Search Results (54)

This article examines the changing social meanings of mining in Roșia Montană (Romania) from late state socialism to the period following the withdrawal of the Roșia Montană Gold Corporation (RMGC), which had proposed a large open-cast gold project there. The study uses an exploratory sequential mixed-methods design. It draws on seven semi-structured interviews with local clergy of different confessions, conducted in spring 2019, and on questionnaire surveys of 282 residents and 45 resettled former residents, carried out in 2020, before the site’s inscription on the UNESCO World Heritage List in 2021. Perceptions are traced across four moments: the state-socialist period; the post-1989 years before the closure of the state mine; the RMGC investment phase; and its aftermath. Treating priests as local moral authorities and interpreters of change, the article finds that mining was remembered not merely as employment but as a source of order, prestige and collective identity under state socialism; that the post-1989 transition bred moral ambivalence; and that the RMGC years polarised the community. At the time of the research, perceptions remained divided but were increasingly articulated through memory, heritage and survival rather than extraction. The article shows how religious actors mediate collective memory and local responses to economic change in post-socialist mining communities. Full article

Gold-mine tailings have attracted increasing interest as alternative constituents in cement-based materials, yet their use in structural concrete remains limited by the lack of multivariable approaches capable of capturing the interaction between tailing fractions with different functional roles. In this study, a tailing-derived fine aggregate and a fine tailing sludge from the Cisneros Project (Santo Domingo, Antioquia, Colombia) were jointly incorporated into structural concrete and evaluated through a response surface methodology based on a central composite design. The tailings were characterized by physical, chemical, mineralogical, and morphological analyses, while concrete mixtures proportioned according to ACI 211 were assessed in terms of 28-day compressive strength. The statistical model revealed a significant quadratic response and a strong interaction between both incorporation variables. The most favorable strength region, based solely on 28-day compressive strength, was identified at sludge contents below 20% and tailing aggregate replacement below 90%, with the latter interpreted as a preliminary mechanical threshold rather than as a practical recommendation for field application. Higher incorporation levels led to strength losses associated with the increasing fineness of the system and greater water demand. This study demonstrates that the performance of tailing-modified structural concrete depends on the coordinated dosage of fractions with distinct roles and provides preliminary mechanical incorporation limits based solely on 28-day compressive strength. Since durability and environmental safety tests, including heavy metal/cyanide leaching, permeability, shrinkage, and chemical resistance, were not conducted, these limits should not be interpreted as definitive recommendations for long-term structural application. Full article

Declining gold discovery rates require prospectivity workflows that are statistically transparent at the regional scale, while remaining adaptable to project-scale geological interpretation. We present a robust sampled weights-of-evidence (sampled-WoE) workflow for gold prospectivity mapping in the Yilgarn Craton, Western Australia. Mine and deposit records were cleaned using 400 m spatial deduplication, yielding 7203 representative mineralized points from 12,036 strict training records. Unlabeled background points were repeatedly sampled within the Yilgarn Craton and stratified by lithology, greenstone-belt membership, and structural-density class. Ten evidence variables were evaluated diagnostically, and an independence audit based on Spearman correlation and Cramér’s V defined a six-layer regional stack comprising lithological setting, fault density, magnetic anomaly, gravity anomaly, K, and Th. Stress tests showed limited sensitivity to random seeds and background-sample sizes, whereas larger exclusion buffers systematically inflated several weights. The conservative no-buffer scenario was therefore selected as the primary model. The highest-ranked 5% of the study area captured 49.23% of the valid representative mineralized points, corresponding to a descriptive 9.85-fold enrichment over random spatial selection; spatial-block out-of-sample validation retained a 45.4% Top-5% capture and 9.1-fold enrichment. The reproducible regional baseline provides a consistent basis for separate project-scale geological refinement and validation. Under spatial-block cross-validation, the out-of-sample Top-5% capture was 45.4% (9.1-fold enrichment), and a non-spatial random cross-validation (49.3%) confirmed that spatial blocking removes the optimism introduced by spatial autocorrelation. Full article

Ground deformation monitoring is critical for safety and environmental management in modern mining. Active mining sites are highly exposed to terrain instabilities and subsidence, risking infrastructure integrity, disrupting operations, and posing hazards to communities. In this context, Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques provide an effective and non-invasive tool capable of detecting millimetric surface displacements. This study implements the Small Baseline Subset (SBAS) technique through an open-source workflow based on the Python package hyp3_sbas, enabling semi-automated and reproducible interferometric processing by combining HyP3 with MintPy. The workflow is applied to the Björkdal gold mine (Sweden), a pilot site of the Horizon Europe XTRACT project focused on enhancing resilience in critical raw material supply chains. Integrating Sentinel-1 viewing geometries resolves the true vertical deformation field, yielding an overall mean velocity of −3.99 mm/year across the mining complex, with significant displacement rates concentrated below the 25th percentile (Q1) at −11.07 mm/year. Sector-specific analysis reveals localised subsidence accelerating over underground footprints and tailings storage facilities (mean velocities of −6.56 and −3.98 mm/year; Q1 thresholds near −13.00 mm/year), contrasting with the geomechanical stability observed at the open-pit area (mean: −0.45 mm/year). The proposed open-source framework shows strong potential for operational satellite-based monitoring, supporting predictive maintenance and early-warning strategies for risk management in mining environments while simplifying and standardising the interferometric processing workflow. Full article

