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Exposure models for regional seismic risk assessment often place assets at the centroids of administrative units for which data are available. At best, a top-down approach is followed, where such data are spatially disaggregated over a denser spatial grid, using proxy datasets such as the distribution of population or the density of night-time lights. The resolution of the spatial grid is either dictated by the resolution of the proxy dataset, or by constraints in computational resources. On the other hand, if a building-by-building database is available, it often needs to be aggregated and brought to a resolution that ensures acceptable calculation runtimes and memory demands. Several studies have now investigated the impact of exposure aggregation on loss estimates. Herein, unlike previous attempts, we can leverage upon an extensive building-by-building database for the Swiss territory, which we can use as ground truth. We firstly proceed to assess the aggregation-induced errors of standard risk metrics at different spatial scales. Then a new strategy for performing said aggregation is proposed, relying on a K-means clustering of site parameters and a reduction of the loss ratio uncertainty for aggregated assets. These interventions are designed with the objective of minimizing errors, while keeping the computational cost manageable. [ABSTRACT FROM AUTHOR]

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.

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 (H i ), that allows conversion of a dustiness value to a release constant. Therefore, a H i , 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 H i 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 H i derived for the 2 test methods with increasing pouring height. Nearly all the H i 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. [ABSTRACT FROM AUTHOR]

While the use of antibiotics has been reported as extensive in the rearing of agricultural animals, insufficient information is available on the antibiotic residues in animal products and the adverse impact that consistent low-level exposure to antibiotics might have on the human body and its microbiome. The aim of this study was to estimate the antibiotic concentrations that humans are exposed to via their diet using the concentration of antibiotics in animal food products and water and an online survey on dietary intake. A total of 131 participants completed the dietary intake survey, with the majority belonging to the omnivorous diet group (76.3%). Distinct dietary trends were observed in the omnivorous and unknown groups eating animal products, with specific food types dominating each meal: pork (e.g., ham) and dairy products (e.g., milk, yoghurt) during breakfast, beef (e.g., burgers) and chicken (e.g., chicken breast) products during lunch, and fish (e.g., salmon fillet) during dinner. In total, 34 different animal-based food and drink products were tested for the presence of ten different antibiotics. Of all the products tested, over 35% exceeded the acceptable daily antibiotic intake for amoxicillin, ampicillin, and enrofloxacin. [ABSTRACT FROM AUTHOR]

Water use of domestic activities was quantified by interviewing 217 people in a peri-urban community near Bandung, Indonesia. Resulting in data on domestic water demand and data needed for exposure modelling of domestic activities: drinking, cooking, brushing teeth, swimming, bathing, laundry, dishwashing, religious cleansing, washing hands and cleaning food. Average total domestic water usage was 117 l/person/day, topping the WHO guidelines for basic needs (50–100 l/person/day). This water use level is comparable with higher income countries for the same set of activities but 100% higher than water use in an Indonesian traditional rural community. The final dataset provides insight in quantity of water used for domestic activities, as well as the use-frequency, duration and water sources used. These data are scarce for Indonesia and other low-middle income countries but necessary for water demand studies and estimating risks through exposure to pathogens and emerging contaminants in human exposure modelling. [ABSTRACT FROM AUTHOR]

Task-based respirable crystalline silica (RCS) exposure monitoring data was collected from construction work sites across 3 Canadian provinces: Alberta, British Columbia (BC), and Manitoba. In total 373 RCS samples were obtained from 70 worksites across 44 companies. Sampling was conducted between May 2015 and August 2020. The overall geometric mean (GM) RCS exposure was 0.045 mg/m3 (geometric standard deviation, GSD = 6.8). Alberta had the highest average exposure and the highest variability with GM of 0.060 mg/m3 (GSD = 9.3), the GM in BC was 0.044 (GSD = 4.3), and in Manitoba the GM was 0.033 (GSD = 7.0). A multivariable model was built using forward stepwise linear regression modeling. Province, task type, work environment (indoor vs. outdoor), construction material, sampling duration, and engineering control use were all statistically significant predictors of exposure level in partial F -tests (P < 0.05). Overall, the model explained 42% of the RCS concentration variability. Task type contributed most to the model's explanatory power. The task type with highest average exposure levels was demolition (GM 0.30 mg/m3, GSD 0.49). Breaking (GM 0.16 mg/m3, GSD 8.4) and grinding (GM 0.081 m/m3, GSD 7.4) also had high-exposure levels. Working outdoors was associated with exposure levels 39% lower than indoors. Exposure control measures such as local exhaust ventilation and wetting were also associated with lower exposure levels. Among construction materials, Cement, sand, and stone were associated with higher RCS exposure levels relative to the reference material, concrete. The results of this study indicate that workers in western Canada remain exposed to RCS at levels that exceed the health-based American Congress for Governmental Industrial Hygienists Threshold Limit Value of 0.025 mg/m3. Although there were some differences in exposure levels between the provinces, the determinants of exposure were similar in all 3. The overall GM RCS exposure was 0.045 mg/m3 (geometric standard deviation, GSD = 6.8). Alberta had the highest average exposure and the highest variability with GM of 0.060 mg/m3 (GSD = 9.3), the GM in BC was 0.044 (GSD = 4.3), and in Manitoba the GM was 0.033 (GSD = 7.0). [ABSTRACT FROM AUTHOR]

