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Exposure models are essential for a range of contexts involving exposure science. The Exposure Models Working Group, established under ISES Europe, identified that to improve model use, suitable training and education is required. However, there is currently no formal educational training programme for exposure modelling in Europe. We present results from an online survey disseminated to the European exposure science community to identify modelling training needs. The questionnaire had three sections: background information about the respondents and interests in exposure science, previous attendance of exposure modelling courses, interest in future training and education in exposure modelling and their coverage and format.A total of 88 survey recipients completed the survey. Most respondents were from governmental organizations (36 %), with 50 % of all respondents having less than 10 years of experience. About two-thirds of the respondents stated that they had previously attended exposure modelling courses. These were mostly focused on specific models, up to one day in duration and took place in-person. Two thirds of respondents expressed interest in attending future exposure modelling training modules, with the most important topics being interpretation of model results and use of models to meet regulatory standards/requirements. Preferred attendance of training courses was virtual or blended. Costs and certificates of attendance seemed less influential when selecting a training course. Our survey suggests that there is a demand for training in exposure modelling and provides insight to inform the development of training modules that are suitable to fulfil the training needs of exposure scientists and practitioners.

Biobanks are important in biomedical and public health research, and future healthcare research relies on their strength and capacity. However, there are financial challenges related to the operation of commercial biobanks and concerns around the commercialization of biobanks. Non-commercial biobanks depend on grant funding to operate and could be valuable to researchers if they can enable access to quality specimens at lower costs. The objective of this study is to estimate the value of specific biobank attributes. We used a rating-based conjoint experiment approach to study how researchers valued handling fee, access, quality, characterization, breadth of consent, access to key endemics, and time taken to fulfil requests. We found that researchers placed the greatest relative importance on the quality of specimens (26%), followed by the characterization of specimens (21%). Researchers with prior experience purchasing biological samples also valued access to key endemic in-country sites (11.6%) and low handling fees (5.5%) in biobanks., (© 2023. The Author(s).)

On 20 October 2020, the Working Group "Exposure Models" of the Europe Regional Chapter of the International Society of Exposure Science (ISES Europe) organised an online workshop to discuss the theoretical background of models for the assessment of occupational exposure to chemicals. In this report, participants of the workshop with an active role before and during the workshop summarise the most relevant discussion points and conclusions of this well-attended workshop. ISES Europe has identified exposure modelling as one priority area for the strategic development of exposure science in Europe in the coming years. This specific workshop aimed to discuss the main challenges in developing, validating, and using occupational-exposure models for regulatory purposes. The theoretical background, application domain, and limitations of different modelling approaches were presented and discussed, focusing on empirical "modifying-factor" or "mass-balance-based" approaches. During the discussions, these approaches were compared and analysed. Possibilities to address the discussed challenges could be a validation study involving alternative modelling approaches. The wider discussion touched upon the close relationship between modelling and monitoring and the need for better linkage of the methods and the need for common monitoring databases that include data on model parameters.

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.

