Comparing the Advanced REACH Tool's (ART) estimates with Switzerland's occupational exposure data

The Advanced REACH Tool (ART) is the most sophisticated tool used for evaluating exposure levels under the European Union's Registration, Evaluation, Authorisation and restriction of CHemicals (REACH) regulations. ART provides estimates at different percentiles of exposure and within different confidence intervals (CIs). However, its performance has only been tested on a limited number of exposure data. The present study compares ART's estimates with exposure measurements collected over many years in Switzerland. Measurements from 584 cases of exposure to vapours, mists, powders, and abrasive dusts (wood/stone and metal) were extracted from a Swiss database. The corresponding exposures at the 50th and 90th percentiles were calculated in ART. To characterize the model's performance, the 90% CI of the estimates was considered. ART's performance at the 50th percentile was only found to be insufficiently conservative with regard to exposure to wood/stone dusts, whereas the 90th percentile showed sufficient conservatism for all the types of exposure processed. However, a trend was observed with the residuals, where ART overestimated lower exposures and underestimated higher ones. The median was more precise, however, and the majority (≥60%) of real-world measurements were within a factor of 10 from ART's estimates. We provide recommendations based on the results and suggest further, more comprehensive, investigations

Stoffenmanager exposure model: Development of a quantitative algorithm

In The Netherlands, the web-based tool called 'Stoffenmanager' was initially developed to assist small- and medium-sized enterprises to prioritize and control risks of handling chemical products in their workplaces. The aim of the present study was to explore the accuracy of the Stoffenmanager exposure algorithm. This was done by comparing its semi-quantitative exposure rankings for specific substances with exposure measurements collected from several occupational settings to derive a quantitative exposure algorithm. Exposure data were collected using two strategies. First, we conducted seven surveys specifically for validation of the Stoffenmanager. Second, existing occupational exposure data sets were collected from various sources. This resulted in 378 and 320 measurements for solid and liquid scenarios, respectively. The Spearman correlation coefficients between Stoffenmanager scores and exposure measurements appeared to be good for handling solids (rs = 0.80, N = 378, P 10 Pa (rs = 0.56, N = 104, P < 0.0001) and non-volatile substances with a vapour pressure ≤10 Pa (rs = 0.53, N = 216, P < 0.0001). The mixed-effect regression models with natural log-transformed Stoffenmanager scores as independent parameter explained a substantial part of the total exposure variability (52% for solid scenarios and 76% for liquid scenarios). Notwithstanding the good correlation, the data show substantial variability in exposure measurements given a certain Stoffenmanager score. The overall performance increases our confidence in the use of the Stoffenmanager as a generic tool for risk assessment. The mixed-effect regression models presented in this paper may be used for assessment of so-called reasonable worst case exposures. This evaluation is considered as an ongoing process and when more good quality data become available, the analyses described in this paper will be expanded. Based on these analyses, the algorithm will be refined in the near future. © The Author 2008. Published by Oxford University Press on behalf of the British Occupational Hygiene Society

Advanced REACH Tool:Development and application of the substance emission potential modifying factor

The Advanced REACH Tool (ART) is an exposure assessment tool that combines mechanistically modelled inhalation exposure estimates with available exposure data using a Bayesian approach. The mechanistic model is based on nine independent principal modifying factors (MF). One of these MF is the substance emission potential, which addresses the intrinsic substance properties as determinants of the emission from a source. This paper describes the current knowledge and evidence on intrinsic characteristics of solids and liquids that determine the potential for their release into workplace air. The principal factor determining the release of aerosols from handling or processing powdered, granular, or pelletized materials is the dustiness of the material, as well as the weight fraction of the substance of interest in the powder and the moisture content. The partial vapour pressure is the main intrinsic factor determining the substance emission potential for emission of vapours. For generation of mist, the substance emission potential is determined by the viscosity of the liquid as well as the weight fraction of the substance of interest in the liquid. Within ART release of vapours is considered for substances with a partial vapour pressure at the process temperature of 10 Pa or more, while mist formation is considered for substances with a vapour pressure =10 Pa. Relative multipliers are assigned for most of the intrinsic factors, with the exception of the weight fraction and the vapour pressure, which is applied as a continuous variable in the estimation of the substance emission potential. Currently, estimation of substance emission potential is not available for fumes, fibres, and gases. The substance emission potential takes account of the latest thinking on emissions of dusts, mists, and vapours and in our view provides a good balance between theory and pragmatism. Expanding the knowledge base on substance emission potential will improve the predictive power of occupational exposure models and thereby the accuracy and precision of the exposure estimates. © The Author 2011

Validation of the inhalable dust algorithm of the Advanced REACH Tool using a dataset from the pharmaceutical industry

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 = 192) were collated from a multinational pharmaceutical company with exposure levels ranging from 5 × 10-5 to 12 mg m-3. 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 -32%). 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 Royal Society of Chemistry