Background Occupational exposure to soluble chlorinated platinum (Pt) salts, commonly called chloroplatinates, is a known cause of Pt salt sensitisation (PSS) and occupational asthma. We aimed to model inhalable soluble Pt salts exposure levels based on measurements in precious metal refineries for use in a retrospective cohort study on PSS. Methods Five platinum refineries located in the United Kingdom (3 sites), United States, and South Africa provided time weighted average inhalable soluble Pt salts exposure data, measured in 2,982 personal air samples over a 17-year period (2000-2016). We used a Bayesian hierarchical model to estimate geometric mean (GM) exposure levels for each refinery and job title over time. Results The GM of measured exposure levels over all facilities was 92 ng/m3 with a geometric standard deviation (GSD) of 9.07. Facility-specific GMs ranged from 48 ng/m3 (GSD 15.3) to 242 ng/m3 (GSD 5.99). Exposure modelling showed that soluble Pt salts exposure levels declined approximately 10% per year in two of the five facilities, but there were no clear time trends in the other facilities. A priori specified exposure groups captured most of the between-jobs differences, which helps to accurately predict exposures for jobs with no measurement data available. Conclusions We applied exposure modelling to estimate time, refinery, and job-specific soluble Pt salts exposures. A significant annual decline in exposure levels was observed in two of the five participating facilities. Modelled exposure levels can be linked to individual workers' job history for exposure–response analysis of PSS in an epidemiological study. [ABSTRACT FROM AUTHOR]

Wood dust is an established carcinogen also linked to several non malignant respiratory disorders. A major limitation in research on wood dust and its health effects is the lack of (historical) quantitative estimates of occupational exposure for use in general population-based case-control or cohort studies. The present study aimed to develop a multinational quantitative Job Exposure Matrix (JEM) for wood dust exposure using exposure data from several Northern and Central European countries. For this, an occupational exposure database containing 12653 personal wood dust measurements collected between 1978 and 2007 in Denmark, Finland, France, The Netherlands, Norway, and the United Kingdom (UK) was established. Measurement data were adjusted for differences in inhalable dust sampling efficiency resulting from the use of different dust samplers and analysed using linear mixed effect regression with job codes (ISCO-88) and country treated as random effects. Fixed effects were the year of measurement, the expert assessment of exposure intensity (no, low, and high exposure) for every ISCO-88 job code from an existing wood dust JEM and sampling duration. The results of the models suggest that wood dust exposure has declined annually by approximately 8%. Substantial differences in exposure levels between countries were observed with the highest levels in the United Kingdom and the lowest in Denmark and Norway, albeit with similar job rankings across countries. The jobs with the highest predicted exposure are floor layers and tile setters, wood-products machine operators, and building construction labourers with geometric mean levels for the year 1997 between 1.7 and 1.9 mg/m3. The predicted exposure estimates by the model are compared with the results of wood dust measurement data reported in the literature. The model predicted estimates for full-shift exposures were used to develop a time-dependent quantitative JEM for exposure to wood dust that can be used to estimate exposure for participants of general population studies in Northern European countries on the health effects from occupational exposure to wood dust. [ABSTRACT FROM AUTHOR]

While the use of antibiotics has been reported as extensive in the rearing of agricultural animals, insufficient information is available on the antibiotic residues in animal products and the adverse impact that consistent low-level exposure to antibiotics might have on the human body and its microbiome. The aim of this study was to estimate the antibiotic concentrations that humans are exposed to via their diet using the concentration of antibiotics in animal food products and water and an online survey on dietary intake. A total of 131 participants completed the dietary intake survey, with the majority belonging to the omnivorous diet group (76.3%). Distinct dietary trends were observed in the omnivorous and unknown groups eating animal products, with specific food types dominating each meal: pork (e.g., ham) and dairy products (e.g., milk, yoghurt) during breakfast, beef (e.g., burgers) and chicken (e.g., chicken breast) products during lunch, and fish (e.g., salmon fillet) during dinner. In total, 34 different animal-based food and drink products were tested for the presence of ten different antibiotics. Of all the products tested, over 35% exceeded the acceptable daily antibiotic intake for amoxicillin, ampicillin, and enrofloxacin.

Esters of 1,2-benzene dicarboxylic acid (or phthalates) are general purpose plasticizers used in multiple polyvinyl chloride (PVC) consumer applications. Some of these plasticizers are permitted for safe use in a narrow subset of food packaging applications by global regulatory agencies, including the US FDA. Several US studies have reported the presence of trace concentrations of phthalates (parts per billion) in the diet. These findings have prompted calls for regulatory action based on the potential for adverse impacts on public health. These claims are misguided. Global food safety regulatory frameworks are designed with the expectation that low concentrations of food contact materials may be present in food. These frameworks include guardrails (in the form of content limits and/or migration limits) to minimize the potential for dietary risk. This concept of exposure and risk is often missing in many studies identifying low concentrations of phthalates in food. Dietary risk assessments, based on total diet studies, have been published by food safety agencies in the EU, Australia, New Zealand, UK, and Canada. Without exception, all risk assessments confirm that concentrations of phthalates in food are low and do not pose a public health concern. In this review, we calculate dietary risk estimates for concentrations of high molecular weight phthalates reported in some US food articles. The results confirm that dietary exposures, even in the most conservative scenarios, are below levels of concern. [ABSTRACT FROM AUTHOR]

[Display omitted] 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. [ABSTRACT FROM AUTHOR]

