Environment In Mining Area Research Articles

Research on Coal Mine Environmental Pollution Management and Ecological Restoration Technology

This paper analyses the current situation of environmental pollution in coal mines, its causes, and its impact on the ecological environment, and systematically researches the management of environmental pollution in coal mines and ecological restoration technology. The paper analyses the main categories of coal mine environmental pollution, including water pollution, air pollution, and solid waste pollution, and discusses the causes of these pollution and their destructive effects on the ecological environment. Immediately after that, the article elaborates on the treatment technologies of coal mine environmental pollution, including physical, chemical and biological treatment technologies for water pollution control, blocking, adsorption and covering technologies for air pollution control, and landfill, incineration and resource utilization strategies for solid waste disposal. This paper also discusses coal mine ecological restoration techniques, including species selection and allocation for vegetation restoration, vegetation restoration models, physical, chemical and biological methods for soil improvement, and engineering, vegetation and agricultural measures for soil and water conservation. Through the research of this paper, the researchers aim to provide scientific basis and technical support for the management of coal mine environmental pollution and ecological restoration and to promote the restoration of the ecological environment in mining areas and the sustainable development of the coal industry.

Research on ecological restoration and its impact on society in coal resource-based areas: Lessons from the Ruhr area in Germany and the Liulin area in China

The coal resource-based areas rely on coal resources and primary processing as their pillar industries, such as the old industrial areas in China and Germany. Long-term, large-scale coal mining has significantly damaged the ecological environment of mining areas. Environmental restoration refers to repairing, rehabilitating, or revitalizing ecosystems that have been degraded, damaged, or destroyed by human activities or natural disasters. In fact, ecological restoration is not just an environmental issue and it is a societal problem. Ecological restoration is closely linked to natural resources, the environment, the economy, society, and politics. These factors form a social ecological system and it is the basis for local stability and sustainable development in the coal resource-based areas. In this process, the relationship between government, enterprise, and local people is constantly being reshaped and defined, then it causes changes in the local social ecology and political ecology. The paper researches the Ruhr area in Germany and the Liulin County in China, the former is a world-famous old industrial and the latter is a typical coal mining subsidence district. By analyzing and comparing the ecological restoration and significant social changes in the Ruhr area and the Liulin County at different periods, the findings show the unique ecology— social system of the coal resource-based area, then enhances the effective measures for ecological restoration and sustainable development of the coal resource-based areas.

Study on Plant-blanket to reduce heavy metal migration caused by precipitation and to improve the soil environment of pyritic tailings

The increasing demand for mineral resources due to industrial development has led to significant tailings pollution during the mineral extraction process. In the southwestern region of China, a large amount of pyritic tailings containing pyrite cinder easily leaches heavy metals and other pollutants when exposed to precipitation, resulting in widespread soil contamination. Effective remediation methods are urgently needed to address this issue. This study utilized naturally occurring Plant-blanket formed by the symbiosis of moss and herbaceous plants on pyritic tailings as restoration material. Through leaching experiments and staining tracer techniques, the study investigated the ability of Plant-blanket to reduce the migration of heavy metals from pyrite cinder to soil under the influence of precipitation and its role in improving the soil environment. The results showed that within 12 h, the Plant-blanket could absorb water equivalent to 206.9 % of its own weight and had good water retention ability. It reduced the stained area ratio of soil horizontal and vertical profiles after precipitation leaching by a maximum of 76.08 % and 46.41 %, respectively, and improved the pH, cation exchange capacity (CEC), bulk density, and water content of soil at different depths. In addition, after being covered by Plant-blanket, the migration of Cd and Cu was reduced by a maximum of 44.35 % and 55.77 % respectively, and it increased the diversity and abundance of bacterial communities, promoting the recovery of soil microbial ecological functions. These findings indicate that Plant-blanket can regulate water and improve soil environment, and has certain control ability on the migration of Cd and Cu produced by pyritic tailings. Meanwhile, Plant-blanket plays an important role in improving the soil environment in mining areas and promoting ecosystem restoration, providing valuable reference for further exploration of ecological restoration of tailings.

