Search Results (48)

Coal mining provides energy and economic benefits but also causes environmental damage, including land degradation, pollution, and surface temperature anomalies. Underground coal fires can severely impact the environment, leading to abnormal heat, ground deformation, and ecological harm. Using Landsat-9 imagery and meteorological data, we developed a new threshold-based method to detect large-scale land surface temperature anomalies (LSTAs). By analyzing multiple images from November to February, we improved the accuracy of this method. The LSTA data were integrated with topographic indexes and different coal seam depths to filter irrelevant points. A Wilcoxon test, correlation analysis, and linear regression were performed with the LSTA multi-data matrix to quantify the relationships between the topographical and temperature indexes. The results revealed significant differences in elevation (relative elevation), slope, and TWI across different coal seam depths (p < 0.001). LST distribution in November, December, and February was significantly different among the three different seam depth units (p < 0.001). Relative elevation strongly correlated with temperature. The relationship between relative elevation and temperature may change seasonally due to seasonal climatic fluctuations and heterogeneous underlying surface characteristics. Full article

Coal fires are disasters that occur when underground coal seams are subjected to combustion conditions induced by natural or human factors. This study attempts to investigate the impact of coal fires on the surrounding environment by assessing the eco-environmental quality and its dynamic changes in the Surablak coal fire area. To achieve this, an improved remote sensing ecological index (termed RSEIds) is introduced to assess and track the quality and dynamics of eco-environmental conditions in the Surablak coal fire area from 1990 to 2022. Subsequently, this index is combined with a geographic detector (GeoDetector) model to identify potential factors influencing eco-environmental quality. The findings indicate that (1) compared with the established Remote Sensing Ecological Index (RSEI), the RSEIds provides a high degree of precision in reflecting the eco-environmental conditions within the regions affected by coal fires, (2) the eco-environmental quality within the Surablak coal fire area underwent a continuous deterioration from 1990 to 2022, with the area of ecological degradation constituting 53.41% of the study region, (3) regions with excellent and good RSEIds values are mainly found in the forested mountainous regions located in the northern section of the coal fire area, whereas regions with poor and fair RSEIds values largely coincide with the coal fire locations, and (4) since 2006, the distance to the coal fire has become the key factor influencing eco-environmental quality in the Surablak area, while temperature and precipitation remained important factors. The outcomes of this study will provide essential references for guiding ecological restoration and promoting sustainable development in coal fire areas. Full article

We will continue to rely on fossil fuel energy generation for at least this century. Reducing our carbon footprint is vital for the welfare of our environment and human health. The province we live in, Saskatchewan, is the second-highest emitter of CO₂ in Canada. This is primarily due to our reliance on coal-fired power plants for electricity. The Boundary Dam power plant in Estevan, SK, is the first-ever commercial power plant equipped with CCS technology. The current CCS process is highly efficient in capturing its carbon dioxide emissions and storing them underground. As with any first-of-its-kind project, numerous operational challenges have occurred that have affected the capture plant availability and, in turn, resulted in reduced efficiency of the plant. One of the major concerns is fly ash accumulation on plant equipment, which causes outages and the accumulation of fly ash in the amine-based absorbent that is utilized for capturing CO₂. This is primarily due to the transfer of PMs in the fly ash from pre-conditioning to downstream equipment. This study identified three alternatives to address PM accumulation and improve the operation of the capture facility: using a water and oil column, a hybrid electrostatic precipitator, and polytetrafluoroethylene (PTFE) membrane filters. Full article

