Search Results (390)

Objectives: This study assessed the effectiveness of a cognitive behavioral therapy (CBT)-based fine dust education program, grounded in the Health Belief Model (HBM), on elementary students’ fine dust knowledge, related behaviors, and mental health (depression, anxiety, stress, sleep quality). Methods: From September to November 2024, 95 students (grades 4–6) living near a coal-fired power plant in midwestern South Korea were assigned to either an intervention group (n = 44) or a control group (n = 51). The intervention group completed a three-session CBT-based education program; the control group received stress management education. Assessments were conducted at weeks 1, 2, 4, and 8 using standardized mental health and behavior scales (PHQ: Patient Health Questionnaire, GAD: Generalized Anxiety Disorder Assessment, PSS: Perceived Stress Scale, ISI: Insomnia Severity Index). Results: A chi-square test was conducted to compare pre- and post-test changes in knowledge and behavior related to PM2.5. The intervention group showed significant improvements in seven fine dust-related knowledge and behavior items (e.g., PM2.5 awareness rose from 33.3% to 75.0%; p < 0.05). The control group showed limited gains. Regarding mental health, based on a mixed-design ANCOVA, anxiety scores significantly declined over time in the intervention group, with group and interaction effects also significant (p < 0.05). Depression scores showed time effects, but group and interaction effects were not significant. No significant changes were observed for stress, sleep, or group × PM2.5 interactions. Conclusions: The CBT-based education program effectively enhanced fine dust knowledge, health behaviors, and reduced anxiety among students. It presents a promising, evidence-based strategy to promote environmental and mental health in school-aged children. Full article

Considering the serious hazard of respiratory dust in underground coal mines and the low efficiency of traditional dust-reduction technology, this study optimizes the atomisation parameters of the gas–liquid two-phase flow nozzle through numerical simulation and experimental testing, and designs an on-board dust-reduction system. Based on the Fluent software (version 2023 R2), a flow field model outside the nozzle was established, and the effects of the air supply pressure, gas-phase inlet velocity, and droplet mass flow rate on the atomisation characteristics were analyzed. The results show that increasing the air supply pressure can effectively reduce the droplet particle size and increase the range and atomisation angle, and that the dust-reduction efficiency is significantly improved with the increase in pressure. The dust-reduction efficiency reached 69.3% at 0.6 MPa, which was the economically optimal operating condition. Based on the parameter optimization, this study designed an annular airborne gas–liquid two-phase flow dust-reduction system, and a field test showed that the dust-reduction efficiency of this system could reach up to 86.0%, which is 53.5% higher than that of traditional high-pressure spraying, and that the dust concentration was reduced to less than 6 mg/m³. This study provides an efficient and reliable technical solution for the management of underground coal mine dust and guidance for promoting the development of the coal industry. Full article

The occurrence of haze pollution significantly deteriorates air quality and threatens human health, yet persistent knowledge gaps in real-time source apportionment of fine particulate matter (PM_2.5) hinder sustained improvements in atmospheric pollution conditions. Thus, this study employed single-particle aerosol mass spectrometry (SPAMS) to investigate PM_2.5 sources and dynamics during winter haze episodes in Yinchuan, Northwest China. Results showed that the average PM_2.5 concentration was 57 μg·m⁻³, peaking at 218 μg·m⁻³. PM_2.5 was dominated by organic carbon (OC, 17.3%), mixed carbonaceous particles (ECOC, 17.0%), and elemental carbon (EC, 14.3%). The primary sources were coal combustion (26.4%), fugitive dust (25.8%), and vehicle emissions (19.1%). Residential coal burning dominated coal emissions (80.9%), highlighting inefficient decentralized heating. Source contributions showed distinct diurnal patterns: coal combustion peaked nocturnally (29.3% at 09:00) due to heating and inversions, fugitive dust rose at night (28.6% at 19:00) from construction and low winds, and vehicle emissions aligned with traffic (17.5% at 07:00). Haze episodes were driven by synergistic increases in local coal (+4.0%), dust (+2.7%), and vehicle (+2.1%) emissions, compounded by regional transport (10.1–36.7%) of aged particles from northwestern zones. Fugitive dust correlated with sulfur dioxide (SO₂) and ozone (O₃) (p < 0.01), suggesting roles as carriers and reactive interfaces. Findings confirm local emission dominance with spatiotemporal heterogeneity and regional transport influence. SPAMS effectively resolved short-term pollution dynamics, providing critical insights for targeted air quality management in arid regions. Full article

