Search Results (277)

This paper presents a critical and comprehensive review of the application of mining waste, specifically waste rock and tailings, in asphalt pavements, with the aim of synthesizing performance outcomes and identifying key research gaps. A systematic literature search yielded a final dataset of 41 peer-reviewed articles for detailed analysis. Bibliometric analysis indicates a notable upward trend in annual publications, reflecting growing academic and practical interest in this field. Performance-based evaluations demonstrate that mining wastes, particularly iron and copper tailings, have the potential to enhance the high-temperature performance (i.e., rutting resistance) of asphalt binders and mixtures when utilized as fillers or aggregates. However, their effects on fatigue life, low-temperature cracking, and moisture susceptibility are inconsistent, largely influenced by the physicochemical properties and dosage of the specific waste material. Despite promising results, critical knowledge gaps remain, particularly in relation to long-term durability, comprehensive environmental and economic Life-Cycle Assessments (LCA), and the inherent variability of waste materials. This review underscores the substantial potential of mining wastes as sustainable alternatives to conventional pavement materials, while emphasizing the need for further multidisciplinary research to support their broader implementation. Full article

The spontaneous combustion disaster of coal not only causes a waste of resources but also affects the safe production of coal mines. In order to accurately detect the range and location of the spontaneous combustion source of coal, this paper studies and summarizes previous research results, and based on the principles and research and development progress of existing detection technologies such as the surface temperature measurement method, ground temperature measurement method, wellbore temperature measurement method, and infrared remote sensing detection method, it briefly reviews the application of various detection technologies in engineering practice at this stage and briefly explains the advantages and disadvantages of each application. Research shows that the existing technologies are generally limited by the interference of complex environmental conditions (such as temperature measurement deviations caused by atmospheric turbulence and the influence of rock layer structure on ground temperature conduction) and the implementation difficulties of geophysical methods in mining applications (such as the interference of stray currents in the ground by electromagnetic methods and the fast attenuation speed of waves detected by geological radar methods), resulting in the insufficient accuracy of fire source location and difficulties in identifying concealed fire sources. In response to the above bottlenecks, the ”air–ground integrated” fire source location determination technology that breaks through environmental constraints and the location determination method of a CSC fire source based on a multi-physics coupling mechanism are proposed. By significantly weakening the deficiency in obtaining parameters through a single detection method, a new direction is provided for the detection of coal spontaneous combustion fire sources in the future. Full article

Life Cycle Impact Assessments (LCIAs) examine the environmental impacts of products using life cycle inventories (LCIs) of quantified inputs and outputs of a product through its life cycle. Currently, estimated impacts from mining are dominated by long-term metal release from tailings due to inaccurate assumptions regarding metal release and transport within and from mine materials. A conceptual model approach is proposed to support the development of a new database of LCI data, applying mechanistic processes required for the release and transport of metals through tailings and categorizing model inputs into ‘bins’. The binning approach argues for accuracy over precision, noting that precise metal release rates are likely impossible with the often-limited data available. Three case studies show the range of forecasted metal release rates, where even after decades of monitoring within the tailings and underlying aquifer, metal release rates span several orders of magnitude (<100 mg/L to >100,000 mg/L sulfate at the Faro Mine). The proposed tool may be useful for the development of a new database of LCI data, as well as to analyze mine’s regional considerations during designs for risk evaluation, management and control prior to development, when data is also scarce. Full article

Hyperspectral imaging has been increasingly used in mining for detailed mineral characterization and enhanced ore–waste discrimination, which is essential for optimizing resource extraction. However, the full deployment of this technology still faces challenges due to the variability of field conditions and the spectral complexity inherent in real-world mining environments. In this study, we compare the performance of two approaches for ore–waste discrimination in both laboratory and actual mine site conditions: (i) a data-driven feature extraction (FE) method and (ii) a knowledge-based mineral mapping method. Rock samples, including ore and waste from an open-pit gold mine, were obtained and scanned using a hyperspectral imaging system under laboratory conditions. The FE method, which quantifies the frequency absorption peaks at different wavelengths for a given rock sample, was used to train three discriminative models using the random forest classifier (RFC), support vector classification (SVC), and K-nearest neighbor classifier (KNNC) algorithms, with RFC achieving the highest performance with an F1-score of 0.95 for the laboratory data. The mineral mapping method, which quantifies the presence of pyrite, calcite, and potassium feldspar based on prior geochemical analysis, yielded an F1-score of 0.78 for the ore class using the RFC algorithm. In the next step, the performance of the developed discriminative models was tested using hyperspectral data of two muck piles scanned in the open-pit gold mine. The results demonstrated the robustness of the mineral mapping method under field conditions compared to the FE method. These results highlight hyperspectral imaging as a valuable tool for improving ore-sorting efficiency in mining operations. Full article