New data, including Raman spectroscopy, characterize unusual mineral assemblages from rocks of the Naylga and Khamaryn–Khyral–Khiid combustion metamorphic complexes in Mongolia. Several samples of melilite–nepheline paralava and other thermally altered (metamorphosed) sedimentary rocks contain troilite (FeS), metallic iron Fe⁰, kamacite α-(Fe,Ni) or Ni-bearing Fe⁰, taenite γ-(Fe,Ni) or Ni-rich Fe⁰, barringerite or allabogdanite Fe₂P, schreibersite Fe₃P, steadite Fe₄P = eutectic α-Fe + Fe₃P, wüstite FeO, and cohenite Fe₃C. The paralava matrix includes a fragment composed of magnesiowüstite–ferropericlase (FeO–MgO solid solution), as well as of spinel (Mg,Fe)Al₂O₄ and forsterite. The highest-temperature mineral assemblage belongs to a xenolithic remnant, possibly Fe-rich sinter, which is molten ash left after underground combustion of coal seams. The crystallization temperatures of the observed iron phases were estimated using phase diagrams for the respective systems: Fe–S for iron sulfides and Fe–P ± C for iron phosphides. Iron monosulfides (high-temperature pyrrhotite) with inclusions of Fe⁰ underwent solid-state conversion into troilite at 140 °C. Iron phosphides in inclusions from the early growth zone of anorthite–bytownite in melilite–nepheline paralava crystallized from <1370 to 1165 °C (Fe₂P), 1165–1048 °C (Fe₃P), and <1048 °C (Fe₄P). Phase relations in zoned spherules consisting of troilite +Fe⁰ (or kamacite + taenite) +Fe₃P ± (Fe₃C, Fe₄P) reveal the potential presence of a homogeneous Fe–S–P–C melt at T~1350 °C, which separated into two immiscible melts in the 1350–1250 °C range; namely, a dense Fe–P–C melt in the core and a less dense Fe–S melt in the rim. The melts evolved in accordance with cooling paths in the Fe–S and Fe–P–C phase diagrams. Cohenite and schreibersite in the spherules crystallized between 988 °C and 959 °C. The crystallization temperatures of minerals were used to reconstruct redox patterns with respect to the CCO, IW, IM, and MW buffer equilibria during melting of marly limestone and subsequent crystallization and cooling of melilite–nepheline paralava melts. The origin of the studied CM rocks was explained in a model implying thermal alteration of low-permeable overburden domains in reducing conditions during wild subsurface coal fires, while heating was transferred conductively from adjacent parts of ignited coal seams. The fluid (gas) regime in the zones of combustion was controlled by the CCO buffer at excess atomic carbon. Paralava melts exposed to high-temperature extremely reducing conditions contained droplets of immiscible Fe–S–P–C, Fe–S, Fe–P, and Fe–P–C melts, which then crystallized into reduced mineral assemblages. Full article

A large amount of energy can accumulate and be stored during underground coal fires. As thermal energy cannot be easily removed using the traditional technologies of fire prevention and extinguishment, there is a potential benefit to collecting and utilizing thermal energy from coal fires and converting it to electrical energy. Thus, this work proposes a thermoelectric generator as a solution to convert thermal energy from coal fires to electrical energy. To improve the thermal energy conversion efficiency, an experimental test system was established using a thermosyphon, an electric heating module, a cooling circulation module, a thermoelectric module, and a data acquisition module. Under the condition of ensuring the same input heat and cooling boundary conditions, the influence of three factors, namely the cooling method, the connection method, and the coverage rate of thermoelectric devices, on the performance of the coal fire waste heat conversion system was studied. The results show that, compared with air cooling, water cooling provides a greater temperature difference for the thermoelectric module, and the maximum temperature difference can reach 65.90 °C. Series connection between thermoelectric devices will generate a higher open-circuit voltage and output voltage. The maximum horizontal open-circuit voltage value can reach 3.34 V, and the maximum output voltage is 2.61 V. Compared with the coverage rates of thermoelectric devices of 15.0% and 30.0%, the output power under the coverage rate of 22.5% is the largest at 0.35 W, and its thermoelectric conversion efficiency is also the largest at 0.35%. The optimal combination of thermoelectric modules obtained from the research results can provide ideas for the application of in situ coal fire prevention and control. Full article

During the process of mining underground coal, the coal emits a large amount of methane into the mining space, which may lead to methane accumulation and exceed explosion safety limits When the methane encounters a fire source, a methane explosion may occur. The forceful impact caused by a methane explosion in an underground roadway can cause serious damage to the roadway structures and even lead to the collapse of the ventilation system. At the same time, the explosion impact may result in the death of workers and cause physical injury to the surviving workers. Therefore, it is necessary to study the damage effect and injury range of methane explosions. On the basis of the damage criteria and damage characteristics of methane explosions, according to the overpressure distribution of shock waves in the propagation process of a methane explosion, the explosion hazard range is divided into four ranges (from inside to outside): death range, serious injury range, minor injury range, and safety range. Four injury degrees of shock wave overpressure to personal body (slight, medium, serious injury, death), and seven damage degrees of overpressure to structures are also analyzed. The thresholds of their damage (destruction) are determined. On this basis, an experimental system and numerical simulation are constructed to measure damage characteristics, the overpressure value, and the range distance of a methane explosion with different initial explosion intensities. According to the experimental and numerical results, the attenuation formula of a methane explosion shock wave in the propagation process is derived. The research results show that the overpressure and impulse of shock waves are selected as the damage criteria for comprehensive evaluation, and the overpressure criterion is suitable of determining the injury (failure) range over long distances. The four injury ranges are in line with the actual situation and are reasonable. The injury degree also conforms to the medical results, which can be used to guide the injury degree of mine methane explosions. The injury range caused by methane explosions with different initial explosion intensities is reasonable and is basically consistent with the on-site situation. The derived attenuation formula and calculated safety distance are in good agreement with the experimental and numerical results. The research results can provide guidance and help in the escape, rescue, and protection of coal mine underground person. Full article

