Meta-analysis of the quantitative effectiveness of risk management measures (RMM) in the workplace.

BACKGROUND AND OBJECTIVES: This paper describes an evaluation and analysis of an updated version of ECEL v3.0-an integrated risk management measure (RMM) library developed as part of a CEFIC LRI initiative. The occupational module contains extensive data on the quantitative effectiveness of RMMs to control inhalation and dermal exposure in the workplace. The objective was to investigate the effectiveness and variability in effectiveness of RMM and to explore the difference between optimal and non-optimal RMM applications in the workplace. METHODS: A new database structure and interface were developed and the content of the database was updated with a systematic literature review and integration with other databases (totalling 3373 records from 548 studies). To analyse the data, Bayesian linear mixed models were constructed with the study as a random effect and various study characteristics and RMM categories as fixed effects individually in separate models. A multivariate mixed model was used on a stratified dataset to test (amongst others) the conditions of RMM use. RESULTS: Analyses of the data indicated effectiveness values for each RMM category (for example ~87% for technical emission controls compared with ~60% for technical dispersion controls). Substantial variability in effectiveness was observed within and between different types of RMM. Seven study characteristics (covariables) were included in the analyses, which indicated a pronounced difference in as-built (optimal/experimental) and as-used (workplace) conditions of RMM use (93.3% and 74.6%, respectively). CONCLUSIONS: This library provides a reliable evidence base to derive base estimates of RMM effectiveness-beneficial for both registrant and downstream users. It stresses the importance of optimal use of RMMs in the workplace (technical design/functioning, use, and maintenance). Various challenges are foreseen to further update ECEL to improve guidance, for deriving improved estimates and ensure user-friendliness of the library.

The Dermal Advanced REACH Tool (dART): A Bayesian Model for Dermal Exposure Assessment.

The dermal Advanced REACH Tool (dART) is a tier 2 exposure model for estimating dermal exposure to the hands (mg min-1) for non-volatile liquid and solid-in-liquid products. The dART builds upon the existing ART framework and describes three mass transport processes (deposition (Dhands), direct emission and direct contact (Ehands), and contact transfer (Thands)) that may each contribute to dermal exposure. The mechanistic model that underpins the dART and calibration of the mechanistic model, such that the dimensionless score that results from encoding contextual information about a task into the determinants of the dART can be converted into a prediction of exposure (mg min-1), have been described in previous work. This paper completes the methodological framework of the dART model through placing the mechanistic model within a wider statistical modelling framework. A mixed-effects model, within a Bayesian framework, is presented for modelling the rate of dermal exposure per minute of activity. The central estimate of exposure for a particular task is provided by a calibrated mechanistic model (and thus based upon contextual information about a task). The model also describes between- and within-worker sources of variability in dermal exposure, with prior distributions for variance components based upon the literature. Estimates of exposure based upon informative prior distributions may be updated using measurement data associated with the task. The dART model is demonstrated using three worked examples, where estimates are initially obtained based upon the prior distributions alone, and then refined through accommodating measurement data on the tasks.

Ethics and Privacy Considerations Before Deploying Sensor Technologies for Exposure Assessment in the Workplace: Results of a Structured Discussion Amongst Dutch Stakeholders.

Will sensor-based exposure assessment be the future in workplace settings? Static instruments with embedded sensors are already applied to monitor levels of dangerous substances-in the context of acute health effects-at critical locations. However, with wearable, lightweight, miniaturized (low-cost) sensors developing quickly, much more is possible with sensors in relation to exposure assessment. Sensors can be applied in the work environment, on machines, or on employees and may include sensors that measure chemical exposures, but also sensors or other technologies that collect contextual information to support the exposure measurements. Like every technology it also has downsides. Sensors collect data on individuals that, depending on the purpose, need to be shared with others (e.g. health, safety and environment manager). One can imagine that people are afraid of misuse. To explore possible ethical and privacy issues that may come along with the introduction of sensors in the workplace, we organized a workshop with stakeholders (n = 32) to discuss three possible sensor-based scenarios in a structured way around five themes: purpose, efficacy, intrusiveness, proportionality, and fairness. The main conclusion of the discussions was that stakeholders currently see benefits in using sensors for applied targeted studies (short periods, clear reasons). In order to find acceptance for the implementation of sensors, all individuals affected by the sensors or its data need to be involved in the decisions on the purpose and application of sensors. Possible negative side effects need to be discussed and addressed. Continuous sensor-based monitoring of workers currently appears to be a bridge too far for the participants of this workshop.

A Review of Workplace Risk Management Measures for Nanomaterials to Mitigate Inhalation and Dermal Exposure.

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.

Occupational dermal exposure to nanoparticles and nano-enabled products: Part 2, exploration of exposure processes and methods of assessment.