Progress of Ecological Environment Research in Mining Areas based on Remote Sensing Technology

Significant progress has been made in the application of remote sensing technology in the study of ecological environment in mining areas. Using technologies such as hyperspectral remote sensing, multispectral remote sensing, low-altitude remote sensing by unmanned aerial vehicles and the construction of monitoring indicator systems, it has been widely applied to mine development and land use, monitoring of vegetation cover in mines, monitoring of the geological and hydrological environment in mines and monitoring of environmental pollution in mines. In the future, with the continuous emergence of new technologies and the optimization of remote sensing technology, the application of remote sensing technology in the monitoring and protection of mining ecological environment will be more extensive and in-depth, which can provide stronger support for mining ecological environment protection and sustainable development.

Risk assessment and source analysis of heavy metals in soil around an asbestos mine in an arid plateau region, China

Asbestos is widely used in construction, manufacturing, and other common industrial fields. Human activities such as mining, processing, and transportation can release heavy metals from asbestos into the surrounding soil environment, posing a health hazard to the mining area's environment and its surrounding residents. The purpose of the present study was to determine the extent of ecological and human health damage caused by asbestos pollution, as well as the primary contributors to the contamination, by examining a large asbestos mine and the surrounding soil in China. The level of heavy metal pollution in soil and sources were analyzed using methods such as the geo-accumulation index (Igeo), potential ecological risk index (RI), and positive matrix factorization (PMF) model. A Monte Carlo simulation-based health risk model was employed to assess the health risks of heavy metals in the study area’s soil to human beings. The results showed that the concentrations of As, Pb, Cr, Cu, and Ni in the soil were 1.74, 0.13, 13.31, 0.33, and 33.37 times higher than the local soil background values, respectively. The Igeo assessment indicated significant accumulation effects for Ni, Cr, and As. The RI evaluation revealed extremely high comprehensive ecological risks (RI ≥ 444) in the vicinity of the waste residue heap and beneficiation area, with Ni exhibiting strong individual potential ecological risk (Eir ≥ 320). The soil health risk assessment demonstrated that As and Cr posed carcinogenic risks to adults, with mean carcinogenic indices (CR) of 1.56E − 05 and 4.14E − 06, respectively. As, Cr, and Cd posed carcinogenic risks to children, with mean CRs of 1.08E − 04, 1.61E − 05, and 2.68E − 06, respectively. Cr also posed certain non-carcinogenic risks to both adults and children. The PMF model identified asbestos contamination as the primary source of heavy metals in the soil surrounding the asbestos mining area, contributing to 79.0%. According to this study, it is recommended that management exercise oversight and regulation over the concentrations of Ni, Cr, Cd, and As in the soil adjacent to asbestos mines, establish a designated control zone to restrict population activities, and locate residential zones at a safe distance from the asbestos mine production zone.

Citric acid-induced photochemical behavior of Cr(III)-substituted ferrihydrite: Fe and Cr release, mineral transformation and reactive oxygen species generation

Cr(III)-substituted ferrihydrite (Fh-Cr(III)) is widespread in the surrounding environment of mining areas. Fh-Cr(III) is unstable and susceptible to the influence of environmental factors, such as dissolved organic matter (DOM) and light, so Cr species embedded in mineral crystal layers are likely to have more profound negative effects on the environment with the photochemical behaviors of minerals. However, the photochemical behaviors of Fh-Cr(III) in the presence of DOM remains poorly understood. For this reason, citric acid (CA) was chosen as the representative DOM to study its combined effects with visible light irradiation on Fh-Cr(III) dissolution and phase transition. The results showed that CA hindered the agglomeration of Fh-Cr(III) particles, thereby slowing the phase transition of Fh-Cr(III). However, CA exacerbated the release of Fe and Cr by maintaining Fh-Cr(III) under unstable crystal structure. Moreover, due to the occurrence of ligand-metal charge transfer (LMCT) in (CA)n-Fh-Cr(III) formed on the Fh-Cr(III) surface, the synergistic effect between CA and light irradiation greatly promoted the dissolution of Fh-Cr(III). In the mixed system of Fh-Cr(III) (3 g/L) and CA (5 mM) at initial pH 3.0, the maximum concentrations of TFe and TCr were 18.17 and 5.68 mg/L after 6 h of light reaction, which were 1.82 and 3.62 times of those in the corresponding system in the darkness. Meanwhile, the Fe(III)/Fe(II) cycling in solution and solid surfaces was affected by various reactive oxygen species (ROS) generated from the LMCT process, in which the photoproduced Fe(II) further accelerated Cr(III) dissolution under acidic solution. The fast release of Cr(III) may pose greater danger to the environment as the more toxic Cr(VI) can be easily formed through the oxidation of dissolved Cr(III). This work offers fresh insights into the migration and transformation of Cr elements in the natural environment.

