Mining Research Articles

A 35-Year Analysis of Vegetation Cover in Rare-Earth Mining Areas Using Landsat Data

Fractional vegetation cover (FVC) plays a significant role in assessing ecological quality and protection, as well as soil and water conservation. As a typical rare-earth resource county in China, Dingnan County has experienced rapid development due to rare-earth mining, resulting in significant alterations to vegetation cover. To elucidate the spatio-temporal changes in vegetation within Dingnan County over the past 35 years and the effects of natural and human factors on these changes, the spatial and temporal variations in FVC were analyzed using Landsat-TM/OLI multispectral images taken in 1988, 1995, 1997, 2002, 2006, 2013, 2017, and 2023. The findings indicate that (1) vegetation coverage in Dingnan County decreased from 1988 to 2002, followed by a gradual increase; (2) high vegetation cover is predominantly found in forested areas that maintain their natural state, while the central town and mining areas exhibit generally low coverage; (3) there are regional differences in the relationship between vegetation cover and environmental factors in Dingnan County. This research facilitates the alignment of ion-type rare-earth mining with ecological protection, thereby promoting the sustainable development of the mining area and providing scientific guidance for local governments to formulate more effective management and protection strategies for the mining ecosystem. Additionally, this research offers a scientific foundation for mining areas globally to develop sustainable policies and informed decision-making regarding environmental protection and sustainable development.

Application of Aeromagnetic Survey in Detecting Potential Mineralization Zones Around Dongzhongla Deposit, Gangdese Metallogenic Belt

The Dongzhongla deposit is a skarn-type lead–zinc ore deposit located in the eastern segment of the Gangdese metallogenic belt, situated in the Xizang province, China. The high-altitude mountainous terrain of the region poses significant challenges to ground-based exploration. To facilitate more accurate mineral exploration in the deposit and its surrounding area, a high-resolution airborne magnetic survey was conducted over the mining area and its periphery. The airborne magnetic data were processed using derivative and Euler deconvolution methods, yielding results that reflect the geological structural features of the study area. By integrating the geological characteristics of the ore deposit, we inferred that the areas of magnetic anomaly extensions and the peripheries of other magnetic anomalies are favorable zones for mineralization, providing positive leads for further mineral exploration.

Prediction of Floor Failure Depth in Coal Mines: A Case Study of Xutuan Mine, China

Accurately predicting the failure depth of coal seam floors is crucial for preventing water damage, ensuring the safe and efficient mining of coal seams, and protecting the ecological environment of mining areas. In order to improve the prediction accuracy of the coal seam floor failure depth, an improved support vector regression (SVR) model is proposed to predict the floor failure depth by taking the 3234 working face in Xutuan Mine as an example. This improved model incorporates principal component analysis (PCA) and slime mould algorithm (SMA) optimization techniques. First, based on the measured data of seam floor failure depth in several mining areas, a prediction index system of floor failure depth was constructed. Subsequently, the PCA method was used to reduce the dimension of the measured data of the coal seam floor failure depth, and the input structure of the SVR model was optimized. Then, the SMA was used to optimize the key parameters, namely the penalty factor (C) and kernel function parameter (g), in the SVR model, achieving automatic parameter selection and obtaining the optimal parameter combination. This process led to the establishment of a coal seam floor failure depth prediction model based on PCA-SMA-SVR. The predictive performance of the PCA-SMA-SVR model, SMA-SVR model, and SVR model was quantitatively evaluated and compared using four quantitative indicators, and the results showed that the PCA-SMA-SVR model had the smallest MAE, RMSE, MRE, and TIC values, which were 1.0470 m, 1.2928 m, 0.0628, and 0.0374, respectively. Finally, the PCA-SMA-SVR model was used to predict that the floor failure depth of the 3234 working face in Xutun Mine was 17.09 m, and the predicted result was compared and analyzed with the results of four commonly used empirical formulas (16.03–21.74 m). The results show that the model is close to the results of four commonly used empirical formulas, indicating that the model has high predictive performance and good practicality. This study is of great significance for the safety, green mining, and ecological environment protection of coal mines.

