Search

Exposure to manufactured nanomaterials (MNs) is a growing concern for occupational health and safety. Reliable methods for assessing and predicting MN exposure are essential to mitigate associated risks. This study presents the development of the Nano Exposure Quantifier (NEQ), a mechanistic model designed to assess airborne MN exposure in the workplace. By utilizing a dataset of 128 MN measurements from existing exposure studies, the model demonstrates its effectiveness in estimating MN exposure levels for particles smaller than 10 µm. The NEQ provides estimates in terms of particle number concentration accompanied by a 95% confidence interval (CI), enabling a comprehensive assessment of MN exposure. The NEQ includes 2 quantitative models: a simplified tier 1 model and a more comprehensive tier 2 model. Both tier 1 and tier 2 models exhibit robust performance, with correlation coefficients (r) of 0.57 and 0.62, respectively. The models exhibit a moderate level of error, as indicated by residuals' standard deviation of 4.10 for tier 1 and 3.90 for tier 2. The tier 1 model demonstrates a slightly higher overestimation bias (1.15) compared to the tier 2 model (0.54). Overall, the NEQ offers a practical and reliable approach for estimating MN exposure in occupational settings. Future validation studies will investigate the impact of initial calibration efforts, heteroscedasticity, and further refine the model's accuracy., (© The Author(s) 2025. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

This article describes the development of a Safe-by-Design (SbD) module and its integration into an easy-to-use tool, named the Nano Exposure Quantifier-Safe-by-Design (NEQ-SbD) tool. The NEQ-SbD tool guides its user to lower the exposure to nanomaterials at the worksite where nanomaterials are manipulated or handled during a wide range of activities. This allows the tool user with an informed decision to assess airborne exposure and to select, compare, and identify appropriate risk management measures (RMM). The SbD module was developed using various information sources that can support and guide the SbD process, including the (i) RMM effectiveness based on analyses of an Exposure Control Efficacy Library (ECEL), (ii) RMM performance using a Computational Fluid Dynamics (CFD) model, (iii) e-cards based on a qualitative analysis of RMM information sources, and (iv) guidance for SbD strategy using an exposure directionality assessment. This information has been integrated in the user interface of the SbD module and NEQ-SbD tool to facilitate the SbD decision-making process. The SbD concept applied in the integrated NEQ-SbD tool introduces a comparison between a baseline exposure assessment and an (improved) SbD exposure assessment. The integrated NEQ-SbD tool consists of 4 modules including (i) a baseline exposure assessment, (ii) baseline results, (iii) SbD assessment, and (iv) SbD comparative results. The main purpose of the SbD module lies in guiding the user to the most sensitive (exposure) parameters and allowing a side-by-side comparison of potentially suitable RMMs. The integrated NEQ-SbD tool also offers a tiered approach and seamlessly shifts from a tier-1 to tier-2 uncertainty of an exposure assessment. The SbD module is illustrated using a worked example for the transfer of nano powders, showing the possibility of identifying SbD solutions for both safe-by-process and safe-by-material design purposes. The NEQ-SbD tool is a valuable tool for the SbD of nanomaterials and as a decision-making tool to support SbD risk management strategies that lead to minimizing health risks associated with occupational exposures., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Occupational Hygiene Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