Environmental comfort and air pollution are among the most important indicators for assessing the population’s quality of life in urban agglomerations. This study aims to explore long-term memory in air pollution time series by analyzing the dynamics of the Hurst exponent and evaluating the predictability index. This type of statistical pre-forecast analysis is essential for developing accurate forecasting models for such time series. The effectiveness of air quality monitoring systems largely depends on the precision of these forecasts. The Ekibastuz coal-mining center, which houses one of the largest coal-fired power stations in Kazakhstan and the world, with a capacity of about 4000 MW, was chosen as an example for the study. Data for the period from 1 March 2023 to 31 December 2024 were collected and analyzed at the Ekibastuz coal-fired power station. During the specified period, 14 indicators (67,527 observations) were collected at 10 min intervals, including mass concentrations of CO, NO, NO₂, SO₂, PM_2.5, and PM₁₀, as well as current mass consumption of CO, NO, NO₂, SO₂, dust, and NO_x. The detrended fluctuation analysis of a time series of air pollution indicators was used to calculate the Hurst exponent and identify long-term memory. Changes in the Hurst exponent in regards to dynamics were also investigated, and a predictability index was calculated to monitor emissions of pollutants in the air. Long-term memory is recorded in the structure of all the time series of air pollution indicators. Dynamic analysis of the Hurst exponent confirmed persistent time series characteristics, with an average Hurst exponent of about 0.7. Identifying the time series plots for which the Hurst exponent is falling (analysis of the indicator of dynamics), along with the predictability index, is a sign of an increase in the influence of random factors on the time series. This is a sign of changes in the dynamics of the pollutant release concentrations and may indicate possible excess emissions that need to be controlled. Calculating the dynamic changes in the Hurst exponent for the emission time series made it possible to identify two distinct clusters corresponding to periods of persistence and randomness in the operation of the coal-fired power station. The study shows that evaluating the predictability index helps fine-tune the parameters of time series forecasting models, which is crucial for developing reliable air pollution monitoring systems. The results obtained in this study allow us to conclude that the method of trended fluctuation analysis can be the basis for creating an indicator of the level of air pollution, which allows us to quickly respond to possible deviations from the established standards. Environmental services can use the results to build reliable monitoring systems for air pollution from coal combustion emissions, especially near populated areas. Full article

The generation of fine coal particles during mining and processing presents significant environmental and logistical challenges, particularly in coal-dependent, developing countries like South Africa (SA). This review critically evaluates the technical viability of fine coal briquetting as a sustainable waste-to-energy solution within a SA context, while drawing from global best practices and comparative benchmarks. It examines abundant feedstocks that can be used for valorization strategies, including fine coal and agricultural biomass residues. Furthermore, binder types, manufacturing parameters, and quality optimization strategies that influence briquette performance are assessed. The co-densification of fine coal with biomass offers a means to enhance combustion efficiency, reduce dust emissions, and convert low-value waste into a high-calorific, manageable fuel. Attention is also given to briquette testing standards (i.e., South African Bureau of Standards, ASTM International, and International Organization of Standardization) and end-use applications across domestic, industrial, and off-grid settings. Moreover, the review explores socio-economic implications, including rural job creation, energy poverty alleviation, and the potential role of briquetting in SA’s ‘Just Energy Transition’ (JET). This paper uniquely integrates technical analysis with policy relevance, rural energy needs, and practical challenges specific to South Africa, while offering a structured framework for bio-coal briquetting adoption in developing countries. While technical and economic barriers remain, such as binder costs and feedstock variability, the integration of briquetting into circular economy frameworks represents a promising path toward cleaner, decentralized energy and coal waste valorization. Full article

