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Coal is a major source of fuel in many countries, but its mining and use increase the impacts on human and environmental health. Given the wide variation in coal use by nation, we focused on one—the United States. Specifically, we examined the public health, community, and demographic characteristics of 130 U.S. counties with underground and/or surface coal mines that exemplify a land use that leads to a combination of natural and anthropogenic risks. We compared these 130 to other U.S. counties, finding that the coal counties had poorer health outcomes and behaviors, fewer community assets, lower socioeconomic status, and higher population losses compared to the remaining counties in their host states and other U.S. counties. Next, we looked for differences within the 130 coal counties. Counties with the most coal mines and production had the worst outcomes, especially when located in rural areas. We then examined federal programs to assist these coal communities, observing that the largest federal government programs appear to be sending more resources to the most distressed coal counties compared to the less distressed ones. The daunting challenge for the most heavily coal-dependent counties, their state governments, and federal government supporters is to jointly develop plans that are realistic and affordable, take advantage of local natural and human resources, and offer a path to sustainable existence. If the efforts do not succeed, these places run the risk of becoming politically invisible and their populations are likely to empty out. [ABSTRACT FROM AUTHOR]

This paper presents a development of a "smart center" for studying particulate matter (PM) and other gaseous emissions pollution in a surface coal mine located in the Jharia coalfield of Jharkhand, India, utilizing internet of things (IOT)-based capabilities and low-cost sensors data. These pollutants in the air in and around surface mines present significant environmental challenges that require comprehensive assessment and management. This study undertook four winter months from January to April 2023 of real-time, low-cost IoT-based monitoring of PM1, PM2.5, PM10, SO2, NO2, O3, CO, CO2, TVOC, and noise pollution, along with meteorological parameters, such as humidity, rainfall, and temperature. Data were collected at three locations: within a mine site area, in a buffer zone located 1.5 km from the mine, and at a non-impacted residential area within the university campus. Mining operations and active mine fires are primary contributors to pollution. Peak PM concentrations around the mining site were observed during morning and evening hours (5–7 a.m. and 4–6 p.m.). This study further identified that air pollutant concentrations were positively correlated with humidity but negatively correlated with the atmospheric temperature at the mine site, but not at the university campus of the IIT–ISM. [ABSTRACT FROM AUTHOR]

In this study, 47 coal samples from 16 selected coal mines from four provinces of Pakistan (Punjab, Sindh, Balochistan, and Khyber Pakhtunkhwa) were collected and analysed using a HPGe-based gamma spectrometry system. The objective of the study was to assess the occupational radiological risk from coal reserves in Pakistan. The 226Ra concentration values were found to be higher in coal samples collected from two locations in Meting-Jhumpir Coal Fields and one location of Chakwal Coal Field as compared to the recommended value by UNSCEAR (2000). The 232Th concentration values were found to be higher in coal samples collected from two locations in Padhrar Coal Field, one location in Dandot Coal Field and one location in Cherat Coal Field as compared to the recommended value by UNSCEAR (2000). The 40K values in all the analysed samples were found to be well below the recommended value by UNSCEAR (2000). From the radiological parameters, the values of the representative gamma index, which corresponds to an annual effective dose, were found to be higher than 1 Bq-kg−1 among the samples collected from Meting-Jhumpir coal fields, Chakwal coal field, Padhrar coal fields, Dandot coal fields, Hangu coal field, and Cherat coal fields. Excess lifetime cancer risk was estimated to be in the range of 0.07 × 10−3 − 0.34 × 10−3 with an average value of 0.18 × 10−3. The annual effective dose was estimated in the range of 0.01–0.07 µSv- y−1, which is below than the value established by the IAEA as the safe limit for the public in a planned exposure situation (1 mSv-y−1). It can be concluded that for some of the coal fields, the radionuclide concentration values and some of the radiological parameter values were found to be higher than the recommended values. Site-specific studies using direct radiation and radon measurement instruments are proposed for these coal fields to further investigate the radiological situation and its implications on workers and the public's health. Furthermore, we have used a theoretical approach to estimate the occupational health hazard based on the activity concentration of radionuclides in the coal samples, which needs to be validated with the direct-dose measurement techniques. [ABSTRACT FROM AUTHOR]

The net primary productivity (NPP) of vegetation is the key indicator for assessing ecosystem productivity and carbon cycling. The Ulan Mulun River Basin (UMRB) in Northwest China is a typical coal mining area, including open-pit mining (OPM) and underground coal mining (UGM). There are limited studies utilizing long-term, high-resolution data to investigate the spatiotemporal and driving mechanisms of NPP in different types of mining and non-coal mining (NCM) areas. In this study, NPP was estimated using high-resolution Landsat data (30 m) and an improved CASA model for the period 1987–2022. The spatiotemporal variations in NPP across the basin were systematically investigated using Theil–Sen–MK trend analysis, partial derivatives, and multivariate regression residual to explore and quantify the impacts of climate variability (CV) and human activities (HAs) on the different coal mining and NCM areas. The research results show that the overall fluctuating upward trend of vegetation cover in the country is 64.84% during the period from 1987 to 2022. However, there is a decreasing trend of NPP in the coal mining areas. Precipitation was the major factor influencing the change in NPP (21.835 gC/m2/a), while HAs had a lesser effect (4.667 gC/m2/a). In addition, UGM and NCM were more positively affected by HAs than OPM, while OPM was more positively affected by CV than UGM and NCM. These findings can guide scientific ecological restoration strategies, assess carbon balance impacts, and optimize land management and planning in mining areas to achieve a balance between resource development and environmental protection. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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 Rudarsko-Geolosko-Naftni Zbornik is the property of Faculty of Mining, Geology & Petroleum Engineering 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.)