Baseline assessment of microplastics and biochemical response of Anadara antiquata as a sentinel species for biomonitoring in Fiji

Context Microplastics are a concern for maritime nations such as Fiji, which rely heavily on seafood, such as bivalves, which can transfer pollutants through the food chain. The lack of biomonitoring studies in the Pacific region highlights the necessity of researching microplastic pollution in seafood. Aims This study quantifies microplastics in Anadara antiquata, a commonly consumed shellfish in Fiji, and evaluates its general biochemical responses. As a baseline, this study is not to draw an association between the two endpoints (microplastics and biochemical responses), rather present these as baselines for future studies. Methods A total of 58 specimens from Ba River Delta, Rakiraki Bay and Vueti Navakavu were examined, where differences in potential sources or pathways for microplastics, including anthropogenic pollutants with the potential to induce stress on marine animals, were considered (rivers, industrial zones, stormwater outlets, sewerage outfalls and mining area). Specific hepatopancreatic enzyme activities associated with detoxification (glutathione-S transferase, GST) and oxidative stress (glutathione peroxidase, GPX, and glutathione reductase, GR) were measured. Key results Microplastics were extracted, classified by morphology and quantified. The study found that 64% of specimens had microplastics, <1.0 mm being more prevalent. Ba River Delta showed significant biochemical stress (Kruskal–Wallis test; P < 0.05) with GST (χ2 = 40.28, d.f. = 2, P-value < 0.001), GPX (χ2 = 38.38, d.f. = 2, P-value < 0.001) and GR χ2 = 45.14, d.f. = 2, P-value < 0.001) being considered as likely to be responding to pollution. Conclusion As a baseline, the study underlines the need for biomonitoring as a result of varying and concerning levels of pollution and biochemical stress responses found across the study areas. Integrating biomonitoring methods into risk-assessment protocols in Fiji may support establishment of opportunities or considerations for health guidelines and policy interventions to minimise human exposure to microplastics, and regulate environmental pollution. Implications These measures are crucial for protecting public health and monitoring pollution impacts.

Presence of Potentially Toxic Elements in Historical Mining Areas in the North-Center of Mexico and Possible Bioremediation Strategies

This paper provides an overview of the impacts of mining-related environmental liabilities on humans, soils, sediments, surface water and groundwater across various mining districts in Zacatecas, Mexico. An analysis has been carried out on the areas of the state most affected by the presence of potentially toxic elements (PTEs) such as arsenic, lead, cadmium, copper, chromium and zinc, identifying priority areas for environmental assessment and remediation. Likewise, a review of the concentrations of PTEs reported in different environmental matrices of the state’s mining areas with the presence of environmental liabilities was carried out, most of which exceed the maximum permissible limits established by Mexican and international regulations, generating an environmental risk for the populations near these districts due to their potential incorporation into the food chain. Additionally, this study explores research focused on the biostabilization of PTEs using microorganisms with specific metabolic activities. Phytoremediation is presented as a viable tool for the stabilization and elimination of PTEs, in which endemic plants from arid–semi-arid climates have shown favorable results in terms of the phytostabilization and phytoextraction processes of the PTEs present in mining waste.

Tackling soil erosion and contamination within the SDGs framework: a case study of the Erdenet copper-molybdenum mine

AbstractMining operations in Mongolia have contributed significantly to national economic growth. However, the lack of adequate mine land rehabilitation practices has resulted in various forms of land degradation, including land cover change, soil erosion and contamination with heavy metals and metalloids. These issues have negatively affected ecosystems and posed potential risks to human health due to the interconnected relationships between land, water and human activities. This study focuses on the copper-molybdenum mining site of Erdenet, the oldest and one of the largest copper mines in Mongolia, to investigate the main drivers of soil degradation and evaluate effective rehabilitation strategies. By combining findings from our previous studies on soil erosion and contamination in the Erdenet area with a review of existing research, we assess key rehabilitation priorities. Taking a Nexus approach, this study explores the interconnections between environmental, economic and social sectors, emphasizing the importance of balancing mining activities with sustainable land management. The previous studies suggest that for the next 10–15 years, priorities should focus on tailings storage facility rehabilitation and soil contamination remediation, while longer-term goals include developing sustainable environmental management strategies that foster cooperation between mining corporations and local communities, enforce regulations and improve monitoring in the Erdenet mining area. The study aligns these priorities with the Sustainable Development Goals, offering science-based recommendations for managing soil erosion and reducing contamination.

