Search Results (2,465)

Efficient and clean utilization remains a pivotal development focus within the coal industry. Nevertheless, the application of weakly caking coal results in energy loss due to the caking property, thereby leading to a waste of resources. This paper, therefore, concentrates on the caking property, offering insights into the relevant caking mechanism, evaluation indexes, and regulation technologies associated with it. The caking mechanism delineates the transformation process of coal into coke. During pyrolysis, the active component generates the plastic mass in which gas, liquid, and solid phases coexist. With an increase in temperature, the liquid phase is diminished gradually, causing the inert components to bond. Based on the caking mechanism, evaluation indexes such as that characteristic of char residue, the caking index, and the maximal thickness of the plastic layer are proposed. These indexes are used to distinguish the strength of the caking property. However, they frequently exhibit a poor differentiation ability and high subjectivity. Additionally, some technologies have been demonstrated to regulate the caking property. Technologies such as rapid heating treatment and hydrogenation modification increase the amount of plastic mass generated, thereby improving the caking property. Meanwhile, technologies such as mechanical breaking and pre-oxidation reduce the caking property by destroying agglomerates or consuming plastic mass. Full article

To remain competitive in the decarbonization process of the economy worldwide, energy companies must preserve their market value to attract new investors and remain resilient throughout the transition to net zero. This article examines the market value of US energy companies during the period 2012–2024 in relation to their power generation mix. Panel regression analyses reveal that Tobin’s q and price-to-book ratios increase significantly for solar and wind power, while they experience moderate increases for natural gas power. In contrast, Tobin’s q and price-to-book ratios decline for nuclear and coal power. Furthermore, accounting-based profitability, measured by the return on assets (ROA), does not show significant variation with any type of power generation. The findings suggest that market investors prefer solar, wind, and natural gas power generation, thereby attributing greater value (that is, demanding lower risk compensation) to green companies compared to traditional ones. These insights provide guidance to executives, investors, and policy makers on how the power generation mix can influence strategic decisions in the energy sector. Full article

Understanding how energy use and economic activity shape carbon emissions is pivotal for achieving global climate targets. This study quantifies the dynamic nexus between disaggregated energy consumption, economic growth, and CO₂ emissions in India and China—two economies that together account for more than one-third of global emissions. Using annual data from 1990 to 2021, we implement Long Short-Term Memory (LSTM) neural networks, which outperform traditional linear models in capturing nonlinearities and lagged effects. The dataset is split into training (1990–2013) and testing (2014–2021) intervals to ensure rigorous out-of-sample validation. Results reveal stark national differences. For India, coal, natural gas consumption, and economic growth are the strongest positive drivers of emissions, whereas renewable energy exerts a significant mitigating effect, and nuclear energy is negligible. In China, emissions are dominated by coal and petroleum use and by economic growth, while renewable and nuclear sources show weak, inconsistent impacts. We recommend retrofitting India’s coal- and gas-plants with carbon capture and storage, doubling clean-tech subsidies, and tripling annual solar-plus-storage auctions to displace fossil baseload. For China, priorities include ultra-supercritical upgrades with carbon capture, utilisation, and storage, green-bond-financed solar–wind buildouts, grid-scale storage deployments, and hydrogen-electric freight corridors. These data-driven pathways simultaneously cut flagship emitters, decouple GDP from carbon, provide replicable models for global net-zero research, and advance climate-resilient economic growth worldwide. Full article

