Size Distribution Of Emissions Research Articles

Analysis of gaseous emission and particle number size distributions in metal casting processes with binder jetting moulds

The impact on indoor air quality during metal casting processes using the 3D printing (3DP) binder jetting technique to manufacture moulds is analyzed in this research. This study investigates the particle size distribution and gas concentration during the manufacturing stages of 3DP moulds, with focus on particle deposition in the human respiratory system. The goal is to understand the risks associated with particle and gas emissions in binder jetting 3D printing, and thus improve worker safety. The results indicate that particle emission rates are lowest during printing (0.01 1011particles min−1) but increase during post-processing and melting-pouring phases (3.07 1011 particles min−1). During melting and pouring, the emission of particles was mainly in the range 7.9–71 nm, with values 10 times higher than in the previous phases. The study calculates the deposition of inhaled particles in different parts of the respiratory tract and reveals a 2.39 times higher extrathoracic mass deposition during 3DP mould manufacturing stages compared to melting-pouring stages. Additionally, alveolar mass deposition is higher during melting-pouring stages due to an increase in ultrafine emission rates. The study emphasizes the importance of insulation equipment and workplace ventilation in indoor spaces, particularly during heating processes that generate ultrafine particles through nucleation, so that health risks can be mitigated.

Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model

Abstract. In September 2020, a global aerosol forecasting model was implemented as an ensemble member of the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Ensemble Forecasting System (GEFS) v12.0.1 (hereafter referred to as “GEFS-Aerosols”). In this study, GEFS-Aerosols simulation results from 1 September 2019 to 30 September 2020 were evaluated using an aerosol budget analysis. These results were compared with results from other global models as well as reanalysis data. From this analysis, the global average lifetimes of black carbon (BC), organic carbon (OC), dust, sea salt, and sulfate are 4.06, 4.29, 4.59, 0.34, and 3.3 d, respectively, with the annual average loads of 0.14, 1.29, 4.52, 6.80, and 0.51 Tg. Compared with the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System–Goddard Chemistry Aerosol and Radiation Transport (GEOS4-GOCART) model, the aerosols in GEFS-Aerosols have a relatively short lifetime because of the faster removal processes in GEFS-Aerosols. Meanwhile, in GEFS-Aerosols, aerosol emissions are the determining factor for the mass and composition of aerosols in the atmosphere. The size (bin) distribution of aerosol emissions is as important as its total emissions, especially in simulations of dust and sea salt. Moreover, most importantly, the strong monthly and interannual variations in natural sources of aerosols in GEFS-Aerosols suggest that improving the accuracy of the prognostic concentrations of aerosols is important for applying aerosol feedback to weather and climate predictions.

The Role of Emission Size Distribution on the Efficacy of New Technologies to Reduce Methane Emissions from the Oil and Gas Sector.

Methane emissions from oil and gas operations exhibit skewed distributions. New technologies such as aerial-based leak detection surveys promise cost-effective detection of large emitters (greater than 10 kg/h). Recent policies such as the US Environmental Protection Agency (EPA) methane rule that allow the use of new technologies as part of leak detection and repair (LDAR) programs require a demonstration of equivalence with existing optical gas imaging (OGI) based LDAR programs. In this work, we illustrate the impact of emission size distribution on the equivalency condition between the OGI and site-wide survey technologies. Emission size distributions compiled from aerial measurements include significantly more emitters between 1 and 10 kg/h and lower average emission rates for large emitters compared to the emission distribution in the EPA rule. As a result, we find that equivalence may be achieved at lower site-wide survey frequencies when using technologies with detection thresholds below 10 kg/h, compared to the EPA rule. However, equivalence cannot be achieved with a detection threshold of 30 kg/h at any survey frequency, because most emitters across most US basins exhibit emission rates below 30 kg/h. We find that equivalence is a complex tradeoff among technology choice, design of LDAR programs, and survey frequency that can have more than one unique solution set.

Large Particle Emissions from Human Vocalization and Playing of Wind Instruments.

