Accurate slope stability assessment is essential for the safe and economical operation of deep open-pit mines, especially in areas with complex geological and hydrological conditions. While two-dimensional (2D) analyses are still widely used in engineering practice, they struggle to accurately reflect true failure mechanisms in three-dimensional (3D) environments. This study offers a comprehensive comparison between 2D and 3D slope stability analyses specifically for the Sungun open-pit copper mine in Iran. A detailed 3D base model was developed using Rhinoceros and Griddle to accurately represent the pit geometry, geotechnical domains, and groundwater surface. This model facilitated the generation of a hexahedral mesh for FLAC3D simulations and allowed for the extraction of multiple 2D cross-sections for FLAC analyses in various directions. The 3D model predicted a rotational failure mechanism, yielding a global safety factor (FS3D) of 1.285, which was validated against field observations of tension cracks and active slope deformation. In contrast, the comparative 2D analyses produced varying results based on the orientation and location of the sections, with FS2D values ranging from 1.04 to 4.11. While some 2D sections approximated FS3D values reasonably, none accurately captured both the geometry and extent of the failure surface. Notably, sections aligned with the primary direction of displacement (North-South) yielded the most representative results. These findings underscore the limitations of relying solely on 2D analyses for pit slope design in geologically complex settings. The integration of 3D numerical modeling with CAD-based geometry management is crucial for achieving reliable slope stability assessments and for minimizing design uncertainties in large-scale mining projects.

Lichen biomonitoring discriminates trace element sources from copper mining and atmospheric deposition in southern Peru.

The use of the Environmental Protection Fund for sustainable mining in Zambia: A comparative case study of Konkola Copper Mines and Lubambe Copper Mines

Bone tool functionality in the Bronze Age copper mines of Great Orme (UK): Preliminary results

Gram-stain-positive, endospore-producing, mesophilic and rod-shaped strain O16T was isolated from a copper mine’s soil and characterized using a polyphasic taxonomic approach. The 16S rRNA gene-sequence analysis revealed that strain O16T belongs to the genus Saccharibacillus. It exhibited the highest sequence similarity to Saccharibacillus endophyticus JM-1350T (97.2%), followed by ‘Saccharibacillus alkalitolerans’ VR-M41T (97.1%), Saccharibacillus sacchari GR21T (96.8%), Saccharibacillus kuerlensis HR1T (96.6%), and Saccharibacillus deserti WLJ055T (95.7%). Genome-based comparisons revealed that the digital DNA–DNA hybridization (dDDH) and average nucleotide identity (ANI) values between strain O16T and its closest relatives, S. endophyticus JM-1350T and ‘S. alkalitolerans’ VR-M41T, were 21.3% and 22.3%, and 76.6% and 77.6%, respectively, which are well below the recommended thresholds for species delineation. The diagnostic diamino acid of the cell wall was meso-diaminopimelic acid. Phosphatidylglycerol and diphosphatidylglycerol were the major polar lipids in strain O16T. The predominant menaquinone was MK-7. The DNA G+C content was 53.4%. The major cellular fatty acids present were anteiso-C15:0 (60.8%), iso-C16:0 (9.5%) and C16:1 ω11c (7.4%). On the basis of phenotypic, chemotaxonomic, and genotypic evidence, strain O16T is considered to represent a novel species within the genus Saccharibacillus. This data strongly supports the classification of the strain O16T as a novel species in the genus Saccharibacillus, for which we propose the name Saccharibacillus soli sp. nov. strain O16T (=CCM 8781T = KCTC 33898T).