Comprehensive evaluation of green mine construction level considering fuzzy factors using intuitionistic fuzzy TOPSIS with kernel distance.

With increasing concerns about climate change and resource-environmental limitations, the green development of the mining industry has become mainstream and gained much support. Driven by the concept of sustainable and green development, China has made the advancement of green mine construction a crucial part of establishing an eco-society and has put forward the overall goal of green mines. An important future strategy is to evaluate a large number of mines. However, developing scientific, reliable, and comprehensive index systems and evaluation methods is extremely difficult because of the objective complexity of green mine evaluation and the fuzziness of some indicators. The kernel method and intuitionistic fuzzy set can effectively handle these problems. This study proposed a comprehensive evaluation index system and a hybrid evaluation method based on the kernel distance measure and intuitionistic fuzzy TOPSIS method. The index system contains 22 indicators considering six aspects: mining area environment, resource development mode, comprehensive utilization of resources, energy saving and emission reduction, technical innovation, and corporation management. The hybrid evaluation method was applied to the practical assessment of ten green mines in Panxi, China. Comparative analyses were carried out to demonstrate its applicability and sensitivity. The results verify that the hybrid method can fully depict the construction achievements of green mines in all aspects with strong reliability and stability. This approach is a valuable reference for evaluators and decision-makers in government departments.

Spatioemporal dynamics and driving forces of soil organic carbon changes in an arid coal mining area of China investigated based on remote sensing techniques

Soil organic carbon (SOC) undergoes rapid changes due to human production activities, which have an impact on the land carbon cycle and ultimately global change. As one of the main human production activities, coal mining significantly impacts the soil carbon cycle. However, due to the lack of remote sensing modeling of soil carbon in mining areas, the spatio-temporal changes and driving mechanisms of SOC in mining areas remain unclear. Therefore, this study investigated and determined SOC data from 300 sampling points (depth of 0–20 cm) located in an arid mining area of China. Remote sensing images were then used to established a soil organic carbon density (SOCD) prediction model within the Random Forest (RF) model to achieve digital mapping of soil organic carbon stocks (SOCS). The spatiotemporal changes of SOCS were analyzed using SOCS digital mapping, and the influencing mechanism of SOCS was revealed using path analysis. The results showed that the constructed SOCD predictive model meets the demand for SOCD prediction (R2 ≥ 0.74, p < 0.01, RMSE ≤ 1.72 kg/m2). Under the combined influence of coal mining and land reclamation, the total amount of surface SOCS in the mining area exhibited a fluctuating upward trend from 1990 (6.34 Tg) to 2021 (7.73 Tg), with an annual growth rate of 0.038 Tg/a. The spatial distribution of SOCS generally increased from southeast to northwest. Precipitation, Normalized Difference Vegetation Index (NDVI), and land use were positively correlated to SOCS spatial distribution, while temperature, elevation, soil erosion, and mining intensity were negatively correlated to SOCS. The impact degree of factors on SOCS was as follows: NDVI > soil erosion > mining intensity > precipitation > elevation > land use > temperature. The negative impact of coal mining on SOCS was mainly indirect, through disturbance to elevation, vegetation, and soil erosion. The uneven ground subsidence and stretching caused by coal mining contribute to intensified soil erosion and vegetation degradation in the affected area, leading to a reduction in SOCS. However, SOCS did not decrease under high intensity mining, which was related to the increase in vegetation and the reduction in soil erosion in the mining area. In this study, a soil carbon prediction model was established based on remote sensing modeling to evaluate the temporal and spatial distribution of soil carbon in an arid mining area. The results can serve as valuable references for the scientific improvement of the ecological environment in mining areas, the rational planning of mining area construction, as well as low-carbon land reclamation and ecological compensation assessments.