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 Author(s) 2024. Published by Oxford University Press on behalf of the British Occupational Hygiene Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Several exposure assessment models use dustiness as an input parameter for scaling or estimating exposure during powder handling. Use of different dustiness methods will result in considerable differences in the dustiness values as they are based on different emission generation principles. EN17199:2019 offers 4 different dustiness test methods considering different dust release scenarios (e.g. powder pouring, mixing and gentle agitation, and vibration). Conceptually, the dustiness value by a given method can be multiplied with a scenario-specific modifier, called a handling energy factor (Hi), that allows conversion of a dustiness value to a release constant. Therefore, a Hi, scaling the effective mechanical energy in the process to the energy supplied in the specific dustiness test, needs to be applied. To improve the accuracy in predictive exposure modelling, we derived experimental Hi to be used in exposure algorithms considering both the mass- and number-based dust release fraction determined by the EN17199-3 continuous drop (CD) and the EN17199-4 small rotating drum (SRD) test methods. Three materials were used to evaluate the relationship between dustiness and dust levels during pouring powder from different heights in a controlled environment. The results showed increasing scatter and difference between the Hi derived for the 2 test methods with increasing pouring height. Nearly all the Hi values obtained for both SRD and CD were <1 indicating that the dustiness tests involved more energy input than the simulated pouring activity and consequently de-agglomeration and dust generation were higher. This effect was most pronounced in CD method showing that SRD mechanistically resembles more closely the powder pouring., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Objectives: Within the chemical legislation, REACH was implemented in order to improve safe working conditions with hazardous substances. Literature and real-life experiences by those concerned have shown that there are still gaps with a need for improved risk communication. This study elaborated on how information provided by REACH is understood and acted on by down- and upstream users, and how it can be further improved., Methods: An extensive literature study including 21 studies and 13 tools was carried out. The outcomes were discussed and further supplemented by means of 18 interviews concerning 37 internal safety and REACH documents to build six different use cases representing different Dutch downstream companies. For the upstream perspective also 2 sector organizations and 2 registrants were interviewed. Three online workshops were organized in order to share insights and gather input on international recognition, potential suggestions and further recommendations with 30 participants from nine different EU countries., Results: Although the methods to collect the data differed between the different stages of the study, the general results from all three stages elucidated similar themes in the data and each of the stages used the results from the previous stage as a starting point. Recurring themes concerned the (i) complexity of documents, (ii) deficiencies as experienced by SMEs in REACH, (iii) feedback and responsibilities in the supply chain, and (iv) the cooperation between REACH and OSH., Discussion: The study at hand revealed that even though there are currently several activities to improve communication on safe-use of chemicals, communication on safe-use in the scope of REACH should be improved. This includes e.g. the future involvement of actual end-users in activities and development related to communication of safe-use information in the scope of REACH including feedback, less complicated and complex documents and clear communication concerning legislations and updates of documents. Furthermore, the issues recognized in the Netherlands are mostly also recognized by international workshop participants, thereby indicating international benefits in various areas by means of improved communication., Conclusions: The study confirmed that many of our generic conclusions were already part of the shared knowledge in the REACH community, but that it is very valuable that this knowledge has been explicated, validated and reported in a structured way in the present project. Besides uncovering some crucial aspects that offer potential improvements regarding risk communication, this study offers possible solutions and next steps to be taken., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Introduction: Oil and gas workers have been shown to be at increased risk of chronic diseases including cancer, asthma, chronic obstructive pulmonary disease, and hearing loss, among others. Technological advances may be used to assess the external (e.g. personal sensors, smartphone apps and online platforms, exposure models) and internal exposome (e.g. physiologically based kinetic modeling (PBK), biomonitoring, omics), offering numerous possibilities for chronic disease prevention strategies and risk management measures. The objective of this study was to review the literature on these technologies, by focusing on: (i) evaluating their applicability for exposome research in the oil and gas industry, and (ii) identifying key challenges that may hamper the successful application of such technologies in the oil and gas industry., Method: A scoping review was conducted by identifying peer-reviewed literature with searches in MEDLINE/PubMed and SciVerse Scopus. Two assessors trained on the search strategy screened retrieved articles on title and abstract. The inclusion criteria used for this review were: application of the aforementioned technologies at a workplace in the oil and gas industry or, application of these technologies for an exposure relevant to the oil and gas industry but in another occupational sector, English language and publication period 2005-end of 2019., Results: In total, 72 articles were included in this scoping review with most articles focused on omics and bioinformatics (N = 22), followed by biomonitoring and biomarkers (N = 20), external exposure modeling (N = 11), PBK modeling (N = 10), and personal sensors (N = 9). Several studies were identified in the oil and gas industry on the application of PBK models and biomarkers, mainly focusing on workers exposed to benzene. The application of personal sensors, new types of exposure models, and omics technology are still in their infancy with respect to the oil and gas industry. Nevertheless, applications of these technologies in other occupational sectors showed the potential for application in this sector., Discussion and Conclusion: New exposome technologies offer great promise for personal monitoring of workers in the oil and gas industry, but more applied research is needed in collaboration with the industry. Current challenges hindering a successful application of such technologies include (i) the technological readiness of sensors, (ii) the availability of data, (iii) the absence of standardized and validated methods, and (iv) the need for new study designs to study the development of disease during working life., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Driven by the concept of the 'four generations of nanomaterials', the current state of the knowledge on risk assessment of future generation is explored for active nanomaterials. Through case studies, we identify challenges and evaluate the preparedness of characterization methods, available risk assessment modeling tools, and analytical instrumentation for such future generation active nanomaterials with dynamic hybrid structures of biotic-abiotic and organic-inorganic combinations. Currently available risk assessment tools and analytical instrumentation were found to be lacking the risk preparedness and characterization readiness for active nanomaterials, respectively. Potential future developments in risk assessment modeling tools and analytical techniques can be based upon this work which shall ensure long-term safety of the next generation of nanomaterials., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

