Search Results (309)

With the continuous promotion of the dual carbon target, effective control of high-concentration dust pollutants in industrial sites is of great value for the healthy creation of healthy industrial environments and efficient energy utilization. In this study, we used the spraying method to improve and prepare the dust removal material, polyphenylene sulfide (PPS) fiber filter material, and test the filtration performance, resistance characteristics, and dust-cleaning effect of the improved rGO-PPS material. The results showed that, compared with PPS filter material, rGO-PPS material significantly improved particle filtration efficiency, with a filtration efficiency 0.058–19.417% higher in the particle size range of 0.265–5.75 μm. The higher the spraying concentration of the composite filter material, the higher the filtration efficiency at the same particle size. The comprehensive filtration performance of rGO-PPS composite filter material with a concentration of 3 g/L was better, as it better met the requirements of “high efficiency and low resistance”. With an increase in dust load, the filtration resistance of the filter material showed a continuous upward trend. The dust peeling rate increased with an increase in blowback wind speed. When the blowback wind speed reached 0.3 m/s, the dust-cleaning effect of the filter material tended to stabilize. Under this condition, the dust peeling rate of PPS filter material was 61.58%, and the dust peeling rate of 3 g/L rGO-PPS composite filter material reached 74.52%. These research results provide an experimental basis and technical support for the development and engineering application of high-efficiency purification filter materials for industrial multi-source pollutants. Full article

This study presents the development and numerical investigation of a full-section fog curtain dust suppression system installed in the return airway of a fully mechanized longwall mining face, designed to mitigate airborne dust emissions escaping from the return airway during coal extraction. To optimize nozzle selection, comparative experiments were conducted under varying water pressure conditions. A porous medium model was employed to represent the dust capture mesh, enabling a systematic analysis of the pressure drop and airflow resistance characteristics across a range of wind velocities; the model parameters—viscous resistance coefficient (D) and inertial resistance coefficient (C₂)—were calibrated accordingly. Subsequently, coupled computational fluid dynamics simulations of fog dispersion and airflow fields were performed using a validated full-scale geometric model of the fully mechanized mining face. The influence of mesh pore size—via its effect on droplet size distribution uniformity—on the spatial distribution and velocity profile of the airflow field was quantitatively evaluated. The results show that the optimal spray nozzle was the fan-shaped atomizing spray nozzle, with a selected water pressure of 0.6 MPa. The droplet concentration in the porous media section increased from 0.026 kg∙m⁻³ to 0.052 kg∙m⁻³, and the volume share increased from 51.5% to 74.5%. The concentration of the filtered droplet increased from 0.00067 kg∙m⁻³ to 0.0013 kg∙m⁻³, and the size of particles adsorbed by the porous media increased from 140 μm in the proportion of most particles to 0.0013 kg∙m⁻³. The proportion of most particles above 140 μm was reduced to a range of 0–80 μm, and the optimal pore size was selected to be 100 mesh. Dust measurements were conducted at different measuring points in the return airway of the 25212 comprehensive mining face in the Hongliulin North plate area. The overall dust removal rates at points A, B, and C reached 88.90%, 83.71%, and 84.85%, and the respiratory dust removal rates reached 81.24%, 79.39%, and 80.33%, respectively, indicating that dust removal is effective. Full article

Fine particulate matter PM_2.5 continues to pose a critical public health risk in Northern Thailand, particularly in Chiang Mai, where traditional filtration methods often face limitations in cost and efficiency for large-scale applications. This study introduces a novel “Evaporator Condensation Growth Particle Scrubber (ECGP)” designed to enhance the collection efficiency of sub-micron particles by enlarging their physical size through a pressure-driven growth mechanism. The ECGP system utilizes synergistic effects between solid nuclei, high relative humidity, and mechanical pressure modulation. The ECGP system integrates solid nuclei, ~95% relative humidity and mechanical pressure modulation within a single chamber. Using incense smoke as a PM surrogate, the process utilizes controlled adiabatic cycles to induce stable heterogeneous condensation. The results indicate that the integrated process effectively shifts particle size distribution, reducing the PM_2.5/PM₁₀ mass ratio from 1.00 to 0.83. This indicates that approximately 17.5% (with a standard deviation < 1% across 10 trials, p < 0.05) of the fine mass successfully transitioned into the larger, more filterable PM₁₀ fraction and exhibited high physical stability and resistance to re-evaporation, effectively overcoming the low-efficiency threshold (typically <10%) of standard mechanical scrubbers and cyclones for sub-micron dust. This study concludes that ECGP technology offers a promising, cost-effective alternative for improving indoor air quality in large public infrastructures by leveraging particle inertia for enhanced removal, providing a scalable solution to the persistent smog crisis. Full article

