Evaluation of the well mixed room and near-field far-field models in occupational settings

Estimating airborne trichloramine levels in indoor swimming pools using the well-mixed box model

Exposure to airborne disinfection by-products, especially trichloramine (TCA), could cause various occupational health effects in indoor swimming pools. However, TCA concentration measurements involve specialized analysis conducted in specific laboratories, which can result in significant costs and time constraints. As an alternative, modeling techniques for estimating exposures are promising in addressing these challenges. This study aims to predict airborne TCA concentrations in indoor swimming pools using a mathematical model, the well-mixed box model, found in the IHMOD tool, freely available on the American Industrial Hygiene Association website. The model's predictions are compared with TCA concentrations measured during various bather load scenarios. The research involved conducting 2-hr successive workplace measurements over 16- to 18-hr periods in four indoor swimming pools in Quebec, Canada. TCA concentrations were estimated using the well-mixed box model, assuming a homogeneous mixing of air within the swimming pool environment. A novel approach was developed to estimate the TCA generation rate from swimming pool water, incorporating the number of swimmers in the model. Average measured concentrations of TCA were 0.24, 0.26, 0.14, and 0.34 mg/m3 for swimming pools 1, 2, 3, and 4, respectively. The ratio of these measured average concentrations to their corresponding predicted values ranged from 0.51 to 1.30, 0.67 to 1.04, 0.57 to 1.14, and 0.68 to 1.49 for the respective swimming pools. In a worst-case scenario simulating the swimming pool at full capacity (maximum bathers allowed), TCA concentrations were estimated as 0.23, 0.36, 0.14, and 0.37 mg/m3 for swimming pools 1, 2, 3, and 4. Recalculated concentrations by adjusting the number of swimmers so as not to exceed the recommended occupational limit concentration of 0.35 mg/m3 gives a maximum number of swimmers of 63 and 335 instead of currently 80 and 424 for swimming pools 2 and 4, respectively. Similarly, for swimming pools 1 and 3, the maximum number of swimmers could be 173 and 398 (instead of the current 160 and 225, respectively). These results demonstrated that the model could be used to estimate and anticipate airborne TCA levels in indoor swimming pools across various scenarios.

Use of the dustiness index in combination with the handling energy factor for exposure modelling of nanomaterials

The use of modelling tools in the occupational hygiene community has increased in the last years to comply with the different existing regulations. However, limitations still exist mainly due to the difficulty to obtain certain key parameters such as the emission rate, which in the case of powder handling can be estimated using the dustiness index (DI). The goal of this work is to explore the applicability and usability of the DI for emission source characterization and occupational exposure prediction to particles during nanomaterial powder handling. Modelling of occupational exposure concentrations of 13 case scenarios was performed using a two-box model as well as three nano-specific tools (Stoffenmanager nano, NanoSafer and GUIDEnano). The improvement of modelling performance by using a derived handling energy factor (H) was explored. Results show the usability of the DI for emission source characterization and respirable mass exposure modelling of powder handling scenarios of nanomaterials. A clear improvement in modelling outcome was obtained when using derived quartile-3 H factors with, 1) Pearson correlations of 0.88 vs. 0.52 (not using H), and 2) ratio of modelled/measured concentrations ranging from 0.9 to 10 in 75% cases vs. 16.7% of the cases when not using H. Particle number concentrations were generally underpredicted. Using the most conservative H values, predictions with ratios modelled/measured concentrations of 0.4-3.6 were obtained.

Accuracy of professional judgments for dermal exposure assessment using deterministic models

