Surface Coal Mining Research Articles

Investigation of Work Accidents in Underground and Surface Coal Mining Activities of Western Lignite Corporation by Data Envelopment Analysis (DEA)

Investigation of Work Accidents in Underground and Surface Coal Mining Activities of Western Lignite Corporation by Data Envelopment Analysis (DEA)

The speed, scale, and environmental and economic impacts of surface coal mining in the Mongolian Plateau

Surface coal mining accounts for about 40% of global coal production, and is notorious for its myriad environmental problems and associated social issues. The Mongolian Plateau, consisting of Inner Mongolia of China and the sovereign state of Mongolia, is the world's largest surface coal mining region, producing more than 13% of the total global coal. This study represents the first comprehensive assessment of the spatial extent, expansion rate, and environmental and economic impacts of surface coal mining across the entire plateau, based on data mainly from remote sensing imagery, field surveys, and governmental documents. Our results show that during 1975-2015 the total number of surface coal mines increased from 516 to 10,834 (up 21 times), while the total coal-excavating area expanded from 20.77 to 683.92 km2 (up 33 times). More than 90% of coal mining occurred in Inner Mongolia in 2015. Surface coal mining in the Mongolian Plateau destroyed or damaged more than 10,000 km2 of natural vegetation and agricultural land, and consumed more than 2,315 million m3 of surface water and groundwater, profoundly transforming landscapes with long-lasting impacts on biodiversity, ecosystem processes, and ecosystem services. In addition, rapidly increasing economic inequality raises concerns with social injustice. Policy interventions are needed to stop the rampage of coal mining and promote clean energy-based economic development. Such actions are critical not only for sustaining the Mongolian Plateau, but also for the world to meet emission reduction goals to avert severe environmental and socioeconomic damages of global warming in coming decades.

Slope stability of deep surface coal mines in the presence of a weak zone

Coal and lignite (brown coal) are geo-resources that govern energy production for decades. Geomechanical challenges, particularly slope stability, related to surface coal and lignite mines are critical during operation and determine the post-coal era. Several failure incidents have been reported in mining areas, typically associated with a sub-horizontal failure surface on a weak—clay or marl—layer or an interface of low strength. This weak zone controls the soil profile in terms of stability and is common in several mines globally. In this work, the finite element method with the shear strength reduction technique is primarily employed to evaluate the slope stability of this profile. Three geotechnical software are initially compared, and results are identified as practically identical. Moreover, slopes with benches, as typically in mines, and without benches, as typically in slope stability analysis, are compared, with the no-benches analysis being consistently more conservative. The crucial parameters' effect is then examined: the height and the inclination of the slope, the inclination, thickness, and strength of the weak zone, and the strength of the overburden soil. Their effect on slope stability is quantified by combining the probabilistic point estimate method with the finite element method. It is concluded that the inclination and strength of the weak zone and the water conditions are the most critical parameters and control the stability. This work can support a preliminary slope stability analysis and expands the knowledge and understanding of slope stability of a weak zone profile.

Spatiotemporal Interactions between Surface Coal Mining and Land Cover and Use Changes

Long-term surface mining and land cover and use changes have been evidenced to have a critical relationship. This study conducts trend and correlation analysis by statistical tools to quantitatively evaluate this relationship in the Ptolemais (Northern Greece) coal mining area for the period 1990-2018. Firstly, based on Corine data and satellite images, a relative spatial indicator (RSI) was adopted to describe the mineral land areas. Secondly, land cover and use changes were spatially defined using Corine data and ArcGIS tools. The active mining area was then distinguished by dumping area, using Landsat satellite imagery and mining maps, and finally, mine operation parameters were statistically analyzed. The study revealed that “mineral extraction sites” present a strong correlation with “non irrigated arable land” and “transitional woodland”. The results have shown that between 1990 and 2018 the total forest area was increased by three times, mainly as a result of the dumping sites geometry. Additionally, the mine operation parameters are well correlated with the active mining area.