Rare-earth elements (REEs), including lanthanides, scandium, and yttrium, are important for advanced technologies such as renewable energy systems, electronics, medical diagnostics, and precision agriculture. Despite their relative crustal abundance, REE extraction is impeded by complex geochemical behavior, dispersed distribution, and environmental challenges. This review presents a comprehensive overview of REE geochemistry, mineralogy, and major deposit types including carbonatites, alkaline igneous rocks, laterites, placer deposits, coal byproducts, and marine sediments. It also highlights the global distribution and economic potential of key REE projects. The integration of machine learning has further enhanced exploration by enabling deposit classification and geochemical modeling, especially in data-limited regions. Environmental and health challenges associated with REE mining, processing, and electronic waste (e-waste) recycling are studied, along with the expanding use of REEs in agriculture and medicine. Some recycling efforts offer promise for supply diversification, but significant technological and economic barriers remain. Ensuring a secure and sustainable REE supply will require integrated approaches combining advanced analytics, machine learning, responsible extraction, and coordinated policy efforts. The present review offers a general overview that can be useful for informing future studies and resource-related discussions. Full article

To ensure the green, safe, and efficient extraction of mineral resources and promote sustainability, the stability of mined-out areas has become a critical factor affecting safe production and ecological restoration in underground metal mines. The instability of underground goafs poses a significant threat to mine safety, especially when irregular excavation patterns interact with high ground stress, exacerbating instability risks. Most existing studies lack a systematic and multidisciplinary integrated framework for comprehensive evaluation and management. This paper proposes a trinity research system of “assessment–optimization–governance”, integrating theoretical analysis, three-dimensional fluid–solid coupling numerical simulation, and a filling sequence optimization method based on genetic algorithms. An analysis of data measured from 243 pillars and 49 goafs indicates that approximately 20–30% of the pillars have a factor of safety (FoS) below 1.0, signaling immediate instability risks; additionally, 58% do not meet the threshold for long-term stability (FoS ≥ 1.5). Statistical and spatial analyses highlight that pillar width-to-height ratio (W/H) and cross-sectional area significantly influence stability; when W/H exceeds 1.5, FoS typically surpasses 2.0. Numerical simulations reveal pore water pressures of 1.4–1.8 MPa in deeper goafs, substantially reducing effective stress and accelerating plastic zone expansion. Stability classification categorizes the 49 goafs into 7 “poor”, 37 “moderate”, and 5 “good” zones. A genetic algorithm-optimized filling sequence prioritizes high-risk area remediation, reducing maximum principal stress by 60.96% and pore pressure by 28.6%. Cemented waste rock filling applied in high-risk areas, complemented by general waste rock filling in moderate-risk areas, significantly enhances overall stability. This integrated method provides a scientific foundation for stability assessment and dynamic remediation planning under complex hydrogeological conditions, offering a risk-informed and scenario-specific application of existing tools that improves engineering applicability. Full article

The processing of dimension stones for the construction sector involves transforming rock blocks into slabs via sawing and polishing. This process generates a fine-grained waste composed largely of rock powder derived from the processed rock. Several studies indicate that the rock powder produced as a processing waste can release Ca, Mg, and K. However, alongside the release of macronutrients, there is the possibility of releasing undesirable constituents, such as Na, which is also a component of the minerals forming silicate rocks. This study aimed to analyze the risk of salinization that these materials may cause to soil if applied without a thorough evaluation of their composition. Samples were analyzed in terms of physical, chemical, and mineralogical parameters; exchangeable inorganic constituents; percentage of exchangeable sodium; and sodium adsorption ratio. The data indicate that residues stored in landfills in a random and unsorted manner do not fully meet the criteria established by Brazilian regulations for soil remineralizers. However, their characteristics suggest good potential for use in the agricultural sector, although this would require blending with other agricultural inputs and/or segregating residues from certain types of rocks to comply with current regulations. Full article

