Search

Existing research has found that the number, insertion depth and angle, filling rate, and working fluid of heat pipe (HP) can affect the distribution of temperature field inside coal gangue dumps. However, there is relatively little research on the optimal arrangement of heat pipes (HPs) in coal gangue dumps. In response to the above issues, based on the theoretical model of HP heat transfer, the influence of HPs layout on the temperature field of coal gangue dumps is analyzed through a combination of numerical simulation and experiments, and the optimal layout of HPs is obtained. The results show that the presence of HPs can change the heat conduction path in a coal gangue dump and help the coal gangue dumps to dissipate heat in time. As the insertion spacing of the HPs decreases and the insertion depth of the HPs increases, the area of the spontaneous combustion danger zone (SCDZ) decreases, the maximum temperature value (Tmax) decreases, and the better the cooling effect. The influence of the insertion spacing of HPs on the spontaneous combustion volume of coal gangue dumps is greater than the influence of the insertion depth of HPs. When the insertion spacing of HPs is 3 m and the insertion depth of HPs is 7 m, the spontaneous combustion volume and the highest temperature point respectively decrease by 11755m3 and 302.57 ℃, and the cooling effect of coal gangue dumps is the best. Consequently, this study provides a reference for the design and optimization of coal gangue fire fighting engineering with HP application in the future. [ABSTRACT FROM AUTHOR]

The investigation into the impact of small molecular in coal on its wettability holds significant importance in the field of coal dust control. In this study, eight coal structure models with different small molecules were constructed to analyze the effects of small molecules on the adsorption of H2O in coal, the impact on pore structure, and the interactions between small molecules and H2O. The research results indicate that Toluene and C15H32 had a promoting effect on coal wetting properties, mainly through their interactions with H2O to enhance the wetting characteristics of coal. However, dihydrofuran-2(3 H)-one had an inhibitory effect on coal wetting properties, mainly by altering the pore structure of coal to suppress the adsorption of H2O. The strength of interactions between the three small molecular and H2O was ranked from high to low as follows: dihydrofuran-2(3 H)-one > Toluene > C15H32. There was charge transfer between the three small molecular and H2O, with the amount of transferred charge ranked from large to small as follows: dihydrofuran-2(3 H)-one > Toluene > C15H32. Small molecules affected the wetting properties of coal from both their interactions with H2O and the impact on pore structure. [ABSTRACT FROM AUTHOR]

Coal mine tailings can lead to a range of environmental problems, including toxic metal contamination, soil erosion, acid mine drainage, and increased salinity. Mine spoils from coal mining activities accumulated as gob piles are difficult to reclaim due to constraints such as a steep slope, unsuitable pH, insufficient nutrient supply, metal toxicity, low water-holding capacity, and poor soil structure. We investigated the efficiency of low-cost amendments on coal gob spoils from Carthage Coal Field (CCF) in New Mexico in improving the quality of coal gob spoils. Gob spoil was incubated for 90 days with various rates of organic amendments such as biochar, compost, and a biochar–compost mix. Gob spoil quality parameters such as the pH, water-holding capacity, and total and plant-available nitrogen and phosphorus content of the gob spoil were measured over a period of 90 days. Both biochar and compost amendment led to a significant increase (40–60% for biochar and 70% for compost, p < 0.05) in water-holding capacity of the coal gob spoil. Plant-available nitrogen content increased from <200 mg N/kg to between 400 and 800 mg N/kg in the amended gob spoil. The period of incubation was a significant factor in the improvement of plant-available nitrogen content. Plant-available phosphorus content also increased; compost amendment was more effective than biochar in increasing plant-available P. This study provides crucial information about the optimum organic amendments that would help in optimizing a sustainable reclamation method for CCF. [ABSTRACT FROM AUTHOR]

The recognition of plant biogeographic ranges over time and migration routes is crucial for understanding ancient global plate tectonic configurations. This paper deals with a new fossil plant from the uppermost part of the Taiyuan Formation (earliest Asselian) in the Wuda Coalfield, Inner Mongolia, China. It has a taeniopterid morphology comprising strap-shaped leaves with a prominent midrib and arching secondary veins, and it exhibits dimorphism between its fertile and vegetative leaves. The fertile leaf has a slightly lobed margin, with each lateral vein terminating in a marginal lobe that bears a synangium. Each synangium consists of primarily two, occasionally three, oval sporangia. Based on these distinctive characteristics it is identified as a new species of Ilfeldia. Previously, Ilfeldia had a highly restricted record in the Upper Pennsylvanian of Portugal and Germany into the lower Permian of Germany. The sedimentary and floral context suggests Ilfeldia was a xerophilous element that underwent long-distance dispersal during the Late Pennsylvanian to earliest Asselian, migrating from Gondwana (Iberia) to Cathaysia (North China) via Euramerica (Eastern Avalonia). The palaeogeographical distribution over time of Ilfeldia supports the continental model of the Wegenerian Pangaea configuration and underscores the continental connection between Euramerica and Cathaysia in the Late Pennsylvanian. [ABSTRACT FROM AUTHOR]

Borehole-to-surface electrical (BTSE) technology plays an important role in detecting mining subsidence area in coalfields. However, the ambiguity of linear inversion and the influence of surrounding rock resistivity reduced the effectiveness and accuracy of BTSE technology in identifying mining subsidence area. In this study, the damped least-squares inversion method constrained by inequality was investigated based on the basic principles of BTSE technology. On this basis, a novel method using the ratio of post- to pre-mining inversion resistivity was proposed to detect mining subsidence area. Finally, the application effect of this method was analyzed by using theoretical model and laboratory mining model, respectively. It was found that the resistivity inversion of the BTSE constrained by inequality could obtain good layered information of the stratum provided by prior information. Using the ratio of post- to pre-mining inversion resistivity can eliminate the influence of surrounding rock on the abnormal resistivity and highlight the resistivity anomalies caused by stratum collapse during coal mining. The application results of the theoretical model and laboratory mining model illustrated the feasibility and effectiveness of this novel method in detecting mining subsidence area, which provides important theoretical basis and reference for its future promotion and application. [ABSTRACT FROM AUTHOR]

To study the level of atmospheric PM2.5 and its heavy metal pollution near the coal gangue mountain, this study analyzed the content of seven heavy metals (Zn, Pb, Cu, Cd, Hg, Ni, Cr) and As through the PM2.5 samples from the vicinity of a large-scale coal gangue filed of Tongting coal mine in Huaibei, and evaluated the level of pollution, sources, and health effects. The results showed that during the sampling period, the average concentration of PM2.5 near the coal gangue field was 169.83 µg·m-3, which was 2.26 times that of the national air quality level II daily standard. The coal gangue field may be an important source of air pollution, with the degree of heavy metal and arsenic pollution in the order of Cd, Pb, Zn, Hg (extremely heavy pollution) > As, Cu (medium pollution) > Ni, Cr (light pollution) and coal gangue dust and mining dust contributed more. This study provides data for atmospheric particulate matter and heavy metal and arsenic pollution levels near coal gangue fields and provides a theoretical basis for air pollution prevention and control near coal gangue hills. [ABSTRACT FROM AUTHOR]