Improvement of Coal Mining-Induced Subsidence-Affected (MISA) Zone Irregular Boundary Delineation by MT-InSAR Techniques, UAV Photogrammetry, and Field Investigation

Coal mining-induced ground subsidence is a severe hazard that can damage property, infrastructure, and the environment in the vicinity when the deformation is not negligible. The boundary of a mining-induced subsidence-affected zone refers to the area beyond which the ground subsidence is less concerned. Accurately measuring mining-induced ground deformation is essential for delineating the irregular boundary of the impacted area. This study employs multitemporal interferometric synthetic aperture radar (MT-InSAR) techniques, including differential InSAR (DInSAR), InSAR stacking, and interferometric point target analysis (IPTA), to analyze coal mine subsidence and delineate the boundaries of the mining-impacted zones. DInSAR accurately reconstructs, locates, and detects the trend in mining-induced subsidence and correlates well with documented mining operations. The InSAR stacking method maps the spatial variation of the ground’s average line-of-sight (LOS) velocity over the mining area, delineating the boundary of the impacted zone. IPTA analysis combining multilook and single-pixel phases achieves millimeter-level surface measurement above tunnel alignments and measures unevenly distributed deformation fields. This study considers an average of 4 cm per year of surface deformation in the LOS direction as the subsidence threshold value for delineating the boundary of the mining-induced subsidence-affected (MISA) zone during the active coal mining stage. Interestingly, there are twin transportation tunnels near the mining area. The twin tunnels completed before the coal mining activities started were functioning well, but damage was observed after the mining began. Our study reveals the tunnels are located within the InSAR-derived MISA zone, although the tunnels approach the MISA boundary. As direct signs of subsidence, ground fissures have been identified near the tunnels via field investigations and UAV photogrammetry. Furthermore, the derived distribution of ground fissures validates and verifies InSAR measurements. The integrated approach of MT-InSAR, UVA photogrammetry, and field investigation developed in this study can be applied to delineate the irregular boundary of the MISA zone and study the accumulating effects of mining-induced subsidence on the performance of infrastructure in areas proximate to coal mining activities.

A Case Study Comparing Methods for Coal Thickness Identification in Complex Geological Conditions

This study compares the effectiveness of different methods for coal thickness identification, aiming to identify the most accurate approach and provide a reference for intelligent coalmine development. Focused on the No. 2 coal seam in a mining area in Shanxi, China, the analysis employs well log-constrained impedance inversion and seismic multi-attribute techniques. The results show that the back propagation (BP) neural network model, as part of the seismic multi-attribute approach, delivers prediction accuracy comparable to the well log-constrained inversion method. Specifically, after applying proper static corrections, a four-layer BP neural network was constructed using four optimized sensitive attributes as the input layer, achieving an error range of 0.11% to 1.36%, compared to 0.03% to 6.59% for the logging-based method. The BP neural network demonstrated strong applicability in complex geological environments. Empirical analysis further validated the BP neural network’s geological reliability and practicality in systematic coal thickness determination.

Integrated Assessment of Metal Contamination of Soils, Sediments, and Runoff Water in a Dry Riverbed from a Mining Area Under Torrential Rain Events

Dry riverbeds can transport mining waste during torrential rain events, disseminating pollutants from mining areas to natural ecosystems. This study evaluates the impact of these mine wastes on soils, sediments, and runoff/pore water in the La Carrasquilla dry riverbed (southeastern Spain). An integrated approach utilizing geochemical and mineralogical techniques was employed, analyzing water, soil, and sediment samples from both the headwater and mouth of the riverbed. Soil profiles and pore water were collected at 30 cm, 60 cm, and 90 cm deep, alongside sediment and runoff water samples. The assessment of metal(loid) contamination focused on arsenic, cadmium, chromium, copper, iron, nickel, manganese, zinc, and lead, utilizing sequential extraction to evaluate metal partitioning across soil phases. Various pollution indices, including the contamination factor (Cf), pollution load index (PLI), potential ecological risk index (RI), and metal(loid) evaluation index (MEI), were employed to classify contamination levels. The highest level of contamination was reported in the headwater, which suggested anthropogenic activities linked to the presence of mining residues as the major source of metal(loid)s. However, an active deposition of As, Cd, Cu, Fe, Mn, and Zn was reported in the topsoil at the mouth. In the headwater, a quartz and muscovite-rich zone exhibited the highest Cf for Pb (1022), primarily bound to the soil residual fraction (62.8%). At the headwater and mouth, pore water showed higher concentrations of sulfate, Ca, Na, Cl, Mg, and Mn and higher salinity than acceptable limits for drinking water or irrigation established by the World Health Organization. Runoff-water metal concentrations surpassed established guidelines, with MEI values indicating significant contamination by cadmium (36.1) and manganese (19.0). These findings highlight the considerable ecological risk of Pb and underscore the need for targeted remediation strategies to mitigate environmental impacts in the Mar Menor coastal lagoon.

