Mining Capacity Research Articles

Net present value comparison of different mathematical programming models for multi-element open pit mines

ABSTRACT This paper compares two well-known mathematical programming approaches aiming to maximise multi-element open-pit mines’ net present value (NPV). The first approach, called production scheduling-based (PS-based), decides the optimum schedule of the individual blocks within the pit limit, whereas the second approach, called cut-off grade-based (COG-based), decides the partial extraction of bins derived from a reprehensive grade-tonnage curve of the orebody. A modified COG-based approach is also presented to accentuate the importance of blending requirements in multi-element deposits. The blending constraints in the PS-based model are also considered selectively to understand the paramount effect of the accessibility rules and to compare the two types of strategy fairly. The models were then applied to the Chadormalu iron ore open-pit mine in central Iran. The results were almost identical for those deposits with low stripping ratios and where excessive mining capacity is available. On the other hand, the results were entirely different for deposits with high stripping ratios and insufficient mining capacity. It was also shown that the COG-based models overestimate the NPV, in this special case, about 4.3%, and discriminate the ore-waste untruly. Also, the conventional COG-based models consistently violate the rigid bounds of elements at destinations. This comparison provides a guideline for knowing where the fast COG-based approaches can be used for the project evaluations instead of time-consuming PS-based approaches.

LFL-COBC: Lightweight Federated Learning on Blockchain-Based Device Contribution Allocation

In the distributed cyber-physical systems (CPSs) within the industrial domain, the volume of data produced by interconnected devices is escalating at an unprecedented pace, presenting novel opportunities to enhance service quality through data sharing. Nevertheless, data privacy protection emerges as a significant challenge for data providers in wireless networks. This paper puts forward a solution integrating blockchain and lightweight federated learning, designated as LFL-COBC, which aims to tackle the issues related to data privacy and device performance optimization. We initially analyze multiple dimensions influencing the performance of computing devices, such as mining capacity, data quality, computational efficiency and local device deviation, which are crucial for augmenting user engagement. Based on these dimensions, we deduce a set of cooperation strategies for selecting the optimal committee members and rewarding the contributions of node devices equitably, thereby stimulating cooperation between users and servers. To intelligently and automatically detect device anomalies and alleviate the operational burden, a convolutional neural network (CNN) model is employed. Additionally, to address the escalating cost of customer participation and the potential data explosion issue, a near-optimal model pruning algorithm is designed. This algorithm can make the model obtained from the training of node equipment lightweight, thereby reducing the load of federated learning and the blockchain, as well as enhancing the overall efficiency of the system. The efficacy of our approach is demonstrated through numerical experiments on the HDFS and BGL public data sets. Experimental results indicate that the LFL-COBC scheme can effectively safeguard data privacy and optimize device performance concurrently, providing an effective solution for device anomaly detection in CPSs.

Research on the optimal pick-up heights and their control strategy for the hydraulic double-row jet collector of the manganese nodule miner

As a superior pick-up device in manganese nodule miners (MNMs), the moving velocity and pick-up height of a hydraulic double-row jet collector (HDJC) are key to its collection performance. In this study, coupled computational fluid dynamics and the discrete element method (CFD‒DEM) is employed to numerically explore the optimal pick-up heights for various velocities. The collection efficiency decreases with increasing velocity and pick-up height but stabilizes at velocities below 0.6 m/s and pick-up heights below 115 mm. Lower pick-up heights increase seafloor disturbance. For high collection efficiency and low environmental damage, the optimal pick-up heights are 115 mm at 0.2–0.6 m/s and 105 mm at 0.6–1.0 m/s. Based on these pick-up heights, fuzzy proportional-integral-derivative (PID) control is developed to adjust the HDJC in the MNM multibody dynamics (MBD) model, which integrates hydraulic and control subsystems. This shows high robustness and responsiveness, ensuring excellent trafficability and mining capacity. Velocity, target value, and terrain variations cause significant short-term deviations. On flat ground, the pick-up heights deviate within 5 mm and the pick-up angles remain between ±0.025° across all velocities. During movement on flat-slope ground at maximum velocity, deviations in the pick-up height and angle remain below 10 mm and 0.2°.