[Objective] The primary objective of this study is to tackle the manifold challenges associated with identifying coal gangue during coal mining, including but not limited to the inefficiencies, high operational complexity, and substantial costs inherent in traditional identification methods. By integrating and refining advanced deep learning technologies, particularly the YOLOv8-based object detection model, we seek to develop an intelligent system capable of automatically, rapidly, and precisely identifying coal gangue. This intelligent system will not only enhance the efficiency and quality of coal mining and minimize human errors and cost inefficiencies but also foster the sustainable utilization of coal resources, mitigate environmental pollution, and provide technical support for the green transition of the coal industry. [Methods] To achieve the aforementioned research objectives, this study adopted a systematic research method. First, we conducted an in-depth analysis of the advantages and disadvantages of the YOLOv8 model and proposed the YOLOv8-ER model based on this. This model deeply optimized the backbone network of YOLOv8 by introducing an efficient channel attention network, enabling the model to focus more effectively on key features in the image and improve the accuracy and efficiency of feature extraction. At the same time, we applied structural reparameterization technology to simplify the network architecture of the model, reduce the computational complexity and resource consumption, and improve the inference speed and stability of the model. In the model training phase, we used a large-scale and diverse dataset of coal gangue images and continuously optimized the model parameters through multiple iterations of training to ensure the accuracy and robustness of the model in practical applications. [Results] This study has achieved multiple innovative results in the field of coal gangue identification. First, the YOLOv8-ER model has achieved significant improvements in both processing speed and detection accuracy. The high-speed detection capability of the YOLOv8-ER model (i.e., 240.8 frames/second) can meet the high real-time requirements of application scenarios, with a performance rate of up to 92.3% mAP@0.5, which ensures the accuracy and reliability of recognition. Second, compared with the traditional YOLOv8 model, YOLOv8-ER has made breakthroughs in multiple key indicators, such as an accuracy improvement of 3.2%, mAP@0.5 improved by 4.4%, and PR balance rate improved by 2.6%. These improvements make the model more competitive in practical applications. In addition, by optimizing the network structure and applying reparameterization techniques, we have successfully reduced the computational complexity and resource consumption of the model, improving its operational efficiency and economy. [Conclusions] In summary, this study successfully developed an efficient and accurate coal gangue identification technology by introducing and optimizing the YOLOv8-ER model. This technology not only overcomes the limitations of traditional recognition methods and improves the efficiency and quality of coal mining but also provides strong support for the intelligent transformation of the coal industry. In the future, with the continuous advancement of technology and the expansion of application scenarios, the YOLOv8-ER model is expected to play an important role in more fields, promoting the sustainable development and innovation of related industries. At the same time, we will continue to conduct in-depth research on the optimization and extended application of this model to meet the needs of coal gangue recognition in different scenarios. [ABSTRACT FROM AUTHOR]

Objective - Coal mining operations encounter substantial risks and uncertainties that originate from a wide array of sources, encompassing but not limited to natural calamities, supplier disruptions, market volatilities, regulatory modifications, and geopolitical instability. This study aims to conduct a comprehensive literature review on supply chain resilience in the coal mining industry and pinpoint potential avenues for further investigation. Methodology - A systematic literature review (SLR) was utilized to examine a total of 115 studies in the field of management and the coal mining supply chain. The studies were published from 2010 to 2023. The vulnerabilities and resilience strategies within the coal mining supply chain are the focal points of our research. We have integrated viewpoints from the domains of management and the coal mining supply chain to support our analysis. Findings - Challenges such as resource distribution, government policies, and maintenance are prevalent, pointing to the need for strategies that enhance performance through dynamic optimization and incentivizing integration. Practitioners must identify vulnerabilities in the coal mining supply chain to proactively anticipate and effectively manage potential disruptions, thus bolstering operational resilience. Novelty -This study fills the gap in extant literature by investigating the sequential application of supply chain resilience in the context of coal mining operations using the integrative view of supply chain nodes. [ABSTRACT FROM AUTHOR]

Coal seam water injection is the most basic and effective dust control technology used on the coal mining face. Numerical simulations are helpful for predicting the humidity range of coal seam water injection. The results can provide guidance for the field design of coal seam water injection process parameters. In order to understand the influence of coal seam water injection pressure and water injection time on the coal seam wetting effect, this paper uses the Fluent 17.0 software system to study the process parameters of the coal seam water injection seepage process under different conditions. It is found that in the process of coal seam water injection, with the increase in water injection pressure and the prolongation of water injection time, there is a specific threshold value for the change in coal seam permeability. Only when the water injection pressure and time increase to the threshold value will the permeability of the coal seam be significantly enhanced and the wetting effect improved. The pressure threshold of the mine is 15 MPa–20 MPa, and the time threshold is the first 42 h. [ABSTRACT FROM AUTHOR]

