Dynamic and stationary monitoring of air pollutant exposures and dose during marathons.

Marathon running significantly increases breathing volumes and, consequently, air pollution inhalation doses. This is of special concern for elite athletes who ventilate at very high rates. However, race organizers and sport governing bodies have little guidance to support events scheduling to protect runners. A key limitation is the lack of hyper-local, high temporal resolution air quality data representative of exposure along the racecourse. This work aimed to understand the air pollution exposures and dose inhaled by athletes, by means of a dynamic monitoring methodology designed for road races. Air quality monitors were deployed during three marathons, monitoring nitrogen dioxide (NO2), ozone (O3), particulate matter (PMx), air temperature, and relative humidity. One fixed monitor was installed at the Start/Finish line and one mobile monitor followed the women elite runner pack. The data from the fixed monitors, deployed prior the race, described daily air pollution trends. Mobile monitors in combination with heatmap analysis facilitated the hyper-local characterization of athletes' exposures and helped identify local hotspots (e.g., areas prone to PM resuspension) which should be preferably bypassed. The estimation of inhaled doses disaggregated by gender and ventilation showed that doses inhaled by last finishers may be equal or higher than those inhaled by first finishers for O3 and PMx, due to longer exposures as well as the increase of these pollutants over time (e.g., 58.2 ± 9.6 and 72.1 ± 23.7 µg of PM2.5 for first and last man during Rome marathon). Similarly, men received significantly higher doses than women due to their higher ventilation rate, with differences of 31-114 µg for NO2, 79-232 µg for O3, and 6-41 µg for PMx. Finally, the aggregated data obtained during the 4 week- period prior the marathon can support better race scheduling by the organizers and provide actionable information to mitigate air pollution impacts on athletes' health and performance.

A Screening Approach to the Safe-and-Sustainable-by-Design Development of Advanced Insulation Materials.

Herein, a Safe-and-Sustainable-by-Design (SSbD) screening strategy on four different inorganic aerogel mats and two conventional mineral wools for ranking purposes is demonstrated. Given that they do not consist of particles, the release is first simulated, addressing three occupational exposure scenarios, realistic for their intended use as building insulators. No exposure to consumers nor to the environment is foreseen in the use phase, however, aerosols may be released during mat installation, posing an inhalation risk for workers. All four aerogel mats release more respirable dust than the benchmark materials and 60% thereof deposits in the alveolar region according to modelling tools. The collected aerogel dust allows for subsequent screening of hazard implications via two abiotic assays: 1) surface reactivity in human blood serum; 2) biodissolution kinetics in lung simulant fluids. Both aerogels and conventional insulators show similar surface reactivity. Differences in biodissolution are influenced by the specifically designed organic and inorganic structural modifications. Aerogel mats are better-performing insulators (2-fold lower thermal conductivity than the benchmark) However, this work demonstrates how investment decisions can be balanced with safety and sustainability aspects. Concepts of analogy and similarity thus support easily accessible methods to companies for safe and economically viable innovation with advanced materials.

Development of handling energy factors for use of dustiness data in exposure assessment modelling.

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

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.

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.

Workplace Exposure to Nanoparticles during Thermal Spraying of Ceramic Coatings.

Thermal spraying is widely used for industrial-scale application of ceramic coatings onto metallic surfaces. The particular process has implications for occupational health, as the high energy process generates high emissions of metal-bearing nanoparticles. Emissions and their impact on exposure were characterized during thermal spraying in a work environment, by monitoring size-resolved number and mass concentrations, lung-deposited surface area, particle morphology, and chemical composition. Along with exposure quantification, the modal analysis of the emissions assisted in distinguishing particles from different sources, while an inhalation model provided evidence regarding the potential deposition of particulate matter on human respiratory system. High particle number (>10(6) cm-3; 30-40 nm) and mass (60-600 µgPM1 m-3) concentrations were recorded inside the spraying booths, which impacted exposure in the worker area (10(4)-10(5) cm-3, 40-65 nm; 44-87 µgPM1 m-3). Irregularly-shaped, metal-containing particles (Ni, Cr, W) were sampled from the worker area, as single particles and aggregates (5-200 nm). Energy dispersive X-ray analysis confirmed the presence of particles originated from the coating material, establishing a direct link between the spraying activity and exposure. In particle number count, 90% of the particles were between 26-90 nm. Inhaled dose rates, calculated from the exposure levels, resulted in particle number rates (n˙) between 353 × 10(6)-1024 × 10(6) min-1, with 70% of deposition occurring in the alveolar region. The effectiveness of personal protective equipment (FPP3 masks) was tested under real working conditions. The proper sealing of the spraying booths was identified as a key element for exposure reduction. This study provides high time-resolved aerosol data which may be valuable for validating indoor aerosol models applied to risk assessment.

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.

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 ±â€¯0.19 and 0.84 ±â€¯0.12 for small and big bags, respectively, when using the one box model, and 0.88 ±â€¯0.25 and 0.82 ±â€¯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.

In vitro interaction of emerging contaminants with the cytochrome p450 system of Mediterranean deep-sea fish.

The interactions of emerging contaminants with the xenobiotic and endogenous metabolizing system of deep-sea fish were compared. The drugs diclofenac, fluoxetine, and gemfibrozil belong to different pharmaceutical classes with diverse mechanistic actions, and the personal care products triclosan, galaxolide, and nonylphenol are representative of antibacterial agents, nitro-musks, and surfactants, respectively. The fish compared are representative of the middle and lower slope of deep-sea habitats. The species were adults of Trachyrynchus scabrus, Mora moro, Cataetix laticeps, and Alepocehalus rostratus. The hepatic metabolic system studied were the activities associated with several cytochrome P450 isoforms (CYPs): 7-ethoxyresorufin-O-deethylase (EROD), benzyloxy-4-[trifluoromethyl]-coumarin-O-debenzyloxylase (BFCOD), and 7-ethoxycoumarin-O-deethylase (ECOD). Results showed differences in baseline activities and sensitivity to chemicals which were species, chemical, and pathway dependent. T. scabrous was the most sensitive species to chemical interactions with the xenobiotic and endogenous metabolizing (EROD and BFCOD) systems, especially in the case of diclofenac interference with BFCOD activity (IC50 = 15.7 ± 2.2 µM). Moreover, T. scabrous and A. rostratus possessed high basal ECOD activity, and this was greatly affected by in vitro exposure to diclofenac in T. scabrous also (IC50 = 6.86 ± 1.4 µM). These results highlight the sensitivity of marine fish to emerging contaminants and propose T. scabrous (middle slope) and A. rostratus (lower slope) as sentinels and the inclusion of ECOD activity as a sensitive biomarker to these exposures.