Copper mining industry generates water with high sulfate (SO4 2-) concentrations. The hydrogen-based membrane biofilm reactor (H2-MBfR) is a promising sulfidogenesis solution, using H2 as a clean electron donor. An H2-MBfR was operated for 209 days treating synthetic mining-influenced water under varying conditions (HRT, H2 pressure, SO4 2- loadings). The system proved highly resilient, achieving stable SO4 2- removal (> 90%) and fully recovering from a severe shock load (4500 mg S L-1). To identify the governing mechanisms, a transient pseudoanalytical biofilm model was developed. A Global Sensitivity Analysis (Sobol) showed performance is dominated by the maximum specific growth rate ( ), detachment coefficient ( ), and H2S inhibition ( ). The model was calibrated on Stages 1-3 (Days 0-169, n = 44), achieving R² = 0.962 (calibration) and R² = 0.572 (blind validation, Stage 4). Crucial findings from the model calibration ( = 0.344 d-1) and a diagnostic analysis using the Thiele Modulus (mean = 0.224) strongly indicate that the system operated in a kinetically-limited regime. Performance was governed by the delicate balance of slow growth and high detachment, not by mass transfer (H2 supply or SO4 2- diffusion). This research validates the H2-MBfR for high-rate applications and correctly shifts the bottleneck for future optimization from mass transfer to biofilm retention kinetics.

Nitzschia sp., a diatom isolated from Paposo (Antofagasta, northern Chile), was evaluated as a biological solution for removing kaolinite-type clay minerals from recycled process water in large-scale copper mining. Optimization of culture conditions to maximize extracellular polymeric substance (EPS) production revealed that supplementing with 0.1 gL−1 of glucose yielded the highest EPS levels on day 17, reaching 1285 ± 58.9 mgL−1 (control equal to 237.8 ± 34 mgL−1 on day 17). However, maximum dry weight biomass productivity was achieved in the presence of sodium carbonate at a concentration of 1 gL−1 (319 ± 12.5 mgL−1d−1), significantly exceeding the productivity of the control group (242.7 ± 5.4 mgL−1d−1). Notably, low glucose supplementation enhanced EPS synthesis. Application of control-derived EPS of 1 gL−1 rapidly decreased kaolinite initial turbidity from ~2024 FNU to ~354 ± 0.74 FNU within one minute. Even more glucose-derived EPS (1 gL−1) further reduced turbidity to ~22.2 ± 0.1 FNU at 5 min, achieving a flocculation efficiency of ~98.9% after 15 min. Genomic analysis and KEGG annotation identified abundant genes for EPS and carbohydrate metabolism, including numerous glycosyltransferases, glycoside hydrolases, and multiple copies of UDP-glucose 4-epimerase, consistent with strong polysaccharide-biosynthesis capacity. Physicochemical characterization (particle sizing, HPLC, SEM, zeta-potential and FT-IR) showed EPS comprised mainly of rhamnose, fucose, arabinose, xylose and glucose, featuring functional groups (–OH, C=O/COO–, O-acetyl, uronic/guluronic signatures) that interact with kaolinite to promote aggregation. These findings demonstrate that Nitzschia-derived EPS, especially from glucose-supplemented cultures, represent promising sustainable bioflocculants for treating kaolinite-contaminated recycled water in mining operations.

The development of mines creates substantial amounts of soil-rock mixture (S-RM) waste that is accumulated as waste dumps. These dumps pose significant safety hazards that require management. In this study, S-RM was sampled from a waste dump at a copper mine in Jiangxi Province, China. Consolidated-undrained triaxial tests were conducted on four gradations of S-RM specimens. Numerical simulations of dump slope stability were performed by considering factors such as groundwater level, rainfall intensity, and root reinforcement depth. The findings are as follows: (1) cohesion and friction angle are sensitive to rock content; (2) the power-law model outperforms the Duncan-Chang model in fitting triaxial data; (3) the stability of the dump deteriorates as the groundwater level gets shallower; (4) the factors of safety decrease with increasing rainfall duration and intensity with an approximately exponential decay pattern; (5) vegetation root reinforcement improves slope stability; however, extreme rainfall can trigger perched water accumulation, which can compromise stability. These findings provide valuable indicators that can assist in managing the safety hazard posed by such waste dumps.