The deep integration of computer field and coal mining field is the only way to coal mine intellectualization. A variety of artificial intelligence tools have been applied in open-pit and shallow coal mines. However, with the geometric increase of coal demand, the contradiction between supply and demand is becoming more and more serious, and the exploitation of resources from shallow layer (> 600 m) has become an inevitable trend. Well then, as a new engineering scene, the harsh conditions of "three high and one disturbance" seriously threaten the safety of personnel. The superposition of complex mining environment makes the number of input factors increase sharply, which leads to the application of artificial intelligence in deep coal mine roadway engineering. The guidance is not mature, the construction of various databases is missing, and there are still some problems in universality and applicability. To this end, this paper starts with the introduction of the operating characteristics of various artificial intelligence tools, and conducts a comprehensive study of the relevant high-level articles published in top journals. It systematically sorts out the research progress that has successfully solved the five directions of rock mechanics strength, surrounding rock stability, rock-burst, roof fall risks and micro-seismic events. While objectively evaluating the comprehensive performance of different tools, it also expounds its own views on key research and results. Literature review shows that whether as a development tool or a comparative model, the application of ANN in the field of coal mining is more than 98%, and it performs extremely well in the direction of surrounding rock stability and roof fall risk, with an accuracy rate of more than 90%. As the most mature direction of AI tools application, rock mechanical strength has experienced the development process from "SVM → ANN → DL → XGBoost → RF". The dataset is from small samples (< 100) to big samples (> 1000), and the R2 of tree-based models can be stabilized at more than 95%. The research on rock-burst prediction mainly focuses on field factors and micro-seismic monitoring data. Whether it is a small sample or a large-scale data model, the accuracy of BN remains above 85%. The prediction and evaluation of micro-seismic events is a new direction in recent years. The image processing and application of CNN is extremely important. The signal recognition and classification accounts for more than 90%, and the research potential of source location needs to be further explored. In general, the nature of the rock itself is the first choice for almost all influencing factors. At the same time, the update iteration of monitoring methods (micro-seismic, ground sound, separation, deformation, etc.) expands the development of the database, making it possible to obtain the data due to threat to life and cost of equipment, which is very difficult to obtain before. In the process of parameter selection at the input end, the method of combining lithology conditions, geological environment and monitoring data will gradually become the first choice for research. Finally, in the follow-up work collation and on-the-spot investigation, it mainly focuses on the existing problems of deep coal mines, explores the application potential of artificial intelligence in deep coal mine roadway engineering, puts forward the possible research focus and challenging problems in the future, and gives its own opinions. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In particular, the secondary development of overlying strata fractures can easily lead to the upper goaf, resulting in gas and water gathered in the goaf entering the working face of the lower coal seam through the overlying strata fractures, threatening the safety of coal mine production. Security risks may arise. To further understand the caving and evolution law of overlying strata during repeated mining in extremely close distance coal seam down mining, 9# coal and 10# coal in the Nanyaotou Coal Industry were used as the engineering background. The caving characteristics and fracture evolution law of overlying strata during single and repeated mining were analyzed through similar material simulation tests. Based on fractal geometry theory, the relationship between the advancing distance of the working face and the fractal dimension of the overlying strata fracture is established to reflect the changing trend of fracture development. The calculation formula is derived from the tensile rate of rock strata to predict the development height of water-conducting fractures. The results show that the overlying strata failure structure is mainly a "hinged structure" and a "step structure," which respectively promotes and inhibits the development of overlying strata fractures. Repeated mining causes mininginduced fractures in the lower coal seam to pass through the goaf of the upper coal seam and develop more vigorously in the upper coal seam, and the fractal dimension can effectively reflect the development of overlying strata fractures. The height of the water-conducting fracture zone increases in four stages: incubation, gradual increase, further gradual increase, and stability, eventually stopping development under the influence of the key layer (thick mudstone) bearing the load above. The development height of water-conducting fractures predicted by on-site water injection measurement is similar to that predicted by simulation experiments and theoretical calculations, verifying the feasibility of predicting the development height of water-conducting fractures through simulation tests and theoretical analysis. This study provides a reference for coal seam mining under similar conditions. [ABSTRACT FROM AUTHOR]

Mine water surge is one of the main safety risks in coal mines. This research offers a novel mine water source identification model (BO-CatBoost) to successfully avoid and control mine sudden water catastrophes by properly identifying the sources of mine water. First, the classification model is trained and built using the Categorical Boosting (CatBoost) algorithm. The Gaussian process Bayesian optimization (BO) algorithm is used to optimize parameters, and the optimal parameter combination is integrated into the CatBoost algorithm to build the BO-CatBoost mine water source identification model, which further improves the accuracy of mine water source identification. The model was also applied to the Pingdingshan mine to verify the practicality of the model. Then, 29 groups of unknown water sources in Pingdingshan were selected as validation samples for the model and compared with the conventional CatBoost, Light Gradient Boosting Machine (LightGBM), and Extreme Gradient Boosting (Xgboost) models. The comparison results demonstrate that the accuracy of LightGBM, Xgboost, CatBoost, and BO-CatBoost models can reach 69%, 79.3%, 79.3%, and 100% respectively, and the RMSE is 0.947, 0.643, 0.719, and 0.0 respectively. The comprehensive analysis shows that, when it comes to mine water source detection, the BO-CatBoost model performs noticeably better than other models in terms of discriminative accuracy and generalization capacity. Lastly, the multi-output prediction and decision-making process of the BO-CatBoost water source identification model is visualized by the interpretability analysis performed with the SHAP approach. The research demonstrates that the BO-CatBoost model can more precisely and impartially identify mine water sources, offering fresh concepts for mine water source detection. [ABSTRACT FROM AUTHOR]

Coal gasification fine slag (CGFS) is a large solid waste in the field of coal chemical industry, and its land occupation and environmental pollution caused by stockpiling and landfill make its comprehensive utilization imminent. The composition and structure of CGFS is the basis of its resource utilization, particle size classification and density classification is the important means to achieve the separation and enrichment of components in CGFS, while there are significant differences in the properties of CGFS in different particle size and different density fractions. Therefore, a CGFS sample from Shaanxi, China was used as an example in this paper, and X-ray diffraction analyzer (XRD), X-ray fluorescence spectrometry (XRF), Fourier Transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), and low-temperature N2 adsorption tester were applied to comprehensively analyze the compositional and structural properties of the raw as well as the graded (both size-graded and density-graded) samples. The results show that the proximate composition, mineral composition, elemental composition, surface functional groups, apparent morphology, and pore structure show a good regularity with the particle size and density of the samples. Meanwhile, these properties and their variations with particle size and density were analyzed for their implication in the separation of components and resource utilizations of CGFS. The findings of this study provide ideas and data support for large-scale dissipation and high value-added disposal of CGFS. [ABSTRACT FROM AUTHOR]

The primary objective of this study was to evaluate the bound fractions of mercury (Hg), physicochemical parameters, and mineral composition of coal. Coal samples were collected from various depths within Block-VII of the Thar coalfield in Pakistan. The Hg associated with different chemical fractions of coal was extracted using a sequential extraction scheme as per the community bureau of reference (BCR) protocol. This study utilized both the BCR-sequential extraction method (BCR-SEM) and a single-step sequential extraction based on an ultrasonic-assisted method (SSE-UAM) for the fractionation analysis of Hg in coal. The extraction methodologies, BCR-SEM and SSE-UAM, were specifically designed for analyzing Hg fractionation in coal samples. The SSE-UAM offers an operational advantage, requiring only 2 h compared to the 51 h needed for BCR-SEM. The analyses were validated using standard reference material (SRM-1635a) and the spiking addition method, achieving a recovery percentage of 97.1% for total Hg concentrations using the pseudo-extraction method in SRM-1635A. Total Hg content in the coal samples ranged from 0.60 to 2.34 µg g−1 across four different coal seams from Block-VII of the Thar coalfield. Additionally, Hg concentration was observed to decrease with increasing depth, attributed to changes in mineralogical composition. The highest concentration of Hg was detected at a depth of 200–203 m, while the lowest concentration was at a depth of 152–154 m. The concentration of Hg in various fractions was 32–60% in the acid-soluble fraction, 1.72–4.92% in the reducible fraction, and 9.58–50.8% in the oxidizable fractions. The coal sample characteristics were analyzed using an elemental analyzer and scanning electron microscopy with energy-dispersive spectroscopy. Cold vapor atomic absorption spectrometry (CV-AAS) was used to measure the extracted fractional concentration of Hg in coal. [ABSTRACT FROM AUTHOR]