Failure mechanism and control technology of soft-rock roadways subjected to high structural stress

The prevention and control of deformation and instability in high-stress soft rock roadways hold significant value for ensuring normal mine production and the safety of personnel and equipment. This study focuses on the pedestrian descent from the 11th mining area of the Yindonggou Mine, providing a thorough elucidation of the internal mechanisms leading to large deformation and instability in the roadway. It accounts for the influences of surrounding rock lithology, geological structure, and support measures. Consequently, based on the theory of rock instability, corresponding tunnel repair measures and control strategies were proposed and verified through field application. The results indicate that: (1) High strength dispersion and insufficient support resistance of the expansive weak and fractured surrounding rock sections are critical factors inducing significant deformation in the soft rock roadway of Yindonggou Mine. (2) The primary factor contributing to the large deformation disaster in the Yindonggou Mine roadway is the disturbance caused by proximate coal seam mining, which exacerbates the conflict between the high structural stress in the strata and the low strength of the surrounding rock. High-level stress initially leads to deformation in the weakly supported floor, followed by deformation and instability of the surrounding rock, ultimately culminating in the collapse of the entire roadway section. (3) Soft rock support should be designed with varying schemes tailored to the rock type and structural stress of the surrounding rock in the tunnel. For tunnels with carbon mudstone and expansive soft rock as the main roof and floor components, the support plan should primarily focus on enhancing the support stiffness of the tunnel wall. Conversely, for tunnels where sandstone predominates as the roof and floor material, the support plan should aim to restore the three-dimensional stress state of the surrounding rock and fully utilize its self-supporting capacity. (4) Based on the engineering conditions of pedestrian downhill in No.11 mining area of Yindonggou Mine, a differentiated support scheme is proposed. The feasibility and effectiveness of each support scheme are verified by numerical simulation, so as to provide valuable reference and enlightenment for similar projects.

Modeling Land Use and Land Cover Changes and Its Atmospheric Pollutant Concentration in the Coal Mining Area of Ramgarh District of Jharkhand, India, Using Multi‐Layer Perceptron Neural Networks (MLPNN)

ABSTRACTLand use refers to anthropogenic phenomena in the natural environment; humans utilize land resources for their developmental activities. On the other hand, the ecosystems of land use and land cover alter the natural world—the artificial infrastructure leads toward a busted concrete jungle instead of a green footprint. The global green footprint is continually shrinking owing to overutilization of natural resources. The present research examines the land use pattern that changes from 1990 to 2021 and projected projections for 2041 and 2061 in the Ramgarh District. The study also focuses on how artificial modifications alter the concentration level of pollutants in the atmosphere. The Landsat data utilized for 1990, 2000, 2011, and 2021 were incorporated into the LULC map using supervised classification and for analysis of future predictions for 2041 and 2061 using an ANN‐based on MLPNNs (multi‐layer perceptron neural networks) for Ramgarh District. It also focuses on the trend and patterns of atmospheric pollutants from data using NASA‐GIOVANNI MERRA‐2. The current study reveals that in 1990, water bodies, coal mining, vegetation, built‐up, agriculture, and barren land were 3.01%, 2.24%, 54.07%, 3.64%, 36.85%, and 0.18 %. However, in 2021, water bodies decreased to 1.61%, vegetation to 45.47%, barren land to 0.65%, and an increasing tendency was observed in built‐up areas to 6.65%, coal mining to 2.43%, and farmland to 43.19%. A significant trend in atmospheric pollutants, such as CO2, SO2, SO4, NO2, and dust, is observed in the Ramgarh district. The importance of this study is to attain the maximum level of environmental sustainability; it would also encourage the local level planning fitted during the extraction of natural resources.

