Green Mining Research Articles

Construction Practices of Green Mines in China

To maintain high-level economic development, protect the ecological environment, and achieve carbon peaking and carbon neutrality goals, the construction of green mines has become a critical issue in China. In this study, the importance of mineral resources to human society is discussed, and the construction experiences and sustainable development directions of green mines are summarized, which can provide valuable references for the global mining industry. The entry and management process in China was introduced to help understand green mines’ construction objectives and tasks. Moreover, based on the successful construction cases of green mines, four typical green mine models are concluded: the green technology mining model, operation modernization mining model, stability mining model, and ecological restoration mining model. In addition, the key construction elements of green mines are concluded, for example, the mining environment, mining methods, comprehensive utilization of resources, energy conservation, emission reduction, scientific and technological innovation and intelligence, and enterprise-land stability, which provided the directions and guidance for green mine construction.

Thoughts on green mine construction of sand and gravel industry in China

Green mine construction is an essential manifestation of ecological civilization in the mining industry. The green mine construction of China’s sand and gravel industry has five significant progress as follows. First, the standard system for Green Mine Construction in the sand and gravel industry has been established. Second, large-scale and intensive sand and gravel production promotes sand and gravel supply-side reform. Third, the green industrial chain of sand and gravel has been extended. Fourth, a circular economy fosters resource conservation. Fifth, “Mine restoration+” has become a new development trend. On this basis, this article summarizes three development characteristics and proposes five policy recommendations, aiming to provide Chinese cases for promoting green mining construction globally.

Assessing the progress of the mining industry towards green growth in China: A three-stage dynamic network slacks-based measure approach

Promoting green growth in the mining sector requires efficient use of mineral resources, improving economic operations' quality and performance and strengthening ecological and environmental governance. Local economies face different and conflicting plans, along with potential implementation constraints, while implementing green growth initiatives. Efficiency in mining green growth is a crucial aspect to monitor the progress of China's local mining industry in the future. This paper presents a framework for three-stage network structure evaluation of mining industry's green growth efficacy. A dynamic network model, using Slacks-Based Measure (SBM) approach, analyzes the green growth of the mining industry in 21 Chinese provinces between 2005 and 2019. The Malmquist index is used to analyze the dynamic patterns and endogeneity of mining green growth efficiency. The results show that the efficiency of most provinces exhibited a decrease before rebounding during the observation period. Overall efficiency is strongly correlated with improved eco-performance, which is a result of green mining. There are substantial discrepancies in the pace and extent of green growth across different provinces, with a few boasting growth rates exceeding 25% annually. Eastern provinces, particularly Hubei, Fujian, and Shandong, demonstrate impressive trends and substantial potential. However, the unsatisfactory situation in the Northeast and Xinjiang regions persists. Their lack of effectiveness can be attributed to various sub-processes.

Environmental risk of ion-absorbed rare earth ores: concentration of leaching agent and fractionation of Pb.

Rare earth (RE) is an important strategic resource; however, there has been a growing concern about the environmental problems caused by RE mining, such as ammonia nitrogen pollution and heavy metal pollution. There is a limited research about the behavior of leaching agents and the fractionation of RE and heavy metal during the mining process for ion adsorption of rare earth ore (IRE-ore) in the previously available papers. In this study, (NH4)2SO4 solution, which commonly used in the production of mining IRE-ore, was used as a leaching agent. The adsorption behavior of ore soils on ammonium ions was explored by batch experiments. The adsorption process of IRE-ore on ammonium ions followed a pseudo-second-order equation and was controlled by the kinetics of surface adsorption and intra-particle diffusion; the ammonium ion adsorption isotherm conformed to the Freundlich isotherm equilibrium equation, and the higher concentration advantage made the ore soils possess a higher adsorption capacity of ammonium ion. In addition, the fractionation characteristics of lanthanum (La), cerium (Ce), and lead (Pb) in the ore soil during the leaching process were simulated based on the batch and column leaching experiments. The results demonstrated that the exchangeable states of La and Ce in IRE-ore were high, and the exchangeable, carbonate-bound La and Ce were almost all leached out by (NH4)2SO4 leaching agent, while the most of exchangeable Pb flowed out along with leaching agent, and a small amount of leached Pb in the ore soil was converted to iron and manganese oxide-bound Pb and enriched in the direction of migration of the leaching solution, and when the environment (e.g., pH and Eh) changed, this part of Pb may be re-activated. Our research might serve as crucial baseline knowledge for the adsorption of ammonium ions by ore soils, and provide a data reference for reducing the use of leaching agents and developing sustainable technologies for green mining of ion-adsorption RE ores.