During coal mining, it is difficult to avoid gangue generation, and the gangue separation techniques based on spectra and images have problems such as one-sided feature description and weak robustness, which can not meet the practical demands and deal with the complex and abnormal working conditions. In recent years, multimodal technology has been developed and successfully applied in many fields, and this progress provides a new solution for the field of coal gangue identification. There is a lack of a systematic analysis and summary on how to use multimodal technology to improve the accuracy of gangue separation by fusing spectral and image information complementarily. This paper proposes the key techniques of spectral and image fusion, including preprocessing and alignment, representation learning, fusion methods, which builds a technical framework for spectral and image fusion. We focus on the fusion methods of spectral and image, which are classified into four major categories in this paper, including conventional fusion, probabilistic and statistical-based fusion, deep learning-based fusion, and decision fusion, and we further provide guidelines for the use of spectral and image fusion, and the test results on the dataset show that the fusion of spectral and image information can significantly improve the recognition of coal gangue. Based on this, we explore the association between spectral and image features in depth, and propose four optimization methods, including feature reuse, channel-level feature fusion, progressive exploration, and attentional mechanism, which indicate the direction of development after fusion. In addition, we discuss the advantages and limitations of each method, clarify the challenges of spectral and image fusion applied to the field of coal gangue separation. This work study is a guidance and reference for the application of image fusion in the field of coal gangue separation. [ABSTRACT FROM AUTHOR]

Obtaining real-time physical field data inside the boiler furnace is crucial for combustion diagnostics and optimization. In this work, we propose a fast reconstruction technique for the physical fields in a tangentially-fired coal boiler. The method combines the Proper Orthogonal Decomposition (POD) and Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) based on the boiler physical field obtained by computational fluid dynamics (CFD). Firstly, CFD simulations are performed using data from the boiler Distributed Control System (DCS). After verifying the CFD results, we expanded the simulation to 105 operational condition cases sample sets. Then, the physical fields of the sample set undergo POD to determine the appropriate number of POD bases, thereby ensuring the accuracy of the reconstruction. Finally, the cDCGAN method is employed to establish the correlation between the POD bases and the operational conditions of the boiler. Results show that the POD-cDCGAN method achieves rapid and accurate reconstruction of temperature and velocity fields, with mean relative error (MRE) below 1.5% and root relative squared error (RRSE) below 5.7%. The reconstruction time is reduced to 10.57s, significantly faster than direct CFD methods. The POD-cDCGAN method offers an efficient approach for online operational diagnosis and digital twin construction of boiler equipment. [ABSTRACT FROM AUTHOR]

The rockburst risk prediction based on microseismic (MS) data is an important research task in deep mine safety prevention. However, the lack of systematic research on explicit prediction indexes and the waste of a large amount of unlabeled data are still two main problems that hinder the development of rockburst prediction. In this paper, the acoustic emission (AE) event distribution at each coal rock deformation and failure stage is studied based on the laboratory experiment. The spatial-temporal evolution of rockburst in MS data of coal mine fields is explored. Based on systematic research of the AE and MS distribution features considering the physical logic of coal rock mass failure, nine different rockburst prediction indexes are employed to describe the MS data features before rockburst. Then, according to the rockburst prediction indexes, a new self-supervision rockburst risk prediction algorithm is constructed, consisting of the pre-trained model and fine-tuning model with the same encoder and decoder structure. The pre-trained model is trained with unlabeled MS data to automatically learn rockburst prediction index features by reconstructing the masked indexes. Based on the pre-trained encoder and decoder parameters, the fine-tuning model is trained with the labeled MS data to predict rockburst risk. A large number of experiments show that the proposed rockburst prediction self-supervision algorithm is far superior to previous algorithms, by effectively utilizing unlabeled data. The ablation experiment also proves the validity of the studied rockburst prediction indexes. [ABSTRACT FROM AUTHOR]

Flotation is a crucial separation technique in coal beneficiation. However, the inability to quickly and accurately detect ash content during the flotation process hinders the development of flotation automation. This paper introduced a novel hybrid model based on convolutional neural networks, establishing the ash content in tailings. In this method, convolutional neural network is utilized to automatically extract features from tailings images. In the model training and optimization phase after inputting the augmented data, the optimal ResNet18 model is identified by comparing five model optimization methods and replacing the SoftMax classifier with the traditional SVR in ResNet18. Additionally, a PCA-SVR model for predicting tailings ash content is constructed for comparative analysis, employing six different feature combinations to validate the effectiveness of the proposed features, with optimal support vector parameters identified through random search and cross-validation algorithms. The prediction results show that the PCA-SVR model has the highest accuracy when the feature dimension is reduced to 16, and the prediction of ResNet18-SVR is more accurate compared to PCA-SVR. This indicates that the proposed method can predict the ash content more accurately than the traditional feature engineering methods and has a broad application prospect in the field of coal beneficiation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Coal mine fire is a common phenomenon in Indian coalfields and great concerned on safety of the person engaged in mining operations. In opencast coal mine, particularly where the extraction of previously developed coal pillars has been carried out by opencast mining method, chances of spontaneous fire became more frequent and complicated. In such prevailing situations deep holes charging and blasting operation in hot strata may create every possibility to premature detonation of explosives, which leads to fatalities. Henceforth, it is imperative to use appropriate methodology to combat the fires and make it possible for wining of coal safely. This paper highlighted a methodology adopted for safe and effective management of fire by using two different chemical additives admixed with water to bring down temperature under safe workable limit in short duration of time and also make it suitable for charging and blasting operation in hot deep drill holes. On the basis of the magnitude of fires 0.5 to1.0% concentrations of MgCl2 and CaCl2 mixed with water were applied for cooling of high temperature fire in coal bench, overburden as well as hot blast holes with encouraging results in supressing of the flames and rapid cooling of hot strata. [ABSTRACT FROM AUTHOR]