The accuracy of exposure judgments, particularly for scenarios where only qualitative information is available or a systematic approach is not used, has been evaluated and shown to have a relatively low level of accuracy. This is particularly true for dermal exposures, where less information is generally available compared to inhalation exposures. Relatively few quantitative validation efforts have been performed for scenarios where dermal exposures are of interest. In this study, a series of dermal exposure judgments were collected from 90 volunteer U.S. occupational health practitioners in a workshop format to assess the accuracy of their judgments for three specific scenarios. Accuracy was defined as the ability of the participants to identify the correct reference exposure category, as defined by the quantitative exposure banding categories utilized by the American Industrial Hygiene Association (AIHA^®). The participants received progressively additional information and training regarding dermal exposure assessments and scenario-specific information during the workshop, and the relative accuracy of their category judgments over time was compared. The results of the study indicated that despite substantial education and training in exposure assessment generally, the practitioners had very little experience in performing dermal exposure assessments and a low level of comfort in performing these assessments. Further, contrary to studies of practitioners performing inhalation exposure assessments demonstrating a trend toward underestimating exposures, participants in this study consistently overestimated the potential for dermal exposure without quantitative data specific to the scenario of interest. Finally, it was found that participants were able to identify the reference or "true" category of dermal exposure acceptability when provided with relevant, scenario-specific dermal and/or surface-loading data for use in the assessment process. These results support the need for additional training and education of practitioners in performing dermal exposure assessments. A closer analysis of default loading values used in dermal exposure assessments to evaluate their accuracy relative to real-world or measured dermal loading values, along with consistent improvements in current dermal models, is also needed.

Estimating evaporation rates and contaminant air concentrations due to small spills of non-ideal aqueous organic solvent mixtures in a controlled environment

Although small spills of non-ideal organic solvent mixtures are ubiquitous undesirable events in occupational settings, the potential risk of exposure associated with such scenarios remains insufficiently investigated. This study aimed to examine the impact of non-ideality on evaporation rates and contaminant air concentrations resulting from small spills of organic solvent mixtures. Evaporation rate constants alphas (α) were experimentally measured for five pure solvents using a gravimetric approach during solvent evaporation tests designed to simulate small spills of solvents. Two equations were used for estimating contaminants' evaporation rates from aqueous mixtures assuming either ideal or non-ideal behavior based on the pure-chemical alpha values. A spill model also known as the well-mixed room model with exponentially decreasing emission rate was used to predict air concentrations during various spill scenarios based on the two sets of estimated evaporation rates. Model predictive performance was evaluated by comparing the estimates against real-time concentrations measured for the same scenarios. Evaluations for 12 binary non-ideal aqueous mixtures found that the estimated evaporation rates accounting for the correction by the activity coefficients of the solvents (median = 0.0318 min^-1) were higher than the evaporation rates estimated without the correction factor (median = 0.00632 min^-1). Model estimates using the corrected evaporation rates reasonably agreed with the measured values, with a median predicted peak concentrations-to-measured peak concentrations ratio of 0.92 (0.81 to 1.32) and a median difference between the predicted and the measured peak times of -5 min. By contrast, when the non-corrected evaporation rates were used, the median predicted peak concentrations-to-measured peak concentrations ratio was 0.31 (0.08 to 0.75) and the median difference between the predicted and the measured peak times was +33 min. Results from this study demonstrate the importance of considering the non-ideality effect for accurately estimating evaporation rates and contaminant air concentrations generated by solvent mixtures. Moreover, this study is a step further in improving knowledge of modeling exposures related to small spills of organic solvent mixtures.

A New Model Algorithm for Estimating the Inhalation Exposure Resulting from the Spraying of (Semi)-Volatile Binary Liquid Mixtures (SprayEva)

The spraying of liquid multicomponent mixtures is common in many professional and industrial settings. Typical examples are cleaning agents, additives, coatings, and biocidal products. In all of these examples, hazardous substances can be released in the form of aerosols or vapours. For occupational and consumer risk assessment in regulatory contexts, it is therefore important to know the exposure which results from the amount of chemicals in the surrounding air. In this research, a mechanistic mass balance model has been developed that covers the spraying of (semi)-volatile substances, taking into account combined exposure to spray mist, evaporation from droplets, and evaporation from surfaces as well as the nonideal behaviour of components in liquids and backpressure effects. For wall-spraying scenarios, an impaction module has been developed that quantifies the amount of overspray and the amount of material that lands on the wall. Mechanistically, the model is based on the assumption that continuous spraying can be approximated by a number of sequentially released spray pulses, each characterized by a certain droplet size, where the total aerosol exposure is obtained by summation over all release pulses. The corresponding system of differential equations is solved numerically using an extended Euler algorithm that is based on a discretisation of time and space. Since workers typically apply the product continuously, the treated area and the corresponding evaporating surface area grows over time. Time-dependent concentration gradients within the sprayed liquid films that may result from different volatilities of the components are therefore addressed by the proposed model. A worked example is presented to illustrate the calculated exposure for a scenario where aqueous solutions of H2O2 are sprayed onto surfaces as a biocidal product. The results reveal that exposure to H2O2 aerosol reaches relevant concentrations only during the spraying phase. Evaporation from sprayed surfaces takes place over much longer time periods, where backpressure effects caused by large emission sources can influence the shape of the concentration time curves significantly. The influence of the activity coefficients is not so pronounced. To test the plausibility of the developed model algorithm, a comparison of model estimates of SprayExpo, SprayEva, and ConsExpo with measured data is performed. Although the comparison is based on a limited number (N = 19) of measurement data, the results are nevertheless regarded as supportive and acceptable for the plausibility and predictive power of SprayEva.