The impact mechanism of long-term creep in gas-containing coal on coal and gas outbursts has not been fully elucidated and remains insufficiently understood for the purpose of disaster engineering control. This investigation conducted triaxial creep experiments on raw coal specimens under controlled confining pressures, axial stresses, and gas pressures. Through systematic analysis of coal’s physical responses across different loading conditions, we developed and validated a novel creep damage constitutive model for gas-saturated coal through laboratory data calibration. The key findings reveal three characteristic creep regimes: (1) a decelerating phase dominates under low stress conditions, (2) progressive transitions to combined decelerating–steady-state creep with increasing stress, and (3) triphasic decelerating–steady–accelerating behavior at critical stress levels. Comparative analysis shows that gas-free specimens exhibit lower cumulative strain than the 0.5 MPa gas-saturated counterparts, with gas presence accelerating creep progression and reducing the time to failure. Measured creep rates demonstrate stress-dependent behavior: primary creep progresses at 0.002–0.011%/min, decaying exponentially to secondary creep rates below 0.001%/min. Steady-state creep rates follow a power law relationship when subject to deviatoric stress (R² = 0.96). Through the integration of Burgers viscoelastic model with the effective stress principle for porous media, we propose an enhanced constitutive model, incorporating gas adsorption-induced dilatational stresses. This advancement provides a theoretical foundation for predicting time-dependent deformation in deep coal reservoirs and informs monitoring strategies concerning gas-bearing strata stability. This study contributes to the theoretical understanding and engineering monitoring of creep behavior in deep coal rocks. Full article

The Junggar Basin contains a large amount of coal resources and is an important coal production base in China. The coal seam in Zhundong coalfield has a large single-layer thickness and high content of inertinite, but large particle Fe-sulphide minerals are associated with coal seams in some mining areas. A series of economic and environmental problems caused by the combustion of large-grained Fe-sulphide minerals in coal have seriously affected the economic, clean and efficient utilization of coal. In this paper, the ultra-thick coal seam of the Xishanyao formation in the Yihua open-pit mine of the Zhundong coalfield is taken as the research object. Through the analysis of coal quality, X-ray fluorescence spectrometer test of major elements in coal, inductively coupled plasma mass spectrometry test of trace elements, SEM-Raman identification of Fe-sulphide minerals in coal and LA-MC-ICP-MS test of sulfur isotope of marcasite, the coal quality characteristics, main and trace element characteristics, macro and micro occurrence characteristics of Fe-sulphide minerals and sulfur isotope characteristics of marcasite in the ultra-thick coal seam of the Xishanyao formation are tested. On this basis, the occurrence state and genesis of large particle Fe-sulphide minerals in the ultra-thick coal seam of the Xishanyao formation are clarified. The main results and understandings are as follows: (1) the occurrence state of Fe-sulphide minerals in extremely thick coal seams is clarified. The Fe-sulphide minerals in the extremely thick coal seam are mainly marcasite, and concentrated in the YH-2, YH-3, YH-8, YH-9, YH-14, YH-15 and YH-16 horizons. Macroscopically, Fe-sulphide minerals mainly occur in three forms: thin film Fe-sulphide minerals, nodular Fe-sulphide minerals, and disseminated Fe-sulphide minerals. Microscopically, they mainly occur in four forms: flake, block, spearhead, and crack filling. (2) The difference in sulfur isotope of marcasite was discussed, and the formation period of marcasite was preliminarily divided. The overall variation range of the δ³⁴S value of marcasite is wide, and the extreme values are quite different. The polyflake marcasite was formed in the early stage of diagenesis and the δ³⁴S value was negative, while the fissure filling marcasite was formed in the late stage of diagenesis and the δ³⁴S value was positive. (3) The coal quality characteristics of the thick coal seam were analyzed. The organic components in the thick coal seam are mainly inertinite, and the inorganic components are mainly clay minerals and marcasite. (4) The difference between the element content in the thick coal seam of the Zhundong coalfield and the average element content of Chinese coal was compared. The major element oxides in the thick coal seam are mainly CaO and MgO, followed by SiO₂, Al₂O₃, Fe₂O₃ and Na₂O. Li, Ga, Ba, U and Th are enriched in trace elements. (5) The coal-accumulating environment characteristics of the extremely thick coal seam are revealed. The whole thick coal seam is formed in an acidic oxidation environment, and the horizon with Fe-sulphide minerals is in an acidic reduction environment. The acidic reduction environment is conducive to the formation of marcasite and is not conducive to the formation of pyrite. (6) There are many matrix vitrinite, inertinite content, clay content, and terrigenous debris in the extremely thick coal seam. The good supply of peat swamp, suitable reduction environment and pH value, as well as groundwater leaching and infiltration, together cause the occurrence of large-grained Fe-sulphide minerals in the extremely thick coal seam of the Xishanyao formation in the Zhundong coalfield. Full article