An important issue to the earth's atmosphere is the volatilisation of elements such as selenium, from the burning of coal at different temperatures. In the current work, the volatilisation of selenium (Se) during combustion of coal samples at different control temperature range in an electrically controlled furnace was carried out. The coal samples were obtained from various coal fields of Sindh, Pakistan. The duplicate coal samples were combusted in controlled furnace by applying three temperature rounds (200°C, 400°C and 900°C). The ash formed following each temperature round was examined to know the volatilisation contents of Se after burning of coal samples at different temperature. The fractionation of Se in coal ash gained after combustion at 900°C was subjected to three-stage sequential extraction scheme (SES). The obtained data indicated that the total contents of Se in coal samples of block II of Thar coal field (TCF), and Site I and Site II of Lakhra coal field (LCF) were observed in the range of 7.72–14.3, 9.02–16.3 and 8.92–14.2 mg/kg, respectively. It was observed that after the burning of coal samples at 900°C, about 75–81.8% of the total Se was volatised out into atmosphere. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of World Nuclear Geoscience is the property of World Nuclear Geoscience Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose. To justify and develop a model that describes the effect of magnetic treatment of blast reagents and carbon-containing products on the gasification process for predicting the intensification of gas formation. Methodology. The study involves theoretical modeling based on experimental data to investigate the influence of magnetic fields on the underground coal gasification process and co-gasification of coal and carbon-containing products. The Arrhenius equation was used to estimate the rate constants of gasification reactions in the temperature range of 800–1,000 °C. The effect of the magnetic field was incorporated by adjusting the activation energy (Ea). The results of analytical and experimental studies were processed using methods of computer and mathematical modeling. Findings. The results show that the application of magnetic fields significantly intensifies the gasification process of carbon containing products. Increasing the reactivity of the blast reagents, particularly water and oxygen, leads to a higher overall yield of combustible gases. The use of magnetic fields in the gasification process substantially increases the reaction rate (k) due to the reduction in activation energy (Ea), improving the overall efficiency of gasification. Originality. For the first time, an analytical model has been developed to describe the effect of magnetic treatment of blast reagents and carbon-containing products on the gasification process in the temperature range of 800–1,000 °C. The obtained reaction rates follow an exponential trend. The established and correlation-validated pattern shows the relationship between changes in the approximation coefficient (F) and the change in the carbon fraction (C, %) during the magnetic treatment of blast components within the specified temperature range. Practical value. The results of this study can be applied to enhance the efficiency of industrial gasification processes, particularly underground coal gasification and co-gasification of coal and carbon-containing productss. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Insufficient handling of spontaneous combustion in coal piles arises from the influence of natural wind during the piling process, resulting in the displacement of the heat source. To investigate the impact of wind flow on heat source movement in simulated coal piles under varying wind velocities, an experimental stage was established. The research findings elucidate that both normal and tangential winds exert an influence on the heat source position, with normal winds exhibiting a greater effect than tangential winds. The relationship between heat source position speed and wind speed magnitude follows a common fitting function under both wind conditions. Specifically, the speed of the heat source at the edge position demonstrates a linear correlation with the magnitude of wind speed, while the speed of the heat source at the center position conforms to a quadratic function with the wind speed magnitude. The heat source moves at a distance of 0.8 cm to 5.3 cm on the Y = 0 tangent, corresponding to a moving speed of 0.03 cm/min to 0.18 cm/min. On theY = −20 tangent, the heat source moves at a distance of 2.1 cm to 8.1 cm, corresponding to a moving speed of 0.07 cm/min to 0.27 cm/min. Moreover, the study reveals that the influence on heat source movement at the center of the simulated coal pile diminishes as wind speed decreases under both wind conditions. These research findings provide a theoretical foundation for managing spontaneous combustion in coal piles and offer insights into precise management of heat source positions within coal piles. [ABSTRACT FROM AUTHOR]

Coalfield fires have become a major hidden danger in mining operations. In order to analyze the laws of coal oxidation and combustion under stress, a uniaxial pressurized experiment was conducted on briquettes. The results show that as the temperature rises, the oxygen consumption rate of the oxidative combustion of the coal sample increases. This rate is higher in the active stage (120–200°C). CO and CO2 gases begin to be generated in the awakening stage (60–70°C), while hydrocarbon gases are gradually generated in the active stage. Additionally, the index gas escape rate is relatively high under a specific axial pressure (4MP). The cross point temperature of the coal sample at 4MP is lower (86.9°C), and the maximum heating rate is higher (0.117°C/s) compared to other coal-oxygen samples with axial pressure applied. The application of axial pressure has two functions including opening pore channels and compacting particle space, which affect the oxidative spontaneous combustion of coal samples. The research results provide a strong scientific basis and theoretical guidance for the detection and prevention of coalfield fires. [ABSTRACT FROM AUTHOR]

To understand the development status and frontier trends in the prevention and control of coal mine water hazards, a dataset of 962 articles indexed in Web of Science was used. Visualization maps were created using CiteSpace software to conduct statistical analyses on the publication volume, journal distribution, researchers, research institutions, keywords, and burst terms in the field of coal mine water hazard prevention and control in China from 2000 to 2023. The study reveals that the number of publications related to the prevention and control of coal mine water hazards in China has gone through rapid growth periods as well as stable fluctuations. The literature cooperation network in the field of coal mine water hazard prevention and control consists of two main collaboration groups and a series of independent authors, with the core research strength concentrated in institutions such as China University of Mining and Technology, Shandong University of Science and Technology, China University of Mining and Technology (Beijing), and Xi'an Research Institute of China Coal Technology and Engineering Group. Keywords such as "Coal mine water hazards," "Water inrush," "numerical simulation," "aquifer," and "risk assessment" collectively form larger clusters, primarily revolving around three main research directions: "water source," "water inflow pathways," and "water inflow intensity." In-depth exploration of the mechanisms of water inrush in coal mines, the revelation of water-conducting fracture evolution patterns, understanding underground water seepage characteristics, and hydraulic characteristics, along with the extensive use of new technologies like artificial intelligence and big data, will be the future hotspots in research. [ABSTRACT FROM AUTHOR]

Core samples from four boreholes (SAV-1, SAV-117, SAV-124, SAV-125) within the Vaddugudem block of the Godavari Valley Coalfield, Southern India have been palynologically investigated to understand the stratigraphic setting of that area. Only 60 out of the 172 samples yielded identifiable palynoassemblages. From the observed palynofloral composition, five distinct palynoassemblages (Scheuringipollenites Assemblage: PA-I, Striatopodocarpites + Faunipollenites Assemblage: PA-II, Striates + Striasulcites Assemblage: PA-III, Striates + Guttulapollenites Assemblage: PA-IV, Lundbladispora + Verrucosisporites Assemblage: PA-V) were identified. Furthermore, five distinct palynozones (Scheuringipollenites barakarensis Zone = PZ-1, Striatopodocarpites + Faunipollenites Zone = PZ-2, Gondisporites raniganjensis Zone = PZ-3, Guttulapollenites gondwanensis-Striatopodocatpites tiwarii Zone = PZ-4 and Playfordiaspora cancellosa Zone = PZ-5) were identified. These correspond to the Artinskian (PZ-1), Wordian–Capitanian (PZ-2 and PZ-3), Wuchiapingian–Changhsingian (PZ-4) and Induan–Olenekian (PZ-5), respectively. The study site is situated within a geologically active region within the basin, primarily attributed to the exposure of elevated basement rocks on the eastern side of the borehole locations. Notably, the palynozones appear as relatively narrow layers in the boreholes investigated within this tectonically disturbed basin. The repetition of palynoassemblages and palynozones at small intervals suggests that the boreholes are located in a fault zone with multiple fault planes and that palynomorphs were reworked along these fault planes. Fault slices of different lithological units containing palynoassemblages may have intersected the boreholes. Specifically, the recurrence of thin marker palynoassemblages and palynozones, which show similarities in age to the Barakar and Lower Kamthi/Raniganj formations, is likely attributable to tectonic disturbances, such as faulting. This disturbance may have induced the reworking or migration of palynomorphs along the fault plane. As a result, it is concluded that variations in the stratigraphic abundance of these reworked palynomorphs can serve as indicators of tectonic settings, even when these settings are not readily discernible in the geological record. [ABSTRACT FROM AUTHOR]