The use of Bayesian networks (BN) for environmental risk assessment has increased in recent years as they offer a more transparent way to characterize risk and evaluate uncertainty than the traditional risk assessment paradigms. In this study, a novel probabilistic approach applying a BN for risk calculation was further developed and explored by linking the calculation a risk quotient to alternative future scenarios. This extended version of the BN model uses predictions from a process-based pesticide exposure model (World Integrated System for Pesticide Exposure - WISPE) in the exposure characterization and toxicity test data in the effect characterization. The probability distributions for exposure and effect are combined into a risk characterization (i.e. the probability distribution of a risk quotient), a common measure of the exceedance of an environmentally safe exposure threshold. The BN model was used to account for variabilities of the predicted pesticide exposure in agricultural streams, and inter-species variability in sensitivity to the pesticide among freshwater species. In Northern Europe, future climate scenarios typically predict increased temperature and precipitation, which can be expected to cause an increase in weed infestations, plant disease and insect pests. Such climate-related changes in pest pressure in turn can give rise to altered agricultural practices, such as increased pesticide application rates, as an adaptation to climate change. The WISPE model was used to link a set of scenarios consisting of two climate models, three pesticide application scenarios and three periods (year ranges), for a case study in South-East Norway. The model was set up for the case study by specifying environmental factors such as soil properties and field slope together with chemical properties of pesticides to predict the pesticide exposure in streams adjacent to the agricultural fields. The model was parameterized and evaluated for five selected pesticides: the three herbicides clopyralid, fluroxypyr-meptyl, and 2-(4-chloro-2-methylphenoxy) acetic acid (MCPA), and the two fungicides prothiocanzole and trifloxystrobin. This approach enabled the calculation and visualization of probability distribution of the risk quotients for the future time horizons 2050 and 2085. The risk posed by the pesticides were in general low for this case study, with highest probability of the risk quotient exceeding 1 for the two herbicides fluroxypyr-meptyl and MCPA. The future climate projections used here resulted in only minor changes in predicted exposure concentrations and thereby future risk. However, a stronger increase in risk was predicted for the scenarios with increased pesticide application, which can represent an adaptation to a future climate with higher pest pressures. In the current study, the specific BN model predictions were constrained by an existing set of climate projections which represented only one IPCC scenario (A1B) and two climate models. Further advancement of the BN modelling demonstrated herein, including more recent climate scenarios and a larger set of climate models, is anticipated to result in more relevant risk characterization also for future climate conditions. This probabilistic approach will have the potential to aid targeted management of ecological risks in support of future research, industry and regulatory needs.

User behaviour for natural ventilation is known to be strongly corelated to outdoor temperatures. In areas of moderate climate, this leads to an increased fresh air supply in summer, which reduces the exposure level towards airborne pathogens. Modelling of numerous random exposure situations in household, school and various settings, based on the long-term climate data from Berlin, showed that this effect is likely to contribute significantly to the overall seasonality of airborne diseases.

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 (D hands), direct emission and direct contact (E hands), and contact transfer (T hands)) 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. [ABSTRACT FROM AUTHOR]

In this article, we have responded to the key statements in the article by Koivisto et al. (2022) that were incorrect and considered to be a biased critique on a subset of the exposure models used in Europe (i.e. ART and Stoffenmanager®) used for regulatory exposure assessment. We welcome scientific discussions on exposure modelling (as was done during the ISES Europe workshop) and criticism based on scientific evidence to contribute to the advancement of occupational exposure estimation tools. The tiered approach to risk assessment allows various exposure assessment models from screening tools (control/hazard banding) through to higher-tiered approaches. There is a place for every type of model, but we do need to recognize the cost and data requirements of highly bespoke assessments. That is why model developers have taken pragmatic approaches to develop tools for exposure assessments based on imperfect data. We encourage Koivisto et al. to focus on further scientifically robust work to develop mass-balance models and by independent external validations studies, compare these models with alternative model tools such as ART and Stoffenmanager®. [ABSTRACT FROM AUTHOR]

Objectives To use the recently developed Ontario Mining Exposure Database (OMED) to describe historical silica exposure in the Ontario metal mining industry and identify predictors of historical silica exposure. Methods Personal respirable crystalline silica (RCS) data for metal mines were extracted from OMED and included both individual and summary measures, where multiple exposure measurements (n > 1) were aggregated and entered as a single exposure value (n = 1). Data were stratified by sample location (underground/surface) for analysis. Monte Carlo simulation was used to simulate individual measures from the summary measures. A fixed effects multiple linear regression model was used to assess the effects of commodity (ore mined), sample year, source of exposure data, and occupational group on RCS concentration. Parameter estimates (β), standard errors, and 95% upper and lower confidence intervals were reported. Results The OMED contained 12 995 silica measurements. After limiting to RCS measurements in metal mines, and measures with sufficient information for analysis, 2883 RCS measurements collected from 1974 to 1991 remained, including 2816 individual and 67 summary measurements. In total, 321 individual RCS measurements were simulated from the 67 summary measures. The analysis database contained 2771 (12% simulated) underground measurements and 366 surface measurements (0% simulated). In the underground group, an overall geometric mean (GM) of 0.05 [geometric standard deviation (GSD) 3.09] mg m−3 was estimated with a 6% annual decrease over time. In this group, the commodity with the highest average RCS level was zinc mines (GM = 0.07 mg m−3) and the lowest was iron mines (GM = 0.01 mg m−3). In the surface group, an overall GM of 0.05 (GSD 3.70) mg m−3 was estimated with an 8% decreased over time. In this group, the commodity with the highest average RCS level was gold mines (GM = 0.07 mg m−3) and the lowest was zinc mines (GM = 0.03 mg m−3). In both groups, company collected data had lower estimated RCS compared with regulator collected data. Conclusions Historical RCS levels decreased over time. Mean measurements exceeded the American Conference of Governmental Industrial Hygienists current health-based threshold limit value (0.025 mg m−3). The main predictors of exposure were commodity, source of exposure data, and sample year. However, low R 2 and high GSD values suggest additional predictors of RCS exposures in Ontario's metal mines exist that were unavailable in OMED. [ABSTRACT FROM AUTHOR]