Floor Heave Mechanism and Control Technique of Water‐Rich Soft‐Rock Roadway in Thick Coal Seam

ABSTRACTThe severe deformation of the surrounding rock of the coal floor in Shanghaimiao mining area is affecting the safe, efficient production of mine wells in this region. In this study, the heave mechanism and control of the roadway floor were investigated through laboratory experiments, field research, theoretical analysis, numerical simulation, and on‐site testing. The results showed that the main reason for the serious damage to the roadway floor was the low strength of the surrounding rock of the roadway floor, and floor damage was exacerbated by the low support strength, hydraulic effects, and mining impact. A mechanical model of the asymmetric floor heave was established, and it was found that the stability of the roadway floor was positively correlated with the floor rock type, the stress concentration coefficients on the two sides of the roadway, and the burial depth, whereas it was negatively correlated with the cohesive force and internal friction angle of the floor rock mass. Expressions for the upward resultant force R of the roadway floor and the stress concentration coefficients K and K′ on both sides of the roadway were derived. The results of a FLAC3D numerical simulation analysis showed that the stress peak in front of the working face was 36 MPa, with a stress concentration factor of 3.7. After the floor support was reinforced, the floor heave was remarkably reduced, with a maximum value of approximately 600 mm, and the floor deformation became somewhat asymmetric. Finally, a double‐seal floor‐reinforcing “inverted arch” control technique was proposed and tested on‐site. The new system could efficiently and stably support the surrounding rock of the roadway.

Predicting Water Flowing Fracture Zone Height Using GRA and Optimized Neural Networks

As coal mining depths continue to rise, consideration of WFFZ elevations is becoming increasingly important to mine safety. The goal was to accurately predict the height of the WFFZ to effectively prevent and manage possible roof water catastrophes and ensure the ongoing safety of the mine. To achieve this goal, we combined the particle swarm optimisation (PSO) algorithm with a backpropagation neural network (BPNN) in order to enhance the accuracy of the forecast. The present study draws upon the capacity of the PSO algorithm to conduct global searches and the nonlinear mapping capability of the BPNN. Through grey relational analysis (GRA), the order of the correlation degree was as follows: mining thickness > mining depth > overburden structure > mining width > mining dip. GRA has identified the degree of correlation between five influencing factors and the height of the WFFZ, among these, mining thickness, mining depth, overburden structure and mining width all show strong correlations, and the mining dip of the coal seam shows a good correlation. The weight ranking obtained by the PSO-BPNN method was the same as that obtained by the GRA method. Based on two actual cases, the relative errors of the obtained prediction results after PSO implementation were 2.97% and 3.47%, while the relative errors of the BPNN before optimisation were 18.46% and 4.34%, respectively, indicating that the PSO-BPNN method provides satisfactory prediction results and demonstrating that the PSO-optimised BPNN is easy to use and yields reliable results. In this paper, the height of the WFFZ model under the influence of five factors is only established for the Northwest Mining Area. With the continuous progress of technology and research, the neural network can consider more factors affecting the height of hydraulic fracturing development zones in the future to improve the comprehensiveness and accuracy of prediction.

Cultural and ecological dialogue: a study of Nagaland Coal mining areas

Cultural and ecological dialogue: a study of Nagaland Coal mining areas

Monitoring and Analysis of Surface Deformation in the Buzhaoba Open-Pit Mine Based on SBAS-InSAR Technology

The Buzhaoba open-pit mine is an important lignite production base in Yunnan Province, China. As mining activities have continued to progress, varying degrees of deformation have occurred in different areas of the Buzhaoba open-pit mine, threatening normal coal production and mine safety. To comprehensively investigate the characteristics of surface deformation and its influencing factors at the Buzhaoba open-pit mine, this study employed the following methods: first, the SBAS-InSAR technique was used to process 86 Sentinel-1A ascending and descending orbit remote sensing images from 2020 to 2023, obtaining LOS surface deformation information for the mining area; second, leveling observation data were used to validate the accuracy of the SBAS-InSAR results, and based on the principle of two-dimensional deformation decomposition, the east–west and vertical surface deformation information of the mining area was obtained; finally, the temporal variation characteristics and influencing factors of the Buzhaoba open-pit mine were analyzed. The study results indicate that (1) the maximum LOS surface deformation rates in the ascending and descending orbits of the mining area were −42.1 mm/a and −114.0 mm/a, respectively; (2) the correlation coefficient between the SBAS-InSAR monitoring results and the leveling observation results was 0.938, confirming the reliability of the SBAS-InSAR monitoring results; (3) the maximum east–west and vertical deformation rates obtained from the two-dimensional deformation decomposition were −103.4 mm/a and −189.2 mm/a, respectively, with the surface deformation in the east–west direction being more pronounced; (4) internal factors such as stratigraphic lithology and geological structures, as well as atmospheric rainfall, have a certain degree of influence on the surface deformation of the Buzhaoba open-pit mine. Therefore, the research results of this study can provide important data support and theoretical references for safety management and disaster prevention in the mining area.