The herbal tea industry has experienced substantial growth, particularly regarding green tea (Camellia sinensis). In the manufacturing of filter tea, fine herbal dust is generated as a residual by-product during grinding and sieving and is typically discarded as waste. This study aims to explore the application of ultrasound-assisted extraction (UAE) for secondary valorisation of green tea herbal dust by investigating the effects of various parameters on extraction efficiency. Antiradical activity of UAE extracts was determined using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, and the total phenolic content (TPC) was measured using Folin–Ciocalteu’s assay. Furthermore, selected phenolics were quantified by HPLC and qualitatively characterised by liquid chromatography coupled with electrospray ionisation and quadrupole time-of-flight tandem mass spectrometry (LC-ESI-QToF-MS/MS). The results demonstrate that UAE parameters have a pronounced influence on the antioxidant activity, TPC, and individual polyphenolic profile of green tea herbal dust extracts. Ethanol–water mixtures at a ratio of around 40–60%, as well as moderate impulse regimes (around 60%) and extraction times (around 10 min), were the most suitable for extracting green tea polyphenols. Epigallocatechin gallate was the predominant phenolic component in most extracts, alongside epicatechin, epigallocatechin, catechin, and gallic acid. The findings highlight the UAE technique as a robust, green, and scalable method for valorising green tea by-products, thereby facilitating the development of high-value natural extracts for applications in the food, pharmaceutical, and cosmetic industries. Full article

The rising demand for sustainable and circular approaches in the agro-industrial sector has generated interest in repurposing herbal tea residues as sources of high-value bioactive compounds. This work focusses on recovering phytochemicals from Rosa canina L. peel and seed dust (by-products of processing of herbal tea in filter tea bags) using green extraction techniques. Two environmentally friendly technologies were used: ultrasound-assisted extraction (UAE) with a sonotrode and subcritical fluid extraction (SBFE). The extracts were qualitatively profiled using (HR) LC-ESI-QToF-MS/MS and quantified using HPLC-PDA. Both by-products contained phenolic substances, including gallic acid derivatives, ellagic acid, and flavonoids such as quercetin and quercetin-3-O-glucoside (only in the peel). Additionally, Folin–Ciocalteu’s assay was used to determine Total Phenolic content (TP). The extraction efficiency was considered in terms of phenolic compound recovery and total phenolic content obtained under the respective experimental conditions. The maximum TP for SBFE was reported in samples extracted with ethanol–water (48:52) at 180 °C, producing 3876.67 GAE mg/L for peel and 1648.57 GAE mg/L for seeds. In the UAE, extraction with ethanol–water (48:52) for 10 min yielded the maximum TP of 2773.81 GAE mg/L for peel and 957.86 GAE mg/L for seeds. These findings highlight the potential of R. canina infusion by-products as long-term sources of bioactive compounds for use in nutraceutical, cosmetic, and pharmaceutical industries. Full article

High-temperature particulate matter (PM) filtration remains a fundamental challenge, because most fiber filters not only face the challenge of high temperatures but also suffer from an inherent trade-off between capture efficiency, pressure drop, and service life. This paper reports a hierarchical layered zirconia (ZrO₂) ceramic fiber aerogel featuring a continuous multiscale gradient. The aerogel was prepared by gradient air-blown spinning, and the resulting structure has directional order, with the fiber diameter gradually decreasing from upstream to downstream, thus forming a pore size gradient and achieving hierarchical particle interception across multiple scales. This rational design simultaneously suppresses surface clogging and reduces flow resistance, resolving the longstanding trade-off between efficiency and permeability. Consequently, this aerogel achieves an ultra-high filtration efficiency of 99.96%, a low pressure drop of 156 Pa, and a high dust-holding capacity of 101 g m⁻². The material also exhibits outstanding mechanical toughness (80% compressive strain elasticity and 25.75% tensile fracture strain) and thermal stability up to 1000 °C. Moreover, it maintains over 99.95% filtration efficiency at high temperatures and can be fully regenerated through 800 °C heat treatment. This work establishes a structure-based design paradigm for high-temperature filtration media and provides a scalable pathway for next-generation industrial flue gas purification. Full article