The independent and joint effects of within- and between-city contrasts in air pollution on mortality have been investigated rarely. To examine the differential effects of between- versus within-city contrasts in pollution exposure, we used both ambient measurements and land use regression models to assess associations with mortality and exposure to nitrogen dioxide (NO2) among ~735,600 adults in 10 of the largest Canadian cities. We estimated exposure contrasts partitioned into within- and between-city contrasts, and the sum of these as overall exposures, for every year from 1984 to 2006. Residential histories allowed us to follow subjects annually during the study period. We calculated hazard ratios (HRs) adjusted for many personal and contextual variables. In fully-adjusted, random-effects models, we found positive associations between overall NO2 exposures and mortality from non-accidental causes (HR per 5 p.p.b.: 1.05; 95% confidence interval (CI): 1.03-1.07), cardiovascular disease (HR per 5 p.p.b.: 1.04; 95% CI: 1.01-1.06), ischaemic heart disease (HR per 5 p.p.b.: 1.05; 95% CI: 1.02-1.08) and respiratory disease (HR per 5 p.p.b.: 1.04; 95% CI: 0.99-1.08), but not from cerebrovascular disease (HR per 5 p.p.b.: 1.01; 95% CI: 0.96-1.06). We found that most of these associations were determined by within-city contrasts, as opposed to by between-city contrasts in NO2. Our results suggest that variation in NO2 concentrations within a city may represent a more toxic mixture of pollution than variation between cities.

Boron is an essential mineral for plants, and as such, is a normal dietary constituent for humans. Humans may be naturally exposed to boron through food and drinking water, or via anthropogenic sources such as consumer products. The World Health Organisation established an acceptable safe range of population mean intakes for boron of 1–13 mg/day. Most studies of dietary boron intake show a range of 1–2 mg/day. Consumer products have been estimated to contribute a geometric mean daily intake of 0.1 mg to total boron exposure; however, there are few published surveys of consumer exposure to boron from use of cleaning products. The Government of Canada published a draft screening assessment report of boric acid, its salts and precursors that included estimates of consumer exposure to boron found as ingredients in consumer products. The manufacturers of consumer cleaning products conducted a survey of boron content of current products and estimated exposure using the publicly available exposure tool ConsExpo Web. Dermal exposures to boron during cleaning product use were estimated to result in annual internal exposures ranging from ≪0.001 to 0.36 μg/kg bw/day based on dermal absorption of 0.5%. Using a conservative point of departure for hazard assessment (2,900 μg boron/kg bw/day), estimated margins of exposure for dermal exposures to boron from cleaning product use range from 8,056 to >1,000,000. This work demonstrates that exposure to boron from cleaning product use is very low and essentially insignificant when compared to other (e.g. dietary) sources of boron intake by Canadian consumers. [ABSTRACT FROM AUTHOR]

OBJECTIVES: This study aimed to determine the extent to which age, gender, body mass index (BMI) and low-back pain (LBP) influence bias in self-reported sedentary behavior and moderate-to-vigorous physical activity (MVPA) among blue-collar workers. METHODS: For 2–4 consecutive working days, 147 workers wore an Actigraph accelerometer on the thigh. Proportional time spent sedentary and in MVPA was determined using the Acti4 software. The same variables were also self-reported in a questionnaire. The difference between self-reported and accelerometer-based sedentary time and MVPA was calculated and linearly regressed against age, gender, BMI, and self-reported LBP intensity as main effects, as well as interaction terms combining each of these factors with objectively measured exposure. RESULTS: Workers objectively spent 64% of their time sedentary and 9% in MVPA. On average, self-reports underestimated sedentary time by 1.5% and overestimated MVPA by 5.5%. Workers with mild/no LBP appeared to have the same size of self-report bias in MVPA regardless of how much MVPA they actually had, while workers with high LBP overestimated MVPA to an increasing extent with increasing exposure [interaction: B=0.29, 95% confidence interval (CI) 0.05–0.53]. Age was positively associated with self-report bias in sedentary time (B=0.31, 95% CI 0.09–0.54) regardless of actual sedentary time. CONCLUSIONS: LBP and age, but not BMI and gender, introduced differential bias in self-reported information on sedentary behavior and MVPA among blue-collar workers. This result suggests that bias correction in future studies based on self-reports of sedentary time and MVPA should account for LBP and age.

The substitution of fish oil and fishmeal with plant-based ingredients in commercial aquafeeds for Atlantic salmon, may introduce novel contaminants that have not previously been associated with farmed fish. The organophosphate pesticide pirimiphos-methyl (PM) is one of the novel contaminants that is most prevalent in commercial salmon feed. In this study, the feed-to-fillet transfer of dietary PM and its main metabolites was investigated in Atlantic salmon fillet. Based on the experimental determined PM and metabolite uptake, metabolisation, and elimination kinetics, a physiologically based toxicokinetic (PBTK) compartmental model was developed. Fish fed PM had a relatively low (~4%) PM retention and two main metabolites (2-DAMP and Desethyl-PM) were identified in liver, muscle, kidney and bile. The absence of more metabolised forms of 2-DAMP and Desethyl-PM in Atlantic salmon indicates different metabolism in cold-water fish compared to previous studies on ruminants. The model was used to simulate the long term (>1.5 years) feed-to-fillet transfer of PM + metabolite in Atlantic salmon under realistic farming conditions including seasonal fluctuations in feed intake, growth, and fat deposition in muscle tissue. The model predictions show that with the constant presence of the highest observed PM concentration in commercial salmon feed, fillet PM+ metabolite levels were approximately 5 nmol kg−1, with highest levels for the metabolite 2-DAMP. No EU maximum residue levels (MRL) for PM and its main metabolites exist in seafood to date, but the predicted levels were lower than the MRL for PM in swine of 32.7 nmol kg−1. [ABSTRACT FROM AUTHOR]

