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Measured data are generally preferred to modelled estimates of exposure. Grouping and read-across is already widely used and accepted approach in toxicology, but an appropriate approach and guidance on how to use existing exposure measurement data on one substance and work situation for another substance and/or work situation is currently not available. This study presents a framework for an extensive read-across of existing worker inhalable exposure measurement data. This framework enables the calculation of read-across factors based on another substance and/or work situation by first evaluating the quality of the existing measurement data and then mapping its similarity or difference with another substance and/or work situation. The system of read-across factors was largely based on the determinants in ECETOC TRA and ART exposure models. The applicability of the framework and its proof of principle were demonstrated by using five case studies. In these case studies, either the 75th percentiles of measured exposure data was observed to lie within the estimated 90% confidence intervals from the read-across approach or at least with the increase in the geometric mean of measured exposure, geometric mean of estimated exposure also increased. Testing and re-evaluation of the present framework by experts in exposure assessment and statistics is recommended to develop it further into a tool that can be widely used in exposure assessment and regulatory practices., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Model tools for estimating hazardous substance exposure are an accepted part of regulatory risk assessments in Europe, and models underpin control banding tools used to help manage chemicals in workplaces. Of necessity the models are simplified abstractions of real-life working situations that aim to capture the essence of the scenario to give estimates of actual exposures with an appropriate margin of safety. The basis for existing inhalation exposure assessment tools has recently been discussed by some scientists who have argued for the use of more complex models. In our opinion, the currently accepted tools are documented to be the most robust way for workplace health and safety practitioners and others to estimate inhalation exposure. However, we recognise that it is important to continue the scientific development of exposure modelling to further elaborate and improve the existing methodologies.

This review describes an evaluation of the effectiveness of Risk Management Measures (RMM) for nanomaterials in the workplace. Our aim was to review the effectiveness of workplace RMM for nanomaterials and to determine whether established effectiveness values of conventional chemical substances applied for modelling purposes should be adopted or revised based on available evidence. A literature review was conducted to collate nano-specific data on workplace RMM. Besides the quantitative efficacy values, the library was populated with important covariables such as the study design, measurement type, size of particles or agglomerates/aggregates, and metrics applied. In total 770 records were retrieved from 41 studies for three general types of RMM (engineering controls, respiratory equipment and skin protective equipment: gloves and clothing). Records were found for various sub-categories of the different types of RMM although the number of records for each was generally limited. Significant variation in efficacy values was observed within RMM categories while also considering the respective covariables. Based on a comparative evaluation with efficacy values applied for conventional substances, adapted efficacy values are proposed for various RMM sub-categories (e.g. containment, fume cupboards, FFP2 respirators). It is concluded that RMM efficacy data for nanomaterials are limited and often inconclusive to propose effectiveness values. This review also shed some light on the current knowledge gaps for nanomaterials related to RMM effectiveness (e.g. ventilated walk-in enclosures and clean rooms) and the challenges foreseen to derive reliable RMM efficacy values from aggregated data in the future.

