Search Results (388)

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

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

The continuous deposition of coal fine in the well can lead to complex problems, such as pump blockage and reduced capacity. The traditional critical velocity model applicable to rigid spherical particles, such as sand grains and glass beads, finds it difficult to accurately predict the migration behavior of coal fine in the wellbore. Therefore, this study aims to reveal the sedimentation law of coal fine particles, establish a critical velocity prediction model applicable to pulverized coal, and provide a theoretical basis for effectively preventing pump blockage and capacity decline problems. This paper analyzes the particle characteristics of coal fine in different mining areas and conducts experiments on the static settling of coal fine particles and the critical transport velocity. The experimental results showed that the larger the mesh size of coal fine, the lower the static settling velocity of coal fine particles. The critical velocity of coal fine increased with the particle size and concentration of the coal fine particles, as well as with the increase of the pipe column inclination. A new empirical formula for calculating the critical velocity of coal fine particles was derived by considering the effects of the coal fine concentration and pipe inclination. Full article

This study examines the influence of particle size on the flotation kinetics parameters of both raw and waste fine coal originating from the anthracite mine “Vrška Čuka”, Serbia. Flotation kinetics modeling was performed using MATLAB for nonlinear regression analysis, based on coal flotation test data. The correlation between total combustible recovery and flotation time was determined using the following models: Classical, Klimpel, Kelsall, Modified Kelsall, and Fully Mixed. The coefficients of determination range from 0.9724 (the Klimpel model) to 1 (the modified Kelsall model) for raw coal and from 0.8609 (the Klimpel model) to 0.9981 (the modified Kelsall model) for waste coal. Although both the Classical and Modified Kelsall models demonstrated a good correlation with the experimental data, the Modified Kelsall model provided a slightly better fit. The maximum values of the flotation rate constant (k) for both coals were obtained for the particle size-class (−0.1 + 0.053) mm for the Classical model and (−0.2 + 0.1) mm for the modified Kelsall model. The relation between flotation kinetics constant (k) and average particle size value (d_sr) was estimated for the Classical model and the modified Kelsall model. It was observed that the flotation kinetics constant (k) for coal particle size could be predicted satisfactorily. 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

In the development of deep coalbed methane (CBM) resources, the adsorption behavior of supercritical methane is a key factor restricting reserve evaluation and development efficiency. This study integrates scanning electron microscopy (SEM), low-temperature CO₂ adsorption (LTCO₂A), mercury intrusion porosimetry (MIP), high-temperature and high-pressure CH₄ adsorption experiments (HTHP-CH₄A), and theoretical models to reveal the pore–fracture structure of deep coal seams and the adsorption characteristics of supercritical methane. Based on a predictive model for supercritical methane adsorption capacity, the adsorption capacity of deep methane was predicted. Results show that micro-pores are well-developed in deep coal rocks, but pore connectivity is generally poor, predominantly consisting of fine bottleneck pores and semi-closed pores, with a certain proportion of open pores. The fractal dimension (D_m) of micro-pore structures in deep coal samples ranges from 2.0447 to 2.2439, indicating high micro-pore surface roughness and a large specific surface area, which provide favorable sites for methane adsorption. Pores larger than 100 nm exhibit fractal values between 2.6459 and 2.8833, suggesting that the pore surfaces in deep coal seams approach a three-dimensional pore space with rough surfaces and complex pore structures. As temperature and pressure enter the supercritical region, the adsorption capacity shows an abnormal trend of “first increasing and then decreasing” with increasing pressure. The deep coal rock–supercritical methane adsorption system exhibits two scenarios in low-pressure and high-pressure regions, corresponding to self-adsorption driven by strong methane adsorption potential and external force adsorption or overpressure micro-pore adsorption, respectively. The supercritical adsorption prediction model considering temperature and methane adsorption phase density has extremely low deviation (1.11–1.25%) and high accuracy. The average dispersion between predicted and actual values ranges from 0.44 cm³/g to 0.48 cm³/g, with small error fluctuations and no significant deviation. This study provides theoretical support for the recoverability evaluation and efficient development of deep CBM resources. Full article