Monitoring ecosystem restoration of multiple surface coal mine sites in China via LANDSAT images using the Google Earth Engine

AbstractThe restoration of surface mining (open‐cast) sites is key to meeting global ecosystem restoration targets. With the improving of data availabilities and technologies, it has become possible to expand restoration monitoring from single to multiple mine sites on a large scale. Based on the MODIS global disturbance index (MGDI), this study proposes a mine landscape restoration index (MLRI), by coupling the LST and EVI to simultaneously monitor the restoration of multiple mine sites. Restoration areas were identified by MLRI time‐series analysis and classified into significant consistent increase (SCI) and significant anti‐consistent increase (SAI) areas. The restoration effects of 46 surface coal mine sites located in the ecologically fragile northwestern region of China from 2000 to 2019 were assessed based on 3,675 LANDSAT images from the Google Earth Engine. Results show that the MLRI was effective at identifying restoration areas and processes, and this effectiveness was validated by high‐resolution images and field investigations of mine samples. The overall percentage of restored area for mines that started mining before 2000 was 55.01% ; for mines that starting mining after 2000, 33.68%. According to the differences of SCI and SAI area percentages, 46 mine sites were classified into three clusters, with 13, 11, and 22 mine sites, respectively. The mine sites with high restoration percentage are located mainly in Hailar and Shanbeimengnan regions. This study provides a new approach for monitoring the restoration effects of multiple mine sites and informs government managers about developing mine restoration programs and sustainable mining development plans.

Assessment of occupational exposure to diesel particulate matter through evaluation of 1-nitropyrene and 1-aminopyrene in surface coal miners, India.

DPM (diesel particulate matter) is ubiquitously present in the mining environment and is known for mutagenicity and carcinogenicity to humans. However, its health effects in surface coal mines are not well studied, particularly in India. In this study, DPM exposure and corresponding exposure biomarkers were investigated in four different surface coal mines in Central India. To document and evaluate the DPM exposure in surface coal miners, we characterized 1-NP (1-nitropyrene) in the mining environment as surrogate for DPM using Sioutas Cascade Impactor. Exposure biomarkers were analyzed by collecting post work shift (8-h work shift) urine samples and determining the concentrations of 1-aminopyrene (1-AP) as a metabolite of 1-NP and 8-hydroxydeoxyguanosine (8OHdG) as DNA damage marker. We observed high concentration of 1-NP (7.13-52.46ng/m3) in all the mines compared with the earlier reported values. The average creatinine corrected 1-AP and 8OHdG levels ranged 0.07-0.43[Formula: see text]g/g and 32.47-64.16[Formula: see text]g/g, respectively, in different mines. We found 1-AP in majority of the mine workers' urine (55.53%) and its level was higher than that reported for general environmental exposure in earlier studies. Thus, the study finding indicates occupational exposure to DPM in all the four mines. However, the association between 1-NP level and exposure biomarkers (1-AP and 8OHdG) was inconsistent, which may be due to individual physiological variations. The data on exposure levels in this study will help to understand the epidemiological risk assessment of DPM in surface coal miners. Further biomonitoring and cohort study are needed to exactly quantify the occupational health impacts caused by DPM among coal miners.

Geotechnical Characterization of Fine-Grained Spoil Material from Surface Coal Mines

AbstractCoal mines produce large amounts of excavated waste soils, known as spoils. These materials can cover vast areas, are typically dumped in heaps without any treatment, and are difficult to e...

Assessment of Surface Ecological Quality of Grassland Mining Area and Identification of Its Impact Range

High-intensity coal mining in grasslands has negative impact on the surface ecology of the mining area and its surroundings. This impact shows spatio-temporal heterogeneity due to differences in mining intensity at various life stages. Based on remote sensing images and experimental test data, this paper took the Baorixile Surface Coal Mine (BSCM), which as the largest open-pit mine in eastern Inner Mongolia, as an example to analyze surface ecological quality and risk at the whole life cycle. In total, 13 indices from three aspects of site structure, spatial pattern, and ecological function were selected to assess surface ecological quality. The geoaccumulation index and potential ecological risk index were used to analyze the ecological risk of surface soil. Identification of impact range of mining activities and pollution sources of soil heavy metal was obtained by correlation analysis. At present, the BSCM is at a stable stage. Ecological quality showed a deteriorating trend during the reaching and stable stages. The soil organic matter content at the BSCM was lower than the Second National Soil Survey and exhibited a decreasing tendency. A low ecological risk was found in soil, and Cd was the main potential ecological risk element. The surface ecology of the boundary and its 2 km buffer zone was affected by mining activities in the BSCM. Mining activities may have an impact on the surface ecology of the 5 km buffer zone. This study provides a reference method for ecological quality assessment and impact scope determination of similar mining areas.