Over the past decade, the primary focus of nanotoxicology and nanoenvironmental health and safety efforts has been largely on inhalation exposure to engineered nanomaterials, at the production stage, and much less on considering risks along the life cycle of nano-enabled products. Dermal exposure to nanomaterials and its health impact has been studied to a much lesser extent, and mostly in the context of intentional exposure to nano-enabled products such as in nanomedicine, cosmetics and personal care products. How concerning is dermal exposure to such nanoparticles in the context of occupational exposures? When and how should we measure it? In the first of a series of two papers (Larese Filon et al., 2016), we focused our attention on identifying conditions or situations, i.e. a combination of nanoparticle physico-chemical properties, skin barrier integrity, and occupations with high prevalence of skin disease, which deserve further investigation. This second paper focuses on the broad question of dermal exposure assessment to nanoparticles and attempts to give an overview of the mechanisms of occupational dermal exposure to nanoparticles and nano-enabled products and explores feasibility and adequacy of various methods of quantifying dermal exposure to NOAA. We provide here a conceptual framework for screening, prioritization, and assessment of dermal exposure to NOAA in occupational settings, and integrate it into a proposed framework for risk assessment.

Quartz and respirable dust in the Dutch construction industry: a baseline exposure assessment as part of a multidimensional intervention approach.

Quartz exposure can cause several respiratory health effects. Although quartz exposure has been described in several observational workplace studies, well-designed intervention studies that investigate the effect of control strategies are lacking. This article describes a baseline exposure study that is part of a multidimensional intervention program aiming to reduce quartz exposure among construction workers. In this study, personal respirable dust and quartz exposure was assessed among 116 construction workers (bricklayers, carpenters, concrete drillers, demolishers, and tuck pointers). Possible determinants of exposure, like job, tasks, and work practices, use of control measures, and organizational and psychosocial factors, were explored using exposure models for respirable dust and quartz separately. Stratified analyses by job title were performed to evaluate the effect of control measures on exposure and to explore the association between control measures and psychosocial factors. Overall, 62% of all measurements exceeded the Dutch occupational exposure limit for quartz and 11% for respirable dust. Concrete drillers and tuck pointers had the highest exposures for quartz and respirable dust (0.20 and 3.43mg m(-3), respectively). Significant predictors of elevated quartz exposure were abrasive tasks and type of material worked on. Surprisingly, in a univariate model, an increased knowledge level was associated with an increase in exposure. Although control measures were used infrequently, if used they resulted in approximately 40% reduction in quartz exposure among concrete drillers and tuck pointers. Only among concrete drillers, the use of control measures was associated with a higher score for social influence (factor 1.6); knowledge showed an inverse association with use of control measures for concrete drillers, demolishers, and tuck pointers. In conclusion, the detailed information on determinants of exposure, use of control measures, and constraints to use these control measures can be used for the determination and systematic prioritization of intervention measures used to design and implement our intervention strategy. This study underlines the need for multidisciplinary workplace exposure control strategies although larger study populations are necessary to determine a possible causal association between organizational and psychosocial factors and psychosocial factors and control measures.

Classification of occupational activities for assessment of inhalation exposure.

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.

Conceptual model for assessment of inhalation exposure: defining modifying factors.

The present paper proposes a source-receptor model to schematically describe inhalation exposure to help understand the complex processes leading to inhalation of hazardous substances. The model considers a stepwise transfer of a contaminant from the source to the receptor. The conceptual model is constructed using three components, i.e. (i) the source, (ii) various transmission compartments and (iii) the receptor, and describes the contaminant's emission and its pattern of transport. Based on this conceptual model, a list of nine mutually independent principal modifying factors (MFs) is proposed: activity emission potential, substance emission potential, localized control, separation, segregation, dilution, worker behavior, surface contamination and respiratory protection. These MFs describe the exposure process at a high level of abstraction so that the model can be generically applicable. A list of exposure determinants underlying each of these principal MFs is proposed to describe the exposure process at a more detailed level. The presented conceptual model is developed in conjunction with an activity taxonomy as described in a separate paper. The proposed conceptual model and MFs should be seen as 'building blocks' for development of higher tier exposure models.

Development and evaluation of an exposure control efficacy library (ECEL).

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.

Tools for regulatory assessment of occupational exposure: development and challenges.

REACH (Registration, Evaluation and Authorization of CHemicals) requires improved exposure models that can be incorporated into screening tools and refined assessment tools. These are referred to as tier 1 and 2 models, respectively. There are a number of candidate in tier 1 models that could be used with REACH. Tier 2 models, producing robust and realistic exposure assessments, are currently not available. A research programme is proposed in this paper that will result in a new, advanced exposure assessment tool for REACH. In addition, issues related to variability and uncertainty are discussed briefly, and some examples of tier 1 screening tools are presented. The proposed framework for the tier 2 tool is based on a Bayesian approach, and makes full use of mechanistically modelled estimates and any relevant measurements of exposure. The new approach will preclude the necessity to conduct of case-by-case exposure measurements for each chemical and scenario, since the system will allow for the use of analogous exposure data from relatively comparable scenarios. The development of the new approach requires substantial effort in the area of mechanistic modelling, database development and Bayesian statistical techniques. In this paper, the data gaps and areas for future research are identified to help realise and further improve this type of approach within REACH. A structured data collection and storage system is a central element of the research programme and the availability of this type of tool may also facilitate the sharing of exposure data down and up the supply chain. In addition, new data that are stored according to the proposed structure could enable the validation of any exposure model and thus this programme enhances the exposure assessment field as a whole.