Mineral resource sustainability in the face of the resource exploitation and green recovery: Challenges and solutions

China's mining sector faces a pressing need to align profitability with eco-friendly resource extraction for sustainable development. Our study delves into the pivotal role of Renewable Energy Technology Innovation (RETI) in enhancing resource efficiency within this context. Analyzing data spanning 40 Chinese regions from 2000 to 2021, our research uncovers notable regional variations in RETI's impact on mineral resource sustainability. Rigorous validation measures, including addressing outliers and utilizing instrumental variable techniques, ensure the robustness of our findings. Specifically, RETI emerges as a catalyst for improving green mining resource efficiency in the Midwest and West regions but exhibits no parallel effect in the East. Crucially, the influence of RETI is intricately tied to changes in economic and human capital, offering valuable insights to expedite its adoption and optimize mineral asset sustainability in China's mining sector. This research contributes essential perspectives to propel the sector toward environmentally conscious practices and underscores the significance of adapting to cleaner energy sources for long-term viability.

Evaluation and quantitative characterization for the ecological environment impact of open pit mining on vegetation destruction from landsat time series: A case study of Wulishan limestone mine

Quantitatively evaluating the ecological environment impacts of vegetation destruction due to open-pit mining activities is vital for enhancing the green mining standard and cost management capabilities of mining enterprises. Based on the Landsat time series, this study proposes an ecological environment impact assessment and quantitative characterization method for vegetation destruction in mining areas resulting from open-pit mining activities. First, the modified normalized difference water index and the normalized difference vegetation index time series data were calculated. The water body thresholds and the fraction of vegetation coverage were ascertained using the K-means clustering algorithm and the dimidiate pixel model, respectively, to determine the area of direct vegetation destruction in mining areas. Second, utilizing the Theil-Sen Median trend analysis and the Mann-Kendall test, the indirect impact area of vegetation in the mining region was identified. Lastly, by integrating vegetation's net primary productivity with the Chinese Emission Allowance price index, the total carbon emission cost of vegetation destruction due to mining activities over 20 years was calculated to be about 2.122 million yuan. The findings indicated that the ecological environmental impact of open-pit mining activities on vegetation destruction cannot be ignored. From 2000 to 2020, open-pit mining at the Wulishan limestone mine in Anhui Province, China, increased the area of direct vegetation destruction by 9.072 × 105 m2, and the indirect impact area on vegetation was 7.371 × 105 m2. The carbon emission cost of vegetation destruction in the direct destruction area was about 104,000 yuan per year, and the carbon emission cost of vegetation damage in the indirect impact area was approximately 2,082.53 yuan per year. This research provides a scientific foundation for ecological environmental protection, regulations, green mining, and cost management for mining enterprises, promoting the harmonious progress of both the economy and environmental protection.

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.