This commentary explores the use of high-resolution data from new, miniature sensors to enrich models that predict exposures to chemical substances in the workplace. To optimally apply these sensors, one can expect an increased need for new models that will facilitate the interpretation and extrapolation of the acquired time-resolved data. We identified three key modelling approaches in the context of sensor data, namely (i) enrichment of existing time-integrated exposure models, (ii) (new) high-resolution (in time and space) empirical models, and (iii) new 'occupational dispersion' models. Each approach was evaluated in terms of their application in research, practice, and for policy purposes. It is expected that substance-specific sensor data will have the potential to transform workplace modelling by re-calibrating, refining, and validating existing (time-integrated) models. An increased shift towards 'sensor-driven' models is expected. It will allow for high-resolution modelling in time and space to identify peak exposures and will be beneficial for more individualized exposure assessment and real-time risk management. New 'occupational dispersion models' such as interpolation, computational fluid dynamic models, and assimilation techniques, together with sensor data, will be specifically useful. These techniques can be applied to develop site-specific concentration maps which calculate personal exposures and mitigate worker exposure through early warning systems, source finding and improved control design and control strategies. Critical development and investment needs for sensor data linked to (new) model development were identified such as (i) the generation of more sensor data with reliable sensor technologies (achieved by improved specificity, sensitivity, and accuracy of sensors), (ii) investing in statistical and new model developments, (iii) ensuring that we comply with privacy and security issues of concern, and (iv) acceptance by relevant target groups (such as employers and employees) and stimulation of these new technologies by policymakers and technology developers., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

For many work situations only insufficient exposure data are available to perform proper risk assessment. Because measuring worker exposure can be time consuming and resource intense, the availability of reliable exposure models is important when performing risk assessments. However, the development and improvement of exposure models are hampered by scarcity of sound exposure data as well as by lack of information on relevant exposure factors and conditions of exposure. This paper describes a study where inhalation and dermal exposure data were collected under defined conditions. Exposure scenarios examined included tasks that have not been investigated in previous validation studies. The results of these measurements were compared with ECETOC TRA model version 3.1 predictions. In this study, five exposure scenarios were selected, namely 'use in a closed batch process' (PROC 4), 'mixing or blending in a partly open batch process' (PROC 5), 'rolling' (PROC 10), 'immersion' (PROC 13), and 'stirring' (PROC 19). These PROCs stem from the descriptors that Registration, Evaluation and Authorization of Chemicals has established to depict the identified uses of chemical substances. These exposure scenarios were selected mainly because little or no data are available for these situations, or ECETOC TRA is likely to underestimate exposure for these situations. Experiments were performed by volunteers for the selected exposure scenarios, in which tasks were performed aiming to represent real workplace situations. In total 70 experiments were performed, during which 70 dermal exposure measurements (5 volunteers × 2 repeats × 7 scenarios) and 32 inhalation exposure measurements (4 volunteers × 2 repeats × 4 scenarios) were collected. Two formulations were used, namely pure Tinopal SWN powder (solid product, a fluorescent tracer) and 0.5% Tinopal SWN dissolved in 1,2-dichloroethane (1,2-DCE). DCE is considered a moderate volatile liquid. For exposure scenarios using the liquid formulation, both inhalation and dermal measurements were performed, while for exposure scenarios using the pure powder only dermal exposure measurements were performed. In addition, photographs were taken under ultraviolet light to qualitatively assess exposure patterns on hands and body. Volunteers repeatedly performed a selection of tasks under standardized conditions in a test chamber for each exposure scenario. Results show that ECETOC TRA overestimated dermal hand exposure for all PROCs included in the study, and was considered to be conservative. Additionally, ECETOC TRA overestimated inhalation exposure for closed and partially closed processes, but underestimated inhalation exposure for rolling and handling of immersed objects. Qualitative assessment of the hands and body showed mainly the hands were exposed for tasks involving closed and partially closed processes and when handling of immersed objects. Exposure to other body segments were also observed for rolling and stirring. In conclusion, this study gave insights into dermal and inhalation exposure levels during selected task scenarios, and showed that ECETOC TRA is conservative when dermal exposure is estimated. Inhalation exposure estimates for PROCs 10 and 13 tasks with the moderate volatility liquid were underestimated in this study. It may be therefore necessary to re-evaluate base model predictions for these scenarios when medium fugacity liquids are involved., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

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.)