The Huayingshan coalfield is one of the most important coal districts in Southwest China. Coal mining may have an impact on the hydrochemical characteristics and regional evolution of karst groundwater. This study aims to analyze the hydrogeochemical characteristics, identify the evolution processes, and influencing factors that govern the hydrochemistry in multilayer karst aquifers in the coalfield. Statistical methods and conventional techniques were utilized to gain a thorough understanding of the origin and hydrogeochemical evolution of karst groundwater. The results revealed that the groundwater was fresh water and natural to mildly alkaline. It suggested that the relative abundance of main ions was proposed to be Ca2+ Mg2+ > K+ + Na+ for cations and > Cl– > for anions. A Piper diagram of the investigated water samples demonstrated that most groundwater was of the HCO3-Ca type. The results showed that dissolution of carbonate, gypsum, halite, and silicate minerals highly influenced the formation of , , Ca2+, Mg2+, and Na+. Cation exchange and/or absorption was another important regulatory process. concentrations were excessively high, proving that karst water was affected by agricultural activities in certain aquifers. Moreover, S2– concentrations were high in the borehole and mine tunnel samples, suggesting great acidification potential. Coal mining carries a risk of deteriorating the local water environment. This exposes sulfide minerals to oxygen and water, increases concentration, and reduces groundwater pH. Scientific research must focus on specific recharge area locations, runoff and drainage pathways, and hydrochemical evolution processes of karst water, and the contact of sulfide with water and oxygen must be controlled to protect groundwater quality and reduce pollution. The results suggest it may be helpful for investigation and treatment of water environment pollution, aid the protection of karst groundwater in the Huayingshan coalfield, and serve as a model for other comparable studies. [ABSTRACT FROM AUTHOR]

It is of great significance for the engineering popularization of CO2-ECBM technology to evaluate the potential of CCUS source and sink and study the matching of pipeline network of deep unworkable seam. In this study, the deep unworkable seam was taken as the research object. Firstly, the evaluation method of CO2 storage potential in deep unworkable seam was discussed. Secondly, the CO2 storage potential was analyzed. Then, the matching research of CO2 source and sink was carried out, and the pipe network design was optimized. Finally, suggestions for the design of pipe network are put forward from the perspective of time and space scale. The results show that the average annual CO2 emissions of coal-fired power plants vary greatly, and the total emissions are 58.76 million tons. The CO2 storage potential in deep unworkable seam is huge with a total amount of 762 million tons, which can store CO2 for 12.97 years. During the 10-year period, the deep unworkable seam can store 587.6 million tons of CO2, and the cumulative length of pipeline is 251.61 km with requiring a cumulative capital of $ 4.26 × 1010. In the process of CO2 source-sink matching, the cumulative saving mileage of carbon sink is 98.75 km, and the cumulative saving cost is $ 25.669 billion with accounting for 39.25% and 60.26% of the total mileage and cost, respectively. Based on the three-step approach, the whole line of CO2 source and sink in Huainan coalfield can be completed by stages and regions, and all CO2 transportation and storage can be realized. CO2 pipelines include gas collection and distribution branch lines, intra-regional trunk lines, and interregional trunk lines. Based on the reasonable layout of CO2 pipelines, a variety of CCS applications can be simultaneously carried out, intra-regional and inter-regional CO2 transport network demonstrations can be built, and integrated business models of CO2 transport and storage can be simultaneously built on land and sea. The research results can provide reference for the evaluation of CO2 sequestration potential of China's coal bases, and lay a foundation for the deployment of CCUS clusters. [ABSTRACT FROM AUTHOR]

This study explores the extraction of rare earth elements (REEs) from high-ash run-of-mine and discard coal sourced from the Waterberg Coalfield. Three distinct methods were employed: (1) ultrasonic-assisted caustic digestion; (2) direct acid leaching; and (3) ultrasonic-assisted caustic-acid leaching. Inductively coupled plasma mass spectrometry was utilized to quantify REEs in both the coals and resultant leachates. Leaching the coals with 40% NaOH at 80 °C, along with 40 kHz sonication, yielded a total rare earth element (TREE) recovery of less than 2%. Notable enrichment of REEs was observed in the run-of-mine and discard coal by 17% and 19%, respectively. Upon employing 7.5% HCl, a recovery of less than 11.0% for TREE was achieved in both coal samples. However, leaching the caustic digested coal samples with 7.5% HCl significantly enhanced the TREE recovery to 88.8% and 80.0% for run-of-mine and discard coal, respectively. X-ray diffraction analysis identified kaolinite and quartz as the predominant minerals. Scanning electron microscopy-energy dispersive microanalysis revealed monazite and xenotime as the REE-bearing minerals within the coal samples. These minerals were found either liberated, attached to, or encapsulated by the clay-quartz matrices. Further mineralogical assessments highlighted the increased REE concentrations in coals post-caustic digestion and subsequent recovery during acid leaching. This increase was attributed to the partial dissolution of kaolinite encapsulating the RE-phosphates and the digestion of REE-bearing minerals. Notably, undissolved REE-bearing elements in the caustic-acid-leached coal indicated the necessity of harsh leaching conditions to augment REE recovery from these coal samples. [ABSTRACT FROM AUTHOR]

Microseismic monitoring is pivotal for mine safety, offering early warnings for coal mining operations. By introducing the MTfit and MSATSI inversion methods to study the focal mechanisms of microseismic events and the stress field in coal mines, we applied these techniques for the first time to the 63upper06 working face in the Dongtan Coal Mine. We selected 107 high-quality microseismic events during the mining process and used MTfit to invert their focal mechanisms. Moreover, we used MSATSI to determine the direction of the maximum horizontal principal compressive stress in the region. This allowed us to establish a connection between mining activities, focal mechanisms, and rock strata fractures. Results show the predominance of normal and reverse faulting with significant CLVD components, underlining tensile and compressive failures as dominant in the mine's seismicity. Further, the study subdivides the research area into three subregions for detailed stress analysis: Subregion 1 is located below the working face with a maximum principal stress of 20.3 MPa, oriented between N60°E and N75°E; Subregion 2 is above the working face and exhibits more complex stress conditions with a maximum principal stress of 30.1 MPa; and Subregion 3 is situated at the roof's right side of the working face, with a maximum principal stress of 20.3 MPa, oriented at 30°northwest. It provides an important reference for seismic risk assessment and disaster prevention and control during mining. [ABSTRACT FROM AUTHOR]