Nanoscale TiO 2 (nTiO 2 ) is manufactured in high volumes and is of potential concern in occupational health. Here, we measured workers exposure levels while ceramic honeycombs were dip coated with liquid photoactive nanoparticle suspension and dried with an air blade. The measured nTiO 2 concentration levels were used to assess process specific emission rates using a convolution theorem and to calculate inhalation dose rates of deposited nTiO 2 particles. Dip coating did not result in detectable release of particles but air blade drying released fine-sized TiO 2 and nTiO 2 particles. nTiO 2 was found in pure nTiO 2 agglomerates and as individual particles deposited onto background particles. Total particle emission rates were 420×10 9 min -1 , 1.33×10 9 μm 2 min -1 , and 3.5mgmin -1 respirable mass. During a continued repeated process, the average exposure level was 2.5×10 4 cm -3 , 30.3μm 2 cm -3 , <116μgm -3 for particulate matter. The TiO 2 average exposure level was 4.2μgm -3 , which is well below the maximum recommended exposure limit of 300μgm -3 for nTiO 2 proposed by the US National Institute for Occupational Safety and Health. During an 8-hour exposure, the observed concentrations would result in a lung deposited surface area of 4.3×10 -3 cm 2 g -1 of lung tissue and 13μg of TiO 2 to the trachea-bronchi, and alveolar regions. The dose levels were well below the one hundredth of the no observed effect level (NOEL 1/100 ) of 0.11cm 2 g -1 for granular biodurable particles and a daily no significant risk dose level of 44μgday -1 . These emission rates can be used in a mass flow model to predict the impact of process emissions on personal and environmental exposure levels., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Nano-specific inhalation exposure models could potentially be effective tools to assess and control worker exposure to nano-objects, and their aggregates and agglomerates (NOAA). However, due to the lack of reliable and consistent collected NOAA exposure data, the scientific basis for validation of the existing NOAA exposure models is missing or limited. The main objective of this study was to gain more insight into the effect of various determinants underlying the potential on the concentration of airborne NOAA close to the source with the purpose of providing a scientific basis for existing and future exposure inhalation models., Method: Four experimental studies were conducted to investigate the effect of 11 determinants of emission on the concentration airborne NOAA close to the source during dumping of ~100% nanopowders. Determinants under study were: nanomaterial, particle size, dump mass, height, rate, ventilation rate, mixing speed, containment, particle surface coating, moisture content of the powder, and receiving surface. The experiments were conducted in an experimental room (19.5 m3) with well-controlled environmental and ventilation conditions. Particle number concentration and size distribution were measured using real-time measurement devices., Results: Dumping of nanopowders resulted in a higher number concentration and larger particles than dumping their reference microsized powder (P < 0.05). Statistically significant more and larger particles were also found during dumping of SiO2 nanopowder compared to TiO2/Al2O3 nanopowders. Particle surface coating did not affect the number concentration but on average larger particles were found during dumping of coated nanopowders. An increase of the powder's moisture content resulted in less and smaller particles in the air. Furthermore, the results indicate that particle number concentration increases with increasing dump height, rate, and mass and decreases when ventilation is turned on., Discussion: These results give an indication of the direction and magnitude of the effect of the studied determinants on concentrations close to the source and provide a scientific basis for (further) development of existing and future NOAA inhalation exposure models., (© The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Background: Control banding can be used as a first-tier assessment to control worker exposure to nano-objects and their aggregates and agglomerates (NOAA). In a second tier, more advanced modelling approaches are needed to produce quantitative exposure estimates. As currently no general quantitative nano-specific exposure models are available, this study evaluated the validity and applicability of using a generic exposure assessment model (the Advanced REACH Tool-ART) for occupational exposure to NOAA., Method: The predictive capability of ART for occupational exposure to NOAA was tested by calculating the relative bias and correlations (Pearson) between the model estimates and measured concentrations using a dataset of 102 NOAA exposure measurements collected during experimental and workplace exposure studies., Results: Moderate to (very) strong correlations between the ART estimates and measured concentrations were found. Estimates correlated better to measured concentration levels of dust (r = 0.76, P < 0.01) than liquid aerosols (r = 0.51, P = 0.19). However, ART overestimated the measured NOAA concentrations for both the experimental and field measurements (factor 2-127). Overestimation was highest at low concentrations and decreased with increasing concentration. Correlations seemed to be better when looking at the nanomaterials individually compared to combined scenarios, indicating that nanomaterial-specific characteristics are not well captured within the mechanistic model of the ART., Discussion: Although ART in its current state is not capable to estimate occupational exposure to NOAA, the strong correlations for the individual nanomaterials indicate that the ART (and potentially other generic exposure models) have the potential to be extended or adapted for exposure to NOAA. In the future, studies investigating the potential to estimate exposure to NOAA should incorporate more explicitly nanomaterial-specific characteristics in their models., (© The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Tiered or stepwise approaches to assess occupational exposure to nano-objects, and their agglomerates and aggregates have been proposed, which require decision rules (DRs) to move to a next tier, or terminate the assessment. In a desk study the performance of a number of DRs based on the evaluation of results from direct reading instruments was investigated by both statistical simulations and the application of the DRs to real workplace data sets. A statistical model that accounts for autocorrelation patterns in time-series, i.e. autoregressive integrated moving average (ARIMA), was used as 'gold' standard. The simulations showed that none of the proposed DRs covered the entire range of simulated scenarios with respect to the ARIMA model parameters, however, a combined DR showed a slightly better agreement. Application of the DRs to real workplace datasets (n = 117) revealed sensitivity up to 0.72, whereas the lowest observed specificity was 0.95. The selection of the most appropriate DR is very much dependent on the consequences of the decision, i.e. ruling in or ruling out of scenarios for further evaluation. Since a basic assessment may also comprise of other type of measurements and information, an evaluation logic was proposed which embeds the DRs, but furthermore supports decision making in view of a tiered-approach exposure assessment., (© The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Increasing production and applications of manufactured nano objects (MNOs) have become a source for human exposure and therefore raise concerns and questions about the possible health effects. In this study, the potential release of nano objects, their agglomerates, and aggregates (NOAA) as a result of sanding of hardwood treated with MNOs-containing coating was examined. Two types of MNO-containing coating were compared with untreated hardwood that allowed the evaluation of the influence of the chemical composition on the release of particles. Furthermore, the rotation speed of the sander and the grit size of the sanding paper were varied in order to assess their influence on the release of particles.Measurements were conducted in a gas-tight chamber with a volume of 19.5 m(3) in which ventilation was minimized during experiments. Particle size distributions were assessed by scanning mobility particle sizer , aerodynamic particle sizer, and electrical low pressure impactor. Furthermore, aerosol number concentrations (Nanotracer), active surface area (LQ1), and fractionated mass (Cascade Impactor) were measured before, during, and after sanding. Scanning electron microscope/energy dispersive X-ray (SEM/EDX) analysis was performed to adequately characterize the morphology, size, and chemical composition of released particles.SEM/EDX analysis indicated that sanding surfaces treated with MNO-containing coating did not release the designated MNO as free primary particles. In both coatings, clusters of MNO were perceived embedded in and attached to micro-sized wood and/or coating particles created by sanding the coated surface. Real-time measurements indicated a lower release of micro-sized particles from sanding of surfaces treated with Coating I than from sanding untreated surfaces or surfaces treated with Coating II. A substantial increase in nanosized and a slight increase in micro-sized particles was perceived as the rotation speed of the sander increased. However, most nanosized particles were most likely emitted by the sanding machine. No effect of the grit size on the release of particles was detected., (© The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

