Over the last few years, under the combined effects of climate change and human factors, the ecological environment of coal mining areas has undergone tremendous changes. Therefore, the rapid and accurate quantitative assessments of the temporal and spatial evolution of the ecological environment quality is of great significance for the ecological restoration and development planning of coal mining areas. This study applied the ecological environment index after topographic correction to improve the remote sensing ecological index (RSEI). Based on a series of Landsat images, the ecological environment quality of Yangquan Coal Mine in Shanxi Province from 1987 to 2020 was monitored and evaluated by an improved remote sensing ecological index. The results show that after topographic correction, the topographic effect of the remote sensing ecological index was greatly reduced, and its practicability was improved. From 1987 to 2020, the ecological environment quality of Yangquan Coal Mine was improved, and the mean of the RSEI increased from 0.4294 to 0.6379. The ecological environment quality of the six coal mines in the study area was improved. Among the six coal gangue dumps, the ecological environmental quality of D1, D2, D3, and D4 has improved, and the ecological environment quality of D5 and D6 worsened. The percentages of improved, unchanged, and degraded ecological environment quality in the entire coal mining area were 77.08%, 0.99%, and 21.93%, respectively. The global Moran’s index was between 0.7929 and 0.9057, and it was shown that there was a strong positive correlation between the ecological environmental qualities of the study area, and that its spatial distribution was clustered rather than random. The LISA cluster map showed that the aggregation and dispersion degree of ecological environment quality was mainly high–high clustering and low–low clustering over the whole stage. During the study period, temperature and precipitation had limited impacts on the ecological environment quality of Yangquan Coal Mine, while the coal mining activities and urbanization construction seriously affected the local ecological environment quality and the implementation of ecological restoration policies, regulations, and measures was the main reason for the improvement of the ecological environment quality.

The large-scale development and utilization of coal resources have brought great challenges to the ecological environment of coal-mining areas. Therefore, this paper has used scientific and effective methods to monitor and evaluate whether changes in ecological environment quality in coal-mining areas are helpful to alleviate the contradiction between human and nature and realize the sustainable development of such coal-mining areas. Firstly, in order to quantify the degree of coal dust pollution in coal-mining areas, an index-based coal dust index (ICDI) is proposed. Secondly, based on the pressure-state-response (PSR) framework, a new coal-mine ecological index (CMEI) was established by using the principal component analysis (PCA) method. Finally, the coal-mine ecological index (CMEI) was used to evaluate and detect the temporal and spatial changes of the ecological environment quality of the Ningwu Coalfield from 1987 to 2021. The research shows that ICDI has a strong ability to extract coal dust with an overall accuracy of over 96% and a Kappa coefficient of over 0.9. As a normalized difference index, ICDI can better quantify the pollution degree of coal dust. The effectiveness of CMEI was evaluated by four methods: sample image-based, classification-based, correlation-based, and distance-based. From 1987 to 2021, the ecological environment quality of Ningwu Coalfield was improved, and the mean of CMEI increased by 0.1189. The percentages of improvement and degradation of ecological environment quality were 71.85% and 27.01%, respectively. The areas with obvious degradation were mainly concentrated in coal-mining areas and built-up areas. The ecological environment quality of Pingshuo Coal Mine, Shuonan Coal Mine, Xuangang Coal Mine, and Lanxian Coal Mine also showed improvement. The results of Moran’s Index show that CMEI has a strong positive spatial correlation, and its spatial distribution is clustered rather than random. Coal-mining areas and built-up areas showed low–low clustering (LL), while other areas showed high–high clustering (HH). The utilization and popularization of CMEI provides an important reference for decision makers to formulate ecological protection policies and implement regional coordinated development strategies.

Coal gangue is an inevitable product in coal mining and processing and is the most important source of pollution in mines. Vegetation restoration of coal gangue piles must consider its special site conditions. Therefore, we conducted unmanned air vehicle (UAV) temperature monitoring, field investigation and experimental analysis on spontaneous combustion coal gangue piles in Lu’an mining area. In the vegetation construction of coal gangue piles, high-temperature stress affects plant survival. The spontaneous combustion coal gangue piles have abnormal temperature, high surface temperature and few vegetation types. The plant community species diversity index (Shannon–Wiener index, Pielou’s index and Species abundance index) is small, the plant community is single and the plant diversity is low. Spontaneous combustion of coal gangue leads to soil acidification, reducing soil water content, soil organic carbon (SOM), available nitrogen (AN), available potassium (AK) and available phosphorus (AP). These factors are single or interactive in plants and have an impact on plant survival and growth. The research results are of great significance to the vegetation restoration of spontaneous combustion coal gangue piles, ecological reconstruction and the improvement of the ecological environment of coal mine areas.

Coal gangue is a solid waste emitted during coal production. Coal gangue is deployed adjacent to mining land and has characteristics similar to those of the soils of these areas. Coal gangue–soil ecosystems provide habitats for a rich and active bacterial community. However, co-existence networks and the functionality of soil and coal gangue bacterial communities have not been studied. Here, we performed Illumina MiSeq high-throughput sequencing, symbiotic network and statistical analyses, and microbial phenotype prediction to study the microbial community in coal gangue and soil samples from Shanxi Province, China. In general, the structural difference between the bacterial communities in coal gangue and soil was large, indicating that interactions between soil and coal gangue are limited but not absent. The bacterial community exhibited a significant symbiosis network in soil and coal gangue. The co-occurrence network was primarily formed by Proteobacteria, Firmicutes, and Actinobacteria. In addition, BugBase microbiome phenotype predictions and PICRUSt bacterial functional potential predictions showed that transcription regulators represented the highest functional category of symbiotic bacteria in soil and coal gangue. Proteobacteria played an important role in various processes such as mobile element pathogenicity, oxidative stress tolerance, and biofilm formation. In general, this work provides a theoretical basis and data support for the in situ remediation of acidified coal gangue hills based on microbiological methods.

Technical challenges associated with drainage and filling efficacy confront the Yellow River sediment filling reclamation, a novel approach to reclaiming coal-mined subsided lands. This study proposes an improved geotextile performance evaluation method to address the shortcomings of current geotextile screening methodologies in the drainage of the Yellow River sediment. This method comprehensively considers essential characteristics under working conditions, such as permeability, soil conservation, and blockage prevention properties, including indicators such as the permeability coefficient and sediment retention rate of geotextiles under pressure. Indoor flume filling and drainage experiments were implemented to verify the efficacy of geotextile drainage. The improved method identified thermal-bonded nonwoven geotextiles of 200 and 250 g·m⁻² as having the highest comprehensive evaluation scores. The experimental results showed that these geotextiles significantly improved their drainage efficiency and better met the specific requirements of the Yellow River sediment filling reclamation. Traditional screening methods may be unsuitable for sediment drainage conditions, necessitating sediment interception and rapid drainage due to the streaming water–sediment mixture. Therefore, the newly established performance evaluation method is more appropriate for the specific requirements. It is recommended that a simple vibrating device be installed to maintain 20 vibrations per minute to keep drainage channels clear and provide stable drainage performance in engineering applications.