Emerson Bainbridge was an important entrepreneur, philanthropist and (briefly) Liberal M.P. whose influence has been overlooked and under-estimated by historians. His wide-ranging industrial success, particularly in coal mining, and his growing personal wealth enabled him to play an important role in the North Midlands region particularly from 1890. His familial roots in Methodism and Temperance and his adherence to the main tenets of political nonconformity and Liberalism were the foundations of his 'world view'. This was to prove of critical importance in the design, development and ethos of the 'model villages' his company founded in the Derbyshire and Nottinghamshire coalfield. The impact and influence of this 'enlightened paternalism' long outlasted him. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the CO2 gas adsorption capability of coals from Sohagpur coalfield, India. Coal bed CO2 sequestration is a technique utilized to mitigate carbon dioxide emissions and improve global warming. Various factors, including pore structure, pore volume, mineral composition, moisture content, cleats, coal quality, pressure, and temperature, influence the adsorption of CO2 in coal seams. To conduct this investigation, multiple coal samples were collected from the study area and subjected to proximate analysis, ultimate analysis, scanning electron microscopy (SEM), Fourier transform-infrared (FT-IR), Brunauer – Emmett–Teller (BET), and measurement of CO2 adsorption rates on the coal samples. Samples were characterized based on their geochemical properties, then pore and fracture properties and maximum adsorption of CO2 gas were determined. The interrelationship between the genetic properties of coal with the adsorption rate of CO2 gas was established. These coals lie mesopore in category with the presence of fractures and hydrogen bonds. The result of BET and kinetics rate indicates that the adsorption of gas was unrestricted multilayer type, and the maximum adsorption of CO2 gas at 50 bar is 2.15 moles gas/kg sample, respectively. [ABSTRACT FROM AUTHOR]

In this study, major ions, isotopes and rare earth elements (REEs) were tested in groundwater from the coal-bearing sandstone aquifer of the Wolonghu coal mine in northern Anhui Province, and the elemental geochemical behavior and controlling factors in groundwater were discussed. The results indicate that the overall sandstone water is weakly alkaline, and the hydrochemical type is SO4-Na. The relationship between δD and δ18O suggests a hydraulic connection between the sandstone aquifer and the limestone aquifer. The composition characteristics of δ34SSO4 a nd δ18OSO4 indicate that the high concentration of SO42- in groundwater mainly comes from the dissolution of sulfate minerals. The content of rare earth elements (ΣREEs) in groundwater is controlled by pH value and carbonate complexation reaction, and it shows a relative enrichment feature of heavy rare earth elements (HREEs) after standardization with Post-Archean Australian Shales. Ce shows a slight negative anomaly and is mainly influenced by the redox environment, while the Eu anomaly is attributed to the dissolution of silicate minerals. Compared to groundwater quality before the mine closure, the weakening of hydraulic conditions led to an increase in ΣREEs, Ca2+, Mg2+, SO42-, and TDS concentrations accompanied by a significant decrease in HCO3- concentration. In addition, the difference between light rare earth elements (LREEs) decreased, whereas the differentiation between LREEs and HREEs gradually increased. Our findings provide valuable insights into the evolution of groundwater quality in abandoned mines and its genesis mechanism. The results could guide the utilization of groundwater resources in abandoned mines. [ABSTRACT FROM AUTHOR]

Taiyuan Formation limestone groundwater is the main aquifer threatening the safety of exploration under deep mining in the Huaibei coalfield. Therefore, acknowledging the hydrochemical characteristics and constructing reverse hydrogeochemical modeling are crucial for predicting and preventing mine water hazards. In this study, the mathematical statistical analysis, Piper threeline diagram, Gibbs diagram, ion proportional relationship, Chlorine-Alkali index, and the reverse hydrogeochemical modeling were employed for determining the hydrochemical characteristics and the formation mechanism. The results revealed that the hydrochemical types of groundwater samples were SO4.Cl-Ca.Mg and HCO3.Cl-Na, respectively. The water-rock interactions were primarily influenced by the leaching and the cation exchange, with these processes being more intense in the eastern region. Through reverse hydrogeochemical modeling, the water-rock interactions in the process of groundwater runoff were quantitatively verified, viz. the calcite and the dolomite were saturated and precipitating, while the gypsum and the halite were unsaturated and still dissolving. Furthermore, the simulations of mass transfer in groundwater runoff indicated that the dissolution and the leaching of gypsum, dolomite and halite, positive ion exchange, the precipitation of calcite, and the dissolution of CO2 gas predominantly occurred along four simulated flow paths. These results offered a scientific foundation for the prevention and controlling of mine water hazards in deep mining contexts. [ABSTRACT FROM AUTHOR]

The ecology of mining areas has been one of the most crucial components in terrestrial ecosystems. However, the over-exploitation of mineral resources has posed a great threaten to the ecosystem in recent years, leading to frequent environmental issues, such as land degradation, vegetation loss, and water scarcity. Therefore, accurate monitoring of mining ecology is of great importance to protect the ecological environment and balance. Remote sensing technology can be expected to provide an effective means for the ecological monitoring in mining areas. In this study, Remote Sensing Ecological Index (RSEI) was improved to realize the overall spatial average on the indicator weights for the ecological monitoring of mining sites. The factor of coal dust pollution was also added into the conventional greenness, wetness, dryness and heatness. The indicator weights were then determined using Geographically Weighted Principal Component Analysis (GWPCA). The indicator was finally selected to construct Geographically Weighted-Remote Sensing Ecological Index (GW-RSEI). Taking the Datong coal field in Shanxi Province as an example, the validity and applicability of GW-RSEI were verified for monitoring mining area ecology using multi-phase remote sensing images from 2000 to 2020. The results showed that the indicator weights of GW-RSEI were varied continuously over the space, indicating the spatial heterogeneity within different local surface areas. GW-RSEI shared the average correlation coefficients with universal normalized vegetation index (UNVI), normalized difference moisture index (NDMI), soil index (SI), temperature vegetation dryness index (TVDI) and index-based coal dust index (ICDI) of 0.76, 0.78, -0.77, -0.82 and -0.41, respectively, (P<0.05). Furthermore, the GW-RSEI was integrated each indicator to fully reflected the ecological environment of mining areas. The overall monitoring that obtained by GW-RSEI was similar to that by RSEI over the past two decades. However, the GW-RSEI was focused on the real ecological impacts at the surface, indicating the more reliable at local scales. Whether in areas with single or complex land use types, GW-RSEI exhibited the higher correlations with soil moisture (SM), net primary productivity (NPP) and particulate matter 2.5 (PM2.5) than RSEI. The GW-RSEI monitoring was more consistent with the actual surface, in order to effectively reflect the ecological environment of the mining areas. Therefore, the GW-RSEI was successfully used to monitor the severe pollution of coal dust in local coal mining activity areas. The grade of GW-RSEI was lower than that of RSEI in the areas with the severe pollution of coal dust. The trend was the gradually increasing from the area with the high level of coal dust pollution as the center to the surrounding areas, indicating the spatial pollution in mining areas. The GW-RSEI values were higher than RSEI ones in urban areas of the county with the medium to high vegetation cover, and in rural areas where the land type was mainly arable land and grassland. There were significantly more medium to low GW-RSEI value in the mining area and surroundings, compared with the RSEI. Furthermore, the gradual trend was highlighted the spatial continuity in ecological environment quality. GW-RSEI averages were 0.51, 0.48, 0.46, 0.59, and 0.56, indicating that the overall ecological environment experienced a process of first deterioration and then improvement. The trend in the southeastern region of Datong Coal field was consistent with the overall trend, while the northwestern region showed a trend of first improvement and then deterioration. The GW-RSEI can provide the more effective way to accurately monitor the ecology of the mining area. [ABSTRACT FROM AUTHOR]

