Coal Mining Activities Research Articles

Vegetation Community Characteristics and diversity in different phases of mining at Charhi and Kuju coal mining areas, Jharkhand, India

The increase in the energy requirement of a country shows its economic advancement. Coal mining activity has increased considerably to compensate for the increased energy requirements. As a result, open-cast coal mining methods induced a drastic change in land use and seriously jeopardized the sustainability of the ecosystem. Once disrupted by open-cast or underground mining, the condition of the land cannot be entirely recovered, making it a non-renewable asset to the environment and support of human life. An attempt was made to study the existing flora of the different zones (operating, abandoned, control) of Charhi and Kuju Coal mining area, Jharkhand, India. From 2015 to 2018,173 species belonging to 75 families of angiosperms, terrestrial and aquatic ferns have been reported and identified so far from this study area. The most dominant family is Poaceae with the maximum number of species in the area, where mining has not yet been done. This paper's findings would help assess the dominant species in this area, which can be used for reclamation of the abandoned mining areas.

Characteristics and Source Analysis of PM1 in a Typical Steel-Industry City, Southwest China

Mining activities have led to severe air pollution problems while they make great contributions to economic construction. Therefore, as a typical steel-industry city in southwest China, Panzhihua, its air pollution has received extensive attention. The characteristics of PM1 in different functional areas of Panzhihua from 2018 to 2019, and the changes of its microstructure and potentially toxic elements (PTEs) and the sources of PM1 were analyzed. The results showed that the mass concentrations of PM1 in the heavy pollution area of Nongnongping (NNP) and the complex industrial pollution area of Hemenkou (HMK) were 12.12–145.30 μg/m3 and 14.38–67.02 μg/m3, respectively. Seasonal PM1 mass concentrations in the two functional areas could be arranged in the following order: winter > autumn > spring > summer. The main particle types in PM1 were fly ash, soot, sulphate particles, aluminosilicate particles and metal particles. Potential sources of PM1 in Panzhihua included coal burning, biomass combustion, automobile exhaust and mining activities. At the same time, the average concentrations of PTEs at NNP were also higher than those at HMK because of smelting activities. Enrichment factor analysis showed that most of the PTEs came from human sources. The results could provide theoretical guidance for environmental management.

Decision-making fusion of InSAR technology and offset tracking to study the deformation of large gradients in mining areas-Xuemiaotan mine as an example

The multi-level disturbance of underground and surface caused by coal mining activities intensifies the deterioration of the ecological environment in the mining area. Among them, the uneven settlement caused by coal mining is the most intuitive manifestation of surface environmental damage. The uneven settlement in the mining area has the characteristics of large settlement magnitude and severe deformation. Therefore, based on 15 Sentinel-1A image data, this paper uses three methods: SBAS InSAR, continuous D-InSAR and offset tracking technology to monitor the surface deformation of the mining area. The results show that the continuous D-InSAR technology SBAS-InSAR technology is applied to the small deformation in the edge area of the subsidence basin. The mining area with low gradient subsidence of SBAS-InSAR can obtain better performance than continuous D-InSAR technology. The offset tracking technique is used to monitor the large gradient deformation in the center of the subsidence basin. Therefore, this paper proposes to expand the quantitative analysis through the spatial coherence threshold and the accuracy and successful image elements of the interference fringe displacement. Combine the advantages of the three methods and overcome the shortcomings of each method, fuse the deformation information of the three methods, and obtain the deformation law of the whole surface subsidence. The results show that the mean absolute error (MAE1-1) of continuity D-InSAR is 0.92 m, the mean absolute error (MAE2-1) of SBAS-InSAR is 0.94 m, and the mean absolute error (MAE3-1) of Offset-tracking is 0.25 m. The results of this fusion method are in good agreement with the measured data, and the mean absolute error (MAE4-1) of vertical displacement is 7 cm. Therefore, the fusion method has advantages over individual methods and provides a new idea in monitoring the large gradient deformation of coal mining subsidence in mining areas.