The current migration assessment requirements regarding safety of plastic food contact materials in Europe (e.g. kitchen utensils, kitchen appliances, packaging, etc.) widely rely on migration testing. According to Annexe V of Regulation (EU) No 10/2011 migration testing requirements consider the specificities of repeated use applications only to a limited extent. Repeated use food contact materials should be tested for three consecutive times at the worst-case contact time and temperature. If diffusion controlled, the migration decreases with increasing number of repeated uses. Compared to single use applications, repeated use food contact materials typically exhibit much shorter contact times, much lower ratios of surface in contact with a given amount of food, and in some cases higher temperatures. Compared to real use, in many cases highly overestimated migration testing result are observed. Overestimation by testing at the beginning of use may be coupled with underestimation at later times. National legislation of the Netherlands on food contact materials has established a classification for repeated use rubber materials based on the R-value indicating whether migration testing is required or not. The R-value considers in more detail specificities of repeated use applications. This publication investigates to which extent it is possible to apply the approach to plastics food contact materials in Europe. It is practically impossible to perform migration tests for various materials by putting them many times in contact with food over a long period of time, typically several years, at several temperatures and areas to food amount ratios migration. Modelling has therefore been used to predict migration from various food contact materials under different repeated use scenarios. Realistic diffusion properties of materials and migrant partitioning behaviour have been assumed to minimise the risk of underestimation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This article studies the effects of the soil data and exposure data of residential building inventories, as well as their spatial resolution, on seismic damage and loss estimates for a given earthquake scenario. Our aim is to investigate how beneficial it would be to acquire higher resolution inventories at the cost of additional effort and resources. Seismic damage computations are used to evaluate the relative influence of varying spatial resolution on a given damage model, where other parameters were held constant. We use soil characterization maps and building exposure inventories, provided at different scales from different sources: the European database, a national dataset at the municipality scale, and local field investigations. Soil characteristics are used to evaluate site effects and to assign amplification factors to the strong motion applied to the exposed areas. Exposure datasets are used to assign vulnerability indices to sets of buildings, from which a damage distribution is produced (based on the applied seismic intensity). The different spatial resolutions are benchmarked in a case-study area which is subject to moderate-to-average seismicity levels (Luchon valley in the Pyrénées, France). It was found that the proportion of heavily damaged buildings is underestimated when using the European soil map and the European building database, while the more refined databases (national/regional vs. local maps) result in similar estimates for moderate earthquake scenarios. Finally, we highlight the importance of pooling open access data from different sources, but caution the challenges of combining different datasets, especially depending on the type of application that is pursued (e.g., for risk mitigation or rapid response tools).

The dermal Advanced REACH Tool (dART) is a Tier 2 exposure modelling tool currently in development for estimating dermal exposure to the hands (mg min−1) for non-volatile liquid and solids-in-liquid products. The dART builds upon the existing ART framework and describes three mass transport processes [deposition (⁠ D h a n d s) ⁠ , direct emission and direct contact (⁠ E h a n d s) ⁠ , and contact transfer (⁠ T h a n d s ⁠)] that may each contribute to dermal exposure. The mechanistic model that underpins the dART and its applicability domain has already been described in previous work. This paper describes the process of calibrating 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). Furthermore, as a consequence of calibration, the uncertainty in a dART prediction may be quantified via a confidence interval. Thirty-six experimental studies were identified that satisfied the conditions of: (i) high-quality contextual information that was sufficient to confidently code the dART mechanistic model determinants; (ii) reliable exposure measurement data sets were available. From these studies, 40 exposure scenarios were subsequently developed. A non-linear log-normal mixed-effect model was fitted to the data set of D h a n d s ,       E h a n d s ⁠ , and       T h a n d s scores and corresponding measurement data. The dART model was shown to be consistent with activities covering a broad range of tasks [spray applications, activities involving open liquid surfaces (e.g. dipping, mixing), handling of contaminated objects, spreading of liquid products, and transfer of products (e.g. pouring of liquid)]. Exposures resulting from a particular task were each dominated by one or two of the identified mass transport processes. As a consequence of calibration, an estimate of the uncertainty associated with a mechanistic model estimate is available. A 90% multiplicative interval is approximately a factor of six. This represents poorer overall precision than the (inhalation) ART model for dusts and vapours, although better than the ART model for mists. Considering the complexity of the conceptual model compared with the ART, the wide variety of exposure scenarios considered with differing dominant routes, and the particular challenges that result from the consideration of measurement data both above and beneath a protective glove, the precision of the calibrated dART mechanistic model is reasonable for well-documented exposure scenarios coded by experts. However, as the inputs to the model are based upon user judgement, in practical use, the reliability of predictions will be dependent upon both the competence of users and the quality of contextual information available on an exposure scenario. [ABSTRACT FROM AUTHOR]