Waste valorization involves reusing and recycling waste materials to create useful products such as materials, chemicals, fuels, or energy. The primary goal is the transition to a circular economy model while minimizing the impacts of hazardous waste. Adopting such policies appears to be a one-way path due to the continuous increase in the consumption of raw materials. According to recent projections, by 2050, 180 billion tonnes of materials will be consumed annually. Since natural resources cannot meet these requirements, new sources must be explored. Waste can serve as an alternative source and cover at least part of the needs that arise. In this work, good practices regarding waste valorization are presented. The case studies examined include the waste/by-products of ultrabasic rocks resulting in chromite and magnesite mining, as well as the tannery sludge produced after the corresponding wastewater treatment. Full article

Active and abandoned mining sites are significant sources of heavy metals and metalloid pollution, leading to serious environmental issues. This study assessed the environmental risks posed by potentially toxic elements (PTEs), specifically arsenic (As) and antimony (Sb), in the Technosols (mining residues) of the former Pejão coal mine complex in Northern Portugal, a site impacted by forest wildfires in October 2017 that triggered underground combustion within the waste heaps. Our methodology involved determining the “pseudo-total” concentrations of As and Sb in the collected heap samples using microwave digestion with aqua regia (ISO 12914), followed by analysis using hydride generation-atomic absorption spectroscopy (HG-AAS). The concentrations of As an Sb ranging from 31.0 to 68.6 mg kg⁻¹ and 4.8 to 8.3 mg kg⁻¹, respectively, were found to be above the European background values reported in project FOREGS (11.6 mg kg⁻¹ for As and 1.04 mg kg⁻¹ for Sb) and Portuguese Environment Agency (APA) reference values for agricultural soils (11 mg kg⁻¹ for As and 7.5 mg kg⁻¹ for Sb), indicating significant enrichment of these PTEs. Based on average I_geo values, As contamination overall was classified as “unpolluted to moderately polluted” while Sb contamination was classified as “moderately polluted” in the waste pile samples and “unpolluted to moderately polluted” in the downhill soil samples. However, total PTE content alone is insufficient for a comprehensive environmental risk assessment. Therefore, further studies on As and Sb fractionation and speciation were conducted using the Shiowatana sequential extraction procedure (SEP). The results showed that As and Sb levels in the more mobile fractions were not significant. This suggests that the enrichment in the burned (BCW) and unburned (UCW) coal waste areas of the mine is likely due to the stockpiling of lithic fragments, primarily coals hosting arsenian pyrites and stibnite which largely traps these elements within its crystalline structure. The observed enrichment in downhill soils (DS) is attributed to mechanical weathering, rock fragment erosion, and transport processes. Given the strong association of these elements with solid phases, the risk of leaching into surface waters and aquifers is considered low. This work underscores the importance of a holistic approach to environmental risk assessment at former mining sites, contributing to the development of sustainable remediation strategies for long-term environmental protection. Full article