Assessment of metal pollution in surface water using pollution indices and multivariate statistics: a case study of Talcher coalfield area, India

Metal pollution in aquatic environment of coal mines is of serious concern and requires to be dealt with to maintain sustainable mining practices. The spatio-temporal variation in metal pollution of surface water of Talcher coalfield area were determined by using multivariate statistical techniques and pollution indices. A total of 56 water samples were collected and analyzed for Fe, Zn, Cu, Cd, Pb, Co, Se, As, Hg, Cr, Ni, Mn, and Al in pre-monsoon and monsoon season. Spatial distribution maps were prepared so that the quality of surface water could easily be recognized. High values of Heavy Metal Pollution Index (HPI), Degree of Contamination (Dc), and Heavy Metal Evaluation Index (HEI) were observed for 3%, 6%, 0% samples in pre-monsoon and 1%, 6%, 3% samples in monsoon. Sewage Treatment Plants (STP), Effluent Treatment Plants (ETP), and Mine Discharge Treatment Plants (MDTP) were found to have low to moderate efficiency in treating metals. The HPI of streams and rivers were observed to be higher in pre-monsoon than that of the monsoon season possibly due to dilution effect caused by intense rain in monsoon. The HPI of downstream was noted to be higher than the upstream indicating pollution due to mine effluent discharge. The average concentrations of Cd, Se, As, Ni, and Al in pre-monsoon and Fe, Cd, Se, As, Ni, and Al in monsoon exceeded the permissible drinking water limits set by WHO (WHO, Guidelines for drinking-water quality, World Health Organization, Geneva, 2011) and BIS (BIS (2012) Drinking water specifications 2nd revision. Bureau of Indian standards (IS 10500: 2012). New Delhi. ftp://law.resource.org/in/bis/S06/is.10500.2012.pdf). Analysis of Variance (ANOVA) revealed significant seasonal variation (p < 0.05) of Fe concentration between pre-monsoon and monsoon. Principal Component Analysis (PCA) identified major sources of metal pollution in water such as earth’s crust and the geological formation of the region, coal mining activities, industrial pollution, vehicular emission and coal burning. Cluster analysis (CA) identified 19 moderately polluted sites, 6 highly polluted sites, 3 very highly polluted sites and 1 severely polluted site in and around the Talcher coalfield area. This study is useful for formulating the metal pollution mitigation plan to enhance the water quality of Talcher coalfield area which affect the aquatic organism as well as the human health.

Remote Sensing for Surface Coal Mining and Reclamation Monitoring in the Central Salt Range, Punjab, Pakistan

The expansion and exploitation of mining resources are essential for social and economic growth. Remote sensing provides vital tools for surface-mining monitoring operations as well as for reclamation efforts in the central Salt Range of the Indus River Basin, Pakistan. This research demonstrates the applicability of remote sensing techniques to the coal mining monitoring scheme to allow for effective and efficient monitoring and to offset the adverse consequences of coal mining activities. Landsat 8 OLI images from June 2019 and 2020, and a Landsat 7 ETM+ image from June 2002, were used for this study. A three-phase methodology including Normalized Difference Vegetation Index (NDVI) analysis, land cover mapping, and change detection approaches was adopted. Image classification based on Tasseled Cap Transformation and the brightness temperature At-satellite using the K-means algorithm was implemented in a GIS program to identify seven land cover classes within the study area. The results show some level of surface disturbance to the landscape due to the coal mining reclamation activities that had taken place over the 18-year time period. From 2019 to 2020, about 3.622 km2 of coal mines or barren land were converted into bare agricultural land. Over the years, it was also observed that reclamation areas exhibited higher values of NDVI than coal mining areas. The mean NDVI for coal mining areas was 0.252 km2, and for areas of reclamation, it was 0.292 km2 in 2020, while in 2019, the value for coal mining sites was 0.133 km2, and 0.163 km2 for reclamation sites. This trend suggests that coal-mining operations can be monitored using satellite data, and the progress of reclamation efforts can be assessed using satellite NDVI data from the target locations. This study is beneficial to agencies responsible for monitoring land cover changes in a coal mine because it provides a cost-effective, efficient, and robust scientific tool for making mine site allocation decisions and for monitoring the progress of reclamation efforts.

