Testing the near field/far field model performance for prediction of particulate matter emissions in a paint factory

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.

Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale

One- and two-box models have been pointed out as useful tools for modelling indoor particle exposure. However, model performance still needs further testing if they are to be implemented as trustworthy tools for exposure assessment. The objective of this work is to evaluate the performance, applicability and reproducibility of one- and two-box models on real-world industrial scenarios. A study on filling of seven materials in three filling lines with different levels of energy and mitigation strategies was used. Inhalable and respirable mass concentrations were calculated with one- and two-box models. The continuous drop and rotating drum methods were used for emission rate calculation, and ranges from a one-at-a-time methodology were applied for local exhaust ventilation efficiency and inter-zonal air flows. When using both dustiness methods, large differences were observed for modelled inhalable concentrations but not for respirable, which showed the importance to study the linkage between dustiness and processes. Higher model accuracy (ratio modelled vs. measured concentrations 0.5-5) was obtained for the two- (87%) than the one-box model (53%). Large effects on modelled concentrations were seen when local exhausts ventilation and inter-zonal variations where parametrized in the models. However, a certain degree of variation (10-20%) seems acceptable, as similar conclusions are reached.

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool

STOFFENMANAGER^® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER^® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER^® and ART are based on a modified multiplicative model where an exposure base level (mg m⁻³) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m⁻³) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER^® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER^® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER^® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER^® and ART. A literature review showed that the models have been validated only at the ‘operational analysis’ level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER^® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson’s correlations (r is <0.6) for both STOFFENMANAGER^® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER^® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.

Assessment of exposure determinants and exposure levels by using stationary concentration measurements and a probabilistic near-field/far-field exposure model

Background: The Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation requires the establishment of Conditions of Use (CoU) for all exposure scenarios to ensure good communication of safe working practices. Setting CoU requires the risk assessment of all relevant Contributing Scenarios (CSs) in the exposure scenario. A new CS has to be created whenever an Operational Condition (OC) is changed, resulting in an excessive number of exposure assessments. An efficient solution is to quantify OC concentrations and to identify reasonable worst-case scenarios with probabilistic exposure modeling. Methods: Here, we appoint CoU for powder pouring during the industrial manufacturing of a paint batch by quantifying OC exposure levels and exposure determinants. The quantification was performed by using stationary measurements and a probabilistic Near-Field/Far-Field (NF/FF) exposure model. Work shift and OC concentration levels were quantified for pouring TiO 2 from big bags and small bags, pouring Micro Mica from small bags, and cleaning. The impact of exposure determinants on NF concentration level was quantified by (1) assessing exposure determinants correlation with the NF exposure level and (2) by performing simulations with different OCs. Results: Emission rate, air mixing between NF and FF and local ventilation were the most relevant exposure determinants affecting NF concentrations. Potentially risky OCs were identified by performing Reasonable Worst Case (RWC) simulations and by comparing the exposure 95 th percentile distribution with 10% of the occupational exposure limit value (OELV). The CS was shown safe except in RWC scenario (ventilation rate from 0.4 to 1.6 1/h, 100 m 3 room, no local ventilation, and NF ventilation of 1.6 m 3/min). Conclusions: The CoU assessment was considered to comply with European Chemicals Agency (ECHA) legislation and EN 689 exposure assessment strategy for testing compliance with OEL values. One RWC scenario would require measurements since the exposure level was 12.5% of the OELV.

Particle Resuspension Dynamics in the Infant Near-Floor Microenvironment

Carpet dust contains microbial and chemical material that can impact early childhood health. Infants may be exposed to greater quantities of resuspended dust, given their close proximity to floor surfaces. Chamber experiments with a robotic infant were integrated with a material balance model to provide new fundamental insights into the size-dependency of infant crawling-induced particle resuspension and exposure. The robotic infant was exposed to resuspended particle concentrations from 10⁵ to 10⁶ m^-3 in the near-floor (NF) microzone during crawling, with concentrations generally decreasing following vacuum cleaning of the carpets. A pronounced vertical variation in particle concentrations was observed between the NF microzone and bulk air. Resuspension fractions for crawling are similar to those for adult walking, with values ranging from 10^-6 to 10^-1 and increasing with particle size. Meaningful amounts of dust are resuspended during crawling, with emission rates of 0.1 to 2 × 10⁴ μg h^-1. Size-resolved inhalation intake fractions ranged from 5 to 8 × 10³ inhaled particles per million resuspended particles, demonstrating that a significant fraction of resuspended particles can be inhaled. A new exposure metric, the dust-to-breathing zone transport efficiency, was introduced to characterize the overall probability of a settled particle being resuspended and delivered to the respiratory airways. Values ranged from less than 0.1 to over 200 inhaled particles per million settled particles, increased with particle size, and varied by over 2 orders of magnitude among 12 carpet types.