Development of Mine Soils in a Chronosequence of Forestry-Reclaimed Sites in Eastern Kentucky

Surface mining for coal has contributed to widespread deforestation and soil loss in coal mining regions around the world, and particularly in Appalachia, USA. Mined land reforestation is of interest in this and other regions where forests are the dominant pre-mining land use. This study evaluated mine soil development on surface-mined sites reforested according to the Forestry Reclamation Approach, representing a chronosequence of time ranging from 0 to 19 years after reclamation. Soils were sampled in depth increments to 50 cm and analyzed for a suite of soil physical and chemical characteristics. Overall, soil fines (silt + clay) tended to increase over time since reclamation (17% silt at year 0 increasing to 35% at year 11; 3.2% clay at year 0 increasing to 5.7% at year 14) while concentrations of metals (e.g., Al, Mg, Mn, Na) demonstrated varied relationships with time since reclamation. Concentrations of organic carbon (OC) tended to increase with time (0.9% OC at year 0 increasing to 2.3% at year 14), and were most enriched in near-surface soils. Some soil characteristics (e.g., Na, OC, Ca) demonstrated patterns of increasing similarity to the forest control, while others were distinct from the forest control throughout the chronosequence (e.g., Al, clay, Mn, gravel). Future surveys of these soils over time will elucidate longer-term patterns in soil development, and better characterize the time scales over which these soils might be expected to approximate forest soil conditions.

Role of the Selected Grass Species in Developing of Swampy Forest System for Passive Treatment of Acid Mine Drainage

Acid Mine Drainage (AMD) is one of the consequences of environmental impact due to surface coal mining and has big challenge how to treat the AMD both active and passive treatment efficient and effectively. The most expensive method to actively raise the pH and concentration heavy metal reduction of this wastewater is the use of chemical additives. We present the development of passive treatment with Swampy Forest (SF) system as a new natural and sustainable method with lower costs, and greater environmental sustainability. The SF system consists of selecting organic matter and combining it with the planting of selected grass and tree species in the form of a forest constructed wetland. As a preliminary to the construction of the SF, a batch reactor system was used to carry out experiments to find the best individual grass species for SF as the development of AMD passive treatment. The four grass species selected were shown to reduce the concentration of Fe and Mn, which generally has out of threshold value, thus achieving the threshold parameter to comply with applicable regulations for managing mine wastewater.

Topsoil alternatives selection for surface coal-mined land reclamation in Inner Mongolia, China: an experimental study

ABSTRACT There are many surface coal mines located in Inner Mongolia, which has dry and scarce topsoil, and the selection of topsoil alternatives is key to coal-mined land reclamation. This study used the largest surface coal mine in the Holonbuyr grassland as the experimental site. The soil of layer II (loess) and layer III (mild clay) under the local topsoil, which has a high clay content and good texture, has the potential to be a substitute for topsoil. To reduce its viscosity and improve its nutrients, soil amendments mixed with organic matter, such as corn stalk and sheep and cattle manure and microbial agents, were added to four mixed substrates with different formulas. Twelve topsoil alternatives were produced and compared for further research. The results show that (1) by mixing a variety of substrates, topsoil alternatives can fully meet the alfalfa (Medicago sativa L.) growth requirement. (2) The addition of exogenous organic matter and microbial agents could significantly increase the nutrient content and the number of microorganisms in the soil, thereby increasing the plant height of alfalfa (Medicago sativa L.) and the average dry mass of the aboveground and underground parts

Research on developing a methodto estimate fugitive CH4 emissionfactors of coal surface mining in Quang Ninh province

