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Introduction: Coal represents a significant natural resource in our world, and its quality and commercial value is primarily determined by its heating capacity. Numerous scientists worldwide have attempted to explore the impact of various environmental factors on coal rank, yet their conclusions are often inconsistent. Methods: In this study, the Illumina MiSeq sequencing approach was used to analyze the bacterial community from a low-rank coal mine as well as a high-rank mine. Moreover, we investigated the relationship between the physical and chemical properties of the coal and the bacterial composition. Results: Overall, we found that the high-rank coal exhibited higher heating value but higher total sulfur and lead levels. Considering the community of bacteria, the abundances of Phascolarctobacterium and Anaerostipes were highly elevated in the high-rank coal group. Most interestingly, the Anaerostipes abundance was correlated with coal quality positively. Additionally, the co-occurrence network of the bacterial community in the high-rank coal group showed much higher complexity. The bacterial functional potential predictions indicated elevated levels of phosphoenolpyruvate carboxykinase ATP, succinate dehydrogenase fumarate reductase flavoprotein subunit, and methylenetetrahydrofolate dehydrogenase NADP methenyltetrahydrofolate cyclohydrolase pathways. Conclusion: This study revealed that high-rank coal had more complicated co-occurrence network and elevated Anaerostipes abundance, which may suggest a potential biological pathway that can be explored to enhance coal quality.

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The secondary mining movement in non-pillar coal extraction causes significant overrun damage to flexible formwork concrete walls, leading to extensive deformation of roadway roof and bottom plates. This adversely affects working face efficiency and safety. The engineering context focuses on the non-pillar gob-side retaining walls in the 1315 working face of Zhaozhuang Coal Mine and the 23107 working face of Xiegou Coal Mine. Through on-site investigation, numerical simulation, theoretical analysis, and testing, we explore the stress migration law and destabilizing mechanism of the flexible formwork concrete wall influenced by the secondary mining movement of the coal-free pillar along the hollow wall. The research results showed that: (1) During the mining back process, the concrete wall formed with flexible formwork may experience stress concentration, leading to excessive damage and compromising mining safety. (2) Developing a predictive stress model for the concrete wall with flexible formwork is essential. If the stress surpasses the ultimate compressive strength during mining back, reinforcement becomes necessary.3) The length of damage overrun in the flexible formwork concrete wall exhibits two distinct stages as the distance back to mining increases. The first stage shows nearly linear growth, while the second stage indicates a decreasing growth rate, ultimately stabilizing. The application of Z6 concrete reinforcing agent effectively strengthens the flexible formwork concrete wall.

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Coalbed methane thermodynamic extraction, as an emerging ECBM recovery method, can effectively improve gas recovery rates. And clarifying methane diffusion and migration law in coal under thermal stimulation is crucial for the selection of its process parameters. Based on laboratory methane adsorption-release experiments, the evolution law of methane diffusion characteristics with temperature and pressure was studied, and the control mechanism of heat-dependent methane diffusion behavior was explored. The results show that both thermal stimulation and high adsorption pressure accelerated the methane diffusion rate in coal. Adsorption pressure had little effect on methane diffusion percentage, but thermal stimulation promoted a significant increase in diffusion percentage and improved the net methane yield. The influence mechanisms of adsorption pressure and thermal stimulation on methane diffusion characteristics are elucidated in relation to the amount and proportion of methane-activated molecules in the diffusion process. The constant diffusion coefficient of methane is heat-dependent, based on which a diffusion model is derived to accurately predict the methane release process in coal. Additionally, temperature has a more important effect on transient diffusion coefficient than pressure. Thermal stimulation leads to a net increase rather than a decrease in diffusion coefficient in the early diffusion stages and can also accelerate the attenuation of diffusion coefficient, with this intensifying effect becoming more pronounced at higher temperatures. The research results can provide some reference for the determination of coal seam gas content and the selection of heat injection process parameters.