The Landscape Pattern Evolution of Typical Open-Pit Coal Mines Based on Land Use in Inner Mongolia of China during 20 Years

As the province most abundant in mineral resources in China, Inner Mongolia has more than 200 open-pit coal mines. The coal mining activities seriously hinder the sustainable use of regional land and the improvement of residents’ wellbeing. Taking 13 typical open-pit coal mines of Inner Mongolia as the study area, combining remote sensing images and the Google Earth Engine (GEE) platform, the trend features of spatial and temporal evolution of land use and landscape patterns from 2001 to 2020 were analyzed by transfer matrix and landscape pattern index methods. According to the mining plan and reclamation measures of the “Land Reclamation Plan”, the impacts of ecological restoration projects on land-use structure and landscape patterns were evaluated. The results showed that the following: (1) The landscape types of typical open-pit coal mining areas were mainly grassland, cropland, and industrial landscapes. The change trend of landscape pattern was obvious over the past 20 years, and the changes in grassland and mining land were relatively large, which decreased by 56.51 km2 and increased by 60.42 km2, respectively. (2) Land reclamation and ecological restoration projects had positive impacts on landscape pattern changes. With the transformation from mining activities to land reclamation activities beginning in 2007, nearly 70% of the study area showed a decreasing trend in landscape fragmentation, indicating a better landscape pattern of mining area. (3) Positive policy orientation of mine ecological restoration promoted more reasonable landscape patterns.

3D in situ stress state modelling and fault reactivation risk exemplified in the Ruhr region (Germany)

Throughout the 700-yearlong coal exploration period in the Ruhr region, an abundance of geological, geophysical, seismic, and in situ stress data was obtained from the Carboniferous strata. In this study, we take advantage of this unique dataset to develop a static 3D geomechanical model to predict the spatially continuous distribution of undisturbed in situ stress state and evaluate the reactivation risk of major fault zones. Compared to the point-wise stress information, the spatially continuous in situ stress state provides an effective tool for planning subsurface operations and assessing seismic hazards in areas where no stress information is available. The developed model was validated against a comprehensive calibration dataset including results from geophysical logging, borehole deformation, and fault-slip analysis, in situ hydrofracturing measurements, distribution of subsidence, microseismicity, and observations from coal mining activities. Consequently, interpretation and assessment of the model results including their uncertainties, reliability, limitations, and perspectives are discussed. The possible applications of the model approach for seismic hazard prediction and utilization of deep geothermal energy in the Ruhr region are outlined.

Quantifying CH4 emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method

Abstract. Intensive coal mining activities in the Upper Silesian Coal Basin (USCB) in southern Poland are resulting in large amounts of methane (CH4) emissions. Annual CH4 emissions reached 448 kt according to the European Pollutant Release and Transfer Register (E-PRTR, 2017). As a CH4 emission hotspot in Europe, it is of importance to investigate its emission sources and make accurate emission estimates. In this study, we use satellite-based total column-averaged dry-air mole fraction of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH4 (TXCH4) from the Infrared Atmospheric Sounding Interferometer (IASI). In addition, the high-resolution model forecasts, XCH4 and TXCH4, from the Copernicus Atmosphere Monitoring Service (CAMS) are used to estimate the CH4 emission rate averaged over 3 years (November 2017–December 2020) in the USCB region (49.3–50.8∘ N and 18–20∘ E). The wind-assigned anomaly method is first validated using the CAMS forecast data (XCH4 and TXCH4), showing a good agreement with the CAMS GLOBal ANThropogenic emission (CAMS-GLOB-ANT) inventory. It indicates that the wind-assigned method works well. This wind-assigned method is further applied to the TROPOMI XCH4 and TROPOMI + IASI TXCH4 by using the Carbon dioxide and Methane (CoMet) inventory derived for the year 2018. The calculated averaged total CH4 emissions over the USCB region is about 496 kt yr−1 (5.9×1026 molec. s−1) for TROPOMI XCH4 and 437 kt yr−1 (5.2×1026 molec. s−1) for TROPOMI + IASI TXCH4. These values are very close to the ones given in the E-PRTR inventory (448 kt yr−1) and the ones in the CoMet inventory (555 kt yr−1), and are thus in agreement with these inventories. The similar estimates of XCH4 and TXCH4 also imply that for a strong source, the dynamically induced variations of the CH4 mixing ratio in the upper troposphere and lower stratosphere region are of secondary importance. Uncertainties from different error sources (background removal and noise in the data, vertical wind shear, wind field segmentation, and angle of the emission cone) are approximately 14.8 % for TROPOMI XCH4 and 11.4 % for TROPOMI + IASI TXCH4. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH4 or CO2 emissions for other regions.