The underground environment and its components are susceptible to various attacks due to their role in monitoring environmental conditions and future predictions. Our review of existing literature reveals that most protocols are vulnerable to impersonation and Man-in-the-Middle attacks, which pose significant risks of data theft from sensors. Additionally, these protocols often impose high computational loads on the sensors. To address these challenges, this article presents an inter-mutual authentication scheme tailored for Wireless Sensor Networks (WSNs). We propose a secure authentication and key agreement protocol using the elliptic curve cryptosystem (ECC), which not only provides session key generation and authentication but also protects against several potential attacks. We conducted comprehensive security analyses, including both formal and informal methods, to validate the robustness of our protocol. The informal analysis, based on a threat model, demonstrates the protocol's effectiveness against various critical attacks. The Random Oracle (RoR) model further establishes that breaking the session key security is challenging. Simulations using Scyther confirm that private parameters remain secure during execution, while AVISPA simulations validate the protocol's resilience against replay attack and Man-in-the-Middle attacks. Furthermore, we assessed the security features, computational and communication costs, and overall performance of the proposed scheme, comparing it with existing studies. Our findings indicate that the protocol offers an average improvement of 36.47% and 48-bits for computation and communication overheads. Additionally, this work also offers enhanced security (secure from all possible attacks), making it an effective solution for securing sensitive data in WSNs. [ABSTRACT FROM AUTHOR]

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

In the present work, processes for wastewater treatment at coal mining enterprises are considered in detail. Such processes are of global importance. The neutralization of soluble and insoluble pollutants in wastewater is investigated; conventional methods are based on the destruction of temporary structures formed by electrical bonds between polarized water molecules, which affect pollutant deposition. Treatment methods for mine wastewater are considered. Calculations of the deposition rate as a function of the combination of treatment parameters are outlined, with graphical interpretation. The deposition rates of coal and rock particles are determined separately, as a function of the relevant parameters. Quantitative relations are established for the reagents used in wastewater treatment. Effective treatment of mine wastewater and other polluted water in settling tanks entails correction of the deposition rates, the size and density of the particles, the static viscosity, the length of the deposition section, the time for the water to pass through that section, and the temperature of the incoming and treated wastewater. The results may be used to optimize the treatment of wastewater in coal mining and other extractive industries. [ABSTRACT FROM AUTHOR]

Abstract Coal is currently the most important energy source in most countries. With the advent of information intelligence, more and more intelligent technologies are being applied in coal mine detection. A new model for coal mine drilling detection, which combines improved YOLOv5 and Gaussian filtering, is proposed to address the low efficiency and poor accuracy in manual detection of coal mine drilling. This new model incorporates attention mechanism and multi-object detection model on the basis of traditional YOLOv5. Due to factors such as equipment vibration and electrical interference in drilling detection, random noise is often mixed into the image signal data obtained. In order to effectively reduce the impact of noise on data and improve signal-to-noise ratio, Gaussian filtering method is studied for data denoising. This new model’s border regression loss value was 0.004 lower than the YOLOv5 loss value. This new optimization method’s accuracy was improved from 0.966 to 0.982. This new model improved the detection accuracy of small cracks by about 0.05. The detection depth of the coal seam in this new model was 9.54 m, which was closer to the true value than other methods. Therefore, using the new model to detect coal mine boreholes can effectively improve the accuracy of borehole detection images, which has a good effect on the analysis of coal mine rock layers. This new model has a good guiding role in the detection images and rock analysis research of future coal mine boreholes. The research has good research value in oil drilling inspection, natural gas pipeline monitoring, and quality inspection of industrial automation systems. This provides important technical support for future coal mine drilling image detection and rock analysis research.

Abstract Roof stability is a critical concern in coal mines, as the potential for roof collapse poses a significant risk to miners' safety and productivity. Roof stability is heavily influenced by the time-dependent properties of the rock mass above the workings. This study uses rock displacement testing to examine the effect of time-dependent properties on roof stability and resistance reduction in coal mines in Iran. The study employed laboratory-based rock displacement tests on samples collected from coal mines in Iran, subjected to varying stress levels over time, to simulate the gradual deterioration of rock mass strength in underground mining conditions. The samples were monitored for displacement under these conditions to quantify the reduction in roof resistance over time and assess its effect on roof stability. The study found that areas with high stress at equilibrium gradually fail with time, and the stress transfers from the failure zone into deeper solid rock. The results demonstrate that varying viscous parameters can lead to different relaxation behaviors and stress distribution. Furthermore, incorporating strength degradation into numerical simulation can capture the failure under creep conditions and improve the accuracy of predicting time-dependent roof failure. This research aims to enhance safety measures and reduce the risk of collapses by investigating the time-dependent properties of roof stability through rock displacement testing in Iran's coal mines. The study's innovative approach uses numerical simulation based on the viscoelastic-plastic model to simulate the time-dependent behavior of the rock and incorporate strength degradation into the simulation. The results provide valuable insights into the time-dependent behavior of rock mass in coal mines in Iran and contribute to developing strategies for improving roof stability and lessening the chance of roof collapses. The instantaneous elastic strain was 4.35 × 10–4, and creep simulation was activated to run for a time equivalent to 2 × 106 s.