The article describes the occurrence of the species Anserindicus, also known as bar headed goose, from a freshwater pitlake of Eastern Coal Fields, India. This species is a widespread winter visitor species in India and is categorized as least concern and is native to countries including Afghanistan, Kyrgyzstan, and Mongolia. Habitat of Anserindicus includes freshwater wetlands, rocky areas, and artificial/aquatic and marine areas.

The Jharia coalfield stands as a paramount asset within the Indian economy. However, many pressing issues, such as coal fires, land subsidence, unplanned mining, child labor, deforestation, and air pollution, demand immediate attention. Effective planning and comprehensive mitigation strategies are imperative to address these challenges. This research centers on evaluating an area near Bhuiyadih village subjected to rat hole mining using non-invasive geophysical methods. The evaluation includes a joint analysis of multiple geophysical techniques, such as gravity, magnetic, and seismic surface wave methods. The potential data has been evaluated by generating edge detection, upward continuation maps, and radial average power spectrum (RAPS) plots. Seismic surface wave velocity structure has been evaluated and used as a constraint to model the subsurface structures using potential field data. Evaluating subsurface layers from the RAPS, Seismic surface wave model, and 2D model generated from the potential data indicates a weathered layer, an overburden sandstone layer, and a coal seam of thickness ~ 4.5 m, ~ 14 m, and ~ 11 m, respectively. The wideness of the gallery boundary has been evaluated using the composite lineament map and found to be surpassing approved limits for underground mining, signifying evidence of rat hole mining practices. The thin pillars in the coal seam and fractures observed on the surface indicate the failure of overburdened rock masses, leading to land subsidence in the nearby villages. The study reinforces the urgency of shifting the local population to a safer environment to avoid unfortunate situations. [ABSTRACT FROM AUTHOR]

For deep underground coal mining ecosystems, research on microbial communities and geochemical characteristics of sediments in different functional zones is lacking, resulting in the knowledge of zone-level mine water pollution prevention and control being narrow. In this study, we surveyed the geochemical distinctions and microbial communities of five typical functional zones in a representative North China coalfield, Xinjulong coal mine. The data indicated that the geochemical compounds and microbial communities of sediments showed distinguishing features in each zone. The microbial community richness and diversity were ranked as follows: surface water > rock roadways > sumps > coal roadways ≥ goafs. Canonical Correlation Analysis (CCA), Spearman correlation and co-occurrence network analysis demonstrated that microbial communities were sensitive and closely related to hydrochemical processes. The microbial community distribution in the underground mine was closely related not only to nutrient elements (i.e., C, S, P and N), but also to redox-sensitive substances (i.e., Fe and As). When it comes to mine water pollution prevention and control, the central zones are goafs. With the increase in goaf closure time, total nitrogen (TN), total organic carbon (TOC) and total sulfur (TS) decreased, but As, Fe and total phosphorus (TP) gradually increased, and the characteristic pollutant SO42− concentration in water samples decreased. Additionally, the sulfate-reducing bacteria (SRB) had relatively higher proportions in goafs, suggesting goafs were able to purify themselves. In practical engineering, in situ nitrogen injection technology used to expel oxygen and create an anaerobic environment can be implemented to enhance SRB reducing sulfate in goafs. Meanwhile, because coal mine pollution discharge generally only discharges mine water and leaves sediment underground, the pollutants can be transferred to the sediment by strengthening the relevant reactions including the heavy metal solidification and stabilization function of bacteria. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Efficient extraction of coal from an underground mine is mainly done under the protection of different forms of coal pillars. It is observed that the coal seams and its host rock contain different geological discontinuities such as weak beds (bands), which affect the strength of pillars. The weak bed creates weak bedding planes. The available pillar strength formulae are based on the width-to-height ratio, depth of cover, and strength of intact coal, and they do not consider the effects of discontinuities. A numerical simulation study on the quarter symmetry model is carried out to assess the impact of weak beds with their positional variation and thickness. The strength of the pillar without discontinuities estimated through the simulation study was validated with those obtained by the indigenous empirical strength formula. A weak bed of 0.2 m, 0.3 m, 0.4 m, and 0.5 m thick was incorporated into the model within the pillar height at different positions and studied its impact on pillar strength. A simulation study revealed that the presence of a weak bedding plane at different positions in the pillar system reduces the strength of the pillar from 3.50% to 15%. However, it was found that the strength is reduced more in the case of a weak roof-pillar interface. [ABSTRACT FROM AUTHOR]

The new economy of Valea Jiului Carboniferous Basin changes the economic profile of the six localities with urban status in Hunedoara County: Petroșani, Vulcan, Lupeni, Petrila, Uricani and Aninoasa. The changes in the new economic landscape occurred in a relatively short period of time (about 33 years) and created educational, social and political imbalances. The new economy proposes the reintegration of a significant part of the population by abandoning extractive operations, reducing the secondary sector of the economy and focusing on the tertiary sector, the service sector. The business environment in the Valea Jiului coalfield is going through a new stage, which began with the restructuring that began in 1990. It is influenced positively or negatively by technological advances, European Union policies, local, national and international political events and the evolution of demand and supply. Technology and strategic innovators have the opportunity to quickly enter competitive markets and replace or assimilate local players. [ABSTRACT FROM AUTHOR]