ОБЕСПЕЧЕНИЕ ЭНЕРГЕТИЧЕСКОЙ БЕЗОПАСНОСТИ В УСЛОВИЯХ РАСШИРЕНИЯ МАСШТАБОВ ИСПОЛЬЗОВАНИЯ ЦИФРОВЫХ ТЕХНОЛОГИЙ В МИРОВОЙ ЭКОНОМИКЕ

The article presents the results of a study of the processes of ensuring energy security in the context of the expansion of the use of digital technologies in the global economy. Data on electric energy consumption by Google Corporation has been analyzed. Data on the consumption of electric energy for bitcoin mining by various countries of the world have been studied. The forecast values of mining capacities in the countries of the world by 2030 are presented. The features of ensuring energy security at the national and global levels in the context of the growing scale of the spread of digital services in the modern economy are determined. The patterns of growth in electric energy consumption in the context of increasing integration of artificial intelligence technologies into the modern economy have been revealed.

A New CRITIC-GRA Model for Stope Dimension Optimization Considering Open Stoping Stability, Mining Capacity and Costs

In the long-hole stage open stoping with subsequent backfill mining of underground metal mines, the selection or optimization of stope dimension parameters is significant for safe and economic mining operations. To analyze the optimal stope sizes, the Mathews empirical graph method and FLAC3D numerical method can be used, but the analyzed safety results of the two methods are generally independent from each other. More importantly, economic indicators including production capacity and mining costs should be considered simultaneously to optimize the stope dimension which was mostly ignored in previous reports. In this paper, a new CRITIC-GRA model was proposed for the first time to build up a multi-factor quantitative optimization for stope dimension, which allows for a comprehensive analysis with preset influential safety and economic indicators. The indicators considered include the safety indicators such as stability probability for the side walls and roof of the open stope via the updated Mathews graph method, maximum displacement, plastic zones volume and maximum principal stress via FLAC3D simulations, as well as economic indicators such as mining costs and stope production capacity in mine operations. The model was then illustrated in an underground iron mine. With the given rockmass quality in the mine, the overall stability of the open stope can be improved instead of reduced to enlarge the single stage stope height (60 m) to a double stage height (120 m) by reducing the stope width from 20 m to 15 m, thereby significantly increasing the mineable ore amount and improving the stope safety. An integrated evaluation of open stope stability, mining capacity and costs objectively determined that scheme No. 10, with a slope length of 50 m, a width of 15 m and a height of 120 m, was the optimum out of the 20 preset schemes. The new CRITIC-GRA model offers a dependable reference tool for determining the optimal stope dimensions in similar underground mines.

Does Mining Fuel Bubbles? An Experimental Study on Cryptocurrency Markets

We investigate how key features associated with the Proof-of-Work consensus mechanism of Bitcoin (commonly referred to as mining) affect pricing. In a controlled laboratory experiment, we observe that price bubble formation can be attributed to mining. Moreover, overpricing is more pronounced if the mining capacity is centralized to a small group of individuals. The order book data reveal that miners seem to play a crucial role in bubble formation. Further probing the mechanism in a second study, we find that both mining costs and decisions jointly with the sluggish rate of supply of the asset contribute to the bubble formation. Our results demonstrate that erratic pricing is an inherent feature of cryptocurrencies based on a mining protocol, thus seriously limiting any prospects for such assets becoming a medium of exchange. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: The funding provided by the University of Heidelberg, Hanken Foundation [Grant 271-6250], and Durham University is gratefully acknowledged. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01238 .