Coal is currently the most important energy source in most countries. With the advent of information intelligence, more and more intelligent technologies are being applied in coal mine detection. A new model for coal mine drilling detection, which combines improved YOLOv5 and Gaussian filtering, is proposed to address the low efficiency and poor accuracy in manual detection of coal mine drilling. This new model incorporates attention mechanism and multi-object detection model on the basis of traditional YOLOv5. Due to factors such as equipment vibration and electrical interference in drilling detection, random noise is often mixed into the image signal data obtained. In order to effectively reduce the impact of noise on data and improve signal-to-noise ratio, Gaussian filtering method is studied for data denoising. This new model's border regression loss value was 0.004 lower than the YOLOv5 loss value. This new optimization method's accuracy was improved from 0.966 to 0.982. This new model improved the detection accuracy of small cracks by about 0.05. The detection depth of the coal seam in this new model was 9.54 m, which was closer to the true value than other methods. Therefore, using the new model to detect coal mine boreholes can effectively improve the accuracy of borehole detection images, which has a good effect on the analysis of coal mine rock layers. This new model has a good guiding role in the detection images and rock analysis research of future coal mine boreholes. The research has good research value in oil drilling inspection, natural gas pipeline monitoring, and quality inspection of industrial automation systems. This provides important technical support for future coal mine drilling image detection and rock analysis research. [ABSTRACT FROM AUTHOR]

Ventilation is critical in underground coal mining (UCM) for safety and productivity. Challenges include mitigating hazardous gases, preventing coal dust accumulation, and achieving a balance between extraction efficiency and environmental concerns. Optimization techniques address these challenges, aiming for enhanced safety, productivity, and sustainability. But, these algorithms need careful tuning and adaptation to dynamic mine conditions to prevent suboptimal solutions and ensure robust optimization performance. Hence, in this research work, a hybrid optimization-based control system is proposed for energy consumption minimization of mine ventilation fan and load management in UCM. The proposed hybrid optimization process is formulated into multi-objective optimization solutions like energy-saving optimization and load management in coal mines. The proposed hybrid optimization technique is the combination of both the Border Collie optimization (BCO) and Aquila optimizer (AO), and hence, it is named as BCOAO technique. At first, based on the ventilation on demand (VOD), the energy consumption is minimized using BCO technique and obtains the optimal main fan speed profile. With this procedure, the energy saving is improved as a consequence, healthy atmosphere with higher performance in the mines. Secondly, based on the time of use (TOU) tariff, the mining schedule starting time is found and analyzed in the load management using AO technique. The performance is carried out in the MATLAB platform and tested with three case studies. The overall energy saving percentage obtained by the proposed hybrid technique for three cases are 25, 38, and 54.5%, respectively. [ABSTRACT FROM AUTHOR]

This paper considers extreme dusty conditions at workplaces in underground coal mine. These extreme conditions stem from various physical factors that affect employees' performance. The extreme effect of the dust can significantly contribute to permanent health damage or even the death of employees. In this study, we present and discuss the results of measurements of airborne dust and respiratory dust taken during wall cutting in a coal mine and propose effective measures to reduce the burden on the life and health of employees and the environment. [ABSTRACT FROM AUTHOR]

In order to meet the requirements for the use of polyurethane for reinforcement in mines, the synthesis temperature of polyurethane needs to be lowered, and the flame-retardant and mechanical properties of polyurethane should also be considered comprehensively. Factors affecting the synthesis temperature of polyurethanes are investigated, low heat storage polyurethanes that meet the temperature requirements for use in plugging crushed coal bodies in coal mines are formulated, and the synthesized polyurethanes are characterised for their flame retardant properties by FTIR, SEM, TG-FTIR and CONE experiments. It was found that in this paper, a new type of polyurethane for coal mines was formed by flame retardant modification of polyurethane by adding nano-system flame retardant and phosphorus-system flame retardant, and the synthetic reaction temperature of the material could reach as low as 51.2 °C, and the pyrolysis onset temperature was increased to 286 °C. The experimental results show that the flame retardant property of this synthetic polyurethane has been significantly improved, and the heat accumulation effect of the synthesis process on the surrounding coal body has been greatly reduced. The physical properties and thermal stability of this synthetic polyurethane in the grouting process meet the safety requirements for use in underground coal mines.