The widespread use of engineered nanomaterials (ENMs) in consumer products and the overwhelming uncertainties in their ecological and human health risks have raised concerns regarding their safety among industries and regulators. There has been an ongoing debate over the past few decades on ways to overcome the challenges in assessing and mitigating nano-related risks, which has reached a phase of general consensus that nanotechnology innovation should be accompanied by the application of the precautionary principle and best practice risk management, even if the risk assessment uncertainties are large. We propose a quantitative methodology for selecting the optimal risk control strategy based on information about human health and ecological risks, efficacy of risk mitigation measures, cost and other contextual factors. The risk control (RC) methodology was developed in the European FP7 research project SUN and successfully demonstrated in two case studies involving real industrial nano-enabled products (NEPs): nano-scale copper oxide (CuO) and basic copper carbonate (Cu 2 (OH) 2 CO 3 ) used as antimicrobial and antifungal coatings and impregnations for the preservation of treated wood, and two nanoscale pigments used for colouring plastic automotive parts (i.e. red organic pigment and carbon black). The application of RC for human health risks showed that although nano-related risks could easily be controlled in automotive plastics case study with modifications in production technology or specific type of engineering controls, nano-related risks due to sanding and sawing copper oxide painted wood were non-acceptable in the use lifecycle stage and would need the identification of a more effective risk control strategy., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The fast penetration of nanoproducts on the market under conditions of significant uncertainty of their environmental properties and risks to humans creates a need for companies to assess sustainability of their products. Evaluation of the potential benefits and risks to build a coherent story for communication with clients, authorities, consumers, and other stakeholders is getting to be increasingly important, but SMEs often lack the knowledge and expertise to assess risks and communicate them appropriately. This paper introduces LICARA nanoSCAN, a modular web based tool that supports SMEs in assessing benefits and risks associated with new or existing nanoproducts. This tool is unique because it is scanning both the benefits and risks over the nanoproducts life cycle in comparison to a reference product with a similar functionality in order to enable the development of sustainable and competitive nanoproducts. SMEs can use data and expert judgment to answer mainly qualitative and semi-quantitative questions as a part of tool application. Risks to public, workers and consumers are assessed, while the benefits are evaluated for economic, environmental and societal opportunities associated with the product use. The tool provides an easy way to visualize results as well as to identify gaps, missing data and associated uncertainties. The LICARA nanoSCAN has been positively evaluated by several companies and was tested in a number of case studies. The tool helps to develop a consistent and comprehensive argument on the weaknesses and strengths of a nanoproduct that may be valuable for the communication with authorities, clients and among stakeholders in the value chain. LICARA nanoSCAN identifies areas for more detailed assessments, product design improvement or application of risk mitigation measures., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

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.

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.

Introduction: In occupational epidemiology, differences in the temporal coverage of the exposure history by available exposure measurement data may affect the uncertainty of exposure estimates. In the reporting of results of studies, greater attention should be paid to the extent to which exposure assessments require extrapolation outside the timeframe for which exposure measurements are available. We propose a simple graphical method that can be used to visualise the temporal coverage of exposure history with exposure measurements and the extent of temporal extrapolation needed., Methods: We construct a graph that displays the accumulated work history years for which exposure had to be assessed in each calendar year. Years for which exposure measurements were available are shaded. The proportion of work history years covered by exposure measurements and the proportion of work history years accrued before the first measurements are summarised. When available, the actual number of measurements available in each calendar year is shown., Results: We demonstrate the application of the graphical tool in three nested case-control studies that reported on leukaemia in relation to low-level benzene exposures in the petroleum industry. Considerable differences in temporal coverage between the studies were illustrated, which may have resulted in differences in the reliability of the retrospective exposure estimates derived for these studies., Conclusion: We introduce a graphical tool for visualising the temporal coverage by available exposure measurement data in epidemiological studies and encourage others to use similar graphs to derive and share better qualitative insights into the uncertainty in exposure assessment.

Objectives: For regulatory risk assessment under REACH a tiered approach is proposed in which the first tier models should provide a conservative exposure estimate that can discriminate between scenarios which are of concern and those which are not. The Stoffenmanager is mentioned as a first tier approach in the REACH guidance. In an attempt to investigate the validity of the Stoffenmanager algorithms, a cross-validation study was performed., Methods: Exposure estimates using the Stoffenmanager algorithms were compared with exposure measurement results (n=254). Correlations between observed and predicted exposures, bias and precision were calculated. Stratified analyses were performed for the scenarios "handling of powders and granules" (n=82), "handling solids resulting in comminuting" (n=60), "handling of low-volatile liquids" (n=40) and "handling of volatile liquids" (n=72)., Results: The relative bias of the four algorithms ranged between -9% and -77% with a precision of approximately 1.7. The 90th percentile estimate of one out of four algorithms was not conservative enough. Based on these statistics and analyses of residual plots the underlying algorithm was adapted. Subsequently, the calibration and the cross-validation dataset were merged into one dataset (n=952) used for calibrating the adapted Stoffenmanager algorithms. This new calibration resulted in new exposure algorithms for the four scenarios., Conclusions: The Stoffenmanager is capable of discriminating among exposure levels mainly between scenarios in different companies. The 90th percentile estimates of the Stoffenmanager are verified to be sufficiently conservative. Therefore, the Stoffenmanager could be a useful tier 1 exposure assessment tool for REACH.

