Explore the vast range of titles available.

The development of green mines is essential for promoting sustainability in the mining sector due to the significant ecological impacts of resource extraction. This study proposes a novel hybrid multi-criteria decision-making (MCDM) framework that integrates Spherical Fuzzy Sets (SFSs) with SWOT analysis, the CRITIC method, and Grey Relational Analysis (GRA). The framework introduces several innovations: it applies SFS-based MCDM for the first time to green mine evaluation in Egypt, structures 37 sustainability-related criteria under SWOT dimensions, and employs SF-CRITIC for objective weighting without subjective comparisons. The model is applied to assess 20 gold mines, where the SF-GRA method is used to rank alternatives based on proximity to an ideal solution. The results show that GME20 consistently ranks highest, while GME5 ranks lowest. A sensitivity analysis is conducted by varying the Grey relational coefficient and simulating 37 weight scenarios, demonstrating stable rankings and strong model resilience. Comparative analysis against ten SFS-based MCDM methods confirms the consistency of results, with Spearman correlation coefficients exceeding 0.77. In addition to its methodological novelty, the framework supports interpretable decision outcomes by identifying key sustainability drivers such as renewable energy adoption and land reclamation. This contributes actionable insights for policymakers and stakeholders, enabling informed green investment and regulatory decisions. The study offers a transparent, reproducible, and scalable tool for sustainability evaluation in resource-intensive industries. The proposed model introduces a structured integration of SWOT-based criteria classification, objective weight computation via SF-CRITIC, and robust alternative ranking using SF-GRA. Furthermore, it contributes uniquely by applying the methodology to the underexplored context of green mine evaluation in Egypt. These distinctions articulate the methodological and application-based novelties of the proposed framework.

The idea of green mining was proposed as a practical approach to make the mining industry more sustainable than before. Green mining is a contemporary mining model centered on the sustainability of resources, environment, and socio-economic benefits. Its purpose is to develop and apply technologies and processes that increase environmental performance while maintaining competitiveness throughout the entire mining cycle from exploration to post-closure. Although the green mining strategy has achieved considerable significance, there is still a considerable gap between its research and practice. This study evaluates the situation of green mine construction in China and suggests a future framework. First, based on the Driver–Pressure–State–Impact–Response model, an evaluation index system composed of 20 indicators was established. The principal component analysis was used to analyze the data collected from mines situated in Yongcheng, China. The results show that the construction of green mines has improved significantly over the years. Energy consumption and pollutant emissions were minimized, the protection of the ecological environment was realized, and secondary processing of mining waste was practiced. However, there are still some unresolved problems, such as the utilization of solid waste, the recovery ratio from ore processing, and the reuse ratio of coal washing water. Thus, the strategic framework has been proposed for improving green mine construction and the sustainability of the mining industry.

Assessing Mine Emergency Rescue Capability (MERC) is critical for ensuring mining safety and advancing sustainable development. However, existing MERC assessments often lack a holistic sustainability perspective. To bridge this gap, this study develops a MERC assessment model grounded in the Triple Bottom Line (TBL) framework, integrating the relative difference function (RDF) to address the fuzziness and subjectivity in evaluation processes. A hierarchical indicator system is constructed, comprising 5 primary factors and 25 sub-indicators across environmental, economic, and social dimensions, reflecting both immediate rescue effectiveness and long-term sustainability performance. Indicator weights are derived from a hybrid approach that combines the subjective G1 method with the objective entropy weight method. RDF is employed to compute membership degrees, and the final MERC level is determined by level characteristic values. The model is validated through an empirical study of six green mines in China. Results demonstrate robust performance and consistency with alternative methods and reveal the environmental dimension as the dominant driver within the TBL framework. This finding supports the ecology-first principle of green mining and underscores the alignment of high-level emergency preparedness with sustainable development objectives. By explicitly embedding sustainability principles into safety assessment, the proposed model provides a scientifically grounded tool to guide the green transformation of the mining industry. Future work will adapt the model to diverse mining contexts and refine the indicators to better support global sustainability goals.