Modeling Clothing as a Vector for Transporting Airborne Particles and Pathogens across Indoor Microenvironments

Evidence suggests that human exposure to airborne particles and associated contaminants, including respiratory pathogens, can persist beyond a single microenvironment. By accumulating such contaminants from air, clothing may function as a transport vector and source of "secondary exposure". To investigate this function, a novel microenvironmental exposure modeling framework (ABICAM) was developed. This framework was applied to a para-occupational exposure scenario involving the deposition of viable SARS-CoV-2 in respiratory particles (0.5-20 μm) from a primary source onto clothing in a nonhealthcare setting and subsequent resuspension and secondary exposure in a car and home. Variability was assessed through Monte Carlo simulations. The total volume of infectious particles on the occupant's clothing immediately after work was 4800 μm³ (5th-95th percentiles: 870-32 000 μm³). This value was 61% (5-95%: 17-300%) of the occupant's primary inhalation exposure in the workplace while unmasked. By arrival at the occupant's home after a car commute, relatively rapid viral inactivation on cotton clothing had reduced the infectious volume on clothing by 80% (5-95%: 26-99%). Secondary inhalation exposure (after work) was low in the absence of close proximity and physical contact with contaminated clothing. In comparison, the average primary inhalation exposure in the workplace was higher by about 2-3 orders of magnitude. It remains theoretically possible that resuspension and physical contact with contaminated clothing can occasionally transmit SARS-CoV-2 between humans.

Estimating Inhalation Exposure Resulting from Evaporation of Volatile Multicomponent Mixtures Using Different Modelling Approaches

In many professional and industrial settings, liquid multicomponent mixtures are used as solvents, additives, coatings, biocidal products, etc. Since, in all of these examples, hazardous liquids can evaporate in the form of vapours, for risk assessments it is important to know the amount of chemicals in the surrounding air. Although several models are available in legal contexts, the current implementations seem to be unable to correctly simulate concentration changes that actually occur in volatile mixtures and in particular in thin films. In this research, the estimation of evaporation rates is based on models that take into account non-ideal behaviour of components in liquids and backpressure effects as well. The corresponding system of differential equations is solved numerically using an extended Euler algorithm that is based on a discretisation of time and space. Regarding air dispersion of volatile components, the model builds upon one-box and two-box mass balance models, because there is some evidence that these models, when selected and applied appropriately, can predict occupational exposures with sufficient precision. That way, numerical solutions for a wide variety of exposure scenarios with instantaneous and continuous/intermittent application, even considering “moving worker situations”, can be obtained. A number of example calculations have been carried out on scenarios where binary aqueous solutions of hydrogen peroxide or glutaraldehyde are applied as a biocidal product to surfaces by wiping. The results reveal that backpressure effects caused by large emission sources as well as deviations from liquid-phase ideality can influence the shape of the concentration time curves significantly. The results also provide some evidence that near-/far-field models should be used to avoid underestimation of exposure in large rooms when small/medium areas are applied. However, the near-field/far-field model should not be used to estimate peak exposure assuming instantaneous application, because then the models tend to overestimate peak exposure significantly. Although the example calculations are restricted to aqueous binary mixtures, the proposed approach is general and can be used for arbitrary liquid multicomponent mixtures, as long as backpressure effects and liquid-phase non-idealities are addressed adequately.

Theoretical Background of Occupational-Exposure Models-Report of an Expert Workshop of the ISES Europe Working Group "Exposure Models"

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.

