Particle size distribution: A key factor in estimating powder dustiness.

A wide variety of raw materials, involving more than 20 samples of quartzes, feldspars, nephelines, carbonates, dolomites, sands, zircons, and alumina, were selected and characterised. Dustiness, i.e., a materials' tendency to generate dust on handling, was determined using the continuous drop method. These raw materials were selected to encompass a wide range of particle sizes (1.6-294 µm) and true densities (2650-4680 kg/m3). The dustiness of the raw materials, i.e., their tendency to generate dust on handling, was determined using the continuous drop method. The influence of some key material parameters (particle size distribution, flowability, and specific surface area) on dustiness was assessed. In this regard, dustiness was found to be significantly affected by particle size distribution. Data analysis enabled development of a model for predicting the dustiness of the studied materials, assuming that dustiness depended on the particle fraction susceptible to emission and on the bulk material's susceptibility to release these particles. On the one hand, the developed model allows the dustiness mechanisms to be better understood. In this regard, it may be noted that relative emission increased with mean particle size. However, this did not necessarily imply that dustiness did, because dustiness also depended on the fraction of particles susceptible to be emitted. On the other hand, the developed model enables dustiness to be estimated using just the particle size distribution data. The quality of the fits was quite good and the fact that only particle size distribution data are needed facilitates industrial application, since these data are usually known by raw materials managers, thus making additional tests unnecessary. This model may therefore be deemed a key tool in drawing up efficient preventive and/or corrective measures to reduce dust emissions during bulk powder processing, both inside and outside industrial facilities. It is recommended, however, to use the developed model only if particle size, true density, moisture content, and shape lie within the studied ranges.

Evaluation of the Dustiness of Different Kaolin Samples.

Several samples of kaolin with different mean particle size were prepared and tested using the continuous drop method, one of the reference test methods according to standard EN 15051:2006 "Workplace atmospheres - Measurement of the dustiness of bulk materials - Requirements and reference test methods." On the other hand, with a view to relating the dustiness of the materials to their properties, particle size distribution, specific surface area, and Hausner ratio of these samples were determined. This article presents a characterization of these samples and an assessment of the influence of some material parameters on dustiness. The results show that dustiness may significantly be affected by mean particle size, specific surface area, and Hausner ratio. Moreover, it is highlighted that a detailed study of the influence of fine particles content on the dustiness was carried out. This information is deemed essential for establishing the most efficient preventive and/or corrective measures to reduce the generation of fugitive emissions of particulate matter during kaolin processing, both into the outside atmosphere (air pollution) and inside the facilities (occupational health).

Size-resolved chemical composition and toxicity of particles released from refit operations in shipyards.

Ship refit and repair operations in shipyards generate aerosol emissions with high potential for environmental impacts. Metal-bearing nano-, fine and coarse particles are incidentally formed and can be released to indoor and ambient air and the aquatic environment. This work aimed to further the understanding of these impacts by characterising particle size-resolved chemical composition (15 nm - 10 µm), organophosphate esters (OPEs) content (e.g., plasticisers) and cytotoxic and genotoxic potential. Results showed that nanoparticle emissions (20-110 nm) took place in bursts, coinciding with the use of mechanical abraders and spray-painting guns. Tracers of these activities were Sc, V, Cr, Co, Ni, Cu, Rb, Nb, and Cs. Key components were V and Cu, probably sourcing from nanoadditives in the coatings. Abrasion of coatings also emitted OPEs, especially from old paints. Toxicity assessments consistently evidenced hazardous potential for the different endpoints assessed, for a number of samples. Exposures to spray-painting aerosols were linked with reduced cell viability (cytotoxicity), significant generation of reactive oxygen species (ROS), and increases in micronuclei frequency (genotoxicity). Even though spray-painting did not contribute significantly to aerosol mass or number concentrations, it was a major driver of potential health effects. Results suggest that aerosol chemical composition (e.g., content in nano-sized Cu or V) may have a larger impact on toxicity than aerosol concentration. While direct human exposures may be prevented using personal and collective protective equipment and environmental release can be minimised by enclosures and filtration systems, impacts on ambient air and the aquatic environment cannot be fully prevented. The continued use of good practices (exhaust, dilution, general ventilation systems, PPE, already in place) is encouraged to reduce inhalation exposures inside the tents. Understanding the size-resolved chemical and toxicological properties of aerosols is key to reducing human health and environmental impacts of ship refit operations in shipyards.

Channeled PM10, PM2.5 and PM1 Emission Factors Associated with the Ceramic Process and Abatement Technologies.

A sampling methodology and a mathematical data treatment were developed that enable to determine not only total suspended particulates (TSP) emitted at channeled sources but also the PM10, PM2.5, and PM1 mass fractions (w10, w2.5, and w1) and emission factors (E.F.), using a seven-stage cascade impactor. Moreover, a chemical analysis was performed to identify the elements present in these emissions. The proposed methodology was applied to different stages of the ceramic process, including ambient temperature (milling, shaping, glazing) and medium-high-temperature (spray-drying, drying, firing, and frit melting) stages. In total, more than 100 measurements were performed (pilot scale and industrial scale), which leads to a measurement time of 1500 h. Related to the mass fractions, in general, the mean values of w10 after the fabric filters operated at high performance are high and with little dispersion (75-85%), and it is also observed that they are practically independent of the stage considered, i.e., they are not significantly dependent on the initial PSD of the stream to be treated. In the case of the fine fraction w2.5, the behavior is more complex (w2.5: 30-60%), probably because the only variable is not the cleaning system, but also the nature of the processed material. Regarding abatement measures, the use of high-efficiency cleaning systems considerably reduces the emission factors obtained for fractions PM10, PM2.5, and PM1. In reference to chemical analysis, the presence of ZrO2 and Ni in the spray-drying and pressing stages, the significant concentration of ZrO2 in the glazing stage, the presence of Pb, As, and Zn in the firing stage, and the presence of Zn, Pb, Cd, and As compounds in the frits manufacturing should all be highlighted. Nevertheless, it should be pointed out that the use of some compounds, such as cadmium and lead, has been very limited in the last years and, therefore, presumably, the presence of these elements in the emissions should have been also reduced in the same way.

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.

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.

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.