Evaluation of green mine construction level in Tibet based on entropy method and TOPSIS

Green mine construction is a systematic project involving the whole life cycle of mineral resources exploitation and utilization, representing the overall level of development potential. As an important strategic mineral resources reserve base in China, Tibet is rich in mineral resources. In order to calculate the level of green mine construction in Tibet, we obtained different data sources such as statistical yearbooks and mine construction information through field research and discussion. We establish the EMUCIMH evaluation system, select a total of 20 indexes from seven aspects(ecological mining environment, scientific mining method, efficient resource utilization, standardization of energy conservation and emission reduction, intelligent mine construction, standardization of enterprise management and harmonization of mining community),using the Entropy Weight TOPSIS Method to study the problems existing in the process of green mine construction, expecting to provide some references for government departments to make management decisions and for mining enterprises to improve green mine construction. The results show that among the 11 national green mines in Tibet, the construction status is uneven, and there are large differences in the mining methods, the comprehensive utilization of resources, and the ecological environment of mining areas. In contrast, The difference of standardization of enterprise management, intelligent mine construction and the harmonization of mining community is small. Among the specific indicators, in terms of exhaust emissions, mining community harmony and corporate culture are doing well, while they are relatively poor in terms of environmental management and monitoring, technological innovation, and intelligent mine, which need to be improved. Large and medium-sized mines, especially metal mines, the overall level of green mine construction is high, followed by small and medium-sized metal mines and individual Non-metal large mines, and mines with more historical problems faced more difficulties and challenges.

The Relationship between Acid Production and the Microbial Community of Newly Produced Coal Gangue in the Early Oxidation Stage.

Coal gangue is a solid waste formed during coal production, and the acid mine drainage it generates during open-pit storage severely pollutes the ecological environment of mining areas. Microorganisms play a crucial catalytic role in acidification, and their species and gene functions change during the oxidation process of coal gangue. In this study, the changes in microbial community structure were investigated during the initial acidification process for newly produced gangue exposed to moisture by monitoring the changes in pH, EC, sulfate ion concentration, and the iron oxidation rate of gangue leaching solutions. Moreover, the composition and functional abundance of microbial communities on the surface of the gangue were analyzed with rainfall simulation experiments and 16S rRNA sequencing. The study yielded the following findings: (1) The critical period for newly produced gangue oxidation spanned from 0~15 d after its exposure to water; the pH of leaching solutions decreased from 4.65 to 4.09 during this time, and the concentration and oxidation rate of iron in the leaching solutions remained at low levels, indicating that iron oxidation was not the main driver for acidification during this stage. (2) When the gangue was kept dry, Burkholderia spp. dominated the gangue microbial community. When the gangue was exposed to moisture, the rate of acidification accelerated, and Pseudomonas replaced Burkholderia as the dominant genus in the community. (3) In terms of gene function, the microbial community of the acidified gangue had stronger nitrogen cycling functions, and an increase in the abundance of microorganisms related to the sulfur cycle occurred after day 15 of the experiment. The microbial community in the acidified gangue had more stress resistance than the community of the newly formed gangue, but its potential to decompose environmental pollutants decreased.

An Approach for Monitoring Shallow Surface Outcrop Mining Activities Based on Multisource Satellite Remote Sensing Data

Monitoring mine activities can help management track the status of mineral resource exploration and mine rehabilitation. It is crucial to the sustainable development of the mining industry and the protection of the geological environment in mining areas. To monitor the mining activities of shallow surface outcrops in the arid and semi-arid regions of northwest China, this paper proposes a remote sensing monitoring approach of mining activities based on deep learning and integrated interferometric synthetic aperture radar technique. This approach uses the DeepLabV3-ResNet model to identify and extract the spatial location of the mine patches and then uses object-oriented analysis and spatial analysis methods to optimize the mine patch boundaries. SBAS-InSAR technique is used to obtain the time-series deformation information of the mine patches and is combined with the multi-temporal optical imagery to analyze the mining activities in the study area. The proposed approach has a recognition accuracy of 95.80% for the identification and extraction of mine patches, with an F1-score of 0.727 at the pixel level, and the average area similarity for all patches is 0.78 at the object-oriented level. The proposed approach possesses the capability to analyze mining activities, indicating promising prospects for engineering applications. It provides a reference for monitoring mining activities using multisource satellite remote sensing.

Responses of soil bacterial community structure to different artificially restored forests in open-pit coal mine dumps on the loess plateau, China.