Effect of injecting inert gas at different spontaneous combustion stages on active groups in coal

Inert gas injection into the mine gob where coal spontaneous combustion occurs can effectively avoid the loss of coal resources, reduce greenhouse gas emissions and realize the green and sustainable mining of coal resources. In this paper, a continuous process of abruptly changing coal from an oxygenated atmosphere to an inert atmosphere in one experiment was realized by a gas atmosphere conversion device, and the effect of inert gas injection on reactive groups in coal at different stages of oxidation was studied based on electron spin resonance technique and spectral peak splitting fitting technique. The experimental results show that the g factor of lignite decreases slowly and then increases with the rising temperature under dry air, and the g factor turning point temperature is 80 °C. The concentration of radicals in lignite increases continuously with rising temperature. The injection of N2 and CO2 at 130 °C has the most significant inhibitory effect on the g factor of coal, with 41.61 % and 65.11 %, respectively. After injecting N2 and CO2 at different stages, the radical concentration of coal suddenly decreases and then continues to increase with the extension of constant temperature time, and the injection of N2 and CO2 at 130 °C has the most significant inhibitory effect on the radical concentration of coal, 28.35 % and 35.44 %, respectively. The radicals in coal can be classified into oxygen-containing radicals, aliphatic radicals, simple aromatic radicals, and π- or σ-type oxygen-containing radicals by the spectroscopic peak splitting technique. The injection of inert gas produces a significant inhibition effect on oxygen-containing radicals in coal. And finally, the inhibition pathway of inert gas on oxygen-containing radicals in coal was revealed from the perspective of radical reaction.

Rheological and mechanical performance analysis and proportion optimization of cemented gangue backfill materials based on response surface methodology.

Cemented backfill mining is a green mining method that enhances the coal mining rate and the safety of mined-out regions. To transport the cemented gangue backfill material (CGBM) into the mined-out regions, it is essential to ensure high flowability and adequate compressive strength after hardening. Based on the response surface methodology (RSM), 29 experiments were conducted in this paper to test the yield stress and plastic viscosity of CGBM slurry. Cubic specimens with dimensions of 100mm were prepared and underwent uniaxial compression tests to obtain the compressive strength at a curing age of 28days. Quadratic polynomial regression models were established for yield stress, plastic viscosity, and compressive strength to explore the effects of fly ash content, water-cement ratio, mass concentration, and superplasticizer dosage on the properties of CGBM. Multi-objective optimization was conducted to determine the optimal material proportion of CGBM. The research results indicate that (1) the mass concentration most profoundly affected the yield stress and plastic viscosity of CGBM, and it increased with an increase in mass concentration. Fly ash content had an inverse relationship with compressive strength. Superplasticizer was found to improve the flowability and strength of CGBM. (2) The established response surface model could reflect the relationship between CGBM's material proportion and rheological and mechanical properties, and predict relevant parameters. (3) Multi-objective optimization determined the optimal proportion of CGBM to be 80% fly ash content, 54% water-cement ratio, 79% mass concentration, and 3% superplasticizer dosage. The research findings offer valuable guidance to mining backfill engineering.

Influence law and control mechanism of overburden isolated grout injection on methane emission in the working face

Overburden isolated grout injection (OIGI) can well reduce surface subsidence, waste emission, and coal resource waste while preserving the ecological integrity of mining areas, thereby becoming the development direction of green coal mining in the future. However, its influence law and control mechanism on methane emission under coal seam mining remain unclear. In light of this, data including methane emission and surface subsidence during the mining of the 22301 working face in Tunlan Mine was collected by on-site measurements through online methane extraction monitoring systems, leveling instruments, and electronic total stations. The collected data and geological information were subject to numerical simulation and theoretical analysis to explore the methane emission law and its controlling factors after OIGI. The results demonstrate the following: (1) The total methane emission decreases by 46% after the implementation of OIGI, primarily due to reduced methane emission from the adjacent seams into the mining coal seam. (2) After OIGI, the vertical stress on the coal and rock strata in goaf rises, while the stress on the surrounding coal pillars decreases; the stress in the whole stope tends to be distributed more uniformly. (3) A relationship between the overburden stress and permeability was established, which reveals that stress plays a major role in controlling methane emission from adjacent seams into the goaf. After OIGI, the rising stress on the overburden above the goaf reduces the porosity and permeability, narrowing methane migration pathways, consequently reducing the volume of methane emission from surrounding seams into the coal seam. Stress redistribution after mining gives rise to methane rivers and low-permeability walls around the goaf, the volumes of which decrease as the grouting pressure rises. Methane rivers are where methane accumulates, and pre-drainage boreholes from adjacent seams should be directed towards these methane rivers to achieve enhanced methane extraction. The conclusions of this study provide theoretical support for efficient methane extraction under OIGI mining.