The assessment of the soil-plant-animal transport of the risk elements at the locations affected by brown coal mining.

The North Bohemian Brown Coal Basin (Czech Republic) is suggested as a source of significant pollution in the surrounding environment with various pollutants, including risk elements. A total of 53 sampling points were selected within the North Bohemian region. The selected sampling points represented either the basin areas (affected by the coal mining and related activities) or the mountain areas (an area unaffected by the coal mining but characterized by the geogenic sources of the risk elements). At each of the sampling points, soils and respective dominant indigenous plant samples were collected. A suite of ecological indices, namely, individual pollution index (Ii), Nemerow index (PN), bioaccumulation factor (BAF), translocation factor (TF), and hazard quotient (HQ), were applied to estimate the environmental risk of As, Be, Cd, and Zn levels in soils, potential soil-plant transfer, and soil-plant-animal transport of these stated elements. The results from Ii showed that the maximum values of As, Be, Cd, and Zn in the investigated soils exceeded the preventive values, where the Ii value was up to 58 for As in the mountain areas, indicating severe pollution. At the same time, mild pollution was recorded in the case of Cd. For Be in the researched soils, its Ii assessment result was a wide range, varying between a clean environment and severe pollution. Whereas As and Be uptake by plants was limited and these elements were retained in the plant's roots, relatively high mobility and soil to plant shoots transport ability of Cd were recorded and documented by the TF values. The HQs calculated for selected herbivorous mammals in the area showed that the potential health risk of As and Be was limited to only plant roots in the hotspots with extreme As and Be contents. In comparison, substantial health risk of Cd was observed in the aboveground biomass of plants. Therefore, the potential remediation of the coal mining areas should be focused on (i) identification of the As and Be hotspots and (ii) to reduce the mobility and plant availability of Cd in the whole investigated area.

Study on the Precursor Characteristics of Instability Failure of Gas-Bearing Coal Based on Stress and Gas Seepage Volume

In coal mining activities, the original stress of the coal body changes, resulting in structural deformation and destruction, which will cause changes in gas seepage volume. The conventional triaxial loading test was carried out by using the triaxial loading-gas adsorption seepage experimental device. The effects of different loading rates, confining pressures, and gas pressures on the peak strength of coal were analyzed; the evolution laws of coal stress, gas seepage volume, stress rate, and gas seepage volume rate at different deformation stages were studied; and it was found that the time, at which the specimen began to enter the crack propagation deformation stage, determined by the change of gas seepage rate or stress rate was not the same. Therefore, combined with gas seepage and stress, a theoretical model of stress rate-seepage volume rate under triaxial pressure was proposed, and the ratio F of the two was used as an early warning index. It was found that the F value was basically stable in the elastic stage and decreased rapidly in the crack propagation stage. Thus, the F value was used as an early warning index for the instability and failure of gas-bearing coal. The F value of the experimental results was consistent with the theoretical model, and the F value entered the crack propagation stage earlier than the stress rate or the gas seepage volume rate. The research results provided a theoretical basis for coal mine safety mining and disaster prevention.

Response Characteristics of Electric Potential and Its Relationship with Dynamic Disaster during Mining Activities: A Case Study in Xuehu Coal Mine, China.