This study investigates the emission characteristics and environmental impacts of pollutants from bagasse-fired biomass boilers through the integrated field monitoring of two sugarcane processing plants in Guangxi, China. Comprehensive analyses of flue gas components, including PM_2.5, NOx, CO, heavy metals, VOCs, HCl, and HF, revealed distinct physicochemical and emission profiles. Bagasse exhibited lower C, H, and S content but higher moisture (47~53%) and O (24~30%) levels compared to coal, reducing the calorific values (8.93~11.89 MJ/kg). Particulate matter removal efficiency exceeded 98% (water film dust collector) and 95% (bag filter), while NOx removal varied (10~56%) due to water solubility differences. Heavy metals (Cu, Cr, Ni, Pb) in fuel migrated to fly ash and flue gas, with Hg and Mn showing notable volatility. VOC speciation identified oxygenated compounds (OVOCs, 87%) as dominant in small boilers, while aromatics (60%) and alkenes (34%) prevailed in larger systems. Ozone formation potential (OFP: 3.34~4.39 mg/m³) and secondary organic aerosol formation potential (SOAFP: 0.33~1.9 mg/m³) highlighted aromatic hydrocarbons (e.g., benzene, xylene) as critical contributors to secondary pollution. Despite compliance with current emission standards (e.g., PM < 20 mg/m³), elevated CO (>1000 mg/m³) in large boilers indicated incomplete combustion. This work underscores the necessity of tailored control strategies for OVOCs, aromatics, and heavy metals, advocating for stricter fuel quality and clear emission standards to align biomass energy utilization with environmental sustainability goals. Full article

Dust emissions from unpaved haul roads in open-pit coal mining pose a significant risk to air quality, health, and operational efficiency of mining operations. This study integrated real-time field monitoring with numerical simulations using ANSYS Fluent 2023 R1 to investigate the generation, dispersion, and migration of particulate matter (PM) at the Ha’erwusu open-pit coal mine under varying meteorological conditions. Real-time measurements of PM2.5, PM10, and TSP, along with meteorological variables (wind speed, wind direction, humidity, temperature, and air pressure), were collected and analyzed using Pearson’s correlation and multivariate linear regression analyses. Wind speed and air pressure emerged as dominant factors in winter, whereas wind and temperature were more influential in summer (R² = 0.391 for temperature vs. PM2.5). External airflow simulations revealed that truck-induced turbulence and high wind speeds generated wake vortices with turbulent kinetic energy (TKE) peaking at 5.02 m²/s², thereby accelerating particle dispersion. The dust migration rates reached 3.33 m/s within 6 s after emission and gradually decreased with distance. The particle settling velocities ranged from 0.218 m/s for coarse dust to 0.035 m/s for PM2.5, with dispersion extending up to 37 m downwind. The highest simulated dust concentration reached 4.34 × 10⁻² g/m³ near a single truck and increased to 2.51 × 10⁻¹ g/m³ under multiple-truck operations. Based on spatial attenuation trends, a minimum safety buffer of 55 m downwind and 45 m crosswind is recommended to minimize occupational exposure. These findings contribute to data-driven, weather-responsive dust suppression planning in open-pit mining operations and establish a validated modeling framework for future mitigation strategies in this field. Full article