Current regulations mandate the monitoring of respirable coal mine dust (RCMD) mass and crystalline silica in underground coal mines to safeguard miner health. However, other RCMD characteristics, such as particle size and chemical composition, may also influence health outcomes. This study collected RCMD samples from two underground coal mines and performed detailed chemical speciation. Source apportionment was used to estimate RCMD and silica contributions from various sources, including intake air, fire suppression limestone dust, coal dust, diesel engine exhaust, and rock strata. The mine dust mass-based size distributions were comparable to those recorded over a decade ago, with a peak around 10 μm and the majority of the mass in the supermicron size range. The current mine conditions and mining practices do not appear to have significantly increased the generation of smaller particles. Limestone rock dust was prevalent in many locations and, along with coal dust, was the main contributor to RCMD at high-concentration locations. Silica accounted for over 10% of RCMD mass at several active mining locations, primarily from limestone and rock strata dust. Reducing the concentration of limestone dust and its silica content could reduce RCMD and silica levels. Further cleaning of the intake air could also improve the overall mine air quality. Full article

Mine fires have always been one of the disasters that restrict coal mining in China and endanger the life safety of underground workers. The research and development of new fire prevention materials are undoubtedly important to ensure the safe and efficient production of modern mines. At present, the main inhibiting materials used are grout material, inert gas, retarding agent, foam, gel, and so on. In order to explore the current situation of coal spontaneous combustion (CSC) fire prevention, the existing fire prevention materials were reviewed and prospected from three aspects: physical, chemical, and physicochemical inhibition. The results show that, at present, most of the methods of physicochemical inhibition are used to inhibit CSC. Antioxidants have become popular chemical inhibitors in recent years. In terms of physical inhibition, emerging biomass-based green materials, including foams, gels, and gel foams, are used to inhibit CSC. In addition, CSC fire-fighting materials also have shortcomings, including incomplete research on the mechanism of material action, poor stability of inhibitory properties, low efficiency, and economic and environmental protection to be improved. The future research direction of fire-fighting materials will be based on theoretical experiments and numerical simulation to study the mechanism and characteristics of CSC and develop new directional suppression materials with physicochemical synergies. These findings have extremely important implications for improving materials designed to prevent CSC. Full article

Fugitive methane emissions from the mining industry, particularly so-called ventilation air methane (VAM) emissions, are considered among the largest sources of greenhouse gas (GHG) emissions. VAM emissions not only contribute to the global warming but also pose a significant hazard to mining safety due to the risk of accidental fires and explosions. This research presents a novel approach that investigates the capture of CH₄ in a controlled environment using 1-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide [BMIM][TF₂N] ionic liquid (IL), which is an environmentally friendly solvent. The experimental and modelling results confirm that CH₄ absorption in [BMIM][TF2N], in a packed column, can be a promising technique for capturing CH₄ from point sources, particularly the outlet streams of ventilation shafts in underground coal mines, which typically accounts for <1% v/v of the flow. This study assessed the effectiveness of CH₄ removal in a packed bed column by testing various factors such as absorption temperature, liquid and gas flow rates, flow pattern, packing size, desorption temperature, and desorption pressure. According to the optimisation results, the following parameters can be used to achieve a CH₄ removal efficiency of 23.8%: a gas flow rate of 0.1 L/min, a liquid flow rate of 0.5 L/min, a packing diameter of 6 mm, and absorption and desorption temperatures of 303 K and 403.15 K, respectively. Additionally, the experimental results indicated that ILs could concentrate CH₄ in the simulated VAM stream by approximately 4 fold. It is important to note that the efficiency of CH₄ removal was determined to be 3.5-fold higher compared to that of N₂. Consequently, even though the VAM stream primarily contains N₂, the IL used in the same stream shows a notably superior capacity for removing CH₄ compared to N₂. Furthermore, CH₄ absorption with [BMIM][TF₂N] is based on physical interactions, leading to reduced energy requirements for regeneration. These findings validate the method’s effectiveness in mitigating CH₄ emissions within the mining sector and enabling the concentration of VAM through a secure and energy-efficient procedure. Full article