In the context of intelligent coal mine safety monitoring, an integrated prediction and early-warning method named MTGNN-Bayesian-IF-DBSCAN (Multi-Task Graph Neural Network–Bayesian Optimization–Isolation Forest–Density-Based Spatial Clustering of Applications with Noise) is proposed to address the challenges of gas concentration prediction and anomaly detection in coal mining faces. The MTGNN (Multi-Task Graph Neural Network) is first employed to model the spatiotemporal coupling characteristics of gas concentration and wind speed data. By constructing a graph structure based on sensor spatial dependencies and utilizing temporal convolutional layers to capture long short-term time-series features, the high-precision dynamic prediction of gas concentrations is achieved via the MTGNN. Experimental results indicate that the MTGNN outperforms comparative algorithms, such as CrossGNN and FourierGNN, in prediction accuracy, with the mean absolute error (MAE) being as low as 0.00237 and the root mean square error (RMSE) maintained below 0.0203 across different sensor locations (T0, T1, T2). For anomaly detection, a Bayesian optimization framework is introduced to adaptively optimize the fusion weights of IF (Isolation Forest) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). Through defining the objective function as the F1 score and employing Gaussian process surrogate models, the optimal weight combination (w_if = 0.43, w_dbscan = 0.52) is determined, achieving an F1 score of 1.0. By integrating original concentration data and residual features, gas anomalies are effectively identified by the proposed method, with the detection rate reaching a range of 93–96% and the false alarm rate controlled below 5%. Multidimensional analysis diagrams (e.g., residual distribution, 45° diagonal error plot, and boxplots) further validate the model’s robustness in different spatial locations, particularly in capturing abrupt changes and low-concentration anomalies. This study provides a new technical pathway for intelligent gas warning in coal mines, integrating spatiotemporal modeling, multi-algorithm fusion, and statistical optimization. The proposed framework not only enhances the accuracy and reliability of gas prediction and anomaly detection but also demonstrates potential for generalization to other industrial sensor networks. Full article

The synergistic development of low-permeability reservoirs such as deep coalbed methane (CBM) and tight gas has emerged as a key technology to reduce development costs, enhance single-well productivity, and improve gas recovery. However, due to fundamental differences between coal seams and tight sandstones in their pore structure, permeability, water saturation, and pressure sensitivity, significant variations exist in their flow capacities and fluid production behaviors. To address the challenges of production allocation and main reservoir identification in the co-development of CBM and tight gas within deep gas-bearing basins, this study employs the transient multiphase flow simulation software OLGA to construct a representative dual-gas co-production well model. The regulatory mechanisms of the gas–liquid distribution, deliquification efficiency, and interlayer interference under two typical vertical stacking relationships—“coal over sand” and “sand over coal”—are systematically analyzed with respect to different tubing setting depths. A high-precision dynamic production allocation method is proposed, which couples the wellbore structure with real-time monitoring parameters. The results demonstrate that positioning the tubing near the bottom of both reservoirs significantly enhances the deliquification efficiency and bottomhole pressure differential, reduces the liquid holdup in the wellbore, and improves the synergistic productivity of the dual-reservoirs, achieving optimal drainage and production performance. Building upon this, a physically constrained model integrating real-time monitoring data—such as the gas and liquid production from tubing and casing, wellhead pressures, and other parameters—is established. Specifically, the model is built upon fundamental physical constraints, including mass conservation and the pressure equilibrium, to logically model the flow paths and phase distribution behaviors of the gas–liquid two-phase flow. This enables the accurate derivation of the respective contributions of each reservoir interval and dynamic production allocation without the need for downhole logging. Validation results show that the proposed method reliably reconstructs reservoir contribution rates under various operational conditions and wellbore configurations. Through a comparison of calculated and simulated results, the maximum relative error occurs during abrupt changes in the production capacity, approximately 6.37%, while for most time periods, the error remains within 1%, with an average error of 0.49% throughout the process. These results substantially improve the timeliness and accuracy of the reservoir identification. This study offers a novel approach for the co-optimization of complex multi-reservoir gas fields, enriching the theoretical framework of dual-gas co-production and providing technically adaptive solutions and engineering guidance for multilayer unconventional gas exploitation. Full article