Background: Nurses and other hospital workers are exposed to antineoplastic drugs during daily activities. Previous studies suggest that antineoplastic drugs at occupational exposure levels may be toxic to reproduction, but these studies are not consistent or conclusive., Methods: Self-administered questionnaires were completed by 4393 exposed and nonexposed nurses employed between 1990 and 1997 (79% response). Questions were asked about pregnancy outcome, work-related exposures, and lifestyle. Exposure to antineoplastic drugs was estimated using task-based dermal exposure measurements and self-reported task frequencies. Time to pregnancy was modeled using survival analysis, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for other reproductive outcomes using multiple logistic regression analysis. Associations were further explored by nonparametric regression modeling., Results: Nurses highly exposed to antineoplastic drugs took longer to conceive than referent nurses (adjusted hazard ratio = 0.8; CI = 0.6-0.9). Exposure to antineoplastic drugs was associated with premature delivery (OR per unit increase in ln[exposure] = 1.08; CI = 1.00-1.17) and low birth weight (OR per unit increase in ln[exposure] = 1.11; 1.01-1.21). Penalized smoothed spline plots corroborated these log-linear relations. Spontaneous abortion, stillbirth, congenital anomalies, and sex of offspring appeared not to be related to exposure to antineoplastic drugs., Conclusion: Antineoplastic drugs may reduce fertility and increase poor neonatal outcomes among occupationally exposed oncology nurses.

Objective: The main goal was to investigate the potential of a probabilistic approach for exposure assessment and use this information to evaluate the impact of a complex of policy actions/interventions on dermal exposure to antineoplastic agents among oncology nurses. The central theme of this study was to make optimal use of existing data, supplemented only with limited additional information from a questionnaire survey., Methods: A task based exposure model was used to estimate dermal exposure of the hands among oncology nurses in non-academic hospitals in the Netherlands. Monte Carlo simulation was used to integrate information from available (exposure) studies and generate exposure distributions for the total population of oncology nurses in both pre- and post-intervention situation. Graphs and descriptive statistics of the simulated exposure distributions were used to evaluate trends in population exposure., Results: The inventory showed that important intervention occurred in the preparation and administering of antineoplastic agents and in the handling of urine. Hardly any changes were identified in de nursing tasks. The use of gloves seemed to have decreased for a number of tasks. The results of the analysis show that the interventions did not affect the median exposure. However frequencies of occurrence of individuals with very high and very low total dermal exposures decreased substantially in the post-intervention situation. Analysis of the effect of pregnancy showed that pregnancy is very unlikely to influence exposure or any of the key input variables., Conclusions: The present study shows that the probabilistic approach adds valuable information to deterministic exposure assessment, especially when extrapolating data on a subpopulation to populations of individuals at large. The results show that the identified changes in the past decade in Dutch non-academic hospitals resulted in changes in the exposure distribution of antineoplastic agents among oncology nurses.

Background: The authors recently developed a Dermal Exposure Assessment Method (DREAM), an observational semiquantitative method to assess dermal exposures by systematically evaluating exposure determinants using pre-assigned default values., Aim: To explore the accuracy of the DREAM method by comparing its estimates with quantitative dermal exposure measurements in several occupational settings., Methods: Occupational hygienists observed workers performing a certain task, whose exposure to chemical agents on skin or clothing was measured quantitatively simultaneously, and filled in the DREAM questionnaire. DREAM estimates were compared with measurement data by estimating Spearman correlation coefficients for each task and for individual observations. In addition, mixed linear regression models were used to study the effect of DREAM estimates on the variability in measured exposures between tasks, between workers, and from day to day., Results: For skin exposures, spearman correlation coefficients for individual observations ranged from 0.19 to 0.82. DREAM estimates for exposure levels on hands and forearms showed a fixed effect between and within surveys, explaining mainly between-task variance. In general, exposure levels on clothing layer were only predicted in a meaningful way by detailed DREAM estimates, which comprised detailed information on the concentration of the agent in the formulation to which exposure occurred., Conclusions: The authors expect that the DREAM method can be successfully applied for semiquantitative dermal exposure assessment in epidemiological and occupational hygiene surveys of groups of workers with considerable contrast in dermal exposure levels (variability between groups >1.0). For surveys with less contrasting exposure levels, quantitative dermal exposure measurements are preferable.