Re-usability of wastewater from open pit coal mines and surface flows is discussed with regard to the adopted water circulation cycles. The analysis of process flow charts of open pit coal mining and water use made it possible to identify the main trends of wastewater application and volume reduction. A flowsheet of integrated treatment and distribution of wastewater in open pit mines is developed. It is shown that efficient management of intramine water consumption and expansion of cooperation with wastewater consumers can allow high-rate recycling of industrial wastewater. The proposed activities can help reduce environmental pressure in coal mining areas, and decrease amount of wastewater which need advanced treatment down to maximum allowable concentration of harmful agents in fishery water bodies. [ABSTRACT FROM AUTHOR]

The emission of gas from the coal seams is one of the most important issues during the underground coal mining operation. Each year, coal gas emission from the underground stopes leads to the death of a large number of miners and is one of the biggest threats to workplace safety. In addition, ventilating and releasing coal gas outside of the mine is too expensive and, in most cases, might be impossible. Therefore, it is necessary to increase gas emissions and improve the efficiency of methane drainage for securing the mining workplace. The main aim of this paper is to investigate the capacity of the drainage system in the Parvadeh Tabas Coal Mine, Iran. For this purpose, the effect of the specification of the drilling pattern such as the length and drilling direction of the drilled boreholes on the methane gas concentration was investigated. The results of this study show that, with the change in the length of the borehole and the angle of the boreholes according to the axis of the tailgates, the volume of the methane drainage changes, significantly. The boreholes with lengths between 60 and 80 m drilled in lines with 16-degree division from a line perpendicular to the tailgate have the highest methane concentration. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, revitalising the coal sector is a key challenge. This article examines how five innovative technologies can transform abandoned or in-use coal mines into sustainable energy centres. From solar thermal to compressed air energy storage, these solutions offer a path to a more sustainable future while addressing the decline in coal production. This approach not only promotes energy efficiency but also contributes to the mitigation of environmental impacts, thus consolidating the transition to a more responsible energy model. Thus, in this document, the reader can find the explanation of why we have opted for these technologies and not other existing ones. In addition, the economic, environmental and technical feasibility of the different technologies is analysed. Finally, real cases of the successful application of these technologies will be presented once they have gone beyond the project idea phase, and the reasons why we are calling for their transposition to the coal industry in the search for its revitalisation will be explained. [ABSTRACT FROM AUTHOR]

In order to solve the problem of low safety and efficiency of underground mine vehicles, a path planning method for underground mine vehicles based on an improved A star (A*) and fuzzy control Dynamic Window Approach (DWA) is proposed. Firstly, the environmental information is analyzed, and the proportion of obstacles is introduced into the A* algorithm to optimize the heuristic function to improve its search efficiency in different environments. Secondly, for the global path, the key node selection strategy is proposed, the node selection method is optimized, and the redundant nodes are deleted. The path is optimized by using a 3 times Clamped-B spline to improve the smoothness of the path. Then, based on the principle of fuzzy control, fuzzy rules are established, and a DWA fuzzy controller is designed to improve the environmental adaptability of the DWA algorithm. Finally, on the basis of the global path, the key node is used as the local target point of the DWA, and the fusion of the improved A* and DWA algorithm is realized. Finally, experiments are conducted to verify the effectiveness and feasibility of the proposed path-planning method. The average deviation of the path is controlled at ±0.109 m, which basically meets the path planning needs of underground mine vehicles. [ABSTRACT FROM AUTHOR]

Abstract There is an urgent need to develop optimal solutions for deformation control of deep high‐stress roadways, one of the critical problems in underground engineering. The previously proposed four‐dimensional support (hereinafter 4D support), as a new support technology, can set the roadway surrounding rock under three‐dimensional pressure in the new balanced structure, and prevent instability of surrounding rock in underground engineering. However, the influence of roadway depth and creep deformation on the surrounding rock supported by 4D support is still unknown. This study investigated the influence of roadway depth and creep deformation time on the instability of surrounding rock by analyzing the energy development. The elastic strain energy was analyzed using the program redeveloped in FLAC3D. The numerical simulation results indicate that the combined support mode of 4D roof supports and conventional side supports is highly applicable to the stability control of surrounding rock with a roadway depth exceeding 520 m. With the increase of roadway depth, 4D support can effectively restrain the area and depth of plastic deformation in the surrounding rock. Further, 4D support limits the accumulation range and rate of elastic strain energy as the creep deformation time increases. 4D support can effectively reduce the plastic deformation of roadway surrounding rock and maintain the stability for a long deformation period of 6 months. As confirmed by in situ monitoring results, 4D support is more effective for the long‐term stability control of surrounding rock than conventional support.