Estimation of Airborne Vapor Concentrations of Oil Dispersants COREXIT™ EC9527A and EC9500A, Volatile Components Associated with the Deepwater Horizon Oil Spill Response and Clean-up Operations

The Deepwater Horizon (DWH) drilling unit explosion above the Macondo oil well on 20 April 2010 caused the release of approximately 4.9 million barrels (779 million L) of oil into the Gulf of Mexico. As part of a larger spill response and clean-up effort, approximately 1.84 million gallons (6.81 million L) of chemical dispersants COREXIT™ EC9500A and COREXIT™ EC9527A were applied to the resultant oil slicks through spraying on the water surface by plane and by vessel and through injection at the release source near the seabed. The GuLF STUDY is investigating the health effects of workers involved in the oil spill response and clean-up after the DWH explosion, and estimates of possible exposure to chemical dispersants were needed. Exposures were estimated to the volatile components of COREXIT™ EC9500A [petroleum distillates, hydrotreated light, and propylene glycol (PG)] and of COREXIT™ EC9527A [2-butoxyethanol (2-BE) and PG] using two of AIHA IHMOD2.0© mathematical modeling tools along with the dispersants' chemical and physical properties. Monte Carlo simulations were used to reflect uncertainty in input parameters with both the two-box, constant emission model and the near and mid field plume model for indoor and outdoor activities, respectively. Possible exposure scenarios considered various evaporation rates, sizes of the dispersant pool, wind speeds, and ventilation rates. For the two-box model, mean near field exposure estimates to 2-BE ranged from 0.9 to 5.7 ppm, while mean far field estimated exposures ranged from 0.3 to 3.5 ppm. Estimates of mean near field plume model exposures ranged from 0.01 to 3.7 ppm at 2.5 ft from the source, and <0.01 to 0.3 ppm at 10 ft from the source. Estimated exposures to PG were approximately 10% of the calculated 2-BE exposures and exposures to petroleum distillates about 40% higher than the 2-BE estimates. Results indicate that compared with current occupational exposure guidelines, overexposure to petroleum distillates and PG probably did not occur in our study, but under some conditions, for short periods, exposure to 2-BE may have exceeded the limits for peak exposures. These estimates were developed for use in job-exposure matrices to estimate exposures of workers having contact with dispersant vapors for the GuLF STUDY.

Modeling occupational exposure to solvent vapors using the Two-Zone (near-field/far-field) model: a literature review

The Two-Zone model is used in occupational hygiene to predict both near-field and far-field airborne contaminant concentrations. A literature review was carried out on 21 scientific publications in which the Two-Zone model was used to assess occupational exposure to solvent vapors. Data on exposure scenarios, solvents, generation/emission rates, near- and far-field parameters, and model performance were collected and analyzed. Over the 24 exposure scenarios identified, 18 were evaluated under controlled conditions, 5 under normal workplace activities, and 1 was reported based on literature data. The scenarios involved a variety of tasks which consisted, mostly, of cleaning metal parts, spraying solvents onto surfaces, spilling liquids, and filling containers with volatile substances. Twenty-eight different solvents were modeled and the most commonly tested were benzene, toluene, and acetone. Emission rates were considered constant in 16 scenarios, exponentially decreasing in 6 scenarios, and intermittent in 2 scenarios. Four-hundred-and-forty-six (446) predicted-to-measured concentration ratios were calculated across the 21 studies; 441 were obtained in controlled conditions, 4 under normal workplace activities, and 1 was calculated based on the literature data. For controlled studies, the Two-Zone model predictive performance was within a factor of 0.3-3.7 times the measured concentrations with 93% of the values between 0.5 and 2. The model overestimated the measured concentrations in 63% of the evaluations. The median predicted concentration for the near-field was 1.38 vs. 1.02 for the far-field. Results suggest that the model might be a useful tool for predicting occupational exposure to vapors of solvents by providing a conservative approach. Harmonization in model testing strategies and data presentation is needed in future studies to improve the assessment of the predictability of the Two-Zone model. Moreover, this review has provided a database of exposure scenarios, input parameter values, and model predictive performances which can be useful to occupational hygienists in their future modeling activities.