IRON ORE ALLOCATION MODEL TO FEEDSTOCK CONCENTRATE PLANTS FROM MULTIPLE SOURCES TO MULTIPLE DESTINATIONS CONSIDERING THE UNCERTAINTY OF GRADE, IN IRON ORE MINES: A CASE STUDY IN SANGAN MINE, IRAN

Operations research is a science that is used in various fields. This science is a set of quantitative techniques that help managers make decisions using scientific methods. This science is related to many axial decision-making issues of managers. For this reason, it is also called the science of management. This science is widely used in industries and mines. One of the most appropriate methods for solving research problems in operations is using linear programming in mining projects. This study was conducted in the Sangan iron ore mine in Iran. In this article, by using linear programming modeling and solving the transportation problem, the allocation of iron ore to feedstock concentrate plants from multiple sources to multiple destinations has been done considering the uncertainty of the grade. This paper is in the field of studying and identifying the quantitative and qualitative amount of extractable iron ore reserves in the mines, and on the other hand, the needs of concentrate plants concerning their feedstock supply by considering the uncertainty of iron ore grade in mines and deciding on their proper allocation. Mineral modeling and estimation of the amount of extractable minerals have been done using the block model. Uncertainty of iron ore grade in the block model is investigated using the sequential Gaussian simulation method. The amount of mining capacity and its sequence is planned considering the type of iron ore used in the plans during 5-year periods. In this article, the modeling of the problem has been done by considering the existing limitations in mines, such as the amount of supply, grade of iron ore, iron oxide and sulfur. On the other hand, the limitations in plants, such as demand, type and grade of iron ore, iron oxide and sulfur are considered in the modeling. In the end, the amount of iron ore tonnage sent from each mine to each plant during 5 years is presented by solving the problem.

Three-Dimensional Geological Modeling of Coal Reservoirs and Analysis of Sensitivity Factors for Combined Mining Capacity

Due to the large non-homogeneity of coal reservoirs, there is a large uncertainty about the extent of the impact on coal bed methane production capacity. The Hanchengbei Block has the problems of early exploration, less available production data, and large variations in developed production capacity within a single well group during test production. Therefore, how to use the existing data to analyze the geological factors affecting the development of coalbed methane in the Hanchengbei Block is particularly important. In this paper, based on the coal seam properties and production characteristics of the Hanchengbei Block, a three-dimensional geological model of the area was meticulously constructed using Petrel 2015 modeling software. Through the utilization of stochastic modeling techniques, reservoir attributes were visualized in three dimensions, and probability distribution functions as well as confidence intervals for different geological parameters were derived through geological statistics. Building upon this foundation, a dual-layer geological model incorporating multiple factors was established using Comet3.0 numerical simulation software. Monte Carlo simulation methods were then employed to simulate the effects of various geological parameters on gas production, yielding corresponding simulation results. Through normalization processes, parameter sensitivity was analyzed to determine the primary controlling factors influencing production capacity. The results show that the thickness of the No. 5 coal seam in the Hanchengbei Block is mainly distributed in the range of 1.35–6.89 m; the gas content is 10.28–15.52 m3/t; and the permeability is 0.014–0.048 mD. Under their joint influence, the average gas production of Hanchengbei Block is between 310–720 m3/d. The main factors affecting the capacity of Hanchengbei Block are the thickness and gas content of the coal seam. This study can provide a basis for the subsequent optimization of favorable areas, the formulation of drainage systems, and the design and optimization of development well networks.

Feasibility assessment of solution mining and gas storage in salt caverns: a case study of the Sanshui salt mine

The Sanshui salt mine is the sole location in the Guangdong province of South China with the potential to construct a salt cavern gas storage (SCGS) facility. Nevertheless, the gas storage construction of this mine faces significant challenges due to the presence of low‒grade salt deposits and numerous interlayers. To demonstrate the feasibility and calculate the gas storage capacity in this specific mining area, two representative salt caverns within this salt mine were simulated using a self-developed cavern-building simulation program, enabling us to accurately determine their respective volumes and shapes. Herein, the findings indicate that the combined caverns possess a total mining space volume of 1,157,000 m3, with the brine space accounting for merely 291,800 m3 (representing 25.22% of the overall mining space), and an extensive sedimentary volume of 865,200 m3 is also observed (constituting approximately 74.78% of the total mining capacity). Fortunately, this study has revealed that the sediments exhibit a porosity exceeding 40% and possess favorable permeability; consequently, countermeasures have been proposed to enhance the gas storage capacity within the pore space of these caverns, and we also utilized FLAC3D software for numerical simulation calculations to compare the stability of the cavern under different conditions of sediment pore utilization by calculating the volume loss rate, cavern wall displacement deformation, and plastic zone distribution. Moreover, the proposed method is anticipated to double the caverns’ working gas volume, increasing it from 40 million m3 to nearly 80 million m3. On the other hand, the long-term stability of caverns is numerically assessed under different pore space utilization rates of the sediments. The results also indicate that the caverns’ volume shrinkage, plastic zones, and surrounding rock displacement remain within allowable limits during 30 years of gas storage operation. The primary problem in the subsequent phase lies in effectively achieving gas injection and brine removal from the pore space of sediments while devising a methodology to extend this method to other salt caverns within similar salt mine areas. Thus, this study provides theoretical and technical guidance for the establishment of gas storage in existing salt caverns in the Sanshui salt mine and in salt mines worldwide that share similar geological conditions.