Diagnosis of sensitive leaf types and spectral segments during maize heading stage under simulated copper stress environment in mining areas

ABSTRACT This paper designed CSSDM (Copper Stress Spectral Diagnosis Method) from the perspective of frequency domain, combined with time-frequency analysis, to obtain sensitive leaf types and spectral segments under heavy metal copper stress, providing technical support for heavy metal monitoring in crops. Firstly, the hyperspectral reflectance data of maize leaves under copper stress were subjected to DD (Double Differentiation) and EE (Envelope Elimination), and transformed into the frequency domain. The d6 (Daubechies wavelet 6-layer) decomposition was performed using time-frequency analysis methods. Then, based on the signal anomaly points, wavelet high value points and DDEE (Double Differentiation Envelope Elimination) curve high value points, the SRVP (Spectral Reflectance Variation Parameters) of maize leaves are defined. Finally, by examining the correlation between spectral reflectance variation parameters and heavy metal content in maize leaves, we aim to explore the leaf types and spectral segments that are sensitive to copper pollution. The results showed that CSSDM can efficiently enhance weak information in maize leaves and accurately locate the spectral anomaly caused by heavy metal copper stress, with the anomaly range concentrated within 350 nm−800 nm. Spectral reflectance variation parameters can quantitatively measure the spectral anomalies of maize leaves under heavy metal copper stress. Under different copper stress gradients, maize new leaves exhibit sensitive leaf types, with sensitive spectral segments including Blue Edges, Green Peaks, Yellow Edges and Red Valleys.

Patterns and Driving Mechanisms of Soil Organic Carbon, Nitrogen, and Phosphorus, and Their Stoichiometry in Limestone Mines of Anhui Province, China

Active vegetation restoration plays an important role in the improvement in soil organic matter (SOM), including the carbon (C), nitrogen (N) and phosphorus (P) sequestration of degraded mining ecosystems. However, there is still a lack of understanding of the key drivers of SOM pool size and dynamics in active vegetation restoration. For this study, soil was collected from five different sites (Xiaoxian, Dingyuan, Chaohu, Tongling and Dongzhi), four habitats (platforms, slopes, steps and native areas) and two soil layers (0–20 cm and 20–40 cm) in limestone mines of Anhui province to quantify the spatial distribution of SOM contents and their stoichiometric characteristics and influential factors. It was found that the top soil in Chaohu had the highest significant C, N and P contents in the ranges of 14.95–17.97, 1.74–2.21 and 0.80–1.24 g/kg, respectively. Comparing the stoichiometric ratios of the different sites revealed significant differences in C:N and N:P ratios, but C:P ratios were relatively consistent. In particular, the C:N and C:P ratios in deep soil were higher than those in top soil, whereas the N:P ratio in deep soil was lower than that in top soil, suggesting that soil N is a major limiting factor in the top soil. The SOM content did not differ significantly between the three reclaimed habitats, but was significantly higher than that in the native habitat, suggesting that mine restoration has significantly enhanced SOM accumulation. Further analysis showed that nutrient availability and enzyme activity are important factors affecting soil C, N and P content in top soil, while the relationship gradually weakens in deep soil. This was attributed to active anthropogenic management and conservation measures during the early stages of reclamation. This study shows that the ecological recovery of the mining area can be enhanced by implementing differentiated vegetation planting strategies and anthropogenic management on different habitats in the mining area.