This study presents the engineering design and system-level modeling of a high-frequency power supply architecture for electrostatic precipitators intended to improve particulate removal efficiency and operational stability. Atmospheric air pollution by fine particulate matter (PM2.5) remains one of the most critical challenges in environmental protection and public health. Although electrostatic precipitators (ESPs) are widely used for industrial gas cleaning, the efficiency and stability of conventional 50 Hz power supplies are limited under conditions of strongly nonlinear corona discharge and high-resistivity dust. This paper presents the development and investigation of an advanced high-frequency power supply system for electrostatic precipitators based on a coupled electrical–electrophysical mathematical model. The work follows an engineering design methodology that integrates converter topology selection, electrophysical modeling of corona discharge, and control-oriented system optimization. The proposed model provides a unified description of electric field formation, space charge accumulation, ion transport, and particle motion in the corona discharge region. The simulation results show that in the operating voltage range of 10–100 kV, the electric field strength reaches (2–5)·10⁶ V/m, the ion concentration stabilizes in the range of 10¹³–10¹⁵ m⁻³, and the particle drift velocity increases from approximately 0.05 to 0.3 m/s, leading to an increase in collection efficiency from about 55% to 93%. It is demonstrated that the proposed system ensures stable output voltage regulation within ±2.5–5% even under strongly nonlinear load conditions. The use of an LC output filter (C = 1–10 nF, L = 10–100 mH) reduces the voltage ripple from about 14% to 1.4–4.8% and significantly improves the transient response. In addition, adaptive adjustment of the pulse repetition frequency in the range of 10–200 kHz makes it possible to reduce energy consumption by 12–18% while simultaneously increasing the collection efficiency by 8–15%. The obtained results confirm that the proposed high-frequency power supply architecture provides a physically well-founded and energy-efficient solution for improving the environmental performance and operational stability of electrostatic precipitators. Full article

In order to address the challenges of limited accuracy in identifying non-meteorological clutter and the spatial overlap between meteorological and non-meteorological echoes in cloud radar observations under complex weather conditions, in this study, we propose a quality-control method for cloud-radar data, which integrates machine learning with neighborhood filtering, This quality-control method first uses the Light Gradient Boosting Machine (LightGBM) to initially identify clutter, then employs a customized neighborhood filtering module to optimize and eliminate residual isolated clutter. This two-stage framework combines the strengths of accurate machine-learning-based classification and physically motivated filtering optimization, enabling reliable discrimination between meteorological and non-meteorological echoes. Based on multi-region, long-term and multi-model radar baseline observations, which cover typical complex weather types such as snow, fog, rain, low clouds and dust, the refined manual labeling of meteorological and non-meteorological echoes is carried out, combined with multi-source ground observation data such as surface observations, temperature and humidity. Based on this, a feature training dataset for machine learning is constructed, which contains over 20 million samples. A multi-index evaluation system—including echo classification accuracy and non-meteorological clutter rejection rate—is used to quantitatively assess the quality-control performance of the method in different weather scenarios. The results indicate that the proposed method demonstrates stable performance in typical complex weather scenarios, with comprehensive scores of 90.73 (snow), 94.23 (rain), 96.49 (low clouds), 91.10 (fog) and 95.79 (dust) on a 100-point scale. Through typical case studies and statistical data analysis, the proposed algorithm achieves better quality-control scores in comparison with the Random Forest and single LightGBM algorithms. It provides a new technical approach for cloud-radar data quality control and also offers a theoretical basis for the feature selection of machine-learning-based quality-control models, further enhancing the application value of cloud-radar data in refined meteorological observations. Full article

This paper presents the design and implementation of a low-cost microcontroller-based dual-channel fan controller optimized for high-power audio amplifiers, yet adaptable to power supplies, electronic loads, and other thermally intensive systems. Unlike conventional designs that drive all fans uniformly, the proposed solution provides fully independent cooling via dual I²C temperature sensors, predictive trend analysis, and multi-stage hysteresis. The controller incorporates advanced features including an anti-dust startup sequence, predictive boost with latching, active cross-cooling, anti-heat-soak protection, and stall detection via tachometer monitoring, complemented by LED-based fault signaling and automatic channel muting during overheating or fan failure. Hardware support for 12 V and 24 V fans, dual power-input options, and a compact PCB layout enhance integration flexibility. The firmware employs temperature-driven PWM mapping with EMA filtering and multi-level hysteresis. The experimental results confirm that all implemented features operate as intended, with each function demonstrating clear practical relevance, whether in improving responsiveness, preventing heat accumulation, or enhancing system reliability under a wide range of operating conditions. Full article