Across the world, coal resource is widely utilized in industrial production. During coal mining activities, dynamic disasters may be induced, such as coal and gas outbursts, or rock burst, resulting in serious accidents or disasters. Previous studies have shown that electric potential (EP) signals can be produced during the deformation and fracture process of coal and rock mass under load. The abnormal response characteristics of EP can reveal the damage evolution and failure feather of coal mass. In this paper, the response characteristics of EP signals are analyzed with high gas testing during mining activities within deep coal seams, and the relationship between the EP response and outburst disaster hazard is studied. The results show that: (1) Under the comprehensive action of mining stress and gas effect, the coal mass was damaged and fractured, which can produce abundant EP signals, while the temporal EP response characteristics can reflect the loading state and damage evolution process inside the coal seam. (2) When coal cannon and a sudden increase of gas concentration occurred in the coal mass, the EP signal was at a high level and fluctuated violently. This can be regarded as precursory information for an outburst risk, which was verified by monitoring the results of mining stress and electromagnetic radiation (EMR). (3) Based on the unilateral inversion imaging method, EP spatial distribution law was studied and abnormal zones with high-value were identified. The zone is close to, or coincident with, the high value interval of EMR intensity and count indexes, which revealed the distribution characteristics of coal damage localization. Hence, EP monitoring results can forecast precursor information of outburst hazards temporally, and identify local zones with outburst hazard spatially. This study provides a new idea and application basis for using the EP method to monitor and prevent coal and rock dynamic disaster hazards in the field.

Assessing the long-term evolution of mine water quality in abandoned underground mine workings using first-flush based models

Coal mining activities can leave an extensive network of abandoned underground workings that gradually flood after operations cease. This rising mine water can eventually lead to uncontrolled releases of harmful acid mine drainage (AMD) to the environment. Treatment plants are used to extract and treat the mine water to maintain its elevation below suspected discharge points. Accurate predictions of long-term water quality, and treatment plant operations, are highly challenging due to the complexity and volume of the underground workings. As numerical models require considerable effort to effectively implement, empirical models that are based on the 'first-flush' phenomenon, where mine water concentrations peak shortly after flooding and then exponentially decline, may provide suitable long-term predictions. The objective of this study was to assess the robustness of first-flush based models for describing mine water behavior at large, complex mine pools in the Sydney Coalfield (Nova Scotia, Canada). Numerous mine pools across the coalfield flooded at various times over 100+ years, with extensive mine water quality data available in various pools of different ages. The historical evolution of mine water quality demonstrated first-flush behavior across key AMD indicator parameters (acidity, sulfate, iron), concentration ranges, and mine pool depths. Two ‘newer’ mine pools, which only flooded in the past 10–15 years, rely on an active treatment plant to manage mine water levels below environmental discharge points. Influent water quality from each mine pool was sampled bi-weekly between 2011 and 2022, and first-flush models were then applied to predict the future quality of mine water entering the treatment plant over the long-term. Knowledge on long-term influent quality can help to optimize treatment plant requirements and related expenses.

Coal Miners and Lung Cancer: Can Mortality Studies Offer a Perspective on Rat Inhalation Studies of Poorly Soluble Low Toxicity Particles?