Spatiotemporal Evolution Mine Groundwater’s Hydrogeochemical Characteristics Under Influence of Mining and Grouting in Gubei Coal Mine, China

Geological conditions or human activities will affect the hydrochemical characteristics and formation mechanism of mine groundwater to varying degrees. The northern part of the Beiyi mining area of Gubei Coal Mine is taken as the research area in this study. Based on the data of 52 groups of limestone water (Taihui water) samples in the primary environment, in the mining stage and after grouting, the spatial and temporal variation trend of the chemical characteristics of Taihui water was studied by means of constant index mathematical statistics, a Piper diagram, total ionic salinity, correlation analysis, the ion ratio method and the saturation index. The purpose of this study is to analyze the influence of special geological structures, mining activities and grouting treatment on the formation process of the chemical characteristics of Taihui water, and to provide a basis for the identification of water inrush sources and the resource utilization of deep mine water in this area. The results show that in the three stages, the order of cation concentration is Na+ + K+ > Ca2+ > Mg2+, and the order of anion concentration is changed from Cl− > SO42− > HCO3− to Cl− > HCO3− > SO42−. The hydrochemical type is the most abundant in the mining stage, and tends to be unified after grouting. The dissolution of carbonate minerals, gypsum, rock salt and silicate minerals; cation exchange; pyrite oxidation; and the mixing of grouting precipitation liquid mainly occur in the limestone water. These effects are enhanced or weakened due to the influence of pumping and drainage and grouting precipitation liquid. The results of this study may be beneficial to the sustainable utilization of deep groundwater resources in other similar mines, and promote the establishment of data management and identification mechanisms of water inrush sources in deep coal seams.

Land Use Legacy Landforms at the UNESCO Heritage Site Tarnowskie Góry, Upper Silesia, Poland—Stratigraphy, Soils and Age

ABSTRACTMetallurgy in Upper Silesia (Poland) has a long tradition of international significance, which was emphasized in 2017 when the historic silver mine in Tarnowskie Góry was inscribed as a UNESCO World Heritage site. The area consists of various anthropogenic landforms, the stratigraphy of which has hardly been studied so far. In this study, we describe five main morphological units: Unit I (RCH) and Unit II (RCH pit), resulting from charcoal production; Unit III (shaft) and Unit IV (shaft heap), resulting from mining; and Unit V (reference forest soil). The first four units are a variation of a Technosol with inherently different properties from the reference forest soil. Unit I exhibits typical properties of a relict charcoal hearth (RCH), whereas Unit II resembles a pit. Unit III consists of a mostly infilled mining shaft remain (MSR), characterized by relocated subsoil. Unit IV consists of material from the adjacent Unit III that has been dumped directly aside. The studied RCH was used no earlier than during the second half of the 17th century, probably between 1725 and 1813. The studied MSR was used most likely between the 3rd and 5th centuries, which is much older than described so far. Together, the units reflect the characteristic heterogeneity of soils in shaft mining and RCH areas.

Monitoring of Overburden Failure with a Large Fractured-Height Working Face in a Deep Jurassic Coal Seam Based on the Electric Method

The development height of a water-flowing fractured zone is the key parameter to consider when carrying out mining under water pressure and coal mining with water conservation. In this paper, Jurassic coal seam 3-1 in the Menkeqing Coal Mine was taken as the research target, and a three-dimensional mining geological model was established by using FLAC3D to study the deformation and failure rules of overburden. Three roof boreholes were drilled in the auxiliary transportation roadway of adjacent working faces for dynamic monitoring by the resistivity method, which can better observe the whole process from failure to stability of the overburden. The results show that due to the complex sedimentary environment and large buried depth of coal seams in western China, there is a large deviation between the calculation results of the empirical formula of the fractured zone height under the “Regulations of buildings, water, railway and main well lane leaving coal pillar and press coal mining” (three regulations) and the simulation and on-site measurement. Based on the comprehensive analysis, the influence range of mining advance abutment pressure is approximately 60 m. The height of the water-flowing fractured zone is approximately 106 m, and it is located at the interface between sandy mudstone and mudstone. The height of the caving zone is approximately 22 m, and it is located at the interface between fine sandstone and medium sandstone. The ratio of the fractured height and coal seam thickness (Rf) reached 24.4, which was basically consistent with the test result of the adjacent Yushenfu mining area (which was 26 on average). There is no obvious change in the development height of the caving zone and water-flowing fracture zone from the working face to the drilling borehole position of more than 120 m, which reflects that the height of the overburden failure zone is related to the control of lithological combination.