Structural evolution of bed drainage channels under the shear effect of the whole process of tailings thickening

Cemented paste backfill (CPB) technology has the advantages of safety, environmental friendliness, economics, and efficiency. This method offers assurances for practical underground mining and tailings pond management. The bed drainage channel structure and coarse particles with diameters above 45 μm were reconstructed and quantitatively characterized in 3D by computed tomography (CT) for the whole tailings thickening process. The spherical pore diameter evolution trends, stick throat channel radius and throat channel length were analyzed with and without shear using the pore network model (PNM). The functional relationship between the average spherical pore diameter and bed pressure is given, and the boundary values between the bed’ primary and secondary drainage channels are clarified. The ratio of throat length to diameter (Tw) is proposed to measure the difficulty of throat channel structure on the water discharge in the bed. The effects of the volume and number of coarse particles with diameters above 45 μm on the bed porosity and pore connectivity were analyzed. The range of particle diameters that significantly affect the bed porosity and pore connectivity was clarified. The results show that the spherical pore diameter, throat channel radius, and throat channel length decrease with increasing bed pressure with and without shear. Moreover, the average spherical pore diameter in the bed has a power-law relationship with the bed pressure. The spherical pore diameter, throat channel radius, and throat channel length with shear were lower than without shear, and the slurry concentration was higher than without shear. The main drainage channels of the bed with and without shear consisted of large pore structures with diameters of not less than 433.3 μm and 329.8 μm, respectively. The throat channel structure parameter Tw increases with the increase of bed pressure. When Tw is higher than 8.7, the discharge of water in the bed is hindered, making it challenging to improve the slurry concentration. The porosity and pore connectivity of the bed decreases with increasing volume and number of coarse particles. Among them, coarse particles in the diameter 150–300 μm range significantly reduce the bed porosity and pore connectivity. This study guides the preparation of high-concentration paste filling slurry, which is helpful to improve the efficient mining capacity of mines and have fewer tailings ponds.

Development and Application of Field Mixing Process and Intelligent Mixing Vehicle for Plateau Type Emulsified Explosives for Open Pit Mining

Abstract To improve mine production efficiency, reduce blasting costs, and meet the needs of mine capacity expansion, the use of an on-site mixing emulsion explosives truck for open pit iron ore deep hole step blasting charging operation. This paper firstly briefly introduces the process flow of emulsion explosives production and makes a detailed introduction to the working principle and process control requirements of each section of emulsion explosives production. Based on the analysis of the basic principle of adaptive control, the adaptive PID controller is designed to control the discharge temperature and density of emulsion explosives production and to achieve self-tuning of parameters, which improves the control accuracy of production parameters and product quality. The research results show that the use of field mixing emulsion explosives, and blasting operations personnel was reduced by 40% to 50%, and the drilling workload was reduced by about 7%. The application of field mixing emulsion technology improves the blasting effect, increases shovel loading efficiency, reduces the labor intensity of workers, saves comprehensive mining costs, and reduces the cost of temporary explosives depot guarding and disposal of used packaging in mines.