Artificial vegetation restoration is an effective method for improving soil quality. In areas experiencing coal mine subsidence, the microbial community is essential for reconstructing the ecological balance of the soil. Studies are needed to examine how soil microbial community structure respond to different artificial forest restoration types and ages, especially over long-term periods. Therefore, in this study, 10, 20, and 30-year trials were chosen with two restoration types: Pinus tabuliformis (PT) and Ulmus pumila (UP). The objective was to determine how various types and ages of forest restoration affect the structure of soil bacterial communities, as well as the soil environmental factors driving these changes. The results showed that artificial 30-year restoration for both PT and UP can improve soil physical and chemical properties more than restoration after 10 and 20 years. The soil bacterial community structure remarkably differed among the different forest types and restoration ages. The bacterial diversity was higher in UP than in PT; the alpha diversity at longer restoration years (30 and 20) was significantly higher than at 10 years for both PT and UP. Moreover, soil nutrients and pH were the primary soil environmental factors driving bacterial community structure in the PT and UP. Finally, the integrated fertility index (IFI) at 30 years of restoration was considerably higher for PT and UP, and thus, is more beneficial to the restoration of soil after coal mining. Our findings are useful for studying improvement in soil quality and the restoration of the ecological environment in mining areas.

Using silkworm excrement to restore vegetation and soil ecology in heavily contaminated mining soils by multiple metal(loid)s: A recyclable sericulture measure

Ecological restoration of heavily contaminated soils by multiple metal(loid)s in mining areas is very difficult. In this study, we provided an attractive measure of using silkworm excrement (SE) and its modified materials to restore the soil heavily contaminated by arsenic (As), antimony (Sb), cadmium (Cd), lead (Pb) and chromium (Cr). We investigated the adsorption capacities and the associated remediation mechanisms for antimonite [Sb(III)] and antimonate [Sb(V)] by raw SE, biochar–modified SE (BC700), iron–modified BC700 (MBC) and sulfhydryl–modified BC700 (SH). Then, we selected SE and SH to compare their outcomes to restore the vegetations and the soil bacterial communities in the investigated soil mentioned above. The results showed that SE displayed the best characteristics for metal(loid) physical adsorption. But SH conferred the strongest capacity to adsorb Sb (max 23.92 mg g–1), suggesting the process of chemical adsorption played a key role in adsorbing Sb via functional groups (–SH). SE and SH both significantly (1) promoted the growth of pakchoi (Brassica campestris L., New Zealand No.2), community abundance of soil bacteria (283–936 OTUs), and the quantity of bacterial genera correlated with resistance, plant growth promotion and specified carbon metabolism; (2) but reduced bacterial genera correlated with pathogenicity. In this study, we suggested an attractive recyclable measure to restore the disturbed ecological environment in mining areas, i.e, using mulberry to restore the vegetation→ using leaves of mulberry to rear silkworms→ using SE to immobilize metal(loid)s in soils growing mulberry or other plants.

Extraction and monitoring of vegetation coverage based on uncrewed aerial vehicle visible image in a post gold mining area

Vegetation coverage reflects the degree of environmental degradation. Timely and effective monitoring of vegetation conditions is the basis for promoting vegetation protection and improving the ecological environment of mining areas. Exploring vegetation coverage extraction methods and selecting the optimal vegetation index in mining areas can provide scientific reference for estimating vegetation coverage based on vegetation index in mining areas. Uncrewed aerial vehicles (UAVs) are widely used because of their fast real-time performance, high spatial resolution, and easy accessibility. In this study, the performances of nine visible vegetation indices and two threshold segmentation methods for extracting vegetation coverage in a post-gold mining area in the Qinling Mountains were comprehensively compared using visible spectrum UAV images. Of the nine indices, the excess green index (EXG) and visible-band difference vegetation index (VDVI) were the most effective in discriminating between vegetation and non-vegetation by visual interpretation. In addition, the accuracy of the bimodal histogram threshold method in extracting vegetation coverage was higher than that of Otsu’s threshold method. The bimodal histogram threshold method combined with EXG yielded optimal extraction results. Based on optimal methods, the total percentages of fractional vegetation coverage in 2019, 2020, and 2021 were 31.47%, 34.08%, and 42.77%, respectively, indicating that the vegetation in the mining area improved. These results provide valuable guidance for extracting vegetation information and evaluating vegetation restoration in mining areas.