The collapse of open-pit coal mine slopes is a kind of severe geological hazard that may cause resource waste, economic loss, and casualties. On 22 February 2023, a large-scale collapse occurred at the Xinjing Open-Pit Mine in Inner Mongolia, China, leading to the loss of 53 lives. Thus, monitoring of the slope stability is important for preventing similar potential damage. It is difficult to fully obtain the temporal and spatial information of the whole mining area using conventional ground monitoring technologies. Therefore, in this study, multi-source remote sensing methods, combined with local geological conditions, are employed to monitor the open-pit mine and analyze the causes of the accident. Firstly, based on GF-2 data, remote sensing interpretation methods are used to locate and analyze the collapse area. The results indicate that high-resolution remote sensing can delineate the collapse boundary, supporting the post-disaster rescue. Subsequently, multi-temporal Radarsat-2 and Sentinel-1A satellite data, covering the period from mining to collapse, are integrated with D-InSAR and DS-InSAR technologies to monitor the deformation of both the collapse areas and the potential risk to dump slopes. The D-InSAR result suggests that high-intensity open-pit mining may be the dominant factor affecting deformation. Furthermore, the boundary between the collapse trailing edge and the non-collapse area could be found in the DS-InSAR result. Moreover, various data sources, including DEM and geological data, are combined to analyze the causes and trends of the deformation. The results suggest that the dump slopes are stable. Meanwhile, the deformation trends of the collapse slope indicate that there may be faults or joint surfaces of the collapse trailing edge boundary. The slope angle exceeding the designed value during the mining is the main cause of the collapse. In addition, the thawing of soil moisture caused by the increase in temperature and the reduction in the mechanical properties of the rock and soil due to underground voids and coal fires also contributed to the accident. This study demonstrates that multi-source remote sensing technologies can quickly and accurately identify potential high-risk areas, which is of great significance for pre-disaster warning and post-disaster rescue. Full article

In order to comprehend the molecular composition of coal and better understand the process of coal combustion, this study involved the development of a molecular structure model for Heiyanquan coal in Xinjiang, as well as the optimization and annealing dynamics simulation of the model. Thermogravimetric analysis (TG), Fourier transform infrared spectroscopy (FTIR), and high-resolution transmission electron microscopy (HRTEM) were utilized to investigate the spontaneous combustion characteristics of coal at different temperatures (room temperature, 50–500 °C with 50 °C interval). The findings revealed that the coal primarily consists of aromatic carbon, with the aromatic structure mainly comprising naphthalene, anthracene, and phenanthrene, and the aliphatic carbon mainly consisting of CH₂ and CH, along with a small quantity of minerals. The empirical molecular formula of Heiyanquan coal was determined to be C₁₇₅H₁₂₅O₂₁N₃. After the optimization, the total energy of the model was significantly reduced, and the aromatic layers tended to align in a regular parallel manner, with van der Waals energy playing a crucial role in maintaining structural stability. As the temperature increased, the activation energy of the three stages also increased, with the combustion stage exhibiting the highest activation energy. The presence of hydroxyl groups and oxygen-containing functional groups was found to mainly participate in the reaction, while the content of aromatic hydrocarbons remained relatively stable, C=C exhibited a decreasing trend, and C-O displayed an increasing trend. Moreover, it was observed that 1 × 1 and 2 × 2 were the predominant aromatic stripes in the coal samples, accounting for more than 90% of the total stripes. Full article