Cities serve as the primary arenas for achieving the strategic objectives of “carbon peak and carbon neutrality”. This study employed the LMDI method to systematically analyze the evolution trend of energy-related carbon emissions in Hong Kong and their influencing factors from 1980 to 2023. The main findings are as follows: (1) Hong Kong’s energy consumption structure remains dominated by coal and oil. Influenced by energy prices, significant shifts in this structure occurred across different periods. Imported electricity from mainland China, in particular, has exerted a promoting effect on the optimization of its energy consumption mix. (2) Economic output and population concentration are the primary drivers of increased carbon emissions. However, the contribution of economic growth to carbon emissions has gradually weakened in recent years due to a lack of new growth drivers. (3) Energy consumption intensity, energy consumption structure, and carbon intensity are the primary influencing factors in curbing carbon emissions. Among these, the carbon reduction impact of energy consumption intensity is the most significant. Hong Kong should continue to adopt a robust strategy for controlling total energy consumption to effectively mitigate carbon emissions. Additionally, it should remain vigilant regarding the potential implications of future energy price fluctuations. It is also essential to sustain cross-border energy cooperation, primarily based on electricity imports from the Pearl River Delta, while simultaneously expanding international and domestic supply channels for natural gas. 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 development of deep coalbed methane (buried depth > 2000 m) in the Yan’an block of Ordos Basin is limited by low permeability, the pore structure of the coal reservoir, and the gas–water occurrence relationship. It is urgent to clarify the key control mechanism of pore structure on gas migration. In this study, based on high-pressure mercury intrusion (pore size > 50 nm), low-temperature N₂/CO₂ adsorption (0.38–50 nm), low-field nuclear magnetic resonance technology, fractal theory and Pearson correlation coefficient analysis, quantitative characterization of multi-scale pore–fluid system was carried out. The results show that the multi-scale pore network in the study area jointly regulates the occurrence and migration process of deep coalbed methane in Yan’an through the ternary hierarchical gas control mechanism of ‘micropore adsorption dominant, mesopore diffusion connection and macroporous seepage bottleneck’. The fractal dimensions of micropores and seepage are between 2.17–2.29 and 2.46–2.58, respectively. The shape of micropores is relatively regular, the complexity of micropore structure is low, and the confined space is mainly slit-like or ink bottle-like. The pore-throat network structure is relatively homogeneous, the difference in pore throat size is reduced, and the seepage pore shape is simple. The bimodal structure of low-field nuclear magnetic resonance shows that the bound fluid is related to the development of micropores, and the fluid mobility mainly depends on the seepage pores. Pearson’s correlation coefficient showed that the specific surface area of micropores was strongly positively correlated with methane adsorption capacity, and the nanoscale pore-size dominated gas occurrence through van der Waals force physical adsorption. The specific surface area of mesopores is significantly positively correlated with the tortuosity. The roughness and branch structure of the inner surface of the channel lead to the extension of the migration path and the inhibition of methane diffusion efficiency. Seepage porosity is linearly correlated with gas permeability, and the scale of connected seepage pores dominates the seepage capacity of reservoirs. This study reveals the pore structure and ternary grading synergistic gas control mechanism of deep coal reservoirs in the Yan’an Block, which provides a theoretical basis for the development of deep coalbed methane. Full article