Funding the supply of critical materials for the transition to renewable energy (RE) is crucial to addressing climate change. For the world’s leading economies in copper and lithium mining, this paper investigates the association among foreign direct investment (FDI), governance, carbon emissions (CO2) and renewable energy consumption (REC). Using 2002–2023 panel data, a unit root test was applied to determine the stationarity of the variables and cointegration tests revealed cointegration in first differences. The variables were cointegrated at the 1% significance level, as indicated by the Kao Residual Cointegration Test. Next, the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) panel regression methods were employed. The FMOLS model findings indicated a long-term negative relationship between FDI and RE. Specifically, a 1% increase in FDI (as a percentage of GDP) reduces REC by 0.24% in the major copper- and lithium-producing economies. Governance, measured by control of corruption, has a positive effect on clean energy consumption, and CO2 emissions are significantly negatively associated with REC. Using the DOLS model, we confirmed the robustness of these long-term panel relationships. Policymakers should strengthen the quality of governance, including combating corruption and encouraging FDI in RE. This strategy should also support sustainable mining practices and responsible consumption, aligning with Sustainable Development Goals (SDGs) 7 and 12, respectively.

Aiming at the significant variation in clay content within the orebody of the Letpadaung copper mine in Monywa, Myanmar, this study conducted comprehensive research on ore classification based on clay content and its impact on bio-heap leaching performance. Pressure filtration tests confirmed that clay content is a critical factor affecting ore permeability and copper leaching efficiency. Accordingly, a classification standard centered on clay content was established based on the ore properties of the Letpadaung Copper Mine, categorizing the ore into four types: low-clay ore (<3%), medium-clay ore Type 1 (3%–10%), medium-clay ore Type 2 (10%–25%), and high-clay ore (>25%). Corresponding differentiated stacking strategies were proposed and applied for the first time in industrial operations at a scale of several hundred thousand tons. Industrial practice results demonstrated that, compared with the unclassified mixed ore with a leaching efficiency of 45.92%, the implementation of classified heap leaching increased the copper leaching rates of low-clay ore and medium-to-high-clay ore to 68.07% and 63.41%, respectively. Moreover, multi-layer heap leaching within the same leaching unit showed consistent leaching efficiency across different layers after ore classification. These results further validate that ore classification based on clay content combined with differentiated heap leaching processes serves as a vital technical approach for ensuring efficient and stable heap leaching operations at the Letpadaung copper mine.

Technology, Human Progress, and Ethics in Copper Mining: A Perspective from Laudato Si’

In 2024, landscape geochemical studies were conducted in the southern regions of Mongolia in the area of coal (Tavan Tolgoi enterprise) and copper (Ouyu Tolgoi enterprise) mining. Samples of groundwater and soils were collected, chemical and analytical work was carried out. The purpose of the work is to assess the ecological state of soils and groundwater in the mining soums of Khanbogd and Tsogttsetsii of the South Gobi aimag of Mongolia. As a result of the studies, it was found that the groundwater in the copper mining area is mainly fresh, while in the coal mining area it is slightly saline. Soils are mainly sierozem-like, belong to carbonate, and sometimes to saline. Foci of groundwater and soil pollution were identified on the territory of farms located near mining enterprises. High concentrations of sodium, fluorine, magnesium, chlorine, sulfates and a number of toxic heavy metals have been found in the waters of wells and boreholes of local residents. Increased levels of nickel, copper, zinc and arsenic have been found in the soils of the same areas, exceeding sanitary and hygienic standards, sometimes by more than 20 times.