Occupational Exposure and Environmental Release: The Case Study of Pouring TiO2 and Filler Materials for Paint Production

Pulmonary exposure to micro- and nanoscaled particles has been widely linked to adverse health effects and high concentrations of respirable particles are expected to occur within and around many industrial settings. In this study, a field-measurement campaign was performed at an industrial manufacturer, during the production of paints. Spatial and personal measurements were conducted and results were used to estimate the mass flows in the facility and the airborne particle release to the outdoor environment. Airborne particle number concentration (1 × 10³–1.0 × 10⁴ cm⁻³), respirable mass (0.06–0.6 mg m⁻³), and PM₁₀ (0.3–6.5 mg m⁻³) were measured during pouring activities. In overall; emissions from pouring activities were found to be dominated by coarser particles >300 nm. Even though the raw materials were not identified as nanomaterials by the manufacturers, handling of TiO₂ and clays resulted in release of nanometric particles to both workplace air and outdoor environment, which was confirmed by TEM analysis of indoor and stack emission samples. During the measurement period, none of the existing exposure limits in force were exceeded. Particle release to the outdoor environment varied from 6 to 20 g ton⁻¹ at concentrations between 0.6 and 9.7 mg m⁻³ of total suspended dust depending on the powder. The estimated release of TiO₂ to outdoors was 0.9 kg per year. Particle release to the environment is not expected to cause any major impact due to atmospheric dilution

On the Relationship between Exposure to Particles and Dustiness during Handling of Powders in Industrial Settings

Exposure to ceramic powders, which is frequent during handling operations, is known to cause adverse health effects. Finding proxy parameters to quantify exposure is useful for efficient and timely exposure assessments. Worker exposure during handling of five materials [a silica sand (SI1), three quartzes (Q1, Q2, and Q3), and a kaolin (K1)] with different particle shape (prismatic and platy) and sizes (3.4-120 µm) was assessed. Materials handling was simulated using a dry pendular mill under two different energy settings (low and high). Three repetitions of two kilos of material were carried out per material and energy conditions with a flow rate of 8-11 kg h-1. The performance of the dustiness index as a predictor of worker exposure was evaluated correlating material's dustiness indexes (with rotating drum and continuous drop) with exposure concentrations. Significant impacts on worker exposure in terms of inhalable and respirable mass fractions were detected for all materials. Mean inhalable mass concentrations during background were always lower than 40 µg m-3 whereas during material handling under high energy settings mean concentrations were 187, 373, 243, 156, and 430 µg m-3 for SI1, Q1, Q2, Q3, and K1, respectively. Impacts were not significant with regard to particle number concentration: background particle number concentrations ranged between 10 620 and 46 421 cm-3 while during handling under high energy settings they were 20 880 - 40 498 cm-3. Mean lung deposited surface area during background ranged between 27 and 101 μm2 cm-3 whereas it ranged between 22 and 42 μm2 cm-3 during materials handling. TEM images evidenced the presence of nanoparticles (≤100 nm) in the form of aggregates (300 nm-1 µm) in the worker area, and a slight reduction on mean particle size during handling was detected. Dustiness and exposure concentrations showed a high degree of correlation (R2 = 0.77-0.97) for the materials and operating conditions assessed, suggesting that dustiness could be considered a relevant predictor for workplace exposure. Nevertheless, the relationship between dustiness and exposure is complex and should be assessed for each process, taking into account not only material behaviour but also energy settings and workplace characteristics.

Toward Rigorous Materials Production: New Approach Methodologies Have Extensive Potential to Improve Current Safety Assessment Practices

Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high-throughput and high-content screening assays, dose-response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer-by-design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation.

The Impacts of Moisture and Ultraviolet Light on the Degradation of Graphene Oxide/Polymer Nanocomposites

The extent to which hydrophilic GO nanofillers regulate polymer degradation during exposure to a combination of ultraviolet (UV) radiation and moisture is presently unknown. Accordingly, this study systematically evaluated the effect of GO on polymer degradability under both humid UV and dry UV conditions. Both GO accumulation at the polymer nanocomposite (PNC) surface and GO release following degradation were also investigated. Different mass loadings of GO were incorporated into waterborne polyurethane (WBPU), a commonly used exterior coating, and the resulting GO/WBPU nanocomposites were exposed to precisely controlled accelerated weathering conditions using the NIST Simulated Photodegradation via High Energy Radiant Exposure (SPHERE) device. Thickness loss and infrared spectroscopy measurements indicated GO slightly improved the durability of WBPU under dry UV conditions but not under humid UV conditions. Raman spectroscopy, scanning electron microscopy, and atomic force microscopy modulus measurements indicated that GO accumulation occurred at and near the PNC surface under both conditions but to a more rapid extent under humid UV conditions. Minimal GO release occurred under dry UV conditions as measured with Raman spectroscopy of aqueous run-off from a simulated rain spray applied to degraded PNCs. In contrast, PNC surface transformations under humid UV conditions suggested that GO release occurred.