The effects of tokenization on ride‐hailing blockchain platforms

AbstractThe rapid development of blockchain has inspired many traditional centralized intermediaries to transform their transaction models, especially for the peer‐to‐peer market. Lately, the token‐based (blockchain) system (with cryptocurrency) is gaining popularity. However, little is known about the (comparative) performance of different operating types. In this study, we build an analytical framework to find the optimal strategies for the token‐based and nontoken‐based blockchain (as a special application scenario) platforms and derive the essential model properties and characteristics. We analytically show how the optimal mining bonus depends on the fraction of reserved tokens sold to customers and on the price‐to‐sales ratio. Furthermore, we obtain several actionable findings for choosing suitable platform types under different scenarios. The shift from the nontoken‐based platform to the token‐based platform may yield greater social welfare unless the nontoken‐based system operates with a much larger ride price, which we show to be unrealistic for the considered Beijing case through numerical studies. Moreover, we find that the matching probability for the token‐based platform is predominantly higher than that for the nontoken‐based one. Besides, government interventions may encourage a path toward a fair consensus mechanism or a high decentralization level in order to enhance social welfare. One unanticipated finding is that a higher decentralization level may lead to a lower mining capacity shortage and so to a more efficient system, indicating that the combination of blockchain and the sharing economy has much potential.

A multi-scale coupled productivity prediction model for conflagration compression fracturing of shale

A multi-fracture pressure flow regime coupled productivity prediction model considering shale gas adsorption and desorption, mass transfer and diffusion and cross-scale zoning was established based on cross-scale seepage characterization in unmodified area, interstitial matrix area, main fracture area, branched micro-fracture area and broken damage area formed from by conflagration compression fracturing. Then, geometric similarity, hydropower similarity and coupled iteration were used to build the model and complete the calculation. Finally, the effects of regional cross-scale seepage, number of fractures, production pressure difference, and fracture zone scale on gas well productivity were analyzed. The following results were obtained. First, the seepage flow of shale gas in different fractured areas is a continuous changing process. Among them, the unaffected area is dominated by transition flow and slip flow while continuous flow exists in the microfracture area-wellbore broken area and artificial fracture area. Second, the productivity of gas wells increases with the increase of fracture length and number, but the productivity increase tends to be stable after the fracture length exceeds 2 m. It is worth to mention that the increase of the number of fractures is more conducive to improving the productivity of shale gas under this condition. Third, when the number of high energy gas fractures is 6, its mining capacity is equivalent to that of hydraulic fracturing fractures with a half-fracture length of about 100 m. Fourth, when the production pressure difference exceeds 22 MPa, the free gas production capacity shows a decreasing trend. Therefore, the preferred production pressure difference is about 22 MPa. Fifth, the greater the number of artificial fractures, the greater the contribution of the increase in the diffusion coefficient to productivity, and the existence of wellbore fracture zone is also conducive to the stimulation of gas wells.

Strategies for the Resilience of Power-Coal Supply Chains in Low-Carbon Energy Transition: A System Dynamics Model and Scenario Analysis of China up to 2060

The global trends of coal phase-out in response to climate change are meeting obstacles in China, where a stable operation of power-coal supply chains remains essential. How to guarantee the resilience of these supply chains during the low-carbon transition becomes a critical issue. This study aims to recommend corresponding strategies by modelling and analysis. A system dynamics model was developed to analyze scenarios of China’s power-coal supply from 2021 to 2060. The results indicated that, firstly, the capacity redundancy of coal mines will increase from 1.13 to 1.32 before 2045, with the rising power-coal demand and its volatility, followed by a sharp decrease after that, in which demand falls in all scenarios. Secondly, increasing coal stock in each link can effectively reduce capacity redundancy of coal mines and imports during the period of rising demand, resulting in 250 million tons of coal mine capacity reduction, but will lead to an opposite result when demand falls. Finally, under high demand fluctuations, coal transport capacity will become a key constraint. It is recommended that China must improve the capacity redundancy of coal mines, coal stock, and coal transport in the near-term, as well as enhance long-term planning to carefully coordinate these factors during the whole process of low-carbon transition.