Humans emit large salivary particles when talking, singing, and playing musical instruments, which have implications for respiratory disease transmission. Yet little work has been done to characterize the emission rates and size distributions of such particles. This work characterized large particle (dp > 35 μm in aerodynamic diameter) emissions from 70 volunteers of varying age and sex while vocalizing and playing wind instruments. Mitigation efficacies for face masks (while singing) and bell covers (while playing instruments) were also examined. Geometric mean particle count emission rates varied from 3.8 min-1 (geometric standard deviation [GSD] = 3.1) for brass instruments playing to 95.1 min-1 (GSD = 3.8) for talking. On average, talking produced the highest emission rates for large particles, in terms of both number and mass, followed by singing and then instrument playing. Neither age, sex, CO2 emissions, nor loudness (average dBA) were significant predictors of large particle emissions, contrary to previous findings for smaller particle sizes (i.e., for dp < 35 μm). Size distributions were similar between talking and singing (count median diameter = 53.0 μm, GSD = 1.69). Bell covers did not affect large particle emissions from most wind instruments, but face masks reduced large particle count emissions for singing by 92.5% (95% CI: 97.9%, 73.7%).

Modeling atmospheric microplastic cycle by GEOS-Chem: An optimized estimation by a global dataset suggests likely 50 times lower ocean emissions

Modeling atmospheric microplastic cycle by GEOS-Chem: An optimized estimation by a global dataset suggests likely 50 times lower ocean emissions

Current Knowledge and Challenges of Particle Size Measurements of Mainstream E-Cigarette Aerosols and Their Implication on Respiratory Dosimetry

The E-cigarette has been promoted as an alternative nicotine delivery device with potentially fewer toxicant emissions. The objective of this review is to summarize the current knowledge on the particle size distribution (PSD) of e-cigarette emissions and to analyze the knowledge gaps between existing particle size measurements and the vision toward harm reduction from e-cigarette use. Here, we focus on firstly describing the physical parameters used to characterize PSD, followed by comparing particle size measurement approaches, investigating the factors that impact the PSD of e-cigarette mainstream aerosols, and conclude by linking size distribution to the respiratory dosimetry by demonstrating the modeling results of particle deposition in the respiratory tract. This review calls for a harmonized testing protocol to conduct inter-comparisons and further understand e-cigarette particle sizes. Among the influencing factors investigated, puff topography, operation power, flavorings, PG/VG ratio, and nicotine strength impose a substantial impact on the PSD, but the underlying mechanisms have not yet been fully investigated. The effects brought by the type of device refill and nicotine are yet inconclusive due to lack of evidence. Coil aging has no significant impact on the PSD of e-cigarette aerosols within the coil lifetime. Lastly, while computational models of particle deposition have been adopted to profile the deposition of e-cigarette mainstream emissions, existing models have limited applicability and generality when dealing with e-cigarette aerosols that have high volatility and hygroscopicity, which can dynamically evaporate or grow during the transport process. Additionally, the size-dependent chemical composition (e.g., nicotine and harmful and potentially harmful constituents) of e-cigarette aerosols is unknown, impeding the understanding of the health effects of e-cigarette use. Therefore, it is essential for future studies to bridge these knowledge gaps and unveil the mechanisms determining PSD and respiratory deposition.

DNA-templated copper nanocluster: A robust and universal fluorescence switch for bleomycin assay

Bleomycin (BLM) is widely utilized for cancer treatment due to the outstanding antitumor activity, but BLM with imprecisely controlled dosage may lead to lethal consequences. It is thus a profound task to accurately monitor the BLM levels in clinical settings. Herein, we propose a straightforward, convenient, and sensitive sensing method for BLM assay. Poly-T DNA-templated copper nanoclusters (CuNCs) are fabricated with strong fluorescence emission and uniform size distribution and served as fluorescence indicators for BLM. The high binding affinity of BLM for Cu2+makes it able to inhibit fluorescence signals generated from CuNCs. This is the underlying mechanism rarely explored and can be utilized for effective BLM detection. A detection limit of 0.27 μM (according to 3σ/s rule) is achieved in this work. And the precision, producibility, and practical useability are also confirmed with satisfactory results. Furthermore, the accuracy of the method is verified by high-performance liquid chromatography (HPLC). To sum up, the established strategy in this work exhibits the advantages of convenience, rapidness, low cost, and high precision. The construction of BLM biosensors is important to achieve the best therapeutic effect with minimal toxicity, which opens a new avenue for monitoring antitumor drugs in clinical settings.