This study examines the influence mechanism of mining depth evolution on dust distribution, using the An Tai Bao open-pit coal mine as the research subject. A spatial coordinate system of the mining area was established utilizing a GIS positioning system, and high-resolution topographic data were extracted using Global Mapper. The research team developed a three-dimensional geological model updating algorithm with depth gradient as the characteristic parameter, enabling dynamic monitoring of mining depth with a model iteration accuracy of 0.5 m per update. A Fluent-based numerical simulation method was employed to construct a depth-dependent dust migration field solving system, aiming to elucidate the three-dimensional coupling mechanism between mining depth and dust dispersion. The findings reveal that mining depth demonstrates a three-stage critical response to dust migration. When the depth surpasses the threshold of 150 m, the wind speed attenuation rate at the pit bottom exhibits a marked change, and the dust dispersion distance decreases by 62% compared to shallow mining conditions. The slope pressure field evolution shows a significant depth-enhancement effect, with the maximum wind pressure at the leeward step boundary increasing by 22–35% for every additional 50 m of depth, resulting in dust accumulation zones with distinct depth-related characteristics. The west wind scenario demonstrates a particularly notable depth amplification effect, with the dust dispersion range in a 200-meter-deep pit expanding by 53.7% compared to the standard west wind condition. Furthermore, the interaction between particle size and depth causes the dust migration distance to exhibit exponential decay as depth increases. This research elucidates the progressive constraining influence of mining depth, a critical control parameter, on dust migration patterns. It establishes a depth-oriented theoretical framework for dust prevention and control strategies in deep open-pit mines. Full article

This study compares long-term air pollution trends and seasonal patterns in Beijing and Seoul from 2014 to 2024, focusing on PM2.5, PM10, CO, NO₂, SO₂, and O₃. Using statistical analyses including Mann–Kendall tests and generalized additive models, we found that Beijing achieved notable reductions in particulate matter, largely due to stricter industrial controls and reduced coal use, though winter pollution peaks remain. In contrast, Seoul’s improvements were slower, mainly due to persistent vehicular emissions and recurring spring dust storms from northern China. Seasonal analysis showed winter peaks in Beijing linked to coal heating, and spring peaks in Seoul driven by transboundary dust, with higher summer ozone in Seoul reflecting photochemical activity. These findings highlight the need for city-specific air quality management and regional cooperation, recommending further reductions in vehicular emissions for Seoul and continued transition from coal in Beijing to mitigate health impacts. This study identifies specific seasonal trends and pollution sources that require targeted policy interventions to improve air quality. Full article

PM₁₀ samples were collected at an urban site of Zhuozhou, the southern gateway of Beijing, from 28 December 2021 to 29 January 2022, in order to explore the chemical composition, sources and physical and chemical formation processes of prominent components. The results showed that five trace elements (Mn, Cu, As, Zn and Pb) had high enrichment in PM₁₀ and were closely related with anthropogenic combustion and vehicle emissions; organic and element carbon had a high correlation due to the same primary sources and similar evolution; nitrate dominated SNA (sulfate, nitrate, ammonium) and nitrate/sulfate ratios reached 2.35 on the polluted days owing to the significant contribution of motor vehicle emissions. Positive matrix factorization analysis indicated that secondary source, traffic, biomass burning, industry, coal combustion and crustal dust were the main sources of PM₁₀, contributing 32.5%, 20.9%, 15.0%, 13.9%, 9.4% and 8.3%, respectively; backward trajectories and potential source contribution function analysis showed that short-distance airflow was the dominant cluster and accounted for nearly 50% of total trajectories. The Weather Research and Forecasting model with Chemistry, with integrated process rate analysis, showed that dominant gas-phase reactions (heterogeneous reaction) during daytime (nighttime) in presence of ammonia led to a significant enhancement of nitrate in Zhuozhou, contributing 12.6 μg/m³ in episode 1 and 22.9 μg/m³ in episode 2. Full article