Greenhouse gas (GHG) emissions related to human activities have significantly caused climate change since the Industrial Revolution. China aims to achieve its carbon emission peak before 2030 and carbon neutrality before 2060. Accordingly, this paper reviews and discusses technical strategies to achieve the “dual carbon” targets in China’s metal mines. First, global carbon emissions and emission intensities from metal mining industries are analyzed. The metal mining status and carbon emissions in China are then examined. Furthermore, advanced technologies for carbon mitigation and carbon sequestration in metal mines are reviewed. Finally, a technical roadmap for achieving carbon neutrality in China’s metal mines is proposed. Findings show that some international mining giants have already achieved their carbon reduction targets and planned to achieve carbon neutrality by 2050. Moreover, improving mining efficiency by developing advanced technologies and replacing fossil fuel with renewable energy are two key approaches in reducing GHG emissions. Green mines can significantly benefit from the carbon neutrality process for metal mines through the carbon absorption of reclamation vegetations. Geothermal energy extraction from operating and abandoned metal mines is a promising technology for providing clean energy and contributing to the carbon neutrality target of China’s metal mines. Carbon sequestration in mine backfills and tailings through mineral carbonation has the potential to permanently and safely store carbon dioxide, which can eventually make the metal mining industry carbon neutral or even carbon negative.

From a commercial viewpoint, mine methane is the most promising object in the field of reducing emissions of climate-active gases due to circular waste management. Therefore, the task of this research is to estimate the technogenic reservoirs resources of mine methane when implementing the circular waste management concept. The novelty of the authors’ approach lies in reconstructing the response space for the dynamics of methane release from the front and cross projections: CH4 = ƒ(S; t) and CH4 = ƒ(S; L), respectively. The research established a polynomial dependence of nonlinear changes in methane concentrations in the mixture extracted by type 4 wells when a massif is undermined as a result of mining in a full-retreat panel. And the distance from the face to the start of mining the panel is reduced by 220 m. For this reason, the emission of mine methane, in case of degasification network disruption in 15 days, can amount to more than 660 thousand m3 only for wells of type no. 4.

In this paper, a method of mathematical modeling for solving the problem of reusing man-made waste from mining and the processing of ores is proposed. The use of intermediate products (man-made waste: tailings of processing plants, rocks from sinking operations and the technical water of mine drainage) in cyclic production presupposes their use as fill material components and placement in the mined-out voids of underground mines. The influence of mining factors on the fill material composition and the parameters of the created fill mass is justified. The results of a practical implementation of the proposed mathematical model are presented, and an algorithm is compiled. Deformation changes and stress concentration are key criteria in the proposed mathematical model. The proposed algorithm allows for the determination of the preferred system of deposit development, and the selection of its parameters and the fill material composition.

The utilization of coalbed methane (CBM) resources in closed coal mines is crucial for energy transition and green low-carbon development. This study systematically analyzed geological factors, CBM reserves, and economic factors to evaluate the potential of CBM extraction from the Songzao mining area of Chongqing. An evaluation indicator system was established, comprising 3 primary indicators, 13 secondary indicators, and 5 closed coal mines as the scheme layer. This system facilitated accurate quantification of feasibility evaluation weights for CBM extraction under complex geological conditions. The game theory was employed to refine the integration of subjective and objective weights, which ensured the objectivity and accuracy of the evaluation results. A feasibility evaluation model for CBM extraction from goafs in closed coal mines was constructed using the TOPSIS method, with results ranked as follows: Songzao coal mine > Fengchun coal mine > Shihao coal mine > Yuyang coal mine > Datong No. 1 coal mine. Furthermore, the trends in energy conservation and emission reduction benefits over the past eight years since the closure of the Songzao coal mine were analyzed, encompassing both CBM emissions and power generation. The findings highlight the necessity of CBM extraction from goafs in closed coal mines in China and demonstrate the significant potential of CBM resource development for reducing greenhouse gas emissions and promoting clean energy alternatives, providing a reference for theoretical research and practice.