Emission rates, size distributions, and generation mechanism of oral respiratory droplets

Emission rates, size distributions, and generation mechanism of oral respiratory droplets

Emission dynamics of tire and road contact particles emitted at the rear of the wheel of a passenger vehicle using on-road experiments on different routes

The study of tire and road contact particles (TRCP) include all particles that are (re)emitted behind the wheel, including wear, re-cycled and re-suspended particles. For instance, some TRCPs would consist of wear particles mixed with mineral and/or organic dust deposited on the road or freshly emitted particles/gazes (e.g. from the braking system, exhaust, etc.). In our case, an analytical platform was developed and mounted on an instrumented vehicle to monitor TRCP emissions under real traffic conditions. TRCP measurements were taken at the rear of the front wheel and the on-board computers gave access to nearly sixty engine and vehicle variables. In total, five campaigns were carried out on highway, beltway, urban, suburban and rural roads. This paper presents the dynamics and size distribution of TRCP emissions as a function of the areas crossed and driving speed.

Reducing particle emissions of heavy-duty diesel vehicles in India: Combined effects of diesel, biodiesel and lubricating oil

Diesel engines contribute significantly to deteriorating air quality. Tightening legislation has led to various technological advances, but developments differ between countries. In India, air quality has not improved and fine particle (PM2.5) related premature deaths are predicted to increase. In this study, we characterized the particle emissions of an Indian-manufactured BS IV (Bharat Stage, comparable to Euro emission standards) heavy-duty diesel vehicle and studied the effects of different fuels, fuel blends and lubricating oils. The main aims of the study were to investigate the particle emission dependency on fuel types and fuel blends used in India and to produce useful data for further use (e.g. legislative parties and modeling): emission factors (PN, PM, BC, other chemical compounds), size distributions and volatility of particles. Additionally, the sensitivity of the emissions to the lubricating oil choice was studied. Two lubricating oils, two fossil fuels conforming to BS IV and BS VI emission standards and two biofuel – BS IV fossil fuel blends were tested, one containing Renewable Paraffinic Diesel (RPD) and the other renewable Fatty Acid Methyl Ester (r-FAME). The tests were conducted on a chassis dynamometer (Delhi Bus Driving Cycle, DBDC). Our results show that the emitted particles were in ultrafine particle size range, and both the soot mode particles and smaller nanoparticles were affected by fuels and lubricating oils. The transition from BS IV grade diesel to BSVI was shown to have potential in reducing particle emissions (PN and eBC) of heavy-duty diesel vehicles in India. Blending fossil fuel with biofuel strongly affected particle number emissions, chemical composition, and eBC emissions and the emissions were highly sensitive to biofuel type. Changing the lubricating oil had a comparable magnitude of effect as changing the fuel and the results indicate that in order to reduce particle emissions, a combination of fuel and lubricating oil should be chosen, instead of choosing them separately.

Comparison of particle number size distribution trends in ground measurements and climate models

Abstract. Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol–cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.

Ultrafine particle number concentration and its size distribution during Diwali festival in megacity Delhi, India: Are 'green crackers' safe?