Effects of Vegetation Types on Carbon Cycle Functional Genes in Reclaimed Soil from Open Pit Mines in the Loess Plateau

Vegetation restoration can effectively improve the ecological environment of mining areas, enhance the ecological service function, and promote the carbon sequestration and sink increase in the ecosystem. The soil carbon cycle plays an important role in the biogeochemical cycle. The abundance of functional genes can predict the material cycling potential and metabolic characteristics of soil microorganisms. Previous studies on functional microorganisms have mainly focused on large ecosystems such as farmland, forest, and wetland, but relatively little attention has been paid to complex ecosystems with great anthropogenic interference and special functions, such as mines. Clarifying the succession and driving mechanism of functional microorganisms in reclaimed soil under the guidance of vegetation restoration is helpful to fully explore how functional microorganisms change with the change in abiotic and biotic conditions. Therefore, 25 topsoil samples were collected from grassland (GL), brushland (BL), coniferous forests (CF), broadleaf forests (BF), and mixed coniferous and broadleaf forests (MF) in the reclamation area of the Heidaigou open pit waste dump on the Loess Plateau. The absolute abundance of soil carbon cycle functional genes was determined using real-time fluorescence quantitative PCR to explore the effect of vegetation restoration on the abundance of carbon cycle-related functional genes in soil and its internal mechanism. The results showed that:① the effects of different vegetation restoration types on the chemical properties of reclaimed soil and the abundance of functional genes related to the carbon cycle were significantly different (P<0.05). GL and BL showed significantly better accumulation of soil organic carbon, total nitrogen, and nitrate nitrogen (P<0.05) than that in CF. ② The gene abundance of rbcL, acsA, and mct was the highest among all carbon fixation genes. The abundance of functional genes related to carbon cycle in BF soil was higher than that in other types, which was closely related to the high activity of ammonium nitrogen and BG enzymes and the low activity of readily oxidized organic carbon and urease in BF soil. The functional gene abundance of carbon degradation and methane metabolism was positively correlated with ammonium nitrogen and BG enzyme activity and negatively correlated with organic carbon, total nitrogen, readily oxidized organic carbon, nitrate nitrogen, and urease activity (P<0.05). ③ Different vegetation types could directly affect soil BG enzyme activity or affect soil nitrate nitrogen content, thus indirectly affecting BG enzyme activity, in turn manipulating the abundance of functional genes related to the carbon cycle. This study is helpful to understand the effects of different vegetation restoration types on the functional genes related to the carbon cycle in the soil of mining areas on the Loess Plateau and provides a scientific basis for ecological restoration and ecological carbon sequestration and sink enhancement in mining areas.

Prediction of the spatiotemporal evolution of vegetation cover in the Huainan mining area and quantitative analysis of driving factors.

The prediction of the spatiotemporal dynamic evolution of vegetation cover in the Huainan mining area and the quantitative evaluation of its driving factors are of great significance for protecting and restoring the environment in this area. This study uses the Landsat 5 TM and Landsat 8 OLI time-series data to estimate the vegetation cover and uses the transition matrix to analyze the spatiotemporal transfer of vegetation cover from 1989 to 2004, 2004 to 2021, and 2021 to 2030. In addition, a structural equation model (SEM) was established in this study to assess the driving factors of vegetation cover. The quantitative analysis and the cellular automata (CA)-Markov model were performed to predict the future vegetation cover in the Huainan mining area. The results are as follows: (1) In different periods, the vegetation cover types were mainly high cover types transferred to other vegetation cover types; (2) human activities are the key factors affecting the vegetation growth, while topographical factor is the most influential factor promoting the vegetation growth; (3) highly consistent CA-Markov and multi-criteria evaluation (MCE) predicted results of vegetation cover in 2030 compared to that in 2021. The proportion of bare soil and low cover types had increased significantly, mainly concentrated in the internal area of the mines. The prediction of the spatiotemporal evolution of vegetation cover in the Huainan mining area and the quantitative change in driving factors are of significant importance for the restoration of the environment in mining areas.

Analysis of changes of the vegetation condition on the area of the closed Prosper-Haniel mine in 1984-2021 using multispectral satellite images

Mining processes have a significant impact on the surrounding environment even after the exploitation has ceased. Today a continuous monitoring of post-mining processes in the areas of water management, vegetation and air pollution is important. In the project “Digital Twin – Integrated Geomonitoring” funded by the RAG Stiftung (no.20-0013) and carried out in cooperation with the Geological Survey of North-Rhine Westphalia, scientists are investigating the possibilities of integrating and fusing data from multiple sources (mining and geological maps, in-situ measurements, drone flights and satellite missions). The goal is to understand the causes and phenomena occurring on the Earth’s surface and thus to generate a process understanding. The key issue of this project is geo-monitoring of the environment in mining areas using vegetation indicators. This paper presents an analysis of the vegetation health of the cover for the period 1984-2021 using selected remote sensing indicators: NDVI, GNDVI, SAVI, MSAVI, NDWI and MNDWI. The studies indicate the possibility of long-term spatial-temporal observations of a selected test area in order to observe the impact of post-mining processes in the area of the closed Prosper-Haniel mine.