Although the organic fraction of PM_2.5 has been extensively studied, there is a considerable gap in understanding the organic fraction of coarse particles with diameters between 2.5 and 10 µm. We investigate the composition of coarse organic aerosol (OA) across rural, suburban, and urban areas of Switzerland. Using Aerosol Mass Spectrometer analyses of water-soluble OA extracted from collected filter samples (one entire year, 441 samples per size fraction), we identified two distinct classes of coarse OA. The first class, which constitutes 41–81% of coarse organic carbon (OC), is associated with primary biological organic carbon (PBOC). PBOC is characterized by specific marker ions (e.g., C₂H₅O₂⁺) and exhibits pronounced seasonal variation, with peak concentrations observed in the summer. This seasonal trend correlates with that of molecular markers such as arabitol and mannitol, as well as the fraction of biological particles determined by automated scanning electron microscopy coupled to energy dispersive X-ray spectroscopy of individual particles. The second class, contributing 7.9–17.8% to OC_coarse, is denoted as sulfur-containing organic carbon (SCOC) due to the presence of sulfur-containing ions such as CH₃SO₂⁺. Elevated concentrations of SCOC in urban environments near roadways suggest a strong influence from non-exhaust traffic emissions and resuspended dust. While the overall variation in coarse OC between rural and urban areas is approximately 10%, PBOC concentrations are 1.4 times higher in rural areas, whereas SCOC concentrations are 1.5 times higher in urban settings. Overall, our study shows that although OC_coarse concentrations in Switzerland are relatively consistent across site types, major water-soluble sources, particle properties and composition vary considerably geographically and seasonally. Full article

Wind catchers are widely used as vernacular systems for natural ventilation in hot–arid regions, yet their performance is often compromised by airborne dust. This study investigates the architectural integration of a camel hair–based filtration layer within a traditional down-draft wind catcher in a rural Saudi Arabian context, focusing on airflow behavior, indoor environmental response, and qualitative particulate interception under natural ventilation. Building on the authors’ previously published laboratory research that quantified the PM₁₀ filtration performance of camel hair–based media under controlled conditions, the present work extends the investigation to an in situ architectural application. Field measurements of air velocity, temperature, and relative humidity were conducted during a 24 h dust event to examine system-level behavior following filter integration. PM₁₀ capture was assessed qualitatively through visual inspection and comparative observation, serving as corroborative evidence rather than a standardized filtration metric. Results indicate that the filtration layer alters airflow characteristics without fundamentally disrupting natural ventilation. Indoor thermal conditions are interpreted within the framework of the Adaptive Thermal Comfort Model, appropriate for a free-running building, emphasizing occupant adaptation rather than fixed comfort thresholds. This study demonstrates the feasibility of integrating a biomimetically inspired, locally sourced natural material within a vernacular ventilation system, contributing architectural insights into balancing dust mitigation and natural ventilation in arid climates. Full article

Historically, the toxicological evaluation of poorly soluble low toxicity particles (PSLTs), such as titanium dioxide nanoparticles (TiO₂ NPs), distinct from conventional pigment-grade TiO₂, has focused on carcinogenicity and lung overload, leaving their pathological function in the development of pneumoconiosis undefined. In this study, we initiated a “Pneumoconiosis Renaissance”, redefining the human “Gold Standard” of pneumoconiosis pathology as a primarily interstitial “Dust Macule (DM) to Mixed Dust Fibrosis (MDF) axis”. In contrast, rats developed a species-specific “Airspace-Dominant Phenotype” (Pulmonary Dust Foci) driven by airspace stagnation. Integrating recent continuous inhalation exposure and recovery after inhalation exposure studies, we demonstrate that this overwhelming alveolar pathology in rats acts as a “Biological Mask”, physically superimposing upon and obscuring human-relevant interstitial sequestration. Crucially, however, extended recovery periods can unmask these interstitial events, revealing the true underlying pathology. We propose that future risk assessments and Adverse Outcome Pathways (AOPs) must incorporate spatial resolution. By rigorously segregating sensitive rat-specific airspace events from human-relevant interstitial remodeling, we can accurately bridge the interspecies gap. This review argues that rather than discarding the rat model, we must learn to decode it—using spatial distinctions to filter the airspace mask and evaluate the true interstitial risk of inhaled biodurable particles. Full article