Fischer–Tropsch synthesis (FTS) facilitates the conversion of syngas, derived from feedstocks such as biomass, coal, and natural gas, into valuable hydrocarbons (HCs). This investigation employed optimization methods, specifically Gibbs energy minimization, to perform a thermodynamic characterization of the low-temperature Fischer–Tropsch (LTFT) reaction for HC generation. The CONOPT3 solver within GAMS 23.2.1 software was utilized for solving the developed model. To represent the complex FTS product spectrum, twenty-three compounds, encompassing C₂–C₂₀ aliphatic hydrocarbons, were considered using a stoichiometric framework. The study explored the impact of operational parameters, including temperature (350–550 K), pressure (5–30 bar), and H₂/CO molar feed ratio (1.0–2.0/0.5–1.0), on hydrocarbon synthesis. Evaluation of the outcomes focused on HC yield and product characteristics. A significant sensitivity of the reaction to operating parameters was observed. Notably, lower temperatures, elevated pressures, and a H₂/CO ratio of 2.0/1.0 were identified as optimal for fostering the formation of longer-chain HCs. The developed model demonstrated robustness and efficiency, with rapid computation times across all simulations. Full article

In comparison to shallow coal seams, deep coal seams exhibit characteristics of high temperature, pressure, and in-situ stress, leading to significant differences in reservoir properties that constrain the effective development of deep coalbed methane (CBM). This study takes the Carboniferous deep 8# coal seam in the Yulin area of Ordos basin as the research subject. Based on the test results from core drilling wells, a comprehensive analysis of the characteristics and variation patterns of coal reservoir properties and a comparative analysis of the exploration and development potential of deep CBM are conducted, aiming to provide guidance for the development of deep CBM in the Ordos basin. The research results indicate that the coal seams are primarily composed of primary structure coal, with semi-bright to bright being the dominant macroscopic coal types. The maximum vitrinite reflectance (R_o,max) ranges between 1.99% and 2.24%, the organic is type III, and the high Vitrinite content provides a substantial material basis for the generation of CBM. Longitudinally, influenced by sedimentary environment and plant types, the lower part of the coal seam exhibits higher Vitrinite content and fixed carbon (FC_ad). The pore morphology is mainly characterized by wedge-shaped/parallel plate-shaped pores and open ventilation pores, with good connectivity, which is favorable for the storage and output of CBM. Micropores (<2 nm) have the highest volume proportion, showing an increasing trend with burial depth, and due to interlayer sliding and capillary condensation, the pore size (<2 nm) distribution follows an N shape. The full-scale pore heterogeneity (fractal dimension) gradually increases with increasing buried depth. Macroscopic fractures are mostly found in bright coal bands, while microscopic fractures are more developed in Vitrinite, showing a positive correlation between fracture density and Vitrinite content. The porosity and permeability conditions of reservoirs are comparable to the Daning–Jixian block, mostly constituting oversaturated gas reservoirs with a critical depth of 2400–2600 m and a high proportion of free gas, exhibiting promising development prospects, and the middle and upper coal seams are favorable intervals. In terms of resource conditions, preservation conditions, and reservoir alterability, the development potential of CBM from the Carboniferous deep 8# coal seam is comparable to the Linxing block but inferior to the Daning–Jixian block and Baijiahai uplift. Full article