Since the air pollution and noise generated from fireworks are related to air quality and human health, the regulatory bodies had implemented the eco-friendly "Green Crackers" in megacity Delhi, India, to celebrate Diwali 2019 with the permission of a specific time slot (8:00 p.m. to 10:00 p.m.). The present study was conducted on a residential educational institute campus to evaluate the particle number size distribution (PNSD) of green cracker emissions. During the Diwali event period, the high peak of particle number concentration (PNC) reached 1.7×105 # cm-3 with a geometric mean diameter (GMD) of ∼44nm. The average PNC increment on Diwali day was 138% and 97% compared to pre (October 26, 2019) and post (October 28, 2019) Diwali period, respectively, including 468%, 142%, 65%, 75% on pre-Diwali and 485%, 110%, 32%, 26% on post- Diwali 2019 period in terms of Nucleation mode (10nm<Dp<20nm), Small Aitken mode (20nm<Dp<50nm), Large Aitken mode (50nm<Dp<100nm), and Accumulation mode (100nm<Dp<1000nm), respectively. Unlike traditional firework emissions, green crackers had a high UFP/Ntotal ratio of 0.72, including Nucleation mode-0.35, Aitken mode-0.30, and Accumulation mode 0.35, distinguishing it from other pre-and post-Diwali particle number size distribution-dN/dlogDp curves. These observations indicate that green crackers emit more particles with smaller diameters than traditional crackers. Recommendations for using green crackers for Diwali celebrations may be an option if lower size-diameter particle emission could be controlled by changing the material composition of the green crackers. More research studies need to be conducted to assess atmospheric emissions of green crackers and their health impacts to evaluate whether they are better or worse than traditional crackers.

Influence of emission size distribution and nucleation on number concentrations over Greater Paris

Abstract. With the growing evidence that high particle number concentrations may impact health, modelling their emissions and understanding formation processes is necessary, especially in cities where many people are exposed. As emission inventories of particle numbers and size distribution over cities are usually not available, a methodology is defined to estimate them from PM2.5 emissions and ratios of PM1 / PM2.5 and PM0.1 / PM2.5 by activity sector. In this methodology, a fitting parameter αem is used to redistribute the number concentrations in the lowest emission diameter range. This parameter is chosen by comparing measured and simulated number concentrations during non-nucleation days. The emission size distribution is then finely discretised by conserving both mass and number in each of the size ranges where emissions are specified. The methodology is applied over Greater Paris during the MEGAPOLI campaign (July 2009). Three-dimensional simulations are performed using the chemistry transport model Polair3D/Polyphemus coupled to the aerosol module SSH-aerosol to represent the evolution of particles by condensation, evaporation, coagulation, and nucleation, with a sectional approach for the size distribution. The model is first compared to measurements during non-nucleation days, and the influence over the month of July 2009 of three different nucleation parameterisations is assessed, i.e. binary (sulfuric acid, water), ternary (sulfuric acid, ammonia, water), and heteromolecular (extremely low-volatility organic compounds (ELVOCs) from monoterpenes and sulfuric acid). The modelled number concentrations compare very well to measurements, with an average normalised mean error of 42 % for the daily number concentrations of particles larger than 10 nm and 37 % for the number concentrations of particles larger than 100 nm. The influence of the binary nucleation is low, and the ternary nucleation scheme leads to better simulated number concentrations (in terms of bias and error) at only one site out of three, but it systematically reduces the model to measurement correlation, suggesting that ternary nucleation may not be the dominant process in new particle formation. However, the relative bias and error, as well as the correlation at suburban sites, are systematically improved using the heteromolecular nucleation scheme involving sulfuric acid and ELVOCs from monoterpenes. This suggests that heteromolecular nucleation may be important in cities, especially at suburban sites in summer, and that a better characterisation of the emissions of ELVOC precursors from traffic is needed.

A prediction model of emission characteristics of oil particles induced by milling process: Emission rate and size distribution

The use of metalworking fluids (MWFs) in the milling process can cause emissions of a large amount of oil particles, which can induce respiratory and immune system diseases of workers. This work examined the emission characteristics of oil particles caused by the milling process. A closed test chamber containing a real milling machine was built. The emission rates of oil particles in various sizes using five kinds of MWFs were measured, and the influence of the rotation speed of the spindle in the milling machine and the physical properties of MWFs on the oil particle emission characteristics was analysed. In addition, a prediction model of emission rate and size distribution of oil particles was introduced. Based on the measured data of oil particle emission rates in each size, the morphological particle size, distribution index and atomization coefficient in the prediction model are fitted. The deviation between the predicted and measured values of the emission rates is about 5%, which confirms the accuracy of the model. The prediction model is helpful for pollution control and ventilation strategy formulation in typical machining plants.