Due to the difficulty of creating directional fractures efficiently and accurately with existing non-explosive rock-breaking methods, a directional fracturing technique utilizing a coal-based solid waste expansive agent, termed the instantaneous expansion with a single fracture (IESF), has been developed. IESF can generate high-pressure gases within 0.05–0.5 s and utilize gas pressure to achieve directional rock fragmentation. The rock-breaking mechanisms under double-borehole conditions of conventional blasting (CB), shaped charge blasting (SCB), and IESF were studied by theoretical analysis, numerical simulation, and in situ test. The gas pressure distribution within directional fractures of IESF was determined, and the crack propagation criterion between double-borehole was established. Numerical simulation results indicated that the stress distribution in CB was random. SCB exhibited tensile stress of −10.89 MPa in the inter-borehole region and −8.33 MPa on the outer-borehole region, while IESF generated −14.47 MPa and −12.62 MPa in the corresponding regions, demonstrating that stresses generated between adjacent boreholes can be superimposed in the inter-hole region. In CB, strain was concentrated along main fractures. SCB exhibited strains of 7 mm and 8 mm in the shaped charge direction, while non-shaped charge directions showed a strain of 1.5 mm. For IESF, strain in the shaped charge direction measured 6 mm, compared to 1 mm in non-shaped charge directions, resulting in superior directional fracture control. In situ test results from Donglin Coal Mine demonstrated that IESF can form superior directional rock-breaking efficacy compared to both CB and SCB, with the average crack rates of 95.5% by IESF higher than 85.0% by SCB. This technique provides a non-explosive method that realizes precise control of the direction of cracks while avoiding the high-risk and high-disturbance problems of explosives blasting. Full article

Resource depletion and environmental degradation have resulted from the substantial increase in the use of natural aggregates and construction materials brought on by the growing demand for infrastructure development. Road building using mining waste has become a viable substitute that reduces the buildup of industrial waste while providing ecological and economic advantages. In order to assess the appropriateness of several mining waste materials for use in road building, this study investigates their engineering characteristics. These materials include slag, fly ash, tailings, waste rock, and overburden. To ensure long-term performance in pavement applications, this study evaluates their tensile and compressive strength, resistance to abrasion, durability under freeze–thaw cycles, and chemical stability. This review highlights the potential of mining waste materials as sustainable alternatives in road construction. Waste rock and slag exhibit excellent mechanical strength and durability, making them suitable for high-traffic pavements. Although fly ash and tailings require stabilization, their pozzolanic properties enhance subgrade reinforcement and soil stabilization. Properly processed overburden materials are viable for subbase and embankment applications. By promoting the reuse of mining waste, this study supports landfill reduction, carbon emission mitigation, and circular economy principles. Overall, mining byproducts present a cost-effective and environmentally responsible alternative to conventional construction materials. To support broader implementation, further efforts are needed to improve stabilization techniques, monitor long-term field performance, and establish effective policy frameworks. Full article

In response to the high cost and environmental impact of backfill materials in Xinjiang mines, an eco-friendly, large-volume composite was developed by bonding desert-sand mortar to waste concrete. A rock-filled concrete process produced a highly flowable mortar from desert sand, cement, and fly ash. Waste concrete blocks served as coarse aggregate. Specimens were cured for 28 days, then subjected to uniaxial compression tests on a mining rock-mechanics system using water-to-binder ratios of 0.30, 0.35, and 0.40 and aggregate sizes of 30–40 mm, 40–50 mm, and 50–60 mm. Mechanical performance—failure modes, stress–strain response, and related properties—was systematically evaluated. Crack propagation was tracked via digital image correlation (DIC) and acoustic emission (AE) techniques. Failure patterns indicated that the pure-mortar specimens exhibited classic brittle fractures with through-going cracks. Aggregate-containing specimens showed mixed-mode failure, with cracks flowing around aggregates and secondary branches forming non-through-going damage networks. Optimization identified a 0.30 water-to-binder ratio (Groups 3 and 6) as optimal, yielding an average strength of 25 MPa. Among the aggregate sizes, 40–50 mm (Group 7) performed best, with 22.58 MPa. The AE data revealed a three-stage evolution—linear-elastic, nonlinear crack growth, and critical failure—with signal density positively correlating to fracture energy. DIC maps showed unidirectional energy release in pure-mortar specimens, whereas aggregate-containing specimens displayed chaotic energy patterns. This confirms that aggregates alter stress fields at crack tips and redirect energy-dissipation paths, shifting failure from single-crack propagation to a multi-scale damage network. These results provide a theoretical basis and technical support for the resource-efficient use of mining waste and advance green backfill technology, thereby contributing to the sustainable development of mining operations. Full article