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.

Health risk assessment from exposure to particles during packing in working environments

Packing of raw materials in work environments is a known source of potential health impacts (respiratory, cardiovascular) due to exposure to airborne particles. This activity was selected to test different exposure and risk assessment tools, aiming to understand the effectiveness of source enclosure as a strategy to mitigate particle release. Worker exposure to particle mass and number concentrations was monitored during packing of 7 ceramic materials in 3 packing lines in different settings, with low (L), medium (M) and high (H) degrees of source enclosure. Results showed that packing lines L and M significantly increased exposure concentrations (119-609 μg m^-3 respirable, 1150-4705 μg m^-3 inhalable, 24,755-51,645 cm^-3 particle number), while non-significant increases were detected in line H. These results evidence the effectiveness of source enclosure as a mitigation strategy, in the case of packing of ceramic materials. Total deposited particle surface area during packing ranged between 5.4 and 11.8 × 10⁵ μm² min^-1, with particles depositing mainly in the alveoli (51-64%) followed by head airways (27-41%) and trachea bronchi (7-10%). The comparison between the results from different risk assessment tools (Stoffenmanager, ART, NanoSafer) and the actual measured exposure concentrations evidenced that all of the tools overestimated exposure concentrations, by factors of 1.5-8. Further research is necessary to bridge the current gap between measured and modelled health risk assessments.

Modeling of High Nanoparticle Exposure in an Indoor Industrial Scenario with a One-Box Model

Mass balance models have proved to be effective tools for exposure prediction in occupational settings. However, they are still not extensively tested in real-world scenarios, or for particle number concentrations. An industrial scenario characterized by high emissions of unintentionally-generated nanoparticles (NP) was selected to assess the performance of a one-box model. Worker exposure to NPs due to thermal spraying was monitored, and two methods were used to calculate emission rates: the convolution theorem, and the cyclic steady state equation. Monitored concentrations ranged between 4.2 × 104-2.5 × 105 cm-3. Estimated emission rates were comparable with both methods: 1.4 × 1011-1.2 × 1013 min-1 (convolution) and 1.3 × 1012-1.4 × 1013 min-1 (cyclic steady state). Modeled concentrations were 1.4-6 × 104 cm-3 (convolution) and 1.7-7.1 × 104 cm-3 (cyclic steady state). Results indicated a clear underestimation of measured particle concentrations, with ratios modeled/measured between 0.2-0.7. While both model parametrizations provided similar results on average, using convolution emission rates improved performance on a case-by-case basis. Thus, using cyclic steady state emission rates would be advisable for preliminary risk assessment, while for more precise results, the convolution theorem would be a better option. Results show that one-box models may be useful tools for preliminary risk assessment in occupational settings when room air is well mixed.

Testing the performance of one and two box models as tools for risk assessment of particle exposure during packing of inorganic fertilizer

Modelling of particle exposure is a useful tool for preliminary exposure assessment in workplaces with low and high exposure concentrations. However, actual exposure measurements are needed to assess models reliability. Worker exposure was monitored during packing of an inorganic granulate fertilizer at industrial scale using small and big bags. Particle concentrations were modelled with one and two box models, where the emission source was estimated with the fertilizer's dustiness index. The exposure levels were used to calculate inhaled dose rates and test accuracy of the exposure modellings. The particle number concentrations were measured from worker area by using a mobility and optical particle sizer which were used to calculate surface area and mass concentrations. The concentrations in the worker area during pre-activity ranged 63,797-81,073 cm^-3, 4.6 × 10⁶ to 7.5 × 10⁶ μm² cm^-3, and 354 to 634 μg m^-3 (respirable mass fraction) and during packing 50,300 to 85,949 cm^-3, 4.3 × 10⁶ to 7.6 × 10⁶ μm² cm^-3, and 279 to 668 μg m^-3 (respirable mass fraction). Thus, the packing process did not significantly increase the exposure levels. Chemical exposure was also under control based on REACH standards. The particle surface area deposition rate in respiratory tract was up to 7.6 × 10⁶ μm² min^-1 during packing, with 52%-61% of deposition occurring in the alveolar region. Ratios of the modelled and measured concentrations were 0.98 ± 0.19 and 0.84 ± 0.12 for small and big bags, respectively, when using the one box model, and 0.88 ± 0.25 and 0.82 ± 0.12, when using the two box model. The modelling precision improved for both models when outdoor particle concentrations were included. This study shows that exposure concentrations in a low emission industrial scenario, e.g. during packing of a fertilizer, can be predicted with a reasonable accuracy by using the concept of dustiness and mass balance models.