The advanced REACH tool (ART):Incorporation of an exposure measurement database

This article describes the structure, functionalities, and content of the Advanced REACH Tool (ART) exposure database (version 1.5). The incorporation of the exposure database into ART allows users who do not have their own measurement data for their exposure scenario, to update the exposure estimates produced by the mechanistic model using analogous measurement series selected from the ART exposure measurement database. Depending on user input for substance category and activity (sub)classes, the system selects exposure measurement series from the exposure database. The comprehensive scenario descriptions and summary statistics assist the user in deciding if the measurement series are indeed fully analogous. After selecting one or more analogous data sets, the data are used by the Bayesian module of the ART system to update the mechanistically modeled exposure estimates. The 1944 exposure measurements currently stored in the ART exposure measurement database cover 9 exposure situations for handling solid objects (n = 65), 42 situations for handling powders, granules, or pelletized material (n = 488), 5 situations for handling low-volatility liquids (n = 88), 35 situations for handling volatile liquids (n = 870), and 26 situations for handling liquids in which powders are dissolved or dispersed (resulting in exposure to mist) (n = 433). These 117 measurement series form a good basis for supporting user exposure estimates. However, by increasing the diversity of exposure situations and the number of measurement series in the database, the usefulness of the ART system will be further improved. Suggestions to stimulate the process of sharing exposure measurement data both to increase the available data in the ART and for other purposes are made

Advanced REACH Tool (ART):Calibration of the mechanistic model

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. © 2011 The Royal Society of Chemistry

Advanced reach tool (ART):Development of the mechanistic model

This paper describes the development of the mechanistic model within a collaborative project, referred to as the Advanced REACH Tool (ART) project, to develop a tool to model inhalation exposure for workers sharing similar operational conditions across different industries and locations in Europe. The ART mechanistic model is based on a conceptual framework that adopts a source receptor approach, which describes the transport of a contaminant from the source to the receptor and defines seven independent principal modifying factors: substance emission potential, activity emission potential, localized controls, segregation, personal enclosure, surface contamination, and dispersion. ART currently differentiates between three different exposure types: vapours, mists, and dust (fumes, fibres, and gases are presently excluded). Various sources were used to assign numerical values to the multipliers to each modifying factor. The evidence used to underpin this assessment procedure was based on chemical and physical laws. In addition, empirical data obtained from literature were used. Where this was not possible, expert elicitation was applied for the assessment procedure. Multipliers for all modifying factors were peer reviewed by leading experts from industry, research institutes, and public authorities across the globe. In addition, several workshops with experts were organized to discuss the proposed exposure multipliers. The mechanistic model is a central part of the ART tool and with advancing knowledge on exposure, determinants will require updates and refinements on a continuous basis, such as the effect of worker behaviour on personal exposure, 'best practice' values that describe the maximum achievable effectiveness of control measures, the intrinsic emission potential of various solid objects (e.g. metal, glass, plastics, etc.), and extending the applicability domain to certain types of exposures (e.g. gas, fume, and fibre exposure). © The Author 2011

Advanced REACH tool:A Bayesian model for occupational exposure assessment

This paper describes a Bayesian model for the assessment of inhalation exposures in an occupational setting; the methodology underpins a freely available web-based application for exposure assessment, the Advanced REACH Tool (ART). The ART is a higher tier exposure tool that combines disparate sources of information within a Bayesian statistical framework. The information is obtained from expert knowledge expressed in a calibrated mechanistic model of exposure assessment, data on inter- and intra-individual variability in exposures from the literature, and context-specific exposure measurements. The ART provides central estimates and credible intervals for different percentiles of the exposure distribution, for full-shift and long-term average exposures. The ART can produce exposure estimates in the absence of measurements, but the precision of the estimates improves as more data become available. The methodology presented in this paper is able to utilize partially analogous data, a novel approach designed to make efficient use of a sparsely populated measurement database although some additional research is still required before practical implementation. The methodology is demonstrated using two worked examples: an exposure to copper pyrithione in the spraying of antifouling paints and an exposure to ethyl acetate in shoe repair

Advanced REACH Tool (ART):overview of version 1.0 and research needs

This paper provides an outline of the Advanced REACH Tool (ART) version 1.0 and a discussion of how it could be further developed. ART is a higher tier exposure assessment tool that combines mechanistically modelled inhalation exposure predictions with available exposure data using a Bayesian approach. ART assesses exposure for scenarios across different plants and sites. Estimates are provided for different percentiles of the exposure distribution and confidence intervals around the estimate. It also produces exposure estimates in the absence of data, but uncertainty of the estimates will decrease when results of exposure measurements are included. The tool has been calibrated using a broad range of exposure data and provides estimates for exposure to vapours, mists, and dusts. ART has a robust and stable conceptual basis but will be refined in the future and should therefore be considered an evolving system. High-priority areas for future research are identified in this paper and include the integration of partially analogous measurement series, inclusion of company and site-specific assessments, user decision strategies linked to ART predictions, evaluation of validity and reliability of ART, exploring the possibilities for incorporating the dermal route and integration of ART predictions with tools for modelling internal dose. ART is initially developed in the scope of REACH but is equally useful for exposure assessment in other areas.</p