The Missing Link in the Genesis of the Lower Paleozoic Copper Deposits of the Anti-Atlas (Morocco): The Late Triassic Central Atlantic Magmatic Province Event

Copper mineralization in the Lower Paleozoic sedimentary cover of the Anti-Atlas (Morocco) is continually being revised not only to improve its mining capacity, but also to determine its origin, which remains a matter of debate. As evidenced by the various models proposed, the related research is fragmented, localized, and confusing. The origin of the Anti-Atlas Lower Paleozoic copper mineralization is shared between synergistic and epigenetic processes or a superposition of the two processes. Based on new tectono-magmatic data and a reinterpretation of the ore structural arrangement, we propose a link between the last concentration of copper deposits and the Late Triassic–Early Liassic CAMP (Central Atlantic Magmatic Province) tectono-thermal event, as evidenced by the significant concentration of copper mineralization in the three NE–SW corridors affected by extensional faults, some of which are filled with dolerite CAMP magma. The heat flow generated by the mafic dykes within these reactivated corridors causes mineralized fluids to up well into the sedimentary layers, depositing material rich in juvenile or leached copper, or even a mixture of the two. In some cases, these fluids are trapped by fracture systems that accompany passive folds initiated on normal faults. In other cases, these fluids can infiltrate bedding planes, and even karst caves, formed during carbonate exhumation. Notably, extensive NE–SW faults systematically cover the early Hercynian structures, suggesting that they belong to a post-Hercynian extensional episode. During the Late Triassic, the global fragmentation of the Pangaea supercontinent was manifested by the stretching of the continental crust at the margin of northwest Africa, with the simultaneous opening of the Central Atlantic Ocean and emplacement of CAMP magmatism. This last and often overlooked tectonothermal event must be considered in the remobilization and reconcentration of copper mineralization and other mineralization in Morocco.

A comparative assessment of value chain criticality of lithium-ion battery cells

As the global transport sector ramps up the transition towards electromobility, the value chain of raw materials for lithium-ion battery (LIB) development is becoming crucial. Assessing the criticality of material value chains identifies potential supply risks within these value chains and can better inform battery technology development. This study uses the ESSENZ method to systematically assess eleven (11) criticality aspects of ten (10) LIB cells. The criticality scores of the LIB cells are evaluated by aggregating the criticality scores of eleven (11) constituent value chains. These criticality scores are further complemented by twelve (12) environmental midpoint impacts performed using life cycle assessments. For the value chains, cobalt dominates the criticality scores in political stability, mining capacity, trade barriers, the feasibility of exploration projects, and the occurrence of co-production. Lithium dominates the criticality scores in demand growth, concentration of reserves, concentration of production, and primary material used. Nickel dominates the criticality scores in price volatility, while natural graphite dominates the criticality scores in company concentration. We further explain in our results the reasons driving the criticalities in the value chains. For the comparative LIB cell assessment, we developed a quadrant matrix chart depicting the relative performance of the LIB cells based on their aggregated elemental criticality and environmental impact scores. This analysis identifies LIB cells with low value chain criticality and environmental scores and those that need improvements on either the criticality or the environmental impact scores. We propose a series of measures, such as the transition towards cobalt-free batteries, material efficiency improvements, and end-of-life recycling to alleviate the criticality and environmental impacts associated with these LIB cells. This research emphasizes the need to include all sustainability dimensions for comprehensive and holistic insights to positively shape the course of action towards sustainable LIB production systems.

A Correlation Analysis Based Risk Warning Service for Cross-Border Trading

Obtaining a high-precision risk warning service, which can improve trading efficiency and legality, by reducing sampling proportion and customs clearance time dramatically is critical for cross-border trades. However, existing anti-fraudulent services are weak either in the precision or the mining capacity of discovering hidden risks. Among the reasons are incomplete data, untrustworthy resources, and old analysis models. On the basis of these observations, this article makes a combined technical solution for a risk warning service to address data resource, integrity, and mining capacity issues. The provided risk warning service is featured with a correlation analysis approach, which is advanced and efficient at addressing multisource and heterogeneous data to identify deep-seated risks with cross-border products, such as fake documents, price concealment, epidemic events, and ingredient pollution. To reveal the hidden correlation risks in cross-border clearance, a set of correlation-oriented data models and multi-attribute, multi-object, and multi-level methods are developed. The involved data sources and objects can be collected from inside businesses and public resources. Data are further structured to depict the whole portrait of a trade. The correlation analysis approach proves to be feasible and efficient in processing multisource and heterogeneous data to discover deep-seated risks with cross-border products. The risk warning service and the used correlation analysis approach have been studied and developed on the basis of a pilot project at an exit-and-entry port in Shanghai.