This article presents the approach and the results of estimating CH4 emission from surface mining in Quang Ninh province to develop its fugitive CH4 emission factors. The two largest active surface mines were selected named Nui Beo and Cao Son. By applying a direct measurement method with samples using a specific chamber, CH4 emission was collected and calculated for the whole mine. Results showed that CH4 emission varied from mine to mine both the total amount and its range of maximum and minimum. In detail, the total amount of CH4 emission from Cao Son is 19,032.87 m3with the range of 73.14% while these numbers of Nui Beo are 2,684.47 m3 and 76.38%, respectively. The CH4emission factors of surface mines then were estimated in the range of 0.0850 m3/ton and 0.0225 m3/ton respect to high emission level and low emission level. These values are close to the emission factors generated from Germany (0.015 - Lignite), Canada (0.088 - Lignite; 0.19 - Bituminous), South Africa (0.002÷0.064 - Bituminous). These emission factors are considered as scientific evidence to propose the national factors of CH4 emission of surface mining.

How High Is the Recreation Value of Successional Forests Growing Spontaneously on Coal Mine Spoil Heaps?

Research highlights: Recreation value increases with the age of replanted as well as successional forests. Successional forests are not systematically less valuable for recreation than replanted forests. Succession may be used as a viable and low-cost reclamation practice of spoil heaps. Background and objectives: Afforestation has been a popular practice in post-mining land reclamation in the Czech Republic. To expand the current evidence on the recreation values of reclaimed forests, we conducted a valuation study for most typical reclaimed forests, as well as for successional forests spontaneously growing on surface coal mine deposit heaps. Using two distinct measurement methods, we also explore whether the estimated recreation value of forests is robust. Materials and Methods: An online survey was conducted in 2016 on a sample of residents living in the vicinity of coal mine deposit heaps, residents of the adjacent region of Karlovy Vary, and a control population from the central Bohemian region. Participants evaluated visual representations of forest stands typical for reclamation and succession, along with commercial spruce forest as a reference type. In the direct measurement, we measured the attractiveness of a respective forest for a walk using a 5-point scale. In the indirect measurement, a hypothetical choice between two forests for a walk was elicited in a discrete choice experiment. Results: Both direct and indirect measurements provide similar results. All reclaimed forests have a lower recreation value than the reference spruce forest. Successional forests are not systematically less valuable for recreation than replanted forests and the recreation value of both types increases with their age. The age, gender, and education of the participants did not affect the recreation value of a forest. Conclusions: We demonstrate that succession may be used as a viable and low-cost reclamation practice of spoil heaps emerging as a by-product of open-cast coal mining. With recreation as only one of many forest uses, our findings need to be interpreted vis-à-vis the objectives and expected results for individual sites and their habitat conditions.

Examination of Bronchial Reactivity in Workers Exposed to Microparticles PM2.5 and PM10 during Coal Surface Mining in the Bellaqevc Power Plants of Kosovo

The impact of air pollution with microparticles (PM2.5 and PM10) on the respiratory systems of workers engaged in thesurface mining of coal at the Bellaqevc power plants of Kosovo is studied in this paper. The parameters of lung functionare defined via body plethysmography. The resistance of the airways (Raw) was recorded, intrathoracic gas volume (ITGV) was measured, and the specific resistanceof the airways (SRaw) and specific conductance (SGaw) were calculated. The research was performed withintwo groups: a control group and experimental group. The control group consisted of 28 healthy people, whereas the experimental group consisted of 50 workers engaged in the surface mining of coal at the Bellaqevc power plants of Kosovo.
 The results obtained from this research indicated that the mean specific resistance (SRaw) was ​​significantly increased in the experimental group (p<0.01) compared to the control group (p>0.1). The study also found that smoking favors the adverse effects of air pollution caused by coalsurface mining at the Bellaqevc power plants (p<0.01).
 Measurements of the respiratory systems were made prior to and following provocation with histamine–aerosol (1 mg/ml) in the control and experimental groups. Changes between these two groups following this provocation with histamine–aerosol were found to be statistically significant (p<0.01).
 In order to cause a respiratory pathology from air pollution, it is required a lot of time, such pollution can permanently cause respiratory system disorders. These scientific findings suggest that the long-term exposure of workers to microparticles PM2.5 and PM10 during the processof surface mining coal at the Bellaqevc power plants of Kosovo poses a risk to their health by causing increased bronchial reactivity, bronchial asthma, orchronic obstructive pulmonary disease (COPD).