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Large-scale coal mine gas explosion (CMGE) accidents have occurred occasionally and exerted a devastating effect on society. Therefore, it is essential to systematically identify the characteristics and association rules of causes of CMGE accidents through analysis on large-scale CMGE accident reports. In this study, 298 large-scale CMGE accidents in China from 2000 to 2021 were taken as the data sample, and mathematical statistical methods were adopted to analyze their general characteristics, coupling cross characteristics, and characteristics of gas accumulation and ignition sources. Moreover, the text mining technology and the Apriori algorithm were used for exploring the formation mechanism of CMGE accidents, during which 46 main causal factors were identified and 59 strong association rules were obtained. Furthermore, an accident causation network was constructed based on the co-occurrence matrix. The key causal items and sets of CMGE accidents were clarified through network centrality analysis. According to the research results, electrical equipment failure, cable short circuit, mine lamp misfire, hot-line work, and blasting spark are the key ignition sources of CMGE. Fan failure, airflow short circuit, and local ventilation fan damage are the main causes of gas accumulation. Besides, the confidence levels of two association rules of "static spark-fan failure" and "blasting spark-airflow short circuit" are higher than 70%, indicating that they are the two dominant risk-coupling paths of gas explosions. In addition, six causes appear frequently in the shortest risk paths of gas explosion and are closely related to other causes, i.e., fan failure, local ventilation fan damage, static sparks, electrical equipment failure, self-heating ignition, and friction impact sparks. This study provides a new perspective on identifying causes of accidents and their complex association mechanisms from accident report data for practical guidance in risk assessment and accident prevention.

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The extraction of coal from open-pit mines significantly contributes to environmental degradation, posing grave risks to human health and the operational stability of machinery. In this milieu, microbial dust suppressants leveraging microbially induced carbonate precipitation (MICP) demonstrate substantial potential for application. This manuscript undertakes an exploration of the dust mitigation efficiency, consolidation attributes, and the fundamental mechanisms of microbial dust suppressants across coal dust samples with varying metamorphic gradations. Empirical observations indicate that, in resistance tests against wind and rain, lignite coal underwent mass losses of 7.43 g·m-2·min-1 and 98.62 g·m-2·min-1, respectively. The production of consolidating agents within the lignite dust, attributable to the microbial suppressants, was measured at 0.15 g per unit mass, a value of 1.25 and 1.07 times greater than that observed in bituminous coal and anthracite, respectively. Scanning electron microscopy coupled with X-ray energy-dispersive spectroscopy (SEM-EDS) and X-ray diffraction (XRD) analyses illuminated that the consolidating products within the coal dust predominantly constituted calcite and vaterite forms of calcium carbonate. The consolidation mechanism of coal dust via microbial suppressants is articulated as follows: Subsequent to the application on coal dust, the suppressants induce the formation of carbonate precipitates with inherent adhesive properties. These carbonates affix to the surfaces of coal dust particles, progressively encapsulating them. Furthermore, they play a pivotal role in bridging and filling the interstices between adjacent dust particles, thereby culminating in the genesis of a dense, cohesive mass capable of withstanding erosive forces.

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To realize the resource utilization of solid waste (coal slime) and further the dual carbon goals, utilizing coal slime and coal ash as adsorbates for CO2 capture is crucial. This study employed low-temperature N2 adsorption, low-pressure CO2 adsorption, X-ray diffraction, X-ray fluorescence, and isothermal adsorption tests to assess coal slime and coal ash's pore/mineral composition characteristics. Subsequently, the influence on CO2 adsorption was analyzed to reveal the CO2 adsorption mechanisms of pores and clay minerals, and CO2 molecule adsorption behavior. The results showed that: (1) ashing led to reductions in total pore volume, specific surface area, micropore volume, and micropore specific surface area, accompanied by substantial decreases in micropores and mesopores; (2) ashing generated high-temperature stable mineral species, including quartz, andalusite, hematite, and gypsum, while all calcite decomposed into CaO; (3) coal slime exhibited greater CO2 adsorption capacity than coal ash, influenced by pore structure and clay minerals; (4) the adsorption behavior of coal slime and coal ash likely aligns with micropore filling theory, suggesting CO2 is adsorbed within the 0.30-1.47 nm pore structure. This research contributes to optimizing coal by-product utilization in mining areas and exploring adsorbate materials for CO2 sequestration in abandoned goaf.