Development status of coal mining in China

Coal mining in China is facing the transition from output to quality. Based on the total mining capacity and average production, the current situation of coal mining at mine, city, and province levels is analysed, and data in support for the layout of sustainable mining development and the optimization of output provided. The results show that 87% of China's coal is mined by underground methods, with an average production capacity of 0.93 Mt/a per mine. Open pit mining accounts for 13%, with an average mine production capacity of 5.73 Mt/a. The average mining capacity of coal mines in China is 1.05 Mt/a, with 1181 coal mines with an average capacity less than 0.3 Mt/a, accounting for 35% of the total coal mines but contributing only 4.51% to output. They are distributed in about 48 cities in six provinces, seriously restricting the transition to green coal mining. The coal industry should speed up the closure of small coal mines in key provinces and cities, eliminate outdated production capacity in the central region, increase the speed and proportion of coal resources moving westward, and promote high-quality development of coal mining.

Production Strategy Optimization of Integrated Exploitation for Multiple Deposits Considering Carbon Quota

Nowadays, the mining industry actively advocates and practices the concept of green and integrated exploitation to realize the sustainable development of resources with low-carbon emissions. The certain carbon quota for mining companies limits the production capacity and resource utilization efficiency. The integrated exploitation of multiple deposits could coordinate resource allocation and operation facilities, which would reduce capital expenditure and operating costs for the mining company from a systematic perspective. In this condition, some deposits located nearby could be treated as one entity to make plans and optimize. An optimization framework is proposed based on the analysis of the characteristics and advantages of integrated exploitation. A new mathematical programming model is presented to optimize production capacity and extracted ore grade for each deposit considering constraints of maximum and minimum mining capacity, extracted ore grade and concentrated ore grade requirement, and metal output target, which has a significant influence on the economic benefit and resource utilization rate for a mining company. The model is verified using the data collected from three deposits of a gold mining company in China to demonstrate its ability to optimize the allocation of production capacity and improve the technical and economic effect of mining under the limitation of carbon quota. The sensitivity analysis of some key parameters is carried out to generate a series of integrated exploitation schemes under different production and operation conditions, which is useful for the mining company to make decisions in different situations.

Stranded assets and early closures in global coal mining under 1.5∘C

With the Glasgow Climate Pact 2021, the global community has committed explicitly to phasing down coal consumption. Yet the coal supply sector continues to develop new capacities, despite the risk of asset stranding. This article presents the first assessment of the implications of 1.5∘C mitigation pathways for the coal mining industry. Based on open coal mine data and a new version of the open coal sector model COALMOD-World, the prospects for individual coal mining regions and their risk of early mine closures and asset stranding are analyzed. Results show that global cumulative production capacity from operating thermal coal mines exceed the remaining consumption values for 2020 through 2050 by more than 50%. This supply-consumption discrepancy would hit Russia and the USA especially hard, causing the stranding of around 80% of operating capacities in each case. But the early closure of operating coal mines would affect all of the world’s major thermal coal producing regions, with most regions seeing more than three-fourths of their mine capacity closing early by 2030. Stranded assets from operating coal mines would total some USD2015 120 to 150 billion until 2050, with an additional USD2015 100 billion should currently proposed new coal mining projects be realized. If demand declines in accordance with 1.5∘C pathways, new coal mines or mine extensions would be redundant in all coal regions. Although the stranded asset value of mines is relatively small compared to that of the coal power plant sector, early closures would especially affect workers and local communities. Thus, efforts are urgently needed to ensure a just transition in coal mining regions and to address excess operating and proposed coal supply capacities that continue to fuel global warming.