Abstract Surface water concentrations of 54 pharmaceuticals were predicted for seven major Swedish rivers and the Stockholm City area basins using the STREAM-EU model. These surface water concentrations were used to predict the ecotoxicological impact resulting from the exposure of aquatic organisms to this mixture of 54 pharmaceuticals. STREAM-EU model results indicated that <10 substances were present at median annual water concentrations greater than 10 ng/L with highest concentrations occurring mostly in the more densely populated area of the capital city, Stockholm. There was considerable spatial and temporal variability in the model predictions (1–3 orders of magnitude) due to natural variability (e.g. hydrology, temperature), variations in emissions and uncertainty sources. Local mixture ecotoxicological pressures based on acute EC50 data as well as on chronic NOEC data, expressed as multi-substance potentially affected fraction of species (msPAF), were quantified in 114 separate locations in the waterbodies. It was estimated that 5% of the exposed aquatic species would experience exposure at or above their acute EC50 concentrations (so-called acute hazardous concentration for 5% of species, or aHC5) at only 7% of the locations analyzed (8 out of 114 l o cations). For the evaluation based on chronic NOEC concentrations, the chronic HC5 (cHC5) is exceeded at 27% of the locations. The acute mixture toxic pressure was estimated to be predominantly caused by only three substances in all waterbodies: Furosemide, Tramadol and Ibuprofen. A similar evaluation of chronic toxic pressure evaluation logically demonstrates that more substances play a significant role in causing a higher chronic toxic pressure at more sites as compared to the acute toxic pressure evaluation. In addition to the three substances contributing most to acute effects, the chronic effects are predominantly caused by another five substances: paracetamol, diclofenac, ethinylestradiol, erythromycin and ciprofloxacin. This study provides regulatory authorities and companies responsible for water quality valuable information for targeting remediation measures and monitoring on a substance and location basis. Graphical abstract Image 1 Highlights • We predicted concentrations of pharmaceuticals in 7 Swedish rivers with STREAM-EU. • We calculated ecotoxicological pressures for the mixture of drugs using msPAF. • < 10 drugs had annual median predicted concentrations >10 ng/L. • msPAF predictions indicate acute HC5 is reached at 7% of the locations. • msPAF predictions indicate chronic HC5 is reached at 27% of the locations. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the accuracy, precision and conservatism of three models (ECETOC TRA 3.1, Stoffenmanager 7.0 and ART 1.5) by comparing model predictions and repeated exposure measurements in Korea. We collected the exposure measurements (n = 390) and detailed contextual information extracted from 10 survey reports published by Ministry of Employment and Labour in the mid-2000s. Using these three models, seven occupational health professionals predicted inhalation exposure to 10 solvents used for cleaning tasks in 51 situations at 33 companies in 15 industries. We applied four comparison approaches previously used by several European studies and calculated the lack of agreement (bias, relative bias, precision), Pearson correlation coefficients (r), level of conservatism, and residuals between the log-transformed predicted estimates and measured exposures on both individual and situation levels. The overall bias and precision were −0.53 ± 2.11 with ART, −1.32 ± 5.88 with Stoffenmanager, and −1.03 ± 8.88 with ECETOC TRA. Pearson correlation coefficients were significantly high in ART (r = 0.95) and Stoffenmanager (r = 0.82), but moderate in ECETOC TRA (r = 0.58). We found ART to be the most accurate model, and Stoffenmanager was the most balanced model in terms of good accuracy, high correlation, and medium conservatism in the model predictions. However, ECETOC TRA showed less accurate outcomes and lower level of conservatism but still had moderate correlations. We observed a systematic tendency to overestimate low exposures and underestimate higher exposures in all models, similar to previous studies. Therefore, our findings suggest that these European models can be used to predict occupational exposure to solvents in Korea. [ABSTRACT FROM AUTHOR]

Objectives This study aimed to determine the extent to which age, gender, body mass index (BMI) and low-back pain (LBP) influence bias in self-reported sedentary behavior and moderate-to-vigorous physical activity (MVPA) among blue-collar workers. Methods For 2–4 consecutive working days, 147 workers wore an Actigraph accelerometer on the thigh. Proportional time spent sedentary and in MVPA was determined using the Acti4 software. The same variables were also self-reported in a questionnaire. The difference between self-reported and accelerometer-based sedentary time and MVPA was calculated and linearly regressed against age, gender, BMI, and self-reported LBP intensity as main effects, as well as interaction terms combining each of these factors with objectively measured exposure. Results Workers objectively spent 64% of their time sedentary and 9% in MVPA. On average, self-reports underestimated sedentary time by 1.5% and overestimated MVPA by 5.5%. Workers with mild/no LBP appeared to have the same size of self-report bias in MVPA regardless of how much MVPA they actually had, while workers with high LBP overestimated MVPA to an increasing extent with increasing exposure [interaction: B=0.29, 95% confidence interval (CI) 0.05–0.53]. Age was positively associated with self-report bias in sedentary time (B=0.31, 95% CI 0.09–0.54) regardless of actual sedentary time. Conclusions LBP and age, but not BMI and gender, introduced differential bias in self-reported information on sedentary behavior and MVPA among blue-collar workers. This result suggests that bias correction in future studies based on self-reports of sedentary time and MVPA should account for LBP and age. [ABSTRACT FROM AUTHOR]