Surfactants are often used in the process of coal dust suppression, and the wetting effect is greatly affected by the surfactant hydrophilic group structures. In order to explore the influence of hydrophilic groups of surfactants on their adsorption states and wetting effect on coal dust, three surfactants with similar hydrophilic groups were selected, namely, anionic surfactant sodium dodecyl sulfate (SDS), anionic-nonionic surfactant alkyl ether sulfate (AES), and nonionic surfactant alkyl polyoxyethylene ether-3 (AEO-3). To assess surfactant efficiency, surface tension, wetting time, infrared spectra, and wetting heat were analyzed. These parameters provide insights into molecular adsorption, interfacial behavior, and energy changes during wetting. The different adsorption states of surfactants on the coal dust surface due to EO and SO₄²⁻ hydrophilic groups were analyzed. Results show that both anionic surfactant SDS and nonionic surfactant AEO-3 form the monolayer adsorption structure on the coal dust surface. Due to the electrostatic repulsion of SO₄²⁻ groups, the adsorption density of SDS is lower than that of AEO-3, which results in the higher wetting heat of AEO-3 compared to SDS. In addition, the EO groups without electrostatic repulsion make AEO-3 molecules more tightly adsorbed at the air–liquid interface, causing the minimal surface tension. Therefore, the wetting time of AEO-3 is shorter than that of SDS. The anionic-nonionic surfactant AES has both EO and SO₄²⁻ groups. Because the EO groups in the inner surfactant adsorption layer can attract Na⁺ ions to distribute around them, the free AES molecules further form the outer adsorption layer under the electrostatic attraction between SO₄²⁻ groups and Na⁺ ions. The double-layer adsorption structure causes the hydrophobic groups of the outer AES molecules to face outward, the hydrophobic sites on the coal dust surface are not completely transformed into hydrophilic sites. Although AES exhibits the highest adsorption density, it has the lowest wetting heat and the longest wetting time. The research results can provide theoretical guidance for the selection of suitable surfactants for coal dust suppression. Full article

Land reclamation is crucial for restoring ecosystems in mining areas, improving land use efficiency, and promoting sustainable regional development. Traditional single-indicator assessments fail to capture the full complexity of reclamation, highlighting the need for a more comprehensive evaluation approach. This study combines field-measured and remote sensing data to develop multiple evaluation indices, creating a comprehensive framework to assess reclamation effectiveness. A soil quality index based on the Minimum Data Set (SQI_MDS) was developed to analyze spatial variations in soil quality, efficiently capturing key soil attributes. Remote sensing data were used to calculate the Dump Reclamation Disturbance Index (DRDI) and the Enhanced Coal Dust Index (E_CDI) to evaluate vegetation recovery and ecological improvements. The Comprehensive Evaluation Quality Index (CEQI) was introduced, synthesizing soil, vegetation, and ecological conditions for a holistic assessment. Key findings include significant soil quality improvement over time, with MDS effectively capturing variations; vegetation recovery increased with reclamation duration, though regional disparities were observed; ecological conditions steadily improved, as evidenced by a decline in ECDI values and reduced contamination; and the CEQI reflected overall improvements in reclamation effectiveness. This study offers a practical framework for coal mining land reclamation, providing scientific support for decision-making and guiding effective reclamation strategies for ecological restoration and sustainable land management. Full article

Aerosol optical depth (AOD) data from 2020 to 2022 during the COVID-19 pandemic in a typical desert industrial city, Wuhai, was analyzed to investigate aerosol optical properties, origins of different types of aerosols, and the impacts of the COVID-19 lockdown on desert pollution. Results show that annual AOD (500 nm) and Ångström exponent α were 0.36 ± 0.12 and 0.75 ± 0.22 in 2020, 0.30 ± 0.12 and 0.75 ± 0.14 in 2021, and 0.28 ± 0.09 and 0.74 ± 0.19 in 2022, respectively, representing a slightly polluted environment characterized by a mixture of coarse-mode dust aerosols and fine-mode anthropogenic aerosols. Seasonal analysis reveals that the highest AOD primarily occurred in spring due to frequent dust events, while the lowest AOD was observed in winter. Potential Source Contribution Function (PSCF) identified the Alxa Desert as a major potential source during the entire year, and anthropogenic industrial and mining activities in northern Ningxia and southern Inner Mongolia were also important contributors, particularly outside of the winter season. The prevailing wind direction in Wuhai was from the northwest (NW-quadrant), originating from the depopulated desert or Gobi area, accounting for 85.11% in spring, 61.45% in summer, 68.09% in autumn, and 100% in winter. The remaining air masses came from southeastern (SE-quadrant) densely populated areas. Despite the dominance of NW air flows, SE anthropogenic air masses resulted in the highest AOD of 0.47 ± 0.24 in spring, 0.38 ± 0.23 in summer, and 0.32 ± 0.17 in autumn, with corresponding finest particle sizes of 0.83 ± 0.31, 0.91 ± 0.30, and 1.02 ± 0.22 in α. This suggests that anthropogenic influence remains significant even under strict control measures during the COVID-19 lockdown. In winter, the northwest air masses contributed to the highest pollution of 0.49 ± 0.39 (AOD) and finest particle size of 0.90 ± 0.32 (α), likely associated with the coal/straw burning for winter heating. In addition, the particles leading to moderate pollution primarily ranged around 0.2–0.25 µm, and fine particle pollution persists throughout the year. Full article