Green mining (GM) can achieve the harmonious development of mineral resource exploitation and environmental protection. Performance evaluation is the key to promoting GM. This research explores favorable methods to evaluate the green mining performance (GMP) of underground gold mines. First, according to the specific characteristics of underground gold mines, an evaluation criteria system for GM is formulated. Meanwhile, the weights are calculated using an integrated gray DEMATEL and ANP technique, which considers the correlation between indicators. Subsequently, the solution methodology for performance evaluation is proposed based on normalization of indicators. Finally, six underground gold mines are utilized as case studies to verify the methodological feasibility. The results of the empirical study show that there is a significant gap between ordinary mines and pilot green mines, and this study, via comparison analysis and cause–effect analysis, gives direction for mines improvement. Not only will the work provide technical and theoretical support for the evaluation and construction of similar green mines, it will also serve as a reference for government policy implementation.

Nowadays, underground coal mine accidents occur frequently, causing huge casualties and economic losses, most of which are gas explosion accidents caused by fires. In order to improve the emergency rescue capability of coal mine fires and reduce the losses caused by coal mine fires, this article is dedicated to the assessment of coal mine fire rescue capability. Taking the fire emergency rescue system of Lugou mine as an example, based on the introduction of gray system theory and gray evaluation method, an evaluation model was established to assess the risk of the fire emergency rescue index system of Lugou mine. Four primary and 19 secondary indicators were delineated, and a hierarchical structure model of the fire emergency rescue capability of the Lugou mine was established by combining expert opinions, and the weights of indicators at all levels were calculated by using hierarchical analysis. We then used the gray system evaluation method and expert scoring to judge the safety level of various indicator factors in the index system. The evaluation results show that the risk level of the emergency rescue system of the Lugou mine fire is higher than the fourth level. The main risk indicator factors are firefighting equipment, decision-making command, emergency education and training, and fire accident alarm. In response to this evaluation result, corresponding control measures were formulated in four aspects: rescue organization guarantee, personnel guarantee, material guarantee, and information guarantee, which optimally improved the emergency rescue capability of the Lugou mine fire and reduced the loss caused by fire.

Open-pit mining seriously damages the original vegetation community and soil layer and disturbs the carbon cycle of vegetation and soil, causing instability in the mining ecosystem and decrease in the carbon sequestration capacity of the mining area. With the deepening of environmental awareness and the influence of related policies, the ecological restoration of open-pit mines has been promoted. The mining ecosystem is distinct owing to the disperse distribution of mines and small scale of single mines. However, the carbon sequestration capability of mines after ecological restoration has not been clearly evaluated. Therefore, this study evaluated the carbon sequestration capacity of restoration mines, taking the mines of the Yangtze River Basin in Jurong City, Jiangsu Province as the research objects. Firstly, the visual effects of the vegetation and soil in their current status were determined through field investigation, the methods for sampling and data collection for the vegetation and soil were selected, and the specific laboratory tests such as the vegetation carbon content and soil organic carbon were clarified. Meanwhile, the evaluation system consisting of three aspects and nine evaluation indexes was established by using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE). The process of evaluation included the following: the establishment of the judgment matrix, calculation of the index weight, determination of the membership function, and establishment of the fuzzy membership matrix. Finally, the evaluation results of the restoration mines were determined with the ‘excellent, good, normal and poor’ grade classification according to the evaluation standards for each index proposed considering the data of the field investigation and laboratory tests. The results indicated that (1) the evaluation results of the mines’ carbon sequestration capacity were of excellent and good grade at a proportion of 62.5% and 37.5%, which was in line with the field investigation results and demonstrated the carbon sequestration capacity of all the restored mines was effectively improved; and (2) the weights of the criterion layer were ranked as system stability > vegetation > soil with the largest value of 0.547, indicating the stability of the system is the main factor in the carbon sequestration capacity of the mines and the sustainability of the vegetation community and the stability of soil fixation on the slope. The proposed evaluation system effectively evaluates the short-term carbon sequestration capability of the restoration mining system according to the visual effects and the laboratory testing results, objectively reflecting the carbon sequestration capacity via qualitative assessment and quantitative analysis. The evaluation method is relatively applicable and reliable for restoration mines and can provide a reference for similar ecological restoration engineering.