This study investigates the coupled effects of waste rock-to-tailings ratio (WTR) and curing temperature on the pore structure and mechanical performance of cemented tailings waste rock backfill (CTRB). Four WTRs (6:4, 7:3, 8:2, 9:1) and curing temperatures (20–50 °C) were tested. Low-field nuclear magnetic resonance (NMR) was used to characterize pore size distributions and derive fractal dimensions ($D_a$, $D_b$, $D_c$) at micropore, mesopore, and macropore scales. Uniaxial compressive strength (UCS) and elastic modulus (E) were also measured. The results reveal that (1) the micropore structure complexity was found to be a key indicator of structural refinement, while excessive temperature led to pore coarsening and strength reduction. $D_a$ = 2.01 reaches its peak at WTR = 7:3 and curing temperature = 40 °C; (2) at this condition, the UCS and E achieved 20.5 MPa and 1260 MPa, increasing by 45% and 38% over the baseline (WTR = 6:4, 20 °C); (3) when the temperature exceeded 40 °C, $D_a$ dropped significantly (e.g., to 1.51 at 50 °C for WTR = 7:3), indicating thermal over-curing and micropore coarsening; (4) correlation analysis showed strong negative relationships between total pore volume and mechanical strength ($R$ = −0.87 for ${\mathsf{\delta }}_a\mathrm{v}\mathrm{s}.\mathrm{U}\mathrm{C}\mathrm{S}),$ and a positive correlation between $D_a$ and UCS (R = 0.43). (5) multivariate regression models incorporating pore volume fractions, $T_2$ relaxation times, and fractal dimensions predicted $\mathrm{U}\mathrm{C}\mathrm{S}$ and E with R² > 0.98; (6) the hierarchical sensitivity of fractal dimensions follows the order micro-, meso-, macropores. This study provides new insights into the microstructure–mechanical performance relationship in CTRB and offers a theoretical and practical basis for the design of high-performance backfill materials in deep mining environments. Full article

High temperatures significantly affect the physical and mechanical properties of rocks in deep geoengineering projects, such as geothermal development, deep mining, and the geological disposal of nuclear waste. Therefore, it is essential to explore the relationship between the thermal damage (TD) of granite and its influencing factors. This paper characterizes the TD of granite specimens subjected to high temperatures of up to 800 °C and proposes a predictive model for this thermal damage. A database, which includes publicly available experimental data of advanced microscopic observations of granite specimens exposed to high-temperature treatments and their changes in physical and mechanical properties, was compiled and analyzed. The collected data revealed a consistent trend: crack development among quartz, feldspar, and biotite minerals was observed to intensify notably between 400 °C and 600 °C, as indicated by changes in the mechanical properties. Based on these characteristics, the relationships between TD and its influential parameters were determined using regression models and several machine learning algorithms. The derived models indicated good predictability performance with a coefficient of determination (R²) varying between 0.60 and 0.97, with the boosted ensemble tree model being the best. Nevertheless, mineral contents were not found to be good predictors of TD, even if they control the evolution of the crack during the heat treatment. It was concluded that the findings of this study could serve as a valuable tool for assessing the thermal damage of rocks. Full article

Unmanned aerial vehicles (UAVs) have increasingly proven to be flexible tools for mapping mine terrain, offering expedient and precise data compared to alternatives. Photogrammetric outputs are particularly beneficial in open pit operations and waste dump areas, since they enable cost-effective and reproducible digital terrain models. Meanwhile, UAV-based LiDAR has proven invaluable in situations where uniform ground surfaces, dense vegetation, or steep slopes challenge purely photogrammetric solutions. Recent advances in machine learning and deep learning have further enhanced the capacity to distinguish critical features, such as vegetation and fractured rock surfaces, thereby reducing the likelihood of accidents and ecological damage. Nevertheless, scientific gaps remain to be researched. Standardization around flight practices, sensor selection, and data verification persists as elusive, and most mining sites still rely on limited, multi-temporal surveys that may not capture sudden changes in slope conditions. Complexity lies in devising strategies for rehabilitated dumps, where post-mining restoration efforts involve vegetation regrowth, erosion mitigation, and altered land use. Through expanded sensor integration and refined automated analysis, approaches could shift from information gathering to ongoing hazard assessment and environmental surveillance. This evolution would improve both safety and environmental stewardship, reflecting the emerging role of UAVs in advancing a more sustainable future for mining. Full article