Technological Adaptation of Internal Dumping to the Operating Mode of Open Pit when Developing Inclined and Steeply Dipping Coal Seams Strata

With surface mining of inclined and steeply dipping coal deposits, the so-called deeping longitudinal mining methods with a gradual deepening of mining from the surface to the final depth are widely spread, while orienting the mining front along the strike line of the seams (strata). When using such mining methods, the volumes of internal dumping are limited or completely absent; there is a peak-like increase in overburden volumes and transportation distance, the land resources disturbing proceeds at a progressive pace. In this regard, it is obvious that an important production task is to find technological solutions and methods to develop coal deposits that reduce the environmental hazard and increase resource conservation in mining by placing overburden in the mined-out space while reducing the area for external dumps and disturbing the earth's surface. If this is not foreseen at the present time, then all coal surface mines in the coming decades will be limited by their own external dumps of overburden, and their further development will be problematic.

Deep convolutional neural networks for surface coal mines determination from sentinel-2 images

ABSTRACT Coal is a principal source of energy and the combustion of coal supplies around one-third of the global electricity generation. Coal mines are also an important source of CH4 emissions, the second most important greenhouse gas. Monitoring CH4 emissions caused by coal mining using earth observation will require the exact location of coal mines. This paper aims to determine surface coal mines from satellite images through deep learning techniques by treating them as a land use/land cover classification task. This is achieved using Convolutional Neural Networks (CNN) that has proven to be capable of complex land use/land cover classification tasks. With a list of known coal mine locations from various countries, a training dataset of “Coal Mine” and “No Coal Mine” image patches is prepared using Sentinel-2 satellite images with 13 spectral bands. Various pre-trained CNN network architectures (VGG, ResNet, DenseNet) are trained and validated with our prepared coal mine dataset of 3500 “Coal Mine” and 3000 “No Coal Mine” image patches. After several experiments with the VGG network combined with transfer learning is found to be an optimal model for this task. Classification accuracy of 98% has been achieved for the validation dataset of the pre-trained VGG architecture. The model produces more than 95% overall accuracy when tested on unseen satellite images from different countries outside the training dataset and evaluated against visual classification.

Improvement of Continuous Lateral Surface Mining Method for Coal Extraction from Closed Mines’ Pillars

The presented paper deals with a continuous lateral method of closed mines' coal pillars surface mining and its advantages in land intensity, dust emissions, maximizing coal extraction, and overburden transporting costs. While inclined and steep coal seam strata in the pillars are widely exploited with land-and-cost intensive deepening longitudinal mining method, this article substantiates the choice of modification of block-and-layer continuous lateral mining method for different kinds of coal deposits. The aim of the study is to specify the modifications of the method proposed, define the stages of their carrying out, and emphasize the advantages over deepening longitudinal method of coal pillars surface mining. The basic principle of the proposed continuous lateral method of mining the coal pillars is limiting the final depth of quarry by the vertical height of the first floor of the underground mine workings. The continuous lateral mining method is detailed in the article in three modifications (for development coal seams strata of high and medium thickness, as well as distanced separate coal seams), which advantages are low land intensity and dust emission from the dump. Attention is also paid to the economic benefits of the block-and-layer continuous lateral method of mining coal pillars of closed mines, whereby the overburden transporting costs can be significantly reduced, while limitations of the proposed mining method concern specific sites of closed mines that make up a small part of the coal pillars extracted by surface mining today.