Size Distribution of Mineral Dust Emissions From Sparsely Vegetated and Supply‐Limited Dryland Soils

AbstractControls on the particle size distribution (PSD) of mineral dust emissions remain poorly understood. Under near‐idealized conditions, dust PSDs can appear invariant with wind friction velocity. However, dryland vegetation attenuates surface friction velocities, and soil crusting reduces the supply of loose erodible material and increases surface resistance to abrasion. Under such conditions, variability in saltation bombardment efficiency and intensity could have a large effect on dust PSDs. We present dust emission measurements from vegetated, supply‐limited aeolian systems that indicate the dependence of emission‐flux PSD on wind friction velocity. We find the fine fraction (&lt;5 μm) of dust particles increases with friction velocity. Results suggest models that assume wind‐invariance of the emission‐flux PSD may not be generalizable for crusted soils with vegetation. There is a need for dust models to represent variability in emission‐flux PSDs for land management, air quality, and climate applications across vegetated and sediment supply‐limited drylands.

Size-resolved aerosol emissions from lignocellulosic biomass and biomass constituent pyrolysis under variable dilution temperatures

Biomass burning events produce significant amounts of particulate matter which influence global radiative forcing, decrease air quality and visibility, and have negative health impacts. The quantity, size distribution, and volatility of biomass burning aerosol emissions are influenced by the combustion mode and ensuing dilution process of the emissions mixing into ambient air. This work examined the emissions from lignocellulosic biomass and its major constituents under laboratory pyrolysis conditions to understand biomass composition and dilution temperature influences on aerosol formation. The major constituents of lignocellulosic biomass, hemicellulose (xylan), cellulose and lignin, were pyrolyzed and the resultant aerosol emissions were characterized in terms of size-resolved number and mass emission factors under variable dilution temperatures. The aerosol emissions formed from biomass constituents were then compared to those of pine and corn stover, and a summative model for predicting characteristics of biomass burning emissions from the behavior of individual constituents was assessed. Results showed a significant influence of dilution temperature on particle size, number, and distribution, with the nucleation mode of particle formation dominating. The summative model performed well in predicting particle number formation from lignocellulosic biomass, but highlighted the effect of uncertainty on predicting particle mass formation.

Airborne Aerosols and Human Health: Leapfrogging from Mass Concentration to Oxidative Potential

The mass concentration of atmospheric particulate matter (PM) has been systematically used in epidemiological studies as an indicator of exposure to air pollutants, connecting PM concentrations with a wide variety of human health effects. However, these effects can be hardly explained by using one single parameter, especially because PM is formed by a complex mixture of chemicals. Current research has shown that many of these adverse health effects can be derived from the oxidative stress caused by the deposition of PM in the lungs. The oxidative potential (OP) of the PM, related to the presence of transition metals and organic compounds that can induce the production of reactive oxygen and nitrogen species (ROS/RNS), could be a parameter to evaluate these effects. Therefore, estimating the OP of atmospheric PM would allow us to evaluate and integrate the toxic potential of PM into a unique parameter, which is related to emission sources, size distribution and/or chemical composition. However, the association between PM and particle-induced toxicity is still largely unknown. In this commentary article, we analyze how this new paradigm could help to deal with some unanswered questions related to the impact of atmospheric PM over human health.