The general ventilation multipliers calculated by using a standard Near-Field/Far-Field model

In conceptual exposure models, the transmission of pollutants in an imperfectly mixed room is usually described with general ventilation multipliers. This is the approach used in the Advanced REACH Tool (ART) and Stoffenmanager® exposure assessment tools. The multipliers used in these tools were reported by Cherrie (1999; http://dx.doi.org/10.1080/104732299302530 ) and Cherrie et al. (2011; http://dx.doi.org/10.1093/annhyg/mer092 ) who developed them by positing input values for a standard Near-Field/Far-Field (NF/FF) model and then calculating concentration ratios between NF and FF concentrations. This study revisited the calculations that produce the multipliers used in ART and Stoffenmanager and found that the recalculated general ventilation multipliers were up to 2.8 times (280%) higher than the values reported by Cherrie (1999) and the recalculated NF and FF multipliers for 1-hr exposure were up to 1.2 times (17%) smaller and for 8-hr exposure up to 1.7 times (41%) smaller than the values reported by Cherrie et al. (2011). Considering that Stoffenmanager and the ART are classified as higher-tier regulatory exposure assessment tools, the errors is general ventilation multipliers should not be ignored. We recommend revising the general ventilation multipliers. A better solution is to integrate the NF/FF model to Stoffenmanager and the ART.

Particle emission rates during electrostatic spray deposition of TiO2 nanoparticle-based photoactive coating

Here, we studied the particle release rate during Electrostatic spray deposition of anatase-(TiO₂)-based photoactive coating onto tiles and wallpaper using a commercially available electrostatic spray device. Spraying was performed in a 20.3m³ test chamber while measuring concentrations of 5.6nm to 31μm-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 1.9×10¹⁰s^-1 and the mean mass emission rate was 381μgs^-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 15h^-1 for <1μm-size and the deposited particles consisted of mainly TiO₂, TiO₂ mixed with Cl and/or Ag, TiO₂ particles coated with carbon, and Ag particles with size ranging from 60nm to ca. 5μm. As expected, no significant VOC emissions were observed as a result of spraying. Finally, we provide recommendations for exposure model parameterization.

Probabilistic risk assessment of emerging materials: case study of titanium dioxide nanoparticles

The development and use of emerging technologies such as nanomaterials can provide both benefits and risks to society. Emerging materials may promise to bring many technological advantages but may not be well characterized in terms of their production volumes, magnitude of emissions, behaviour in the environment and effects on living organisms. This uncertainty can present challenges to scientists developing these materials and persons responsible for defining and measuring their adverse impacts. Human health risk assessment is a method of identifying the intrinsic hazard of and quantifying the dose-response relationship and exposure to a chemical, to finally determine the estimation of risk. Commonly applied deterministic approaches may not sufficiently estimate and communicate the likelihood of risks from emerging technologies whose uncertainty is large. Probabilistic approaches allow for parameters in the risk assessment process to be defined by distributions instead of single deterministic values whose uncertainty could undermine the value of the assessment. A probabilistic approach was applied to the dose-response and exposure assessment of a case study involving the production of nanoparticles of titanium dioxide in seven different exposure scenarios. Only one exposure scenario showed a statistically significant level of risk. In the latter case, this involved dumping high volumes of nano-TiO₂ powders into an open vessel with no personal protection equipment. The probabilistic approach not only provided the likelihood of but also the major contributing factors to the estimated risk (e.g. emission potential).

Exposure to airborne particles and volatile organic compounds from polyurethane molding, spray painting, lacquering, and gluing in a workshop

Due to the health risk related to occupational air pollution exposure, we assessed concentrations and identified sources of particles and volatile organic compounds (VOCs) in a handcraft workshop producing fishing lures. The work processes in the site included polyurethane molding, spray painting, lacquering, and gluing. We measured total VOC (TVOC) concentrations and particle size distributions at three locations representing the various phases of the manufacturing and assembly process. The mean working-hour TVOC concentrations in three locations studied were 41, 37, and 24 ppm according to photo-ionization detector measurements. The mean working-hour particle number concentration varied between locations from 3000 to 36,000 cm⁻³. Analysis of temporal and spatial variations of TVOC concentrations revealed that there were at least four substantial VOC sources: spray gluing, mold-release agent spraying, continuous evaporation from various lacquer and paint containers, and either spray painting or lacquering (probably both). The mold-release agent spray was indirectly also a major source of ultrafine particles. The workers’ exposure can be reduced by improving the local exhaust ventilation at the known sources and by increasing the ventilation rate in the area with the continuous source.