Inhalation studies involving laboratory rats exposed to poorly soluble particles (PSLTs), such as carbon black and titanium dioxide, among others, have led to the development of lung cancer in conditions characterized as lung overload. Lung overload has been described as a physiological state in which pulmonary clearance is impaired, particles are not effectively removed from the lungs and chronic inflammation develops, ultimately leading to tumor growth. Since lung tumors have not occurred under similar states of lung overload in other laboratory animal species, such as mice, hamsters and guinea pigs, the relevance of the rat as a model for human risk assessment has presented regulatory challenges. It has been suggested that coal workers' pneumoconiosis may reflect a human example of apparent “lung overload” of poorly soluble particles. In turn, studies of risk of lung cancer in coal miners may offer a valuable perspective for understanding the significance of rat inhalation studies of PSLTs on humans. This report addresses whether coal can be considered a PSLT based on its composition in contrast to carbon black and titanium dioxide. We also review cohort mortality studies and case-control studies of coal workers. We conclude that coal differs substantially from carbon black and titanium dioxide in its structure and composition. Carbon black, a manufactured product, is virtually pure carbon (upwards of 98%); TiO2 is also a manufactured product. Coal contains carcinogens such as crystalline silica, beryllium, cadmium and iron, among others; in addition, coal mining activities tend to occur in the presence of operating machinery in which diesel exhaust particles, a Type I Human carcinogen, may be present in the occupational environment. As a result of its composition and the environment in which coal mining occurs, it is scientifically inappropriate to consider coal a PSLT. Despite coal not being similar to carbon black or TiO2, through the use of a weight of evidence approach-considered the preferred method when evaluating disparate studies to assess risk- studies of coal-mine workers do not indicate a consistent increase in lung cancer risk. Slight elevations in SMR cannot lead to a reliable conclusion about an increased risk due to limitations in exposure assessment and control of inherent biases in case-control studies, most notably confounding and recall bias. In conclusion, the weight of the scientific literature suggests that coal mine dust is not a PSLT, and it does not increase lung cancer risk.

Using homing pigeons to monitor atmospheric organic pollutants in a city heavily involving in coal mining industry

Coal is the most extensively used fossil fuel in China. It is well documented that coal combustion detrimentally affected air quality, yet the contribution of coal mining activity to air pollution is still largely unknown. Homing pigeons have been applied to assess the occurrence of atmospheric pollutants within cities. Herein, we sampled homing pigeons from both urban and mining areas in a typical coal industry city (Datong, China) as biomonitors for assessing local air pollution. Target organic contaminants, including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and organochlorine pesticides (OCPs) were frequently detected in lung, liver, and fat tissues of the pigeons. The pollutants were predominately accumulated in lung, validating that respiration was the main accumulation route for these compounds in homing pigeons. In addition, pathological damage examination in lung and liver tissues revealed that the exposure to atmospheric pollutants impaired pigeon health. While the concentrations of PCBs and OCPs were similar in pigeons from urban and mining areas, the concentrations of PAHs were higher in pigeons from urban area. In contrast, more elevated levels of PBDEs (particularly BDE-209) were found in the mining area, which was consistent with the greater pathological damages and particulate matter levels. Unlike coal combustion, coal mining activities did not increase atmospheric PAH exposure to homing pigeons, but intensified PBDE contamination along with increasing emission of particulate matters. Overall, homing pigeons are promising biomonitors for assessing the respiratory exposure and risk of atmospheric pollutants within cities.

Assessing the impact of climate change on Ha Tu coal mine, Quang Ninh province

Climate change has been affecting the socio-economic life of Quang Ninh province in general, and the coal mining activities of many companies, including Ha Tu Coal Joint Stock Company in particular. By the methods of collection, synthesis, statistics, field survey, and public consultation, this study has evaluated the climate condition of the study region and the impact of climate change on the coal mines in the past. The environmental incident of landslides caused by heavy rain in 2015 has filled rivers and streams and destroyed infrastructure. According to the scenario of climate change for Quang Ninh province by 2100 (B2), the regional temperature will increase by 2.50C, and the rainfall will increase by 7.3% compared to the period 1980÷1999. The study predicted the potential impacts of climate change on mining operations in the future such as the increased risk of landslides, floods, geological hazards, the drawdown of groundwater levels, and subsidence of the ground surface at the mining site. By the forecast results, the larger the mining depth is, the higher the radius affected by the lowering of the groundwater level will become, which can be up to 2.4 km compared to the mining area. In addition, the increase in temperature will be one of the factors that cause difficulties for production activities, affect the health of workers, slow down the process of reclamation and restoration of the mine environment, and increase electricity and water costs, etc. The study also proposed several technical and management solutions to reduce the risk and respond to environmental incidents before the impact of climate change on the Ha Tu coal mine towards sustainable development.