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., (© Crown copyright 2014.)

The release of pesticides from conventional spray products has been investigated in depth, and suitable analytical techniques detecting the mass of the released substances are available. In contrast, nanoparticle-containing sprays are less studied, although they are perceived as critical for consumers because inhalation exposure can occur to potentially toxic nanoparticles. A few recent studies presented analytical concepts for exposure experiments and generated data for exposure assessment. This study attempts to review and compare the current approaches to characterize nanosprays and to identify challenges for future research. Furthermore, experimental setups used for exposure assessment from conventional sprays are reviewed and compared to setups used for nanoparticle-containing sprays. National and international norms dealing with nanoparticle characterization, spray characterization and exposure are inspected with regard to their usefulness for standardizing exposure assessment. Different approaches in the field of exposure modeling are reviewed and compared. The conclusion is that due to largely varying experimental setups to date exposure values for nanosprays are difficult to compare. All studies are only conducted with a limited set of sprays, and no systematic evaluation of the study conditions is available. A suitable set of experimental setups as well as minimum reporting requirements should be agreed upon to enable the systematic evaluation of consumer sprays in the future. Indispensable features of such experimental setups are developed in this review.

This paper reports a study of the dispersion of manufactured nano-objects (MNOs) through the air, both in time and space, during the use of two commercially available nano-spray products and comparable products without MNOs. The main objective was to identify whether personal exposure can occur at a greater distance than the immediate proximity of the source (>1 m from the source), that is, in the "far field" (bystanders), or at a period after the emission occurred (re-entry). The spray experiments were conducted in an experimental room with well-controlled environmental and ventilation conditions (19.5 m(3)). The concentration of MNOs was investigated by measuring real-time size distribution, number, and active surface area concentration. For off-line analysis of the particles in the air, samples for scanning/transmission electron microscopy and elemental analysis were collected. The release of MNOs was measured at ∼30 and 290 cm from the source ("near field" and "far field", respectively). For all four spray products, the maximum number and surface area concentrations in the "near field" exceeded the maximum concentrations reached in the "far field". At 2 min after the emission occurred, the concentration in both the "near field" and "far field" reached a comparable steady-state level above background level. These steady-state concentrations remained elevated above background concentration throughout the entire measurement period (12 min). The results of the real-time measurement devices mainly reflect the liquid aerosols emitted by the spray process itself rather than only the MNO, which hampers the interpretation of the results. However, the combination of the off-line analysis and the results of the real-time devices indicates that after the use of nano-spray products, personal exposure to MNOs can occur not only in the near field, but also at a greater distance than the immediate proximity of the source and at a period after emission occurred.

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.

Stoffenmanager Nano (version 1.0) is a risk-banding tool developed for employers and employees to prioritize health risks occurring as a result of exposure to manufactured nano objects (MNOs) for a broad range of worker scenarios and to assist implementation of control measures to reduce exposure levels. In order to prioritize the health risks, the Stoffenmanager Nano combines the available hazard information of a substance with a qualitative estimate of potential for inhalation exposure. The development of the Stoffenmanager Nano started with a review of the available literature on control banding. Input parameters for the hazard assessment of MNOs were selected based on the availability of these parameters in, for instance, Safety Data Sheets or product information sheets. The conceptual exposure model described by Schneider et al. (2011) was used as the starting point for exposure banding. During the development of the Stoffenmanager Nano tool, the precautionary principle was applied to deal with the uncertainty regarding hazard and exposure assessment of MNOs. Subsequently, the model was converted into an online tool (http://nano.stoffenmanager.nl), tested, and reviewed by a number of companies. In this paper, we describe the Stoffenmanager Nano. This tool offers a practical approach for risk prioritization in exposure situations where quantitative risk assessment is currently not possible. Updates of this first version are anticipated as more data become available in the future.

