had insufficient measurement to allow detailed analyses (results listed in the Supplementary File). Overall, EMKG-EXPO-TOOL generated more conservative results than TRAv2 and TRAv3 for liquids with high VP. This finding is at least partly due to the fact that the EMKG-EXPO-TOOL only considers pure substances and not mixtures of chemical agents. For 34 out of 40 ESs available for chemicals with VP > 10 Pa, the liquid was a mixture rather than a pure substance. TRAv3 was less conservative than TRAv2, probably due to additional refinement of some input parameters. The percentages of exposure measurement results exceeding the corresponding tool estimates for liquids with VP > 10 Pa by process category and by input parameters were always higher for TRAv3 compared to those for TRAv2. Although the conclusions of this study are limited to liquids with VP > 10 Pa and few process categories, this study utilized the most transparent contextual information compared to previous studies, reducing uncertainty from assumptions for unknown input parameters. A further validation is recommended by collecting sufficient exposure data covering other exposure categories and all process categories under REACH., (Published by Oxford University Press on behalf of The British Occupational Hygiene Society 2018.)