Efficient evacuation route planning during underground coal mine fires is essential to minimize casualties. This study addresses current shortcomings by proposing a real-time method that integrates a multifactor coupling analysis and the optimized multilayer perceptron regressor-shortest path faster algorithm (MSPFA). This research aims to enhance evacuation route planning by overcoming factors such as inadequate consideration, low accuracy, and information lag in existing methods. This study improves the shortest path faster algorithm (SPFA) for dynamic route planning, mitigates the impact of fixed walking speed parameters using the particle swarm algorithm, and selects the optimal model (MLPRegressor) through the Bootstrap algorithm for estimating personnel walking speeds. Validated through smoke-spread experiments, the MSPFA algorithm dynamically adjusts evacuation routes, preventing toxic passages. Visualization via drawing interchange format (DXF) successfully enhances route comprehension. The MSPFA algorithm outperforms the Dijkstra algorithm with a runtime of 78.5 msand a personnel evacuation time of 3344.74 s. This research establishes a theoretical foundation for intelligent evacuation decision making in underground fire disasters. By introducing the MSPFA algorithm, it provides crucial technical support, significantly reducing the risk of casualties during emergencies. Full article

Mine fires are one of the common major disasters in underground mining. In addition to the external fire sources generated by mining equipment and mechanical and electrical equipment during operations, coal is exposed to air during mining, and spontaneous combustion is also the main cause of mine fires. In order to reduce the hidden danger of coal mines caused by spontaneous coal combustion during lignite mining, the microbial inhibition of coal spontaneous combustion is proposed in this paper. Via SEM, pore size analysis, and NMR and FT-IR experiments, the mechanism of coal spontaneous combustion is discussed and revealed. The modification of lignite before and after the addition of retardants is analyzed from the perspective of microstructure, and the change in flame retardancy of the lignite treated with two retardants compared with raw coal is explored. The results show that, compared with raw coal, a large number of calcium carbonate particles are attached to the surface of the coal sample after bioinhibition treatment, and the total pore volume and specific surface area of the coal sample after bioinhibition treatment are decreased by 68.49% and 74.01%, respectively, indicating that bioinhibition can effectively plug the primary pores. The results of NMR and Fourier infrared spectroscopy show that the chemical structure of the coal sample is mainly composed of aromatic carbon, followed by fatty carbon and carbonyl carbon. In addition, the contents of active groups (hydroxyl, carboxyl, and methyl/methylene) in lignite after bioretardation are lower than those in raw coal, and methyl/methylene content is decreased by 96.5%. The comparison shows that the flame-retardant performance of biological retardants is better than that of chemical retardants, which provides an effective solution for the efficient prevention and control of spontaneous combustion disasters in coal mines. Full article

In environments like coal mines and oil wells, electrical equipment carries the risk of disasters such as underground fires and methane gas explosions. However, communication equipment is essential for work. Our team has developed a long-range (approximately 25 km) audio transmission system that operates without the need for terminal power sources, thereby eliminating the risk of electrical sparks. This system leverages the reliability of optical fiber and employs a 1550 nm laser for analog audio transmission. After traveling through 25 km of optical fiber, the signal is converted back into electrical energy using a custom-designed Laser Power Converter (LPC). The optical fiber’s carrying capacity imposes limits on the light signal intensity, which, in turn, affects the signal transmission distance. To enable long-distance transmission, we have carefully chosen the optical wavelength with minimal loss. We observed that different LPC structures operating within the same wavelength band have an impact on the audio quality at the terminal. By comparing their characteristics, we have identified the key factors influencing audio output. The optimal LPC allows audio transmission over 25 km, with an output exceeding 12 mVrms. Full article

A wide variety of natural catastrophes are induced by coal mining, with fire hazard being one of the most significant threats to underground engineering structures. In recent years, there has been an alarming rise in mine fire accidents due to the abundance of coal deposits around the world. Underground fires and explosions have continuously been the primary reason for a significant proportion of deaths and the destruction of infrastructure over the last few decades. Underground mining fires deplete natural coal resources, have an adverse impact on the environment by releasing hazardous chemicals and greenhouse gases into the atmosphere, and cause subsidence due to coal depletion during the combustion process. This study aims to predict fire danger rating of underground mining production processes by using the application of state-of-the-art unsupervised and supervised machine learning techniques. The developed k-nearest-neighbors-based isometric feature mapping and fuzzy c-means clustering algorithm has shown its dependability and superiority with a higher accuracy and has been advantageous to the monitoring and prevention of fire danger in underground mining production processes. The proposed multi-criteria decision intelligence framework permits early fire detection, providing the emergency response team extra time to respond the critical situations in order to prevent the fire from spreading, hence promoting sustainable, green, climate-smart, environmentally friendly and safe mining engineering operations. Full article