Traditional coal quality assessment methods rely exclusively on the laboratory testing of physical samples, which impedes detailed stratigraphic evaluation and limits the integration of intelligent precision mining technologies. To resolve this challenge, this study investigates geophysical logging as an innovative method for coal quality prediction. By integrating scanning electron microscopy (SEM), X-ray analysis, and optical microscopy with interdisciplinary methodologies spanning mathematics, mineralogy, and applied geophysics, this research analyzes the coal quality and mineral composition of the Shanxi Formation coal seams in northern Jiangsu, China. A predictive model linking geophysical logging responses to coal quality parameters was established to delineate relationships between subsurface geophysical data and material properties. The results demonstrate that the Shanxi Formation coals are gas coal (a medium-metamorphic bituminous subclass) characterized by low sulfur content, low ash yield, low fixed carbon, high volatile matter, and high calorific value. Mineralogical analysis identifies calcite, pyrite, and clay minerals as the dominant constituents. Pyrite occurs in diverse microscopic forms, including euhedral and semi-euhedral fine grains, fissure-filling aggregates, irregular blocky structures, framboidal clusters, and disseminated particles. Systematic relationships were observed between logging parameters and coal quality: moisture, ash content, and volatile matter exhibit an initial decrease, followed by an increase with rising apparent resistivity (LLD) and bulk density (DEN). Conversely, fixed carbon and calorific value display an inverse trend, peaking at intermediate LLD/DEN values before declining. Total sulfur increases with density up to a threshold before decreasing, while showing a concave upward relationship with resistivity. Negative correlations exist between moisture, fixed carbon, calorific value lateral resistivity (LLS), natural gamma (GR), short-spaced gamma-gamma (SSGG), and acoustic transit time (AC). In contrast, ash yield, volatile matter, and total sulfur correlate positively with these logging parameters. These trends are governed by coalification processes, lithotype composition, reservoir physical properties, and the types and mass fractions of minerals. Validation through independent two-sample t-tests confirms the feasibility of the neural network model for predicting coal quality parameters from geophysical logging data. The predictive model provides technical and theoretical support for advancing intelligent coal mining practices and optimizing efficiency in coal chemical industries, enabling real-time subsurface characterization to facilitate precision resource extraction. Full article

This study investigates the potential for sustainable concrete production using industrial by-products: used foundry sand (UFS) and coal bottom ash (CBA). These materials were partially substituted for natural aggregates to reduce environmental impact and promote circular economy practices. UFS was used as a replacement for fine aggregate, while both fine and coarse CBA were tested as substitutes for sand and gravel, respectively. The materials were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) to evaluate their mineralogical and microstructural properties. Six concrete mixtures were prepared with varying replacement levels (up to 70% total aggregate substitution) at a constant water-to-cement ratio of 0.50. Compressive strength tests were conducted at 28 days, supported by microstructural observations. Results showed that high levels of UFS and CBA led to reduced strength, mainly due to weak interfacial bonding and porous ash particles. However, moderate replacement levels (e.g., 20% fine CBA) maintained high strength with good structural integrity. The study concludes that both UFS and CBA can be used effectively in concrete when carefully dosed. The findings support the use of industrial waste in construction, provided that material properties are well understood and replacement levels are optimized. Full article

The efficiency of coalbed methane (CBM) extraction is closely related to the drilling response of coal seams, which is significantly influenced by natural fracture development of coal seams. This work investigated 11 coal samples from the Baode, Xinyuan, and Huolinhe mines, employing quantitative fracture characterization, acoustic wave testing, drilling experiments, and cuttings analysis to systematically reveal the relationships and mechanisms between fracture parameters and coal drilling response characteristics. The result found that acoustic parameters (average wave velocity v and drilling surface wave velocity v₀) exhibit significant negative correlations with fracture line density (ρ₁) and area ratio (ρ₂) (|r| > 0.7), while the geological strength index (GSI) positively correlates with acoustic parameters, confirming their utility as indirect indicators of fracture development. Fracture area ratio (ρ₂) strongly correlates with drilling cuttings rate q (r = 0.82), whereas GSI negatively correlates with drilling rate w, indicating that highly fractured coal is more friable but structural stability constrains drilling efficiency, while fracture parameters show limited influence on drill cuttings quantity Q. Cuttings characteristics vary with fracture types and density. Type I coal (low-density coexisting exogenous fractures and cleats) produces cuttings dominated by fine particles with concentrated size distribution (average particle size d ≈ 0.52 mm, crushability index n = 0.46–0.61). Type II coal (exogenous-fracture-dominant) exhibits coarser particle sizes in cuttings (d ≈ 0.8 mm, n = 0.43–0.53). Type III coal (dense-cleat-dominant) drill cuttings are mainly coarse particles and are concentrated in distribution (d ≈ 1.53 mm, n = 0.72–0.98). Additionally, drilling response differences are governed by the coupling effects of vitrinite reflectance (R_o), density, and firmness coefficient (f), with Huolinhe coal being easier to drill due to its lower R_o, f, and density. This study elucidates the mechanism by which fracture development affects coal drilling response through multi-parameter correlation analysis, while also providing novel insights into the optimization of fracturing sweet spot selection for CBM development. Full article

Investigating the microstructural damage and mechanical properties of coal under deep mine hygrothermal conditions is essential for ensuring the safe and efficient extraction of coal resources. In this study, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and nanoindentation techniques were employed to examine the surface morphology and microscale mechanical properties of coal samples exposed to four environmental conditions, initial, humidified, heated, and coupled hygrothermal, under a peak indentation load of 70 mN. The results indicate that humidification led to the formation of dissolution pores and localized surface softening, resulting in a 15.9% increase in the peak indentation depth and reductions in the hardness and elastic modulus by 29.53% and 17.14%, respectively. Heating caused localized disintegration and the collapse of the coal surface, accompanied by surface hardening, with a slight 0.4% decrease in the peak indentation depth and increases in hardness and the elastic modulus by 1.32% and 1.56%, respectively. Under the coupled hygrothermal condition, numerous fine dissolution pores and microcracks developed on the coal surface, and the mechanical properties exhibited intermediate values between those observed in the humidified and heated states. Notably, the elevated temperature suppressed the moisture penetration into the coal matrix to some extent in the hygrothermal environment. A positive correlation was found between the hardness and elastic modulus, independent of the coal sample condition. The mineralogical composition significantly influenced the microscale mechanical behavior, with hard quartz minerals corresponding to lower peak indentation depths and a higher hardness, whereas soft kaolinite showed the opposite trend. Full article