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In the study, the structural parameters of Zichang (ZC) coking coal from northern Shaanxi Province were examined. A theoretical calculation was employed to build a molecular structure model for ZC coal, as well as applying principles of quantum chemistry, the prediction of NMR spectrogram and density for the model was achieved, and the molecular chemical formula was C199H155O36N3. The molecular structure optimization and annealing kinetics calculations are based on molecular mechanics (MM) and molecular dynamics (MD). Subsequently, a representative simplified model was constructed using the aromatic structure as the fundamental unit. On this foundation, the electrostatic potential (ESP), atomic charge distribution, and energy level orbitals were analyzed for this simplified model. The outcomes of this research can serve as an essential guide for determining the reaction order of the active categories during the low-temperature oxidation process for ZC coking coal.

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The quest for scientifically advanced and sustainable solutions is driven by growing environmental and economic issues associated with coal mining, processing, and utilization. Consequently, within the coal industry, there is a growing recognition of the potential of microbial applications in fostering innovative technologies. Microbial-based coal solubilization, coal beneficiation, and coal dust suppression are green alternatives to traditional thermochemical and leaching technologies and better meet the need for ecologically sound and economically viable choices. Surfactant-mediated approaches have emerged as powerful tools for modeling, simulation, and optimization of coal-microbial systems and continue to gain prominence in clean coal fuel production, particularly in microbiological co-processing, conversion, and beneficiation. Surfactants (surface-active agents) are amphiphilic compounds that can reduce surface tension and enhance the solubility of hydrophobic molecules. A wide range of surfactant properties can be achieved by either directly influencing microbial growth factors, stimulants, and substrates or indirectly serving as frothers, collectors, and modifiers in the processing and utilization of coal. This review highlights the significant biotechnological potential of surfactants by providing a thorough overview of their involvement in coal biodegradation, bioprocessing, and biobeneficiation, acknowledging their importance as crucial steps in coal consumption.

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Fly ash is predominately the inorganic byproduct of coal combustion for electrical power generation. It is composed of aluminosilicates with Fe, Mg, K, and Ca forming submicron to 100 µm spheres and amorphous particles. During combustion trace elements are incorporated into the heterogenous fine particles that can pose risks to the environment and human health. This study combines optical, rock magnetic, and geochemical analyses of fly ash originating from Appalachian coal to develop an integrated suite of environmental coal ash tracers. The non-magnetic portion of power plant fly ash has higher abundance of clear spheres and clear amorphous particles, combined with enrichment of As, B, Th, Ba, Li, Se, Cd, Pb, and Tl. The magnetic fraction is enriched in opaque and orange spheres and Cu, U, V, Mo, Cr, Ni, and Co. Plerospheres occur in either fraction. We investigated ash-bearing fluvial sediment from Emory-Clinch River system that was impacted by the instantaneous TVA spill in 2008 and Hyco Lake in North Carolina that was contaminated by chronic releases of fly ash since 1964. Five years after the TVA spill, most ash in the riverbed reflects one population with trace element concentrations proportional to percent total ash. This relationship does not hold for As and Se, volatile elements associated with the outer surface of clear spheres, which are affected by river transport. At Hyco Lake, small clear and opaque spheres correlate with trace elements released from storage ponds. The combination of trace elements, fly ash morphology and rock magnetism provides a powerful set of tools to assess the distribution of ash and potential impact on the environment. We conclude that dispersal of fly ash to the aquatic environment, especially small clear and opaque spheres, should be avoided in favor of dry landfills.

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The direction of China's power supply side to cleaner transformation has become a foregone conclusion, the future will mainly rely on new energy and renewable energy, coal-powered units will gradually from the main power supply to the regulating power supply, standby power change. However, due to China's special policy background and the annual rise in coal costs, China's coal power prices have long been subject to high-cost squeeze, cost-price linkage failure one after another, the survival and development of coal power has brought great risks and challenges. Research shows that the policy changes experienced by China's coal power is the primary reason for its cost system composition and price formation. Therefore, this paper takes the evolution of China's coal power reform policy as the entry point for research, reanalyze the cost composition system of coal-fired power and summarize its impact on the cost of coal-fired power, and puts forward suggestions on cost control in the dimension of sustainable development of coal power, which provides an effective reference to the planning and deployment of solving the predicament of transitioning coal power and narrowing down the profit loss.