Physiological adaptability of three gramineae plants under various vegetation restoration models in mining area of Qinghai-Tibet Plateau

Large-scale coal mining activities on the QTP have affected the natural grassland ecosystem which will take decades to recover. Therefore, looking for an effective vegetation restoration method is the most effective way to restore the ecosystem. In this study, we explored the effects of three vegetation restoration modes (coal mine spoils planting (CK), organic fertilizer planting (OF), and cover soil planting (CS)) on the five cold-resistance related physiological indices of three native Gramineae plants (Elymus nutans, Poa crymophila and Festuca sinensis) growing in three different habitats (shady slope, sunny slope, and flat slope). The higher contents of soluble sugar (SS) in the Elymus nutans (213.46 mg/g) and Festuca sinensis (202.84 mg/g) were recorded under the CS treatment in the sunny slope habitat. The FP contents of Elymus nutans (421.31 μg/g), Poa crymophila (310.06 μg/g), and Festuca sinens (288.45 μg/g) were higher under the CK treatment in the flat ground habitat. The higher (P < 0.05) content of chlorophyll (Chl) was recorded in the Elymus nutans (2.13 mg/g) under the CS treatment in the sunny slope habitat compared to the other two plants. We observed lower MDA contents in the Elymus nutans (3.19 nmol/g) and Festuca sinensis (3.56 nmol/g) under the CK treatment growing in the shady slope habitat. In the shady slope habitat, the H2O2 contents of Elymus nutans (15.86 μmol/g), Poa crymophila (6.78 μmol/g), and Festuca sinensis (8.76 μmol/g) under the CS treatment were significantly lower compared to other treatments. Based on membership function method, the low-temperature adaptability order of the three restoration plants from strong to weak was Elymus nutans > Festuca sinensis > Poa crymophila. While the effectiveness order of the three vegetation restoration models in alpine mining areas from good to bad was CS > OF > CK. This study will provide a theoretical and guiding significance to evaluate the effectiveness of different restoration methods, formulate optimal restoration strategies and guide the sustainable restoration of the damaged ecosystems of the alpine mining areas.

Prevalence of respiratory disease in the population of Queensland communities in proximity to coal mines and coal mining activities

Air quality related to respiratory illness is examined in many settings, including populations that work or reside close to sources of pollution. Industry produced pollution from mining and metal manufacturing, natural environmental pollution as in the case of bushfires and large-scale dust storms are examples. We reviewed any available literature and data concerning the Queensland coal industry and its effect on respiratory health of miners, mining related workers and communities in proximity to coal mines. We searched various databases using keywords related to coal and respiratory diseases, using the five step criteria defined by Denyer and Tranfield. In the Queensland coal mining industry, the negative effect of mining on workers’ respiratory health has been known for many years and has received increased attention in the last five years both nationally and internationally due to the resurgence in Coal Mine Dust Lung Diseases and specifically Coal Worker’s Pneumoconiosis (CWP). A Queensland parliamentary review has prompted regulatory amendments for the permitted (occupational) exposure level (PEL; OEL) to coal dust and silica; amendments have also been enacted for better occupational respiratory health surveillance of Queensland coal miners, both surface and underground. Considering Queensland has a high proportion of Australian coal mines, the literature available on respiratory health in Queensland coal mines and surrounding communities is minimal. There is very limited research into, and possible underreporting of CMDLD amongst the coal mining workers in Queensland. Further studies are required to better understand air pollution and health effects in coal miners in Queensland.

Isolating and Tracking Noise Sources across an Active Longwall Mine Using Seismic Interferometry