Mining activities in Chile generate massive amounts of tailings, creating significant environmental risks due to heavy metal contamination. Phytoremediation offers an eco-friendly solution, yet studies on native Chilean species are scarce. This study evaluates the effects of ethylenediamine tetraacetic acid (EDTA) and nanoscale zero-valent iron (nZVI) on the potential of the native Cistanthe grandiflora for the phytoremediation of copper mine tailings. A six-month pot experiment was conducted with four treatments: EDTA 300 mg·kg-1, EDTA 600 mg·kg-1, nZVI 500 mg·kg-1, and a control group without additions. The results indicate that Cistanthe grandiflora primarily acts as a phytostabilizer, accumulating higher metal concentrations in roots than in aerial parts. The application of EDTA significantly enhanced the Bioconcentration Factor for Cu, Ni, Pb, and Mo, increasing BCF values from 0.5 to 1.0 or more in several cases. Specifically, a lower dose of EDTA (300 mg·kg-1) successfully increased the Translocation Factor (TF) of cadmium to 1.3, suggesting a potential for phytoextraction for this element. Conversely, nZVI application showed a limited impact, slightly improving the Translocation factor for copper and chromium but without exceeding unity. These findings demonstrate that Cistanthe grandiflora, assisted by EDTA, is a promising candidate for the phytostabilization of heavy metals in mine tailings.

ABSTRACT The convex – concave feature of 3D laser point cloud data (3D LPCD) is introduced in fragmentation calculation for blast muck piles in open-pit copper mines to improve the calculation efficiency and accuracy of the blast fragmentation of muck piles (BFMP). First, a supervoxel segmentation method based on point cloud curvature feature (named as CFSS method) is constructed to overcome drawbacks, such as the color difference of the same blast muck pile surface is not evident and has little effect on the 3D LPCD segmentation. Then, a supervoxel clustering method based on boundary extraction (named as BESC method) is constructed to cluster the supervoxel data of the blast muck piles. Finally, on the basis of the supervoxel clustering results, the automatic fragment recognition and fragmentation calculation of the blast muck piles are realized, and the evaluation metrics for the calculation results of the BFMP are introduced. Dexing Copper Mine, the largest open-pit copper mine in China, is considered the study area. Case study results and discussion tests reveal that the ratios of big blocks in the three selected test areas are 0.91%, 0.21%, and 0.83%, and more than 80% of the fragments in the blast muck piles are less than 300 mm, satisfying the actual situation and confirming the effectiveness and accuracy of the proposed method, which is significant for optimizing blast designs and improving mining efficiency in open-pit operations.

The article aims to select the optimal orientation for open-pit mining at the Aynak copper deposit in the central zone of Afghanistan. The one used is the one that studied integrates geological and environmental datasets derived from over 100 samples analyzed by the United States Geological Survey (USGS), the former Soviet Geological Survey, and the Afghanistan Ministry of Mining and Petroleum. The software used for analysis is QGIS, and AutoCAD is used. This research aims to determine the optimal orientation and design configuration for open-pit extraction during the Aynak project's developmental stage. The result demonstrated that the deposit percentage varies from 0.5 to 2.3 percent. Total ore tonnage is 368 Mt, average grade is 1.7 percent, and metal tonnage is 6 Mt. As a result, the best orientation method is from side to center (from the western side to the eastern side).

Abstract The research objective of this study is to review two Synchronous Reference Frame Phase Locked Loop (SRF-PLL) controllers on the performance of a grid-tied Solar Photovoltaic System (SPVS) for industrial applications. This study contributes to a better understanding of Phase Locked Loop (PLL) controllers, their effect on the performance of Photovoltaic (PV) system and the economic analysis of PV systems to assists Khoemacau Copper Mining (KCM) mine and researchers in making decisions in the same field. In this paper a grid-tied SPVS was modelled using the MATLAB software. The irradiance was varied from 500 w/m 2 to 1000 w/m 2 and the frequency of the grid was changed from 50 Hertz to 2 Hertz, output graphs of the SPVS were extracted and reviewed. The economic analysis was performed by calculating the economic indicators of a project. From the two SRF-PPL controllers, SRF-PLL 1 controller has proven to provide better grid synchronization even during frequency changes. The PV system indicated a levelized cost of electricity (LCOE) of BWP 0.27/kWh (USD 0.02/kWh) and a payback period of 4.2 years. The study offers a thorough and visually appealing report comparing the two SRF-PLL controllers that are used to synchronize the SPVS with the grid. The study also fills in the knowledge gap about the two-capacitor Direct Current-Direct Current (DC-DC) boost converter and most importantly; by showing the current prices of PV systems, this literature has offered financial estimates for the present costs of industrial PV systems.