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 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.

There is a large variety of activities in workplaces that can lead to emission of substances. Coding systems based on determinants of emission have so far not been developed. In this paper, a system of Activity Classes and Activity Subclasses is proposed for categorizing activities involving chemical use. Activity Classes share their so-called 'emission generation mechanisms' and physical state of the product handled and the underlying determinants of emission. A number of (industrial) stakeholders actively participated in testing and fine-tuning the system. With the help of these stakeholders, it was found to be relatively easy to allocate a large number of activities to the Activity Classes and Activity Subclasses. The system facilitates a more structured classification of activities in exposure databases, a structured analysis of the analogy of exposure activities, and a transparent quantification of the activity emission potential in (new) exposure assessment models. The first use of the system is in the Advanced REACH Tool.

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.

As workplace air measurements of manufactured nanoparticles are relatively expensive to conduct, models can be helpful for a first tier assessment of exposure. A conceptual model was developed to give a framework for such models. The basis for the model is an analysis of the fate and underlying mechanisms of nanoparticles emitted by a source during transport to a receptor. Four source domains are distinguished; that is, production, handling of bulk product, dispersion of ready-to-use nanoproducts, fracturing and abrasion of end products. These domains represent different generation mechanisms that determine particle emission characteristics; for example, emission rate, particle size distribution, and source location. During transport, homogeneous coagulation, scavenging, and surface deposition will determine the fate of the particles and cause changes in both particle size distributions and number concentrations. The degree of impact of these processes will be determined by a variety of factors including the concentration and size mode of the emitted nanoparticles and background aerosols, source to receptor distance, and ventilation characteristics. The second part of the paper focuses on to what extent the conceptual model could be fit into an existing mechanistic predictive model for ''conventional'' exposures. The model should be seen as a framework for characterization of exposure to (manufactured) nanoparticles and future exposure modeling.

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 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.

Objectives: This paper describes the development and evaluation of an evidence database on the effectiveness of risk management measures (RMMs) to control inhalation exposure. This database is referred to as Exposure Control Efficacy Library (ECEL)., Methods: A comprehensive review of scientific journals in the occupational hygiene field was undertaken. Efficacy values for RMMs in conjunction with contextual information on study design, sampling strategy and measurement type (among other parameters) were stored in an MS Access database. In total, 433 efficacy values for six RMM groups (i.e. enclosure, local exhaust ventilation, specialized ventilation, general ventilation, suppression techniques and separation of the worker) were collected from 90 peer-reviewed publications. These RMM categories were subdivided into more specific categories., Results: Estimated average efficacy values ranged from 87% for specialized ventilation to 43% for general ventilation. Substantial variation in efficacy values was observed within RMM categories based on differences in selected covariables within each study (i.e. study design, sampling strategy, measurement type and others). More contrast in efficacy values was observed when evaluating more detailed subcategories., Conclusions: It is envisaged that ECEL will contribute to exposure modelling, but should be supplemented with expert opinion, preferably in a formal expert elicitation procedure. The work presented here should be considered as a first attempt to collate and analyse RMM efficacy values and inclusion of additional (unpublished) exposure data is highly warranted.

Objectives: The aims of the study were to quantify levels of dermal and inhalation exposure to antineoplastic drugs in an industrial laundry service in the Netherlands and to test the removal efficiency of the washing procedure for removal of antineoplastic drugs., Methods: During four workdays dermal and inhalation exposure to eight frequently used antineoplastic drugs (cyclophosphamide, ifosfamide, methotrexate, 5-fluorouracil, etoposide, cytarabine, gemcitabine and chlorambucil) were measured for all job titles involved in handling unwashed laundry. To test the removal efficiency of the washing procedure, 10 x 10 cm sections were excised before and after the washing procedure. These sections were taken from 15 bed sheets that were collected in hospitals of patients who were treated with one of the selected antineoplastic drugs., Results: During none of the four measurement days, detectable levels of any of the eight antineoplastic drugs (cyclophosphamide, ifosfamide, methotrexate, 5-fluorouracil, etoposide, cytarabine, gemcitabine, or chlorambucil) were found on workers' skin of hands or in any of the air samples. Only four out of the 15 bed sheets from patients that were treated with antineoplastic drugs appeared to be contaminated with detectable levels of antineoplastic drugs before the washing procedure (range 13.0-3,060 ng/100 cm(2)). After the pre-washing and after the complete washing procedure, no detectable levels of any of the eight antineoplastic drugs were found anymore in the selected bed sheets., Conclusions: The implementation of guidelines for working with antineoplastic drugs seems to be successful in reducing exposure to antineoplastic drugs of workers in this laundry facility to an acceptable, non-detectable level and to remove antineoplastic drug contamination from bed linen.