Recycling waste tyre polymer for production of fibre reinforced cemented tailings backfill in green mining

The increasing amount of solid waste, e.g., waste tyres from car industry and tailings from mine operations, causes substantial environmental and societal issues. The recycled tyre polymer fibre (RTPF) reinforced cemented tailings backfill (CTB) is a kind of composite that can treat waste tyres and tailings simultaneously and realize green mining, but its engineering properties have not been well understood. In this study, the rheology (i.e., static and dynamic yield stress, and structural build-up), strength (i.e., uniaxial and triaxial compressive, splitting tensile and flexural strengths), microstructure, and life cycle of RTPF reinforced CTB are comprehensively evaluated. For comparison, the engineering performance of the commonly used polypropylene fibre (PPF) reinforced CTB in mines is tested. The experimental results demonstrate that incorporating 0.6 wt% RTPF into CTB can achieve comparable fluidity and strength to the CTB reinforced with 0.3 wt% PPF at reduced cost and improved sustainability. A strength enhancement approach for RTPF reinforced CTB is also developed by adjusting the viscosity of suspending CTB before the addition of RTPF. With this approach, the splitting tensile strength increases by 68 %. The results obtained from this study pave the way for promoting the recycling of abandoned waste tyres and the safe design of backfill structures in mines.

A hybrid multi-criteria decision-making framework of EWM-BWM-TODIM based on Linguistic Pythagorean fuzzy environment

Linguistic Pythagorean fuzzy set (LPFS) combines Pythagorean fuzzy sets and linguistic term sets, which can effectively deal with fuzzy information in multi-criteria decision-making (MCDM). The entropy weight method (EWM) can reflect the objectivity of decision information, while the best-worst method (BWM) can reflect the subjectivity of decision-makers. The interactive multi-criteria decision-making (TODIM) method can describe the different preferences of decision-makers for gains and losses. In this paper, EWM, BWM, and TODIM are combined and applied to LPFS for the first time. First, we calculate the objective weight and subjective weight of each criterion through EWM and BWM and combine them to get the final weight to balance subjectivity and objectivity. Then, this paper selects the best scheme through TODIM sorting. In conclusion, the LPFS-EWM-BWM-TODIM model is established in this paper. Finally, the paper applies this model to the selection of corporate investment strategy and green mine, verifies the effectiveness of the method, and carries out comparative analysis and sensitivity analysis, proving the rationality and robustness of the model.

Stope Structural Parameters Design towards Green and Deep Mining: A Review

A reliable design of stopes is critical to ensure both safety and efficiency in mining operations. The evolving mining methods and technologies as well as increasing mining depth dictate the need to continually improve stope designs. This paper presents a comprehensive review in order to compare and consolidate various stope design methods. This review covers various aspects of stope design, including design principles, factors to consider, and the diverse range of design methods available. The results led to the classification of various methods encompassing engineering analogies, fundamentals, numerical simulations, and industrial tests. Of particular significance, the review furnishes detailed insights into the research conducted on each method, as well as each method’s practical performance in engineering applications. Furthermore, the review highlights the inherent limitations in current design methods and suggests potential avenues for future research. Finally, by comprehensively considering the functional roles and advantages of each design method, it overcomes the limitations of relying solely on a single method for stope structural parameter design, and a general process is proposed.