To address the limited environmental perception capability and the difficulty of achieving consistent and efficient representation of the workspace feasible domain caused by high dust concentration, uneven illumination, and enclosed spaces in underground coal mines, this paper proposes a digital spatial construction and representation method for underground environments by integrating RGB-D depth vision with ORB-SLAM3. First, a ChArUco calibration board with embedded ArUco markers is adopted to perform high-precision calibration of the RGB-D camera, improving the reliability of geometric parameters under weak-texture and non-uniform lighting conditions. On this basis, a “dense–sparse cooperative” OAK-DenseMapper Pro module is further developed; the module improves point-cloud generation using a mathematical projection model, and combines enhanced stereo matching with multi-stage depth filtering to achieve high-quality dense point-cloud reconstruction from RGB-D observations. The dense point cloud is then converted into a probabilistic octree occupancy map, where voxel-wise incremental updates are performed for observed space while unknown regions are retained, enabling a memory-efficient and scalable 3D feasible-space representation. Experiments are conducted in multiple representative coal-mine tunnel scenarios; compared with the original ORB-SLAM3, the number of points in dense mapping increases by approximately 38% on average; in trajectory evaluation on the TUM dataset, the root mean square error, mean error, and median error of the absolute pose error are reduced by 7.7%, 7.1%, and 10%, respectively; after converting the dense point cloud to an octree, the map memory footprint is only about 0.5% of the original point cloud, with a single conversion time of approximately 0.75 s. The experimental results demonstrate that, while ensuring accuracy, the proposed method achieves real-time, efficient, and consistent representation of the 3D feasible domain in complex underground environments, providing a reliable digital spatial foundation for path planning, safe obstacle avoidance, and autonomous operation. Full article

The widespread application of the drill-and-blast method in tunnel construction generates instantaneous high-concentration dust, posing severe threats to workers’ health and safety. However, existing contact-based monitoring techniques, such as filter membrane weighing and light-scattering sensors, are hindered by operational complexity, maintenance challenges, data latency, and an inability to capture whole-field distribution. To address these limitations, this study conducted in situ experiments to construct a dust image dataset containing rich “real-world noise”. Analysis revealed significant variations in visibility, contrast, and light-scattering intensity across different concentration levels, establishing a physical basis for visual feature extraction. Consequently, a dust concentration prediction method based on transfer learning and CNN was proposed. Comparative training of six network models, including ResNet50, demonstrated that VGG16 achieved the best performance with an R² of 0.9684, verifying the method’s feasibility. Furthermore, hyperparameter optimization (learning rate: 0.001; batch size: 32; dataset split: 8:1:1) was shown to further enhance prediction accuracy. Full article

Background: Occupational exposure to aerosol particles can pose a substantial health risk. The study aimed to characterise the deposition of occupationally relevant aerosols in a 3D anatomical adult nasal cavity model under steady and unsteady flows. Materials: The deposition of aerosolised wheat flour, pine wood sanding dust, carbon black, and Arizona Test Dust A3 was quantified under steady flows (5, 7.5, and 20 L/min per nostril) and an unsteady breathing pattern generated by the commercial breathing simulator. Image analysis with custom software quantified the area covered by deposited particles. The Downstream Penetration Index (DPI) was determined from the outlet mass. Results: The highest segmental deposition occurred in the anterior segment of the lateral wall (WA) and septum (SA), with moderate values in the middle lateral wall (WM) and the lowest in the posterior lateral wall (WP, nasopharynx) and septum (SP). Arizona Test Dust A3 and carbon black demonstrated higher middle-posterior deposition and DPI, consistent with finer particle size distributions (PSD) and greater sub-10 µm fractions. In contrast, wheat flour and pine wood dust, with larger median particle sizes and lower sub-10 µm fractions, showed stronger anterior filtration and lower DPI. Increased flow enhanced anterior filtration of coarse particles and shifted deposition forward, aligning with increased inertial impaction, but elevated DPI for fine particles. Under unsteady flow, deposition was intermediate between 7.5 and 20 L/min. Conclusions: This study shows that PSD, morphology, and flow conditions influence nasal deposition. Coarse aerosols were filtered in the anterior nose, while fine-rich aerosols showed relatively greater middle-posterior deposition and higher DPI. These findings are essential for assessing occupational exposure and developing interventions and prevention strategies. Full article