Here, we studied the particle release rate during Electrostatic spray deposition of anatase-(TiO 2 )-based photoactive coating onto tiles and wallpaper using a commercially available electrostatic spray device. Spraying was performed in a 20.3 m 3 test chamber while measuring concentrations of 5.6 nm to 31 μm-size particles and volatile organic compounds (VOC), as well as particle deposition onto room surfaces and on the spray gun user hand. The particle emission and deposition rates were quantified using aerosol mass balance modelling. The geometric mean particle number emission rate was 1.9 × 10 10 s −1 and the mean mass emission rate was 381 μg s −1 . The respirable mass emission-rate was 65% lower than observed for the entire measured size-range. The mass emission rates were linearly scalable (±ca. 20%) to the process duration. The particle deposition rates were up to 15 h −1 for <1 μm-size and the deposited particles consisted of mainly TiO 2 , TiO 2 mixed with Cl and/or Ag, TiO 2 particles coated with carbon, and Ag particles with size ranging from 60 nm to ca. 5 μm. As expected, no significant VOC emissions were observed as a result of spraying. Finally, we provide recommendations for exposure model parameterization. [ABSTRACT FROM AUTHOR]

Health impacts of air pollutants, especially fine particles (PM2.5) and NO2, have been documented worldwide by epidemiological studies. Most of the existing studies utilised the concentration measured at the ambient stations to represent the pollutant inhaled by individuals. However, these measurement data are in fact not able to reflect the real concentration a person is exposed to since people spend most of their time indoors and are also affected by indoor sources. The authors developed a probabilistic methodology framework to simulate the lifelong exposure to PM2.5 and NO2 simultaneously for population subgroups that are characterised by a number of indicators such as age, gender and socio-economic status. The methodology framework incorporates the methods for simulating the long-term outdoor air quality, the pollutant concentration in different micro-environments, the time-activity pattern of population subgroups and the retrospective life course trajectories. This approach was applied to the population in the EU27 countries plus Norway and Switzerland and validated with the measurement data from European multi-centre study, EXPOLIS. Results show that the annual average exposure to PM2.5 and NO2 at European level kept increasing from the 1950s to a peak between the 1980s and the 1990s and showed a decrease until 2015 due to the implementation of a series of directives. It is also revealed that the exposure to both pollutants was affected by geographical location, gender and income level. The average annual exposure over the lifetime of an 80-year-old European to PM2.5 and NO2 amounted to 23.86 (95% CI: 2.95−81.86) and 13.49 (95% CI: 1.36−43.84) µg/m3. The application of this methodology provides valuable insights and novel tools for exposure modelling and environmental studies.

Specialty software and simplified models are often used to estimate migration of potentially toxic chemicals from packaging into food. Current models, however, are not suitable for emerging applications in decision-support tools, e.g. in Life Cycle Assessment and risk-based screening and prioritization, which require rapid computation of accurate estimates for diverse scenarios. To fulfil this need, we develop an accurate and rapid (high-throughput) model that estimates the fraction of organic chemicals migrating from polymeric packaging materials into foods. Several hundred step-wise simulations optimised the model coefficients to cover a range of user-defined scenarios (e.g. temperature). The developed model, operationalised in a spreadsheet for future dissemination, nearly instantaneously estimates chemical migration, and has improved performance over commonly used model simplifications. When using measured diffusion coefficients the model accurately predicted (R 2 = 0.9, standard error (S e ) = 0.5) hundreds of empirical data points for various scenarios. Diffusion coefficient modelling, which determines the speed of chemical transfer from package to food, was a major contributor to uncertainty and dramatically decreased model performance (R 2 = 0.4, S e = 1). In all, this study provides a rapid migration modelling approach to estimate exposure to chemicals in food packaging for emerging screening and prioritization approaches. [ABSTRACT FROM AUTHOR]

On June 1st, 2007 the European regulation on Registration, Evaluation and Restriction of Chemical substances (REACH) came into force. Aim of the regulation is safe use of chemicals for humans and for the environment. The core element of REACH is chemical safety assessment of chemicals and communication of health and safety hazards and risk management measures throughout the supply chain. Extended Safety Data Sheets (Ext-SDS) are the primary carriers of health and safety information. The aim of our project was to find out whether the actual exposure to methyl methacrylate (MMA) during the application of polymethylmethacrylate (PMMA) in floor coatings as assessed in the chemical safety assessment, reflect the exposure situations as observed in the Dutch building practice. Use of PMMA flooring and typical exposure situations during application were discussed with twelve representatives of floor laying companies. Representative situations for exposure measurements were designated on the basis of this inventory. Exposure to MMA was measured in the breathing zone of the workers at four construction sites, 14 full shift samples and 14 task based samples were taken by personal air sampling. The task-based samples were compared with estimates from the Targeted Risk Assessment Tool (v3.1) of the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC-TRA) as supplied in the safety assessment from the manufacturer. For task-based measurements, in 12 out of 14 (86%) air samples measured exposure was higher than estimated exposure. Recalculation with a lower ventilation rate (50% instead of 80%) together with a higher temperature during mixing (40°C instead of 20°C) in comparison with the CSR, reduced the number of underestimated exposures to 10 (71%) samples. Estimation with the EMKG-EXPO-Tool resulted in unsafe exposure situations for all scenarios, which is in accordance with the measurement outcomes. In indoor situations, 5 out of 8 full shift exposures (62%) to MMA were higher than the Dutch occupational exposure limit of 205mg/m3 (8h TWA), which equals the DNEL. For semi-enclosed situations this was 1 out of 6 (17%). Exposures varied from 31 to 367mg/m3. The results emphasize that ECETOC-TRA exposure estimates in poorly controlled situations need better underpinning. [ABSTRACT FROM AUTHOR]