Abstract Coal mine galleries and construction tunnels are commonly excavated using roadheaders. Estimating the performance of roadheaders is crucial for planning and cost estimation when planning tunnel or tunnel projects. The aim of this study is to derive generalized performance prediction models including Schmidt hammer value, needle penetration index, and volumetric joint count for roadheaders used in coal mines. The performance measurements of axial and transverse type roadheaders were carried out in six different coal mines. Schmidt hammer tests, needle penetration index tests, and of volumetric joint count measurements were also performed at the locations where the performance measurements were conducted. The extensive data were evaluated using multiple linear and nonlinear regression analysis. The developed formulas were evaluated using statistical tests. The Equations that include the Schmidt hammer value or needle penetration index value in addition to cutter head power have been shown to be unreliable. However, the equations that include Schmidt hammer value or needle penetration index value in addition to cutterhead power and volumetric joint count have been shown to be reliable. This study concludes that the developed reliable equations can be used for the performance assessment of roadheaders used in coal mines.

Underground coal mines are always faced with their own specific uncertainties. These uncertainties lead to safety risks and ultimately result in chaos and safety disturbances. Human factors are among the uncertainties that play a vital role in various industries, including underground coal mining. For instance, they affect safety, production processes, machinery maintenance, and productivity. Risk management is one of the primary methods for improving safety in underground coal mines. Risk management is a process that helps identify, assess, and mitigate risks and uncertainties. Its main goal is to protect resources, enhance safety, and increase efficiency through informed decision-making. This article examines the role of human factors in risk assessment of coal mines; it first classifies human factors and then uses the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) method for pairwise comparison to evaluate the risks of underground coal mines. The TOPSIS method is a multi-criteria decision-making technique that operates based on the distance of options from the best and worst solutions. This method ranks the options based on specific criteria and assists in selecting the optimal option. The results of the study on human factors indicated that carelessness, negligence, and distraction had the greatest impact on the risk assessment of underground coal mines, with a similarity index of 0.6516, while the level of education had the least impact with a similarity index of 0.2871.

Gas explosion accidents are the most serious type of accidents that cause losses in coal mines. In order to explore the pattern of unsafe actions related to such accidents and to regulate the behaviors of relevant work types in the operation process of underground coal mines, 116 serious gas explosion accidents in coal mines from 2005 to 2022 were statistically analyzed to explore the distribution characteristics of unsafe actions in different dimensions of gas explosion accidents in coal mines, to discuss the reasons for their occurrence, and to put forward targeted measures. The results show that: from the aspect of the coupling of work type and accident location, blasting operators and tile inspection operators have the highest number of unsafe actions in the face of digging and coal mining, respectively; from the aspect of the coupling of work type and laws and regulations, blasting operators are the operators with the highest frequency of violating the regulations, and the most violated regulations is the Coal Mine Safety Regulations.

The research was employed to simulate the watershed's hydrologic behavior and to predict stream flow in the Mahan River catchment area alongside the effect of six underground (UG) and opencast (OC) mines for the past decades. Following the SWAT model run, the mining area sub-watersheds possess (SW20, SW26, SW28, SW31 and SW38) a comparatively lesser sediment yield of 61.41 Metric Ton/ha than that of non-mining area sub-watersheds 159.40 Metric Ton/ha. Amongst all hydrological components, evapotranspiration with 531.2 mm consumed 39% of the total annual precipitation (1365.3 mm). The total discharge was estimated to be 775.57 mm, which comprises Surface Runoff of about 351.89 mm, Return Flow (402.21 mm) and Lateral flow (21.47 mm), while percolation into the unconfined and confined aquifers as soil and groundwater storage also accounted for 58.86 mm. The statistical indicators and graphs indicate that the model performs satisfactorily for the daily streamflow (R2 = 0.875, p = 0.71, r = 0.76 and NSE = 0.87 during the validation (R2 = 0.817) as that during the calibration period. The model performed satisfactorily during the simulation and the results showed that the mines play a critical role in changing the hydrological regime of the watershed with low recharge and moderate evapotranspiration characteristics. Taken together, the SWAT model appears to be a reliable tool for forecasting stream discharge over long periods of time, in parallel with the likely impacts of mining activity on HRUs. [ABSTRACT FROM AUTHOR]

Research on shantytown transformation in the context of building sustainable human settlements has tended to concentrate on macro and objective factors. However, there is still room for expanding research on the livelihoods of residents in transformed poor communities of resource-based cities. This study is based on household survey data after the coal mine shantytown transformation in Datong, China, and uses the entropy method and Logit regression model to analyze the livelihood level and impact of livelihood capital on the choice of livelihood strategies of the residents after shantytown transformation. Based on the development characteristics of the Datong coal mining community, the traditional sustainable livelihood analysis framework is improved, constructing a livelihood capital evaluation system including natural capital, physical capital, financial capital, social capital, human capital and cultural capital. The research indicates that the livelihoods of the residents after shantytown transformation are in a state of low-value aggregation and differentiation, their livelihood strategies are still dependent on coal mining, financial capital and cultural capital have significant positive impacts on the residents' livelihood strategies of choosing coal mine-related industries, and males and elderly people have a greater likelihood of choosing coal mine-related industries. This study provides micro-level explanations for the livelihood status and livelihood strategy choices of residents after shantytown transformation in a resource-based city and provides policy enlightenment for local governments on how to promote the sustainable development of residents in coal mining communities. [ABSTRACT FROM AUTHOR]