ABSTRACT The ability to monitor seismicity and structural integrity of a mine using seismic noise can have great implication for detecting and managing ground-control hazards. The noise wavefield, however, is complicated by induced seismicity and heavy machinery associated with mining operations. In this study, we investigate the nature of time-dependent noise cross-correlations functions (CCFs) across an active underground longwall coal mine. We analyze one month of continuous data recorded by a surface 17 geophone array with an average station spacing of ∼200 m. To extract coherent seismic signals, we calculate CCFs between all stations for each 5-min window. Close inspection of all 5-min CCFs reveals waveforms that can be categorically separated into two groups, one with strong and coherent 1–5 Hz signals and one without. Using a reference station pair, we statistically isolate time windows within each group based on the correlation coefficient between each 5-min CCF and the monthly stacked CCF. The daily stacked CCFs associated with a high correlation coefficient show a clear temporal variation that is consistent with the progression of mining activity. In contrast, the daily stacked CCFs associated with a low correlation coefficient remain stationary throughout the recording period in line with the expected persistent background noise. To further understand the nature of the high correlation coefficient CCFs, we perform 2D and 3D back projection to determine and track the dominant noise source location. Excellent agreement is observed on both short (5-min) and long (daily) time scales between the CCF determined source locations, the overall migration of the active mining operation, and cataloged seismic event locations. The workflow presented in this study demonstrates an effective way to identify and track mining induced signals, in which CCFs associated with background noise can be isolated and used for further temporal structural integrity investigation.

Forecasting groundwater level of karst aquifer in a large mining area using partial mutual information and NARX hybrid model

Predicting the groundwater level of karst aquifers in North China Coalfield is essential for early warning of mine water hazards and regional water resources management. However, the dynamic changes of strata structure and hydrogeological parameters driven by coal mining activity cause challenges to the process-oriented groundwater model. In order to achieve accurate prediction of groundwater level in large mining areas, this study was the first to use the data-driven Nonlinear Autoregressive with External Input (NARX) model to predict the groundwater level of six karst aquifer observation wells in Pingshuo Mining Area. Three variable input scenarios were set up, solely considering meteorological factors, anthropogenic disturbance factors, and considering both meteorological and anthropogenic disturbance factors. The novel partial mutual information (PMI) screening algorithm was adopted to determine optimized input variables in each scenario. The input and feedback delay coefficients of NARX model were determined by using Seasonal-trend Decomposition Procedure Based on Loess (STL) algorithm and auto- and cross-correlation functions. The results showed that PMI algorithm can effectively screen out the optimal input variables for predicting groundwater level, the NSE coefficients of the PMI-NARX models under the three scenarios were 38.81%, 4.26% and 41.46% higher than those of the corresponding control experiments, respectively. In addition, the prediction performance of the PMI-NARX built on the basis of meteorological factors is poor (NSE <0.63). However, in scenarios which solely use anthropogenic disturbance factors and both use meteorological and anthropogenic disturbance factors, the PMI-NARX coupling models exhibit good prediction performance (NSE and R2 are all greater than 0.8). Especially under solely considering anthropogenic disturbance factors scenario, the model still exhibited good prediction accuracy with a negligible number of input variables. The results can provide technical and theoretical support for the prediction of groundwater level in other mining areas.

Calibration and validation of the SSSPAM coupled soilscape–landform evolution model for simulating short‐term gully development on a post‐mining landform

AbstractPost‐mining landforms consist of unconsolidated waste, which can be highly erodible. In such structures of loosely bonded material, rill erosion and gully erosion are significant issues that lead to landform degradation. These landforms need to be designed to minimize erosion to ensure long‐term stability and sustainability. Various landform evolution models (LEMs) have been used to predict the evolution of such landforms and identify areas prone to gully erosion. However, there is a degree of uncertainty associated with predictions made by LEMs due to the lack of field data that can be used to assess their accuracy. Here we use the State Space Soil Production and Assessment Model (SSSPAM) to simulate gully erosion on a post‐mining landform. For the first time, we performed a qualitative and quantitative comparison between model predictions and field data of a post‐mining landform using the SSSPAM model. SSSPAM is a coupled soilscape–landform evolution model that simulates fluvial erosion and armouring, diffusive erosion, deposition and physical weathering within the soil profile. Here, two sites on an active coal mine with active gullies evolving in waste rock were examined. In addition, novel methodologies for model calibration based on experimental flume data and model parameter modification procedures for conducting model simulations at different spatial and temporal scales are introduced. Site‐specific erosion parameters, initial landform digital elevation models and the daily rainfall record of the site were used to simulate the evolution of gullies at the two different sites. Results show that SSSPAM can predict the gullies' position and general geomorphic characteristics with a high degree of accuracy.