This study suggests a method for analyzing the risk of methane explosions using the N-K model and Social Network Analysis (SNA) to understand how different risk factors related to coal-mine methane explosions are connected and change over time, aiming to prevent these accidents effectively. We identified 41 secondary risk factors and four fundamental risk factors—human, equipment, environment, and management—based on the 4M accident causation theory. The SNA model was utilized to determine the main risk factors and their evolutionary routes, while the N-K model was utilized to quantify the degree of risk coupling. The findings show that the number of risk variables engaged in the methane-explosion risk system closely correlates with the number of accidents that occur and the maximum coupling level among the four elements. The primary control factors in the methane-explosion risk system are poor equipment management, broken safety monitoring and control systems, inadequate safety education and training, safety regulation violations, and poor safety production responsibility system implementation. We utilized the primary evolution paths and key elements to propose risk control approaches. A reference for ensuring safety in coal-mine operations can be found in the research findings. Full article

Co-firing large-sized straw biomass in pulverized coal boilers is a potential pathway for carbon emission reduction in China’s thermal power plants. However, experimental data on large-sized straw combustion under pulverized coal boiler combustion conditions are critically lacking. This study selected typical large-sized wheat straw particles. Employing a two-mode experimental setup in a drop tube furnace (DTF) system simulating pulverized coal boiler conditions, we systematically investigated the combustion behavior and alkali metal release characteristics of this large-sized straw biomass, with combustion processes summarized for diverse particle types. The findings reveal asynchronous combustion progression across particle surfaces due to heterogeneous mass transfer and gas diffusion; unique behaviors distinct from denser woody biomass, including bending deformation, fiber branching, and fragmentation, occur; significant and morphology-specific deformations occur during devolatilization; fragmentation universally produces particles of varied shapes (needle-like, flaky, blocky, semi-tubular) during char combustion; and potassium release exceeds 35% after complete devolatilization and surpasses 50% at a burnout degree exceeding 80%. This work provides essential experimental data on the fundamental combustion characteristics and alkali metal release of large-sized wheat straw particles under pulverized coal boiler combustion conditions, offering engineering application guidance for the direct co-firing of large-sized flexible straw biomass in pulverized coal boilers. Full article

To compensate for the instability of renewable energy sources during China’s energy transition, large thermal power plants must provide critical operational flexibility, primarily through deep peaking. To investigate the combustion performance and wear and tear of a 600 MW pulverized coal boiler under deep peaking, the gas–solid flow characteristics and distributions of flue gas temperature, wall heat flux, and wall wear rate in a 600 MW tangentially fired pulverized coal boiler under variable loads (353 MW, 431 MW, 519 MW, and 600 MW) are investigated in this study employing computational fluid dynamics numerical simulation method. Results demonstrate that increasing the boiler load significantly amplifies gas velocity, wall heat flux, and wall wear rate. The maximum gas velocity in the furnace rises from 20.9 m·s⁻¹ (353 MW) to 37.6 m·s⁻¹ (600 MW), with tangential airflow forming a low-velocity central zone and high-velocity peripheral regions. Meanwhile, the tangential circle diameter expands by ~15% as the load increases. The flue gas temperature distribution exhibits a “low-high-low” profile along the furnace height. As the load increases from 353 MW to 600 MW, the primary combustion zone’s peak temperature rises from 1750 K to 1980 K, accompanied by a ~30% expansion in the coverage area of the high-temperature zone. Wall heat flux correlates strongly with temperature distribution, peaking at 2.29 × 10⁵ W·m⁻² (353 MW) and 2.75 × 10⁵ W·m⁻² (600 MW) in the primary combustion zone. Wear analysis highlights severe erosion in the economizer due to elevated flue gas velocities, with wall wear rates escalating from 3.29 × 10⁻⁷ kg·m⁻²·s⁻¹ (353 MW) to 1.23 × 10⁻⁵ kg·m⁻²·s⁻¹ (600 MW), representing a 40-fold increase under full-load conditions. Mitigation strategies, including ash removal optimization, anti-wear covers, and thermal spray coatings, are proposed to enhance operational safety. This work provides critical insights into flow field optimization and wear management for large-scale coal-fired boilers under flexible load operation. Full article