Oxygen deficiency hazard in confined spaces in the steel industry: assessment through predictive models

Objective. In the steel industry, performing activities in confined spaces where potential oxygen displacement can occur may expose workers to fatal consequences. To the best of our knowledge, no quantitative exposure assessment of oxygen deficiency in steel industry confined spaces is available in the literature. To overcome this gap, we performed oxygen deficiency hazard (ODH) assessments in real confined spaces using two existing models to identify the most critical parameters responsible for ODH, and suggest controls for mitigating the asphyxiation risk. Methods. We applied a well-mixed model and a near field-far field approach to estimate the indoor oxygen level with time during and following release of simple asphyxiants. Model inputs were mainly gathered thanks to audits and instrumental tests in three firms. Results. The most severe ODH exposures are posed in spaces with restricted volume and where accidental releases of inert gases can occur. Such exposures can be controlled through early release detections and augmented reality systems. Conclusions. ODH assessments in confined spaces of steel firms allow the identification of the most critical parameters from an oxygen depletion perspective, focusing on which data need careful measurement, and help to establish controls compatible with the operations conducted in these areas.

Indoor dispersion of airborne nano and fine particles: Main factors affecting spatial and temporal distribution in the frame of exposure modeling

A particle exposure experiment inside a large climate-controlled chamber was conducted. Data on spatial and temporal distribution of nanoscale and fine aerosols in the range of mobility diameters 8-600 nm were collected with high resolution, for sodium chloride, fluorescein sodium, and silica particles. Exposure scenarios studied included constant and intermittent source emissions, different aggregation conditions, high (10 h^-1 ) and low (3.5 h^-1 ) air exchange rates (AERs) corresponding to chamber Reynolds number, respectively, equal to 1 × 10⁵ and 3 × 10⁴ . Results are presented and analyzed to highlight the main determinants of exposure and to determine whether the assumptions underlying two-box models hold under various scenarios. The main determinants of exposure found were the source generation rate and the ventilation rate. The effect of particles nature was indiscernible, and the decrease of airborne total number concentrations attributable to surface deposition was estimated lower than 2% when the source was active. A near-field/far-field structure of aerosol concentration was always observed for the AER = 10 h^-1 but for AER = 3.5 h^-1 , a single-field structure was found. The particle size distribution was always homogeneous in space but a general shift of particle diameter (-8% to +16%) was observed between scenarios in correlation with the AER and with the source position, presumably largely attributable to aggregation.

Source specific exposure and risk assessment for indoor aerosols

Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their environmental and human health impact. The emission sources should be stored in terms of relevant metrics and statistics in an easily accessible format that is applicable for source specific exposure assessment by using mathematical mass balance modelings. This forms a foundation for comprehensive risk assessment and efficient interventions. For such a general exposure assessment model we need 1) systematic methods for indoor aerosol emission source assessment, 2) source emission documentation in terms of relevant a) aerosol metrics and b) biological metrics, 3) default model parameterization for predictive exposure modeling, 4) other needs related to aerosol characterization techniques and modeling methods. Such a general exposure assessment model can be applicable for private, public, and occupational indoor exposure assessment, making it a valuable tool for public health professionals, product safety designers, industrial hygienists, building scientists, and environmental consultants working in the field of IAQ and health.

Interzonal airflow rates for use in near-field far-field workplace concentration modeling

Interzonal air flow rates (β) for a workspace above a table were measured in 12 indoor air spaces using an experimental apparatus simulating a vapor release into an occupied near zone. The near field was modeled as a 0.32 m³ rectangular cube volume 0.60 m high above the 0.60 m × 0.90 m table. A total of 74 experimental measurements of β were made. The apparatus consisted of photoionization detectors measuring concentrations of acetone around an evaporating liquid surface with a robot arm simulating worker motion in the near field. The vapor release rate and the resulting concentrations were used in a near-field far-field (NF-FF) model to calculate β. Measures of mixing within the near-field supported the assumption of the NF-FF model that the near field is well-mixed. Measured values of β ranged from 0.4-19 m³/min with an average of 4.8 m³/min. This corresponds to 1.2-59 air changes per minute in the near field and an average of 15 air changes per minute. The values of β were log normally distributed with a geometric mean of 3.4 m³/min and a geometric standard deviation of 2.3. The 95% confidence interval on the geometric mean of β was 2.8-4.2 m³/min. The product of the random air speed in the room and one half of the near-field free surface area was shown to be a good method of determining β. There was a slight correlation seen between room volume and β, but the effect size was small. Room air change rate was not found to be correlated with β. The observed distribution of β will be helpful in selecting values for interzonal airflow rate in NF-FF modeling of worker exposures.