Coal mines often leave an ecological footprint that can damage the environment. One impact that is often overlooked but has long-term consequences is changes in ground surface temperature, especially in forest areas adjacent to mining sites. This research focuses on an in-depth analysis of the land surface temperature in forested areas around coal mines. Forest areas were chosen as the focus of the study because forests have a crucial role in maintaining climate and ecosystem balance. The analysis method which used in this research is the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) with data sourced from LANDSAT- 8 satellite imagery. The results of the measurements in forest areas adjacent to coal mines showed that ground surface temperatures reached a range of 30.0-36.0°C. This figure is higher when compared to ground surface temperatures in natural forested areas that are not affected by mining activities, which range between 27.5-31.0°C. This significant temperature difference shows the direct influence of mining activities on the thermal conditions of the soil in the forested area around the coal mining area. Increasing ground surface temperatures in forested areas near coal mines can reduce soil moisture and affect vegetation growth. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of The Mineral & Energy Economy Research Institute of the Polish Academy of Sciences / Zeszyty Naukowe Instytutu Gospodarki Surowcami Mineralnymi Polskiej Akademii Nauk is the property of Mineral & Energy Economy Research Institute of the Polish Academy of Sciences 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.)

Abstract Globally, studying the impact of coal mining on groundwater remains challenging. This is because the exploitation of coal resources and the sustainable development of groundwater resources involve economic, social, and environmental aspects. Over the last few decades, the number of publications on groundwater-related studies in coal mining areas has increased. However, they are not currently reviewed in a widely visible manner through bibliometric analyses. This study investigated groundwater research in coal mining areas worldwide using scientometric analysis based on 1196 articles from the Web of Science database to provide a global perspective and gain quantitative insight into research frontiers and trends in the field by mapping existing knowledge. We analyzed the key contributors and development processes of coal mine groundwater research and identified four research frontiers based on scientometric mapping results with an understanding of the research field: numerical modeling, conceptual modeling and mechanisms, feedback mechanisms between anthropogenic-environmental systems and groundwater systems, ground subsidence management, groundwater quality evaluation and risk assessment, and groundwater resource management in coal mines. Finally, we summarize the current challenges and propose methods to promote the green mining of coal resources and the sustainable development and management of groundwater resources.

This paper considers extreme dusty conditions at workplaces in underground coal mine. These extreme conditions stem from various physical factors that affect employees’ performance. The extreme effect of the dust can significantly contribute to permanent health damage or even the death of employees. In this study, we present and discuss the results of measurements of airborne dust and respiratory dust taken during wall cutting in a coal mine and propose effective measures to reduce the burden on the life and health of employees and the environment.

Aerosol optical depth (AOD), an important parameter for ecological studies, is paramount when assessing modifications in climate patterns. To evolve a regional aerosol representation of four varied coalfields across Assam, sixteen years (2003–2019) of aerosol variability and trends in aerosol loading through spectral AOD using MODIS-Terra (Moderate Resolution Imaging Spectroradiometer) was interpreted. Assam is part of the Indo-Gangetic Plain (IGP), India, and can be considered a key hotspot for the continuous contribution of aerosols. This first-of-its-kind study analyzed the long-term spatio-temporal variations in AOD in Assam's coal mines by combining it with the long-term satellite observations from MODIS. The Assam region revealed a varied and distinct spatio-temporal variability in aerosol distribution. For the annual average AOD in coal mines, Assam varied from 0.61 to 0.35, where Singrimari reported the highest mean AOD, indicating it is home to the state's high-polluting coal mines, whereas Sheelveta reported the lowest AOD value. Seasonal variation was additionally extrapolated, with minimum AOD during post-monsoon and monsoon and maximum AOD during summers and winter months. Moreover, a statistically significant increasing trend in the aerosol concentration was noticed in all four regions, namely, Singrimari (27.29%), Sheelveta (14.59%), Dilli-Jeypore (11.58%), and Mikir (16.27%). This study is significant since it evaluates the air pollution produced over mines, as well as the degree of aerosol concentration produced. The study also suggests effective strategies for decreasing mining-induced air pollution. The findings of this study support future climate projections and provides baseline data for policymakers and model simulation for climate change analysis. [ABSTRACT FROM AUTHOR]

The global concern about water quality in coal mining operations is a significant issue. It presents detrimental water-related threats, including pollution, acid mine drainage, and habitat destruction. In this study, an attempt has been made to evaluate the water quality for domestic, irrigation and industrial purposes in the coal mining province of Mahan catchment area, with a particular focus on the impact of coal mining activities. 50 samples from pre-monsoon season of 2018, collected from dug well, tube well, mine water and river water were analyzed. The findings indicate that water in the study area exhibits acidic characteristics, with pH values below the desirable range for drinking water. Elevated electrical conductivity, total dissolved solids, sulphate, total hardness and chloride concentrations are observed, particularly around core mining regions. For irrigation suitability, the study reveals that most of the samples are suitable, based on parameters such as sodium percentage (Na%) sodium adsorption ratio (SAR), magnesium hazard (MH), Kelly's index (KI), permeability index (PI), and residual sodium carbonate (RSC). However, majority of the samples collected from core mines show an elevated range of Na% (>80), SAR (>60), MH (>50), KI (>1), PI (>100), RSC (>2.5) and PS (>5) indicating potential soil permeability issues and crop damage, which restrict its suitability for agricultural use. Furthermore, the assessment of water for industrial suitability by analyzing the scaling and corrosion indices, such as the Langelier index (LI), aggressive index (AI), Ryznar index (RI), Puckorius index (PI), and corrosivity ratio (CR) highlights the presence of a corrosive tendency in majority of the water samples, particularly in the mining areas. [ABSTRACT FROM AUTHOR]