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CO is a hazardous and pollutant gas that can be produced in many scenarios of coal-related operations. The study mainly investigated CO production process and mechanism when coal is subject to external forces. The effects of coal type, particle size, temperature, and inlet atmosphere on CO production from coal body fragmentation were investigated through coal loading experiments. Materials Studio software was used to carry out coal macromolecular mechanics simulation and molecular dynamics simulation, and the gas production mechanism of coal under loading was explored at the molecular level. It was found that under air atmosphere, the low degree of deterioration, small particle size, and elevated temperature are all more likely to cause coal samples to fragment and decompose to produce CO. The carbonyl group in the molecular structure of coal is shed or broken free radical fragments react with oxygen which may lead to CO formation.

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The objective of this study is to investigate the dynamic mechanical properties of coal and rock under deep water conditions. The research employs an enhanced Split Hopkinson Pressure Bar (SHPB) testing system. Five sets of dynamic impact experiments were conducted on coal samples under varying loading conditions to analyse the changes in dynamic strength, energy dissipation, fractal dimension and other characteristics of coal samples under different water content states were analyzed. The experimental results demonstrate that: (1) Under specific strain rate conditions, the dynamic strength of saturated coal samples is lower than that of natural coal samples. As the strain rate gradually increases, the bonding force generated by free water and the Stefan effect jointly act, and the peak strength of saturated coal samples under high strain rate loading conditions is higher than that of natural coal samples. (2) Under certain strain rate conditions, the absorption energy of saturated coal samples is approximately 10% to30% lower than that of natural coal samples, and deformation hysteresis phenomenon occurs in natural coal samples, thereby improving the dynamic strength of natural coal samples relative to saturated coal samples; (3) The fractal dimension of saturated coal samples with a specific strain rate under three-dimensional dynamic static combination loading is higher than that of natural coal samples, and the percentage of small particle coal samples with debris is higher than that of natural coal samples; Finally, based on the HJC model, some coal samples were selected to simulate the coal rock failure characteristics during the triaxial loading process using ANSYS/LS-DYNA, and their stress-strain curves and failure morphology diagrams were obtained. The discrepancy between the numerical simulation and the experimental results was less than 10%, thereby further elucidating and corroborating the coal failure process and dynamic mechanical characteristics.

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In order to find out the main causes of coal mine safety accidents and improve the pertinence of coal mine safety risk management and control, the identification and analysis of coal mine safety risks and hidden dangers are carried out based on the analysis of coal mine accident reports. Combing the complex network theory, a complex network model for the evolution of coal mine safety risks is constructed. The key elements that affect coal mine safety risk accidents are obtained through quantitative research on the characteristic indicators of the complex network model of coal mine safety risks. And the key nodes of coal mine safety risk spread network are obtained through network interference to the overall efficiency. The research results show that the complex network of coal mine safety risks illustrate the characteristics of a small-world network, and the spread of a certain risk is likely to cause coal mine safety accidents. Strengthening the risk management and control of hidden dangers with higher intermediate centrality can isolate the spread of coal mine safety risks and reduce the possibility of coal mine accidents.

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Coal seam mining causes fracture and movement of overlying strata in goaf, and endangers the safety of surface structures and underground pipelines. Based on the engineering geological conditions of 22,122 working face in Cuncaota No.2 Coal Mine of China Shenhua Shendong Coal Group Co., Ltd. a similar material model test of mining overburden rock was carried out. The subsidence of overburden rock was obtained through the full-section strain data of distributed optical fiber technology, and the characteristics of mining surface subsidence were studied. The Weibull model was used to adjust the mathematical form of the first half of the surface subsidence curve via the MMF function. On this basis, the prediction model of coal seam mining surface subsidence was established, and the parameters of the prediction model of surface subsidence were determined. The test results show that with the advancement of coal seam mining, the fit goodness of the surface subsidence prediction curve based on the MMF optimization model reaches 0.987. Compared with the measured values, the relative error of the surface subsidence prediction model is reduced to less than 10%. The model displays good prediction accuracy. The time required for settlement stability in the prediction model is positively correlated with parameter a and negatively correlated with parameter b. The research results can be further extended to the prediction of overburden "three zones" subsidence, and provide a scientific basis for the evaluation of surface subsidence compression potential in coal mine goaf.