Investigation of the effects of split-injection on particle emissions from a Dieseline CI engine

Premixed compression ignition (PCI) combustion techniques utilising low cetane-number (<40) fuels are associated with low engine-out oxides of nitrogen (NOx) and soot emissions. However, fuel-air over-mixing and high combustion noise at low and high engine loads, respectively, have been the challenges with PCI. Fuel split-injection can effectively govern the fuel-air mixing process and subsequently control combustion and emissions characteristics; it is of interest to characterise particle emissions under these PCI conditions. In this study, the effects of double-injection of low-cetane G75-Dieseline (75% gasoline in diesel based on volume) on controlling charge premixing and consequently size distribution of particle emissions were investigated in a production light-duty 4-cylinder CI engine. First injection-quantity ratio was varied from 10% to 50% while using different injection timings at engine loads from 1.4 to 12 bar BMEP and speed of 1800 RPM. Brake specific emissions results were compared to diesel baselines to quantify particles concentration reduction while maintaining the same range of NOx and brake thermal efficiency (BTE). G75 combustion emitted lower number and mass of particles (in all size classes) by up to 99.9% and generally lower NOx by up to 65% compared to diesel. Negligible particle number and mass emissions (as low as 1.91 × 1012 parts/kWh and 138 µg/kWh respectively) were measured for G75 at low-medium loads (3–6 bar BMEP). In the absence of two-stage combustion, the timing of second-injection controlled the combustion-phasing effectively. Lower first injection-quantity ratios (e.g. 10%) are recommended for overall high BTE and low gaseous and particle emissions.

Toward "On-Demand" Materials Synthesis and Scientific Discovery through Intelligent Robots.

A Materials Acceleration Operation System (MAOS) is designed, with unique language and compiler architecture. MAOS integrates with virtual reality (VR), collaborative robots, and a reinforcement learning (RL) scheme for autonomous materials synthesis, properties investigations, and self‐optimized quality assurance. After training through VR, MAOS can work independently for labor and intensively reduces the time cost. Under the RL framework, MAOS also inspires the improved nucleation theory, and feedback for the optimal strategy, which can satisfy the demand on both of the CdSe quantum dots (QDs) emission wavelength and size distribution quality. Moreover, it can work well for extensive coverages of inorganic nanomaterials. MAOS frees the experimental researchers out of the tedious labor as well as the extensive exploration of optimal reaction conditions. This work provides a walking example for the “On‐Demand” materials synthesis system, and demonstrates how artificial intelligence technology can reshape traditional materials science research in the future.

Impact of dust emissions from the silicon production on working conditions

Metallurgical enterprises are one of the largest sources of dust emissions. Dust is the main air pollutant in the working area and is formed in all areas where the metal production process is carried out. Thus, up to 900 kg of dust is formed in the production of 1 ton of silicon. Inhalation of such dust by workers of the foundry can contribute to the development of a number of dangerous respiratory diseases. Therefore, the aim of this paper was to study the dust waste of the silicon production and to analyze the working conditions of employees of the given enterprise in order to develop measures to reduce the dust load and improve the working conditions. The article also presents the results of studies of the particle size distribution of dust emissions in the silicon production. Using the X-ray phase analysis method, it was shown that the dust of the silicon production mainly consisted of amorphous silica, as well as silicon and carborundum. According to the results of the chemical analysis, it was found that this type of waste contained on average 86% of the valuable SiO2 component. The particle-size analysis of the composition of gas cleaning dust from the silicon production showed that there were particles in the dust ranging in size from 0.1 to 600 µm. Most particles had a size of -50.00 + 100.00 µm. Particles of this size are easily inhaled by the operating personnel and quickly penetrate into the lungs and affect the lung tissue. During the assessment of the working conditions of the silicon enterprise by this factor, it has been found that all workplaces of the electrothermal department have hazardous conditions and correspond to the class of working conditions 3.2, and the allowable work period under these conditions is 6 years. The analysis of the above data shows that gas cleaning dust of the silicon production contains a significant amount of the valuable SiO2 component, and the volumes formed allow this material to be used as a silica-containing raw material. Therefore, in order to effectively solve environmental problems and improve the working conditions of silicon production workers, it is necessary to develop innovative technologies for recycling fine silica-containing waste and other methods for their disposal.