Conventional sources of rare earth elements including Yttrium (REY) are not sufficient to meet the global demand. This article targets to delineate alternative resources such as coal and overburden rocks (OB) associated with the respective coal mines. The authors have reported the occurrence and distribution pattern of REY, and seamwise mineralogical variations in some coal mines of Jharia and Rajmahal Basins. In addition to REY, occurrences of some other trace and critical elements like Sc, Ga, Sr, Rb, Nb, etc., in coal and OB have also been reported. The mineralogical transformation and REY partitioning from coal to high-temperature ash (HTA) have also been determined. The highest composition of REY in coal, HTA and OB has reached up to 239.2, 1012.4 and 1051.0 ppm, respectively. Thus, the REY content in all coal and HTA is higher than the global cut-off grade. The enrichment of REY from parent coal to HTA can be understood by the enrichment coefficient (Δe), thus, Δe of each HTA is estimated to reach up to a maximum of 7.01. Outlook coefficient (Cout) is used in demarcating REY ore body as promising, highly promising and unpromising. The Cout of the present study ranges from 0.57 to 2.16. The highest Cout of coal, HTA and OB are 1.09, 0.88 and 2.16, respectively. The findings of the present study are encouraging for some promising secondary resources of REY. Research highlights: Coal, coal ash and OB rocks as alternative sources of rare earths and Yttrium Seamwise mineralogical variations in coal, HTA and OB rocks Occurrence and distribution of REY in Jharia and Rajmahal mines of Gondwana coalfield Use of outlook coefficient to determine potential secondary source of REY [ABSTRACT FROM AUTHOR]

To improve the accuracy of personnel positioning in underground coal mines, in this paper, we propose a convolutional neural network (CNN) three-dimensional (3D) visible light positioning (VLP) system based on the Inception-v2 module and efficient channel attention mechanism. The system consists of two LEDs and four photodetectors (PDs), with the four PDs on the miner's helmet. Considering the height fluctuation of PD and the impact of wall reflection on the received light power, we adopt the Inception module to perform a multi-scale extraction of the features of the received light power, thus solving the limitation of the single-scale convolution kernel on the positioning accuracy. In order to focus on the information that is more critical to positioning among the numerous input features, giving different features of the optical power data corresponding weights, we use an efficient channel attention mechanism to make the positioning model more accurate. The simulation results show that the average positioning error of the system was 1.63 cm in the space of 6 m × 3 m × 3.6 m when both the line-of-sight (LOS) and non-line-of-sight (NLOS) links were considered, with 90% of the localization errors within 4.55 cm. During the experimental stage, the average positioning error was 11.12 cm, with 90% of the positioning errors within 28.75 cm. These show that the system could achieve centimeter-level positioning accuracy and meet the requirements for underground personnel positioning in coal mines. [ABSTRACT FROM AUTHOR]

In order to solve the problem of low safety and efficiency of underground mine vehicles, a path planning method for underground mine vehicles based on an improved A star (A*) and fuzzy control Dynamic Window Approach (DWA) is proposed. Firstly, the environmental information is analyzed, and the proportion of obstacles is introduced into the A* algorithm to optimize the heuristic function to improve its search efficiency in different environments. Secondly, for the global path, the key node selection strategy is proposed, the node selection method is optimized, and the redundant nodes are deleted. The path is optimized by using a 3 times Clamped-B spline to improve the smoothness of the path. Then, based on the principle of fuzzy control, fuzzy rules are established, and a DWA fuzzy controller is designed to improve the environmental adaptability of the DWA algorithm. Finally, on the basis of the global path, the key node is used as the local target point of the DWA, and the fusion of the improved A* and DWA algorithm is realized. Finally, experiments are conducted to verify the effectiveness and feasibility of the proposed path-planning method. The average deviation of the path is controlled at ±0.109 m, which basically meets the path planning needs of underground mine vehicles.