Screening green and low-carbon paste backfilling materials: Framework development and field application at an abandoned copper mine

Radon, a carcinogen for lung cancer is chemically inert, colourless, odourless, and a radioactive gas that originates from uranium and thorium radioelements. This review article presents radon concentrations and annual effective dose (Ey) amongst workers in copper mines, as well as examining factors influencing radon levels. Findings indicate varying radon concentration levels ranging from acceptable values to those exceeding the occupational exposure limit of 1000 Bq.m−3. For instance, mean radon concentrations ranged from 6.6 Bq.m−3 to 2400 Bq.m−3 under mechanical ventilation, increasing by a factor of eight under nonmechanical ventilation. Similarly, Ey values ranged from 0.80 mSv.y−1 to above the 20 mSv.y−1 threshold, reaching as high as 34 mSv.y−1. Ventilation emerged as the prominent factor influencing radon concentration, alongside temperature, seasonal changes, and mining activities. The study recommends adequate ventilation and routine radon monitoring to improve air quality and protect workers.

Real-time prediction of rock slope stability in active mines remains a critical challenge due to complex geology, dynamic mining stress, and environmental factors. The Pulang Copper Mine, with its complex structural setting and ongoing subsidence, requires advanced monitoring to mitigate failure risk. This study aimed to develop and validate an IoT-driven Enhanced Transformer model for real-time prediction of the Factor of Safety (FoS) and stability classification, integrating numerical simulation, IoT data streaming, and deep learning to improve early-warning capability. A FLAC3D simulation replicated two years of mining (730 daily steps) at six strategic monitoring points, generating time-series data for displacement, velocity, acceleration, and FoS. An IoT framework streamed this data with <5-second latency. An Enhanced Transformer architecture with multi-head self-attention, multi-task learning ( λ =0.5), and advanced feature engineering was trained on the sequences. The Enhanced Transformer achieved superior performance, with testing R² ranging from 0.416 (Station 5, characterized by complex transitional kinematics) to 0.991 (Station 4). Testing MAE ranged [0.003596 (Station 2)–0.019071 (Station 5)], a reduction of up to 88% compared to the Standard Transformer. For four-class stability classification, the model attained a mean test accuracy of 0.993, with critical-class recall reaching 1.0—guaranteeing zero missed alarms for life-threatening critical and unstable conditions, the paramount objective for early-warning systems. The proposed IoT-Enhanced Transformer model provides a highly accurate, real-time solution for slope stability prediction, significantly outperforming conventional models.

Identifying discontinuities in high, steep rock slopes is challenging. This study proposes a high-precision geometric feature measurement method for discontinuities on the basis of point cloud data acquired via unmanned aerial vehicle (UAV) photography. The method effectively extracts key parameters, including orientation, trace length, and spacing. The implementation process comprises five main steps. First, principal component analysis (PCA) is used to extract feature information from the point cloud data. Second, the point cloud is preliminarily segmented via a curvature threshold and the density-based spatial clustering with noise (DBSCAN) algorithm. Third, the density peak clustering (DPC) algorithm is adopted to identify cluster centers and divide the discontinuity sets. Fourth, secondary DBSCAN clustering is performed on each discontinuity set to obtain complete individual discontinuities. Finally, geometric characteristics such as orientation, trace length, and spacing are measured on the basis of the principles of analytic geometry. The experimental results show that the orientation deviation calculated by this method is within an acceptable range and that the proposed method has higher computational efficiency than the traditional DPC method. The influence of random fracture networks (DFNs) on the stability of rock slopes was investigated via discrete element numerical simulations.