Coal bottom ash (CBA) is a waste produced by burning coal that presents possible hazards to human well-being and the environment. Rapid economic expansion has increased the utilisation of CBA, resulting in a crisis concerning the disposal of this waste. By employing waste as a replacement for natural materials, it is possible to achieve sustainable and environmentally friendly construction. This study assesses the effects of utilising CBA waste as a replacement for fine aggregate in stone mastic asphalt (SMA) pavement. Seven asphalt mixture proportions were designed, each of which employed a different percentage of CBA (0%, 10%, 20%, 30%, 50%, 70%, and 100%) as a fine aggregate replacement. The performance tests conducted in this research were the Cantabro durability test, resilient modulus test, dynamic creep test, and moisture susceptibility test. The findings showed an improvement in the durability and resistance to permanent deformation of the SMA mixtures with 30% and 50% CBA replacement, respectively. However, further increases in the CBA content caused a decrease in the durability and resistance to permanent deformation. Meanwhile, the stiffness and tensile strength ratio (TSR) value decrease with the use of CBA replacement at any percentage. However, the TSR value of the SMA mixtures with 50% or less CBA replacement was more than 80%, which meets the minimum requirement set by JKR. In conclusion, incorporating CBA into SMA mixture has a positive effect on certain mechanical properties, particularly its durability and resistance to permanent deformation at optimal replacement levels, highlighting its potential to be used as a sustainable material in asphalt pavement construction. Full article

The high-hydrolysis reactivity cement clinker powder in cement plays a major role in cement’s cementation, while low-hydrolysis reactivity mineral admixture powders, such as slag, m mainly serve as a filler. Through optimizing the particle matching of cement clinker powder and slag powder, the mechanical properties of cement can be enhanced. In this study, clinker and slag with differing levels of fineness were obtained by separate grinding, and the particle gradation of clinker powder and slag powder in the cement was optimized. Fine clinker particles were mixed with coarse slag particles to systematically explore their effects on the rheology of cement paste, the formation of hydration products, the evolution of the pore structure, and the material’s mechanical properties. Through experimental tests and microscopic analysis, the mechanism whereby particle gradation is regulated by separate grinding was revealed. The findings of the study are as follows: with the same amount of cinder, finer clinker requires a higher water content of standard consistency. The addition of coarse cinder effectively reduces the standard-consistency water requirement of the blended cement. Fine grinding of coal cinder fails to enhance cement strength effectively but markedly raises the standard-consistency water demand. Thus, the specific surface area of coal cinder should be maintained at approximately 210 m²/kg. Full article

Developing resource-efficient technologies for producing ceramic materials with specific properties and performance characteristics is one of the most important tasks in modern materials science. As natural resources face depletion, the use of anthropogenic wastes, including fly ash from coal combustion, for the development of new compositions and the production of ceramics with an improved microstructure is of particular significance. The use of PM₁₀ fly ash microspheres in ceramic production will help to reduce particulate matter emissions. In this study, fine narrow fractions of PM₁₀ microspheres were successfully separated from coal fly ash using aerodynamic and magnetic separation. Glass–ceramic materials with a homogeneous microstructure, an open porosity of 0.4–37%, a compressive strength of 5–159 MPa, and acid resistance of up to 99.9% were obtained using narrow fractions. The materials obtained are promising for application as highly porous ceramics, effective microfiltration membranes, and fine-structured technical ceramics, which can be used in installations operating in aggressive media and/or at high temperatures. The ceramic membranes were characterised by high liquid permeability values up to 1194 L·m⁻²·h⁻¹·bar⁻¹. Filtration tests showed that the retention coefficient for dispersed microsilica particles with d_av = 1.9 μm is 0.99. Full article

In this study, the characteristics of coal sorbents obtained by the activation of coke fines in an atmosphere of a mixture of gases CO₂ and H₂O were studied. The experiment was conducted at various temperatures (700–900 °C), activation time (60–180 min), and constant CO₂ supply rate (0.5 L/min). The main parameters such as tinder, ash content, bulk density, sorption capacity, total pore volume, and specific surface area were analyzed to assess the efficiency of the process. The results showed that samples of sorbents obtained at a temperature of 800 °C and an activation time of 120 min have the highest sorption capacity for iodine (up to 64.77%). The specific surface area of the obtained carbon sorbents was ~432.6 m²/g. It was found that an increase in temperature to 900 °C leads to a decrease in sorption characteristics, which may be due to partial destruction of the porous structure of the material. It was also found that the duration of activation contributes to an increase in burn-off and ash content, which had an effect on sorption properties. Based on the data obtained, optimal conditions for the production of carbon sorbents have been established and a process model has been developed. Full article