In the context of carbon neutrality, the phase-out of coal from the energy structure has resulted in numerous old coal mines that possess abundant underground space resources suitable for underground pumped hydroelectric energy storage (UPHES). Site selection and estimation of potential are critical to the planning and implementation of UPHES in old coal mines. This paper introduces a two-step site selection concept, including a screening assessment followed by a comprehensive assessment, to determine suitable locations for UPHES. The screening indicators in the screening assessment comprise geological features, mine water disasters, and minimum installed capacity, while the analytic hierarchy process (AHP) is applied in the comprehensive assessment. Additionally, coal mines in Henan Province are preliminarily screened through the screening assessment and the potential for UPHES is thoroughly investigated. The estimated volume of the drifts and shafts in old coal mines is approximately 1.35 × 107 m3, while in producing coal mines, it is around 2.96 × 107 m3. Furthermore, the corresponding annual potential for UPHES is 1468.9 GWh and 3226.3 GWh, respectively. By consuming surplus wind and solar power, UPHES is able to reduce 4.68 × 105 tonnes of carbon dioxide (CO2) emissions. The study provides preliminary guidance for policy-makers in developing UPHES in old coal mines. [ABSTRACT FROM AUTHOR]

Biological invasions are one of the major challenges to the restoration of post-mining sites. Most postmining sites are under technical reclamation with only a few left to spontaneous vegetation processes. Therefore, we know little about alien plant species on spontaneously-vegetated post-coal mine heaps and how native community characteristics predict their establishment. To fill the knowledge gap, we aimed to determine the drivers of alien species colonisation on post-coal mine heaps. Specifically, we asked: (i) Which alien species are the most successful on post-coal mine heaps and why? (ii) What are the drivers of alien species richness and cover, and how are they affected by the native community? (iii) What does it mean for predicting threats from alien species and management? We recorded vascular plant species and their abundance across 400 plots on post-coal mine heaps in Upper Silesia, Poland. We calculated plant community taxonomic and functional characteristics and, using mixed-effects models, we estimated predictors of alien species richness and cover. We found 65 alien species on post-coal mine heaps, comprising 20.4% of all recorded species, including 36 neophytes and 29 archaeophytes. Amongst them -- Erigeron canadensis, Solidago gigantea, Solidago canadensis, Erigeron annuus and Impatiens parviflora -- were the most frequent on the studied heaps. We showed that native functional richness significantly predicts alien species richness and cover. Similarly, native community-weighted mean (CWM) seed mass and plant height predict alien species cover. However, CWM of specific leaf area for native species marginally predicts alien species richness. We showed that alien species cover decreases with native species cover. Our findings revealed the ecological significance of niche-filling and the biotic acceptance hypotheses on post-coal mine heaps. We demonstrated how exploring native community characteristics can help in understanding the invasibility and management of post-industrial vegetation. [ABSTRACT FROM AUTHOR]

The article focuses on a theoretical and experimental framework for the quantification of interaction between nonlinear geomechnical and physicochemical processes in high-stress coal-bearing rock mass during mining under high seismic risk due to large-scale blasting and earthquakes, as well as because of structural and temperature effects. The tests were aimed to examine and study comprehensively the piston mechanism of gas exchange and mass transfer processes, revealed recently at the Institute of Mining, SB RAS, as well as to explain the fact that the earthquake-induced low-velocity (quasi-meter range) pendulum waves (velocity to 1 m/s and frequency of 0.5–5 Hz) could stimulate an increase in the gas content in coal mines. In order to perform laboratory investigation at the Institute of Mining SB RAS, special-purpose stand for analyzing gas exchange and mass transfer processes in coal-bearing geomaterials under various thermodynamic conditions (P, V, T) and gas composition was constructed in cooperation with the Institute of Semiconductors Physics SB RAS. Matching of air flow rate with compression pressures allowed to obtain relations showing that air flow rate increases at the uncertain time interval under the increasing of the compression pressure. The same measurements was carried out with another gases such as Hydrogen H2, Helium He, methane CH4, carbon dioxide CO2 and carbon oxide CO. The laboratory tests aimed to detailed investigation of the previously revealed “piston mechanism” of gas exchange and mass transfer processes in the coal specimens and their quantitative description in terms of theory of the pendulum waves were carried in the first time. Consequently, there are some arguments for the testing of the opportunity of quantitative description of the “piston mechanism” related to gas exchange and mass transfer processes in the scale of coal mines. It is relevant when pendulum waves induced by powerful earthquakes and technical blasting reaches the mine. [ABSTRACT FROM AUTHOR]

Bed-separation water inrush (BSWI) is a new type of coal mine disaster that has caused serious damage. The shortcomings of previous studies on this topic are as follows: 1) most studies focused on the BSWI mechanism, evolution, and control methods, and there is a lack of research on BSWI risk assessment methods and 2) previous risk assessment studies ignored the factors of the water yield property. First, based on the proposed BSWI engineering geological model, three first-order factors are proposed: 1) separation space between layers, 2) water production characteristics, and 3) water resistance effect. Then, eight secondary factors are determined: 1) production thickness (MT), 2) hard rock thickness (HRT), 3) improved lithology index (ILCI), 4) core recovery (CR), 5) aquifer depth (AD), 6) drilling fluid consumption (DFC), 7) protective layer thickness (PLT), and 8) self-healing potential index (SPI). Subsequently, the corresponding weights are calculated, and the multifactor superposition method is used to draw the BSWI risk map. The area is divided into three risk grades: low, medium, and high. The results are validated by observations of BSWI accidents and bed-separation water exploration and discharge boreholes in the study area. The proposed method can be used to effectively prevent BSWI disasters in other coal mines with similar geological conditions. [ABSTRACT FROM AUTHOR]