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Groundwater is one of the chief water sources for agricultural activities in an aggregation of coal mines surrounded by agricultural areas in the Huaibei Plain. However, there have been few reports on whether mining-affected groundwater can be adopted for agricultural irrigation. We attempted to address this question through collecting 71 shallow groundwater samples from 12 coal mining locations. The Piper trilinear chart, the Gibbs diagram, the proportional coefficient of major ions, and principal component analysis were examined to characterize the source, origin, and formation process of groundwater chemical composition. The suitability for agricultural irrigation was evaluated by a final zonation map that establishes a comprehensive weighting model based on analytic hierarchy process and criteria importance though the intercriteria correlation (AHP-CRITIC). The results revealed that the groundwater was classified as marginally alkaline water with a predominant cation of HCO3- and anion of Na+. Total hardness, total dissolved solids, sulfate (SO42-), sodium (Na+), and fluoride (F-) were the primary ions that exceeded the standard. The results also indicated that the dominant hydrochemical facies were Ca-HCO3 and Na-Cl. The dissolution of carbonate, silicate, sulfate minerals, along with cation exchange, were the main natural drivers controlling the hydrogeochemical process of groundwater. The zonation map suggested that 43.17%, 18.85%, and 37.98% of the study area were high, mediate, and low suitability zones, respectively. These results from this study can support policymakers for better managing groundwater associated with a concentration of underground coal mines.

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Coal mining activities greatly damage water resources, explicitly concerning water quality. The adverse effects of coal mining and potential routes for contaminants to migrate, either through surface water or infiltration, into the groundwater table. Dealing with pollution from coal mining operations is a significant surface water contamination concern. Consequently, surface water resources get contaminated, harming nearby agricultural areas, drinking water sources, and aquatic habitats. Moreover, the percolation process connected with coal mining could alter groundwater quality. Subsurface water sources can get contaminated by toxins generated during mining activities that infiltrate the soil and reach the groundwater table. The aims of this study are the creation of models and the provision of proposals for corrective measures. Twenty-five scenarios were simulated using MODFLOW; according to the percolation percentage and contamination, 35% of the study area, i.e., the middle of the research area, was the most affected. About 38.08% of the area around the mining zones surrounding Margherita is prone to floods. Agricultural areas, known for applying chemical fertilizers, are particularly vulnerable, generating a risk of pollution to surrounding water bodies during flooding. The outputs of this research contribute to identifying and assessing flood-vulnerable regions, enabling focused measures for flood risk reduction, and strengthening water resource management.

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Coal mining in the Loess Plateau can very easily generate ground cracks, and these cracks can immediately result in ventilation trouble under the mine shaft, runoff disturbance, and vegetation destruction. Advanced UAV (Unmanned Aerial Vehicle) high-resolution mapping and DL (Deep Learning) are introduced as the key methods to quickly delineate coal mining ground surface cracks for disaster prevention. Firstly, the dataset named the Ground Cracks of Coal Mining Area Unmanned Aerial Vehicle (GCCMA-UAV) is built, with a ground resolution of 3 cm, which is suitable to make a 1:500 thematic map of the ground crack. This GCCMA-UAV dataset includes 6280 images of ground cracks, and the size of the imagery is 256 × 256 pixels. Secondly, the DRA-UNet model is built effectively for coal mining ground surface crack delineation. This DRA-UNet model is an improved UNet DL model, which mainly includes the DAM (Dual Dttention Dechanism) module, the RN (residual network) module, and the ASPP (Atrous Spatial Pyramid Pooling) module. The DRA-UNet model shows the highest recall rate of 77.29% when the DRA-UNet was compared with other similar DL models, such as DeepLabV3+, SegNet, PSPNet, and so on. DRA-UNet also has other relatively reliable indicators; the precision rate is 84.92% and the F1 score is 78.87%. Finally, DRA-UNet is applied to delineate cracks on a DOM (Digital Orthophoto Map) of 3 km2 in the mining workface area, with a ground resolution of 3 cm. There were 4903 cracks that were delineated from the DOM in the Huojitu Coal Mine Shaft. This DRA-UNet model effectively improves the efficiency of crack delineation.