Environment monitoring of mining area with comprehensive mining ecological index (CMEI): a case study in Xilinhot of Inner Mongolia, China

ABSTRACT The monitoring and evaluation of environmental and ecological status in mining area is critical for effective mineral management guidance, and remote sensing is a cost-effective solution for covering a wide spatial area with high temporal frequency. However, the diverse landscape in mining areas presents a challenge for finding a suitable monitoring method. To address this challenge, this study proposes a remote sensing-based comprehensive mining ecological index (CMEI), which integrates vegetation greenness, soil wetness, urban heat, air quality and water quality indicators obtained from Landsat images and Moderate Resolution Imaging Spectroradiometer (MODIS) products. The integration is achieved through a principal component analysis (PCA) to encapsulate various aspects of the environment in opencast mining areas. The proposed CMEI was then applied to assess the performance of an ecological restoration project carried out in the Xilinhot coalfield in Inner Mongolia, China, over the past two decades. Our findings show that the overall ecological environment in the dumping sites and backfilling sites of Xilinhot coalfield has improved from a score of 0.15 in 2005 to 0.33 in 2020, according to the CMEI. Nevertheless, our study also highlights that some newly established dumping sites require further strengthening of management and maintenance measures. The CMEI presents a novel and effective approach for monitoring and evaluating the ecological environment in mining areas, and it can potentially be applied to assess the ecological environment of opencast mining areas globally.

Effect of soil compaction on hydraulic properties and macropore structure: Evidence from opencast mines in the Loess Plateau of China

Affected by heavy machinery, the soil compaction in the opencast coal mine area is serious, which will change the characteristics of soil macropores, then affect the soil hydraulic properties and damage the ecological environment in mining area. In this study, the disturbed soil samples from the dumping area of Pingshuo opencast coal mine of China were collected. The soil samples were processed in bulk density from 1.30 g·cm−3 to 1.70 g·cm−3, and the soil hydraulic properties were measured, and the soil macropore characteristics were obtained using computerized tomography scanning in laboratory. The path analysis method was applied to analyze the effect of macropore characteristics caused by compaction on soil hydraulic properties. Soil compaction resulted in severe effects on soil hydraulic characteristics and macropore properties. Under same soil suction, the water contents remained in soil decreased with increasing compaction. The explanatory variables (average Euler number (AEN), macropore throat number (MTN), and macropore fractal dimension (MFD)) were main determinants of soil-water characteristic curve (SWCC), and the indirect path coefficient of macroporosity. The effects of AEN and MFD on soil infiltration properties were relatively high. The bulk density of 1.4 g·cm−3 was a critical point of affecting macropore properties then affecting soil hydraulic properties, and some soil reclamation measures should be conducted to make bulk density < 1.4 g·cm−3 for compacted soil in opencast coal mining area. This study provides a basis for selecting technology of land reclamation and the subsequent monitoring and maintenance of soil quality in mining areas.

Stability Monitoring of Goaf Based on Remote Sensing Image

Large scale mining of coal resources is a major factor causing goaf collapse in China. According to the statistics of 21 major coal mining provinces, the area of coal mining surface subsidence is up to 4.5 billion m2, posing a great threat to the regional ecological environment and people's lives and property. The rapid development of remote sensing technology has changed the traditional field survey method and has become one of the important means of environmental monitoring. Information can be obtained not only by photography, but also by scanning. The amount of information obtained by remote sensing far exceeds that obtained by conventional traditional methods. Based on remote sensing images, this paper studies the stability monitoring of coal mine goaf, establishes a ground pressure monitoring network suitable for the actual situation of the mining area, and carries out long-term effective ground pressure monitoring. Through remote sensing images, we can fully grasp and avoid the hazards of the goaf. Remote sensing technology has the characteristics of wide use, large detection range, and rich information acquisition. It can comprehensively obtain the basic information of the mining area environment, and then monitor the mining area environment.