Dustiness is not an intrinsic physically defined property of a powder, but the tendency of particles to become airborne in response to mechanical and/or aerodynamic stimuli. The present study considers a set of 10 physical properties to which the powder dustiness can be attributed. Through a preliminary investigation of a standardized continuous drop test scenario, we present first set of results on the varying degrees or weights of influence of these properties on the aerosolization tendency of powder particles. The inter-particle distance is found to be the most dominant property controlling the particle aerosolization, followed by the ability of powder particles to get electrostatically charged. We observe the kinetics involved during powder aerosolization to be governed by two ratios: drag force/cohesive force and drag force/gravitational force. The converging tendencies in these initial results indicate that these physical properties can be used to model dustiness of falling powder, which can eventually be used in risk assessment tools for an efficient exposure estimation of the powders., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

This article describes the development of a mechanistic model for underpinning the dermal Advanced REACH Tool (dART), an extension of the existing ART model and its software platform. It was developed for hand exposure to low volatile liquids (vapour pressure ≤ 10 Pa at 20°C) including solids-in-liquid products. The model is based on an existing conceptual dermal source-receptor model that has been integrated into the ART framework. A structured taxonomy of workplace activities referred to as activity classes are adopted from ART.  Three key processes involved in mass transport associated with dermal exposure are applied, i.e. deposition, direct emission and contact, and transfer. For deposition, the model adopts all the relevant modifying factors (MFs) applied in ART. In terms of direct emission and contact (e.g. splashes) and transfer (e.g. hand-surface contacts), the model defines independent principal MFs, i.e. substance-related factors, activity-related factors, localized- and dispersion control and exposed surface area of the hands. To address event-based exposures as much as possible, the model includes crucial events during an activity (e.g. hand immersions) and translates objective information on tools and equipment (manual or automated) to probable events (e.g. splashes) and worker behaviours (e.g. surface contacts). Based on an extensive review of peer-reviewed literature and unpublished field studies, multipliers were assigned to each determinant and provide an approximated (dimensionless) numerical value. In the absence of (sufficient) evidence, multipliers were assigned to determinants based on assumptions made during discussions by experts in the consortium. A worked example is presented to illustrate the calculation of hand exposure for a specific scenario. The dART model is not yet implemented in the ART software platform, and a robust validation of the model is necessary to determine its predictive ability. With advancing knowledge on dermal exposure and its determinants, this model will require periodic updates and refinements, in addition to further expansion of the applicability domain of the model., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Introduction: Knowledge on the exposure characteristics, including release of nanomaterials, is especially needed in the later stages of nano-enabled products' life cycles to perform better occupational risk assessments. The objective of this study was to assess the concentrations during sawing and drilling in car bumpers containing multi-walled carbon nanotubes (MWCNTs) and nanosized organic pigment (OP) under variable realistic workplace situations related to the ventilation in the room and machine settings., Methods: Twelve different experiments were performed in triplicate (N = 36) using tools powered by induction engines that allow interference-free particle measurements. A DiSCmini was used to measure particle number concentrations, whereas particle size distributions were measured using Aerodynamic Particle Sizer (TSI), Scanning Mobility Particle Sizer (TSI), and Electrical Low Pressure Impactor (Dekati). In addition, inhalable particles were sampled using IOM samplers on filters for scanning electron microscope/energy-dispersive X-ray spectrometry (SEM/EDX) analyses. Data were analysed to estimate the effects of individual exposure determinants, in a two-stage modelling strategy using Autoregressive Integrated Moving Average models (stage 1) and subsequently combining first stage results in simulations using multiple linear regression models (stage 2)., Results: In sawing experiments, partly melted carbon-rich particles (mainly ~2 to ~8 µm) were identified with SEM/EDX, whereas drilling experiments revealed no activity-related particles. In addition, no pristine engineered nanoparticles (MWCNTs and OP) were observed to be liberated from the matrix. Statistical analyses showed significant effects of a higher sawing speed, a reduction in air concentration due to mechanical ventilation, and less exposure during sawing of car bumpers containing MWCNTs compared to bumpers containing OP., Conclusion: The experiments in this study give an indication of the effects of different abrasive activities (sawing, drilling), machine settings (sawing speed, drill size), mechanical ventilation, and material characteristics on the manufactured nano-objects, their agglomerates, and aggregates concentration levels., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

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.

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 dermal model, no or hardly any measured dermal exposure data were available. Therefore, gathering of more dermal exposure levels is recommended, specifically for situations not yet sufficiently covered in the present data set., (© The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

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.)