Construction of copper-based core-shell composite for efficient removal of xanthate from wastewater

As the most widely used flotation agent in mineral processing, xanthate in flotation wastewater causes significant damage to the environment and is a major obstacle to the construction of green mines. It is of great urgency to develop a low-cost, easy-to-separate and high-efficient adsorbent to remove xanthate from flotation wastewater. In this study, novel copper-based core-shell adsorbents with a large particle size are prepared by the hydrothermal crystallization-surface replacement method for xanthate removal. The as-prepared adsorbents were characterized by XRD, SEM-EDS, TEM, N2 adsorption-desorption, FTIR, XPS analyses. Because of the larger specific surface area and higher Cu element content on surface, CuO-based adsorbent (CuA-2) possesses a higher adsorption capacity and faster adsorption rate of potassium ethyl xanthate (KEX) when compared with Cu4(NO3)2(OH)6-based adsorbents (CuA-1). The removal percentage of 99% KEX can be obtained by adjusting dosage and the adsorption capacity is reduced by increasing solution pH due to the electrostatic repulsion. The maximum adsorption capacity of CuA-1 and CuA-2 are 645 and 1128 mg·g−1, respectively. The adsorption kinetic can be described by the pseudo-second-order model while the Langmuir adsorption isotherm is in good agreement with experimental results. EX- anion adsorbs and precipitates on the adsorbent in the form of flakes. A strong chemisorption of EX- anion occurs on the adsorbent surface, generating the Cu-xanthate complex. Moreover, the possible adsorption mechanism of KEX is proposed. The novel copper-based core-shell adsorbents show a promising application prospect in the treatment of flotation wastewater.

A model based on the evolutionary game theory for implementing green mining principles in riverine sand and gravel resources

An evolutionary Game Theory (GT) model was presented to study the dynamics between the mine management and government for implementing Green Mining (GM) principles in riverine sand and gravel mines. In this regard, a game was planned in which the mine management is the executing agent, while the government acts as the supervisor. Investigating the performance of the proposed model, regulatory factors such as governmental incentives and penalties were introduced. In order to compare the results, the effects of regulatory measures on strategy changes by mine management were analyzed into two distinct scenarios: classical GT and evolutionary GT, which provide valuable insights into the complex interactions between mine management and government. The Shahed sand and gravel mine near the Kordan River in Alborz province, Iran, was selected as a case study to validate the developed GT models. The results obtained from the classical GT model showed that a fine of $ 0.2 per tonne and a 30% governmental incentive for the mining and equipment costs, may encourage the mine management to choose the GM strategy. Conversely, the results of the evolutionary GT model indicated that by increasing the government subsidy from 30% to 50%, the rate of encouraging the mine management to choose the GM strategy could be accelerated. This situation is similar to the government incentive for mine management in case of fines from $0.2 to $1 per tonne. According to the results of the evolutionary GT model, when the population ratio increases over time, the selected strategy is more compatible and powerful compared to other ones. Therefore, it is concluded that the mine management in Shahed mine may turn to the GM strategy by imposing a penalty more than $0.6 per tonne.

Green Mining: Environmental Ethics in Mining Engineering

Green mining, an evolving paradigm within mining engineering, is driven by a commitment to environmental ethics and sustainability. This article explores the principles, benefits, and challenges associated with green mining, presenting a comprehensive view of its potential transformation of the mining industry. Traditional mining practices have historically resulted in habitat destruction, air and water pollution, and other environmental challenges. However, green mining principles emphasize resource efficiency, minimal environmental disturbance, responsible waste management, and social responsibility. The adoption of these principles promises numerous advantages, including environmental conservation, reduced carbon footprint, economic efficiency, and long-term sustainability. Despite various challenges, such as economic pressures and regulatory hurdles, the transition to green mining is gaining momentum. This shift embodies an ethical imperative and a practical approach to ensuring responsible resource extraction while preserving the planet's delicate ecosystems and the well-being of local communities.