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Accurately obtaining the geological characteristic digital model of a coal seam and surrounding rock in front of a fully mechanized mining face is one of the key technologies for automatic and continuous coal mining operation to realize an intelligent unmanned working face. The research on how to establish accurate and reliable coal seam digital models is a hot topic and technical bottleneck in the field of intelligent coal mining. This paper puts forward a construction method and dynamic update mechanism for a digital model of coal seam autonomous cutting by a coal mining machine, and verifies its effectiveness in experiments. Based on the interpolation model of drilling data, a fine coal seam digital model was established according to the results of geological statistical inversion, which overcomes the shortcomings of an insufficient lateral resolution of lithology and physical properties in a traditional geological model and can accurately depict the distribution trend of coal seams. By utilizing the numerical derivation of surrounding rock mining and geological SLAM advanced exploration, the coal seam digital model was modified to achieve a dynamic updating and optimization of the model, providing an accurate geological information guarantee for intelligent unmanned coal mining. Based on the model, it is possible to obtain the boundary and inclination information of the coal seam profile, and provide strategies for adjusting the height of the coal mining machine drum at the current position, achieving precise control of the automatic height adjustment of the coal mining machine.

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Understanding the sources of mercury (Hg) in coal is crucial for understanding the natural Hg cycle in the Earth's system, as coal is a natural Hg reservoir. We conducted analyses on the mass-dependent fractionation (MDF), reported as δ202Hg, and mass-independent fractionation (MIF), reported as Δ199Hg, of Hg isotopes among individual Hg species and total Hg (THg) in Chinese coal samples. This data, supplemented by a review of prior research, allowed us to discern the varying trend of THg isotope fractionation with coal THg content. The Hg isotopic composition among identified Hg species in coal manifests notable disparities, with species exhibiting higher thermal stability tending to have heavier δ202Hg values, whereas HgS species typically display the most negative Δ199Hg values. The sources of Hg in coal are predominantly attributed to Hg accumulation from the original plant material and subsequent input from hydrothermal activity. Hg infiltrates peat swamps via vegetation debris, thus acquiring a negative Δ199Hg isotopic signature. Large-scale lithospheric Hg recycling via plate tectonics facilitates the transfer of Hg with a positive Δ199Hg from marine reservoirs to the deep crust. The later-stage hydrothermal input of Hg with a positive Δ199Hg enhances coal Hg content. This process has resulted in an upward trend of Δ199Hg values corresponding with the increase in coal THg content, ultimately leading to near-zero Δ199Hg in high-Hg coals. Coal Hg reservoirs are affected by large-scale natural Hg cycling, which involves the exchange of Hg between continents and seas.

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The persistent reliance on coal has resulted in the accumulation of substantial coal gangue, a globally recognized problematic solid waste with environmental risks. Given the coal gangue properties and global land degradation severity, the resourceful utilization of coal gangue as soil conditioners is believed to be a universally applicable, cost-effective, high-demand and environment-friendly model with broad application prospect. The direct application of raw coal gangue faces challenges of low active beneficial ingredients, inadequate water and fertilizer retention, presence of potentially toxic elements, resulting in limited efficacy and environmental contamination. This paper provided a comprehensive review of various modification methods (including mechanical, chemical, microbiological, thermal, hydrothermal and composite modifications) employed to enhance the soil improvement performance and reduce the environmental pollution of coal gangue. Furthermore, an analysis was conducted on the potential application of modified coal gangue as a muti-function soil conditioner based on its altered properties. The modified coal gangue is anticipated to effectively enhance soil quality, exhibiting significant potential in mitigating carbon emissions and facilitating soil carbon sequestration. This paper provided innovative ideas for future research on the comprehensive treatment of coal gangue and restoration of degraded soil in order to achieve the dual goals of zero-coal gangue waste and sustainable agriculture.