Semantic Segmentation Deep Learning for Extracting Surface Mine Extents from Historic Topographic Maps

Historic topographic maps, which are georeferenced and made publicly available by the United States Geological Survey (USGS) and the National Map’s Historical Topographic Map Collection (HTMC), are a valuable source of historic land cover and land use (LCLU) information that could be used to expand the historic record when combined with data from moderate spatial resolution Earth observation missions. This is especially true for landscape disturbances that have a long and complex historic record, such as surface coal mining in the Appalachian region of the eastern United States. In this study, we investigate this specific mapping problem using modified UNet semantic segmentation deep learning (DL), which is based on convolutional neural networks (CNNs), and a large example dataset of historic surface mine disturbance extents from the USGS Geology, Geophysics, and Geochemistry Science Center (GGGSC). The primary objectives of this study are to (1) evaluate model generalization to new geographic extents and topographic maps and (2) to assess the impact of training sample size, or the number of manually interpreted topographic maps, on model performance. Using data from the state of Kentucky, our findings suggest that DL semantic segmentation can detect surface mine disturbance features from topographic maps with a high level of accuracy (Dice coefficient = 0.902) and relatively balanced omission and commission error rates (Precision = 0.891, Recall = 0.917). When the model is applied to new topographic maps in Ohio and Virginia to assess generalization, model performance decreases; however, performance is still strong (Ohio Dice coefficient = 0.837 and Virginia Dice coefficient = 0.763). Further, when reducing the number of topographic maps used to derive training image chips from 84 to 15, model performance was only slightly reduced, suggesting that models that generalize well to new data and geographic extents may not require a large training set. We suggest the incorporation of DL semantic segmentation methods into applied workflows to decrease manual digitizing labor requirements and call for additional research associated with applying semantic segmentation methods to alternative cartographic representations to supplement research focused on multispectral image analysis and classification.

Carbon Sequestration by Reforesting Legacy Grasslands on Coal Mining Sites

Future carbon management during energy production will rely on carbon capture and sequestration technology and carbon sequestration methods for offsetting non-capturable losses. The present study quantifies carbon sequestration via reforestation using measurements and modeling for recent and legacy surface coal mining grasslands that are re-restored through tree planting. This paper focuses on a case study of legacy coal mining sites in the southern Appalachia the United States. This five million-hectare region has a surface mining footprint of approximately 12% of the land area, and the reclamation method was primarily grassland. The results of the soil carbon sequestration rates for restored forest soils approach 2.0 MgC ha−1 y−1 initially and average 1.0 MgC ha−1 y−1 for the first fifty years after reclamation. Plant, coarse root and litter carbon sequestration rates were 2.8 MgC ha−1 y−1 with plant carbon estimated to equilibrate to 110 MgC ha−1 after forty years. Plant, root and litter carbon stocks are projected to equilibrate at an order of magnitude greater carbon storage than the existing conditions, highlighting the net carbon gain. Reforestation of legacy mine sites shows carbon sequestration potential several orders of magnitude greater than typical land sequestration strategies for carbon offsets. Projections of future scenarios provide results that show the study region could be carbon neutral or a small sink if widespread reforesting during reclamation was implemented, which is contrary to the business-as-usual projections that result in a large amount of carbon being released to the atmosphere in this region.

The growth of faults and fracture networks in a mechanically evolving, mechanically stratified rock mass: a case study from Spireslack Surface Coal Mine, Scotland

Abstract. Fault architecture and fracture network evolution (and resulting bulk hydraulic properties) are highly dependent on the mechanical properties of the rocks at the time the structures developed. This paper investigates the role of mechanical layering and pre-existing structures on the evolution of strike–slip faults and fracture networks. Detailed mapping of exceptionally well exposed fluvial–deltaic lithologies at Spireslack Surface Coal Mine, Scotland, reveals two phases of faulting with an initial sinistral and later dextral sense of shear with ongoing pre-faulting, syn-faulting, and post-faulting joint sets. We find fault zone internal structure depends on whether the fault is self-juxtaposing or cuts multiple lithologies, the presence of shale layers that promote bed-rotation and fault-core lens formation, and the orientation of joints and coal cleats at the time of faulting. During ongoing deformation, cementation of fractures is concentrated where the fracture network is most connected. This leads to the counter-intuitive result that the highest-fracture-density part of the network often has the lowest open fracture connectivity. To evaluate the final bulk hydraulic properties of a deformed rock mass, it is crucial to appreciate the relative timing of deformation events, concurrent or subsequent cementation, and the interlinked effects on overall network connectivity.