A Multi-Criteria Decision Intelligence Framework to Predict Fire Danger Ratings in Underground Engineering Structures

A wide variety of natural catastrophes are induced by coal mining, with fire hazard being one of the most significant threats to underground engineering structures. In recent years, there has been an alarming rise in mine fire accidents due to the abundance of coal deposits around the world. Underground fires and explosions have continuously been the primary reason for a significant proportion of deaths and the destruction of infrastructure over the last few decades. Underground mining fires deplete natural coal resources, have an adverse impact on the environment by releasing hazardous chemicals and greenhouse gases into the atmosphere, and cause subsidence due to coal depletion during the combustion process. This study aims to predict fire danger rating of underground mining production processes by using the application of state-of-the-art unsupervised and supervised machine learning techniques. The developed k-nearest-neighbors-based isometric feature mapping and fuzzy c-means clustering algorithm has shown its dependability and superiority with a higher accuracy and has been advantageous to the monitoring and prevention of fire danger in underground mining production processes. The proposed multi-criteria decision intelligence framework permits early fire detection, providing the emergency response team extra time to respond the critical situations in order to prevent the fire from spreading, hence promoting sustainable, green, climate-smart, environmentally friendly and safe mining engineering operations.

A novel approach to forecast dust concentration in open pit mines by integrating meteorological parameters and production intensity.

Mine dust pollution poses a hindrance to achieving green and climate-smart mining. This paper uses weather forecast data and mine production intensity data as model inputs to develop a novel model for forecasting daily dust concentration values in open pit mines by employing and integrating multiple machine learning techniques. The results show that the forecast model exhibits high accuracy, with a Pearson correlation coefficient exceeding 0.87. The PM2.5 forecast model performs best, followed by the total suspended particle and PM10 models. The inclusion of production intensity significantly enhances model performance. Total column water vapor exerts the most significant impact on the model's predictive performance, while the impacts of rock production and coal production are also notable. The proposed daily forecast model leverages production intensity data to predict future dust concentrations accurately. This tool offers valuable insights for optimizing mine design parameters, enabling informed decisions based on real-time forecasts. It effectively prevents severe pollution in the mining area while maximizing the use of natural meteorological conditions for effective dust removal and diffusion.

Analysis of Carbon Sequestration Effects in Green Mining Construction

This article underscores the significance of the mining industry while acknowledging the detrimental environmental and social repercussions typically associated with conventional mining practices. This paper introduces the transformative concept of green mining construction, which seeks to seamlessly merge the mining sector with environmental stewardship, social responsibility, and economic viability. The article highlights that the adoption of sustainable strategies within green mining construction can amplify carbon sequestration effects, concurrently curbing carbon emissions and bolstering carbon absorption and storage within ecosystems. This holistic approach serves as a potent weapon against climate change, safeguarding the environment, and propelling progress towards sustainable development goals.

Influencing factors of coal elastic parameters based on the generalized Gassmann equation: A case study in Yuwang colliery, eastern Yunnan province

AbstractCoal elastic parameters are an important index reflecting the material composition and porosity, which can be used to guide reservoir evaluation and the safe mining of coal and coalbed methane. In this study, coal samples collected from coal seams #2, #3, #7 + 8 and #9 in the Yuwang colliery, eastern Yunnan, were studied, and the influences of organic matter, ash content and porosity on the elastic parameters of coal samples were investigated. The results show that the elastic parameters of coal are negatively correlated with organic matter content and porosity, and positively correlated with ash content. This means that the bulk modulus and primary‐wave velocity of coal decrease with a gradual increase in organic matter content or porosity and increase with a gradual increase in ash content. The main reason for this is that the ash modulus is typically higher than that of coal. When the ash content gradually increases, the contribution of ash to the equivalent modulus of coal increases, whereas the contribution of organic matter and pores decreases. In this study, the primary‐wave velocity of the target coal seam was fitted based on the generalized Gassmann equation. The calculation results were consistent with the observations and the relative error was within 7%. According to the distribution behaviour of elastic parameters, this provides adequate data support for the prediction of gas content in coal mines and ensures safe and green mining of coal resources.