Exposure to whole-body vibration (WBV) presents an occupational health risk and several safety standards obligate to measure WBV. The high cost of direct measurements in large epidemiological studies raises the question of the optimal sampling for estimating WBV exposures given by a large variation in exposure levels in real worksites. This paper presents a new approach to addressing this problem. A daily exposure to WBV was recorded for 9–24 days among 48 all-terrain vehicle drivers. Four data-sets based on root mean squared recordings were obtained from the measurement. The data were modelled using semi-variogram with spectrum analysis and the optimal sampling scheme was derived. The optimum sampling period was 140 min apart. The result was verified and validated in terms of its accuracy and statistical power. Recordings of two to three hours are probably needed to get a sufficiently unbiased daily WBV exposure estimate in real worksites. The developed model is general enough that is applicable to other cumulative exposures or biosignals. Practitioner Summary:Exposure to whole-body vibration (WBV) presents an occupational health risk and safety standards obligate to measure WBV. However, direct measurements can be expensive. This paper presents a new approach to addressing this problem. The developed model is general enough that is applicable to other cumulative exposures or biosignals. [ABSTRACT FROM PUBLISHER]

The use of exposure modelling tools for estimating chemical airborne exposure has increased since the European Union's REACH legislation for safe use of industrial chemicals came into force. Two tools that European Chemicals Agency recommends are Stoffenmanager® and the Advanced REACH Tool (ART). The aim of this study was to investigate the validity of these two exposure modelling tools by comparing the lack of agreement between estimated and measured exposure. We examined the airborne chemical exposure at companies in seven different types of industries: wood, printing, foundry, spray painting, four milling, chemical industry, and plastic moulding industry. The inhalable exposure of liquids or powders at two to three situations at each company was modelled with both tools and measured. To study the validity of the tools, the mean differences and precisions (lack of agreement) of exposures from both situations handling liquids and powders were calculated by using the 50th percentile outcome of the tools and the geometric mean of the measured exposure (all data were ln transformed). For Stoffenmanager, the mean difference and precision of the situations concerning liquids were 0.22 ± 1.0 and for powders -0.024 ± 0.66. It was also shown that Stoffenmanager overestimated low exposures and underestimated high exposures. Stoffenmanager showed higher agreement with the measured exposure in the wood and four mill industries than in foundry and the plastic moulding industry. For ART, the mean difference and precision of liquids were -0.55 ± 0.88 and for powders -1.4 ± 1.6. ART showed lower agreement with the measured exposure in the wood industry. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The study is focused on applying uncertainty and sensitivity analysis to support the application and evaluation of large exposure models where a significant number of parameters and complex exposure scenarios might be involved. The recently developed MERLIN-Expo exposure modelling tool was applied to probabilistically assess the ecological and human exposure to PCB 126 and 2,3,7,8-TCDD in the Venice lagoon (Italy). The ‘Phytoplankton’, ‘Aquatic Invertebrate’, ‘Fish’, ‘Human intake’ and PBPK models available in MERLIN-Expo library were integrated to create a specific food web to dynamically simulate bioaccumulation in various aquatic species and in the human body over individual lifetimes from 1932 until 1998. MERLIN-Expo is a high tier exposure modelling tool allowing propagation of uncertainty on the model predictions through Monte Carlo simulation. Uncertainty in model output can be further apportioned between parameters by applying built-in sensitivity analysis tools. In this study, uncertainty has been extensively addressed in the distribution functions to describe the data input and the effect on model results by applying sensitivity analysis techniques (screening Morris method, regression analysis, and variance-based method EFAST). In the exposure scenario developed for the Lagoon of Venice, the concentrations of 2,3,7,8-TCDD and PCB 126 in human blood turned out to be mainly influenced by a combination of parameters (half-lives of the chemicals, body weight variability, lipid fraction, food assimilation efficiency), physiological processes (uptake/elimination rates), environmental exposure concentrations (sediment, water, food) and eating behaviours (amount of food eaten). In conclusion, this case study demonstrated feasibility of MERLIN-Expo to be successfully employed in integrated, high tier exposure assessment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Quantitative microbial risk assessment (QMRA), the current method of choice for evaluating human health risks associated with disease-causing microorganisms, is often constrained by issues such as availability of required data, and inability to incorporate the multitude of factors influencing risk. Bayesian networks (BNs), with their ability to handle data paucity, combine quantitative and qualitative information including expert opinions, and ability to offer a systems approach to characterisation of complexity, are increasingly recognised as a powerful, flexible tool that overcomes these limitations. Objectives We present a QMRA expressed as a Bayesian network (BN) in a wastewater reuse context, with the objective of demonstrating the utility of the BN method in health risk assessments, particularly for evaluating a range of exposure and risk mitigation scenarios. As a case study, we examine the risk of norovirus infection associated with wastewater-irrigated lettuce. Methods A Bayesian network was developed following a QMRA approach, using published data, and reviewed by domain experts using a participatory process. Discussion Employment of a BN facilitated rapid scenario evaluations, risk minimisation, and predictive comparisons. The BN supported exploration of conditions required for optimal outcomes, as well as investigation of the effect on the reporting nodes of changes in ‘upstream’ conditions. A significant finding was the indication that if maximum post-treatment risk mitigation measures were implemented, there was a high probability (0.84) of a low risk of infection regardless of fluctuations in other variables, including norovirus concentration in treated wastewater. Conclusion BNs are useful in situations where insufficient empirical data exist to satisfy QMRA requirements and they are exceptionally suited to the integration of risk assessment and risk management in the QMRA context. They allow a comprehensive visual appraisal of major influences in exposure pathways, and rapid interactive risk assessment in multifaceted water reuse scenarios. [ABSTRACT FROM AUTHOR]