Coal dust seriously affects the underground working environment. The current water-spray dust reduction technology uses a large amount of water and has a poor effect on coal dust with poor wettability. This study proposed a clean and sustainable technology using plasma-activated water (PAW) to alter the wettability of coal dust and improve its dust control effect. The PAW was prepared and its physical and mathematical properties were tested by a device designed in-house. The influence of PAW on the wettability of coal dust was determined by the coal dust contact angle experiments. The effect of PAW on the surface morphology of coal dust was analyzed by a scanning electron microscope. The effect of PAW on the pore structure of coal dust was analyzed through the specific surface area and pore size experiments. The results showed that PAW contained a large number of active substances such as H₂O₂, NO₃⁻, and NO₂⁻, showing strong and stable oxidation. PAW could significantly reduce the instantaneous contact angle of coal dust, and the higher the degree of coal dust metamorphism, the more significant the reduction effect. The surface morphology, pore volume, specific surface area, and fractal dimension of the coal dust were significantly changed after PAW treatment. PAW could transform the non-uniform three-dimensional spatial distribution of the coal dust surface into an approximate two-dimensional planar distribution, thus enhancing the wettability of the coal dust. With the increase in PAW ionization intensity, the contact angle of long-flame coal was negatively correlated with the mesoporous pore volume. The contact angle of gas coal was negatively correlated with the micropore volume and micropore specific surface area, and was positively correlated with the mesopore volume. The contact angle of meager lean coal was positively correlated with the macropore specific surface area. The surface morphology, pore volume, specific surface area, and fractal dimension changes in coal dust treated with PAW can reveal the wettability enhancement mechanism to some extent. The results of the study can provide pre-theoretical guidance for the field application of PAW coal mine dust reduction technology. Full article

Background: This study aims to investigate the impact of coal dust (silicon dioxide) exposure on dyslipidemia and its underlying mechanisms, with a focus on the association between coal dust exposure and hepatic metabolic disorders. Methods: Clinical data were collected from 5433 coal mine workers to compare the incidence of dyslipidemia between the dust-exposed group and the non-exposed group. A mouse model of silicon dioxide exposure was established to observe hepatic fat accumulation and pathological changes. Liver tissue sequencing was performed to screen for key differential genes. In vitro cell experiments were utilized to identify the molecular mechanisms underlying hepatocyte metabolic abnormalities induced by silicon dioxide exposure. Results: Clinical data revealed that 69.2% of miners in the dust-exposed group developed dyslipidemia, which was higher than the 30.7% in the non-exposed group. Animal data showed that silicon dioxide exposure led to hepatic fat deposition and pathological damage, with the degree of injury positively correlated with exposure time. Liver sequencing identified a significant upregulation of the FMO3 (flavin monooxygenase 3) gene in mouse liver tissue following silicon dioxide exposure, accompanied by enhanced inflammatory responses. Mechanistic studies demonstrated that silicon dioxide activates Kupffer cells to secrete IL-6 (interleukin-6), which induces high expression of FMO3 in hepatocytes through the PKC/YY1 signaling pathway, thereby disrupting lipid metabolism. Conclusions: Silicon dioxide exposure can promote the upregulation of FMO3 expression in hepatocytes by activating Kupffer cells to release IL-6 via the PKC/YY1 pathway, ultimately leading to lipid metabolic disorders and dyslipidemia Full article