Flotation tailings, the primary solid waste generated during gold extraction, may pose issues such as land occupation, environmental pollution, and geological hazards in open-pit mining areas. This study systematically investigated the environmental characteristics, long-term pollutant release patterns, and migration risks associated with flotation tailings by taking a specific backfill project as a case study and employing short-term leaching tests, long-term column leaching experiments, and multi-model numerical simulations. Short-term leaching tests indicated that tailings leachate exhibited weak alkalinity (pH 8.21−8.45) with low pollutant leaching concentrations, meeting the fundamental requirements for open-pit backfilling. Notably, leaching characteristics varied significantly among tailings from different sources, and an extended storage duration enhanced chemical stability. Long-term leaching tests identified nine characteristic pollutants, including fluoride and sulfate, with their release patterns categorized into three types: continuous slow release, initial rapid leaching, and delayed/complex release. Furthermore, simulation results from the HYDRUS and MODFLOW/MT3DMS models indicated that the maximum predicted concentrations of characteristic pollutants in the surrounding soil and groundwater will remain at low levels for 50 years post-backfilling. The site’s “micro-to-weakly permeable” strata exhibited significant pollutant retention capabilities. Based on these experimental and simulation results, a three-tier risk management system—”source control, process monitoring, and end-point surveillance”, was developed to provide technical support for the long-term environmental safety of the flotation tailings backfill project. This study revealed the environmental risk characteristics associated with the storage of flotation tailings, including land occupation, environmental pollution, and the potential for geological hazards in open pits. Furthermore, the leaching characteristics, long-term release patterns, and migration mechanisms of tailings used to backfill open pits have been elucidated, providing theoretical references and practical guidance for similar solid waste resource recovery and backfilling projects. Full article

Economic evaluation plays a pivotal role in investment decision-making for mining projects, especially under volatile market conditions. In this study, a risk-based decision-support framework is developed to assess the economic sustainability of an open-pit gold mining operation by integrating sensitivity analysis with Monte Carlo simulation, where Net Present Value (NPV) is used as the primary performance indicator. The proposed approach provides a flexible and practical computational framework for evaluating investment risk under uncertainty. A case study from an open-pit gold mine in Kyrgyzstan is used to compare two scenarios: continuation of the current operation and an alternative option involving a $30 million investment to improve mill processing performance. The sensitivity analysis shows that gold price, mining cost, and recovery rate are the most influential parameters affecting project outcomes, while Monte Carlo simulation is used to capture uncertainty in these variables and to generate a distribution of possible NPV results. The results indicate that gold price and recovery rate have a dominant influence on project value, and that improving mill performance leads to higher recovery and increased economic returns. The simulation results show a median NPV of approximately 220 million USD with a probability of negative NPV (17.52%), while the enhanced scenario achieves an IRR of approximately 13%, indicating improved financial performance. In addition, the findings suggest that accounting for uncertainty provides more reliable support for investment decisions and contributes to a more efficient use of mineral resources. In this context, the proposed framework contributes to sustainability assessment tools by supporting economically sustainable resource utilization through risk-based evaluation of recovery improvement under uncertainty. While the present study focuses on the economic pillar of sustainability, the framework can provide a basis for future integration of environmental and social indicators. Full article

Thin, stratiform ore bodies pose persistent challenges for conventional underground mining due to limited thickness, high ore-grade dilution, and restricted operating space. This study introduces a morphology-based scoring framework for assessing the suitability of ore deposits for the Narrow Reef Mining Equipment method—an ultra-low-profile mechanized technique designed for stoping width up to 1.7 m and inclination up to 22°. A dataset comprising 178 ore deposits/mines was evaluated using integrated geological, morphological, and economic criteria. The results demonstrate that NRE suitability is primarily controlled by ore morphology, which is governed by the genetic model. The highest compatibility is associated with stratiform mineralization formed in layered mafic–ultramafic intrusions (e.g., Bushveld Complex, Great Dyke) and sediment-hosted stratiform copper and gold deposits developed along laterally extensive depositional or redox-controlled interfaces (e.g., Kupferschiefer, Witwatersrand). Although genetic origin defines deposit-scale suitability, secondary geological disturbances—post-genetic tectonism and hydrothermal overprinting—restrict NRE applicability to individual ore bodies within otherwise favourable deposits. By formalizing ore body dip and thickness into standardized efficiency and suitability classes, the proposed scoring system provides a reproducible early-stage geological screening methodology for evaluating NRE applicability during initial mine project development. Economic evaluation based on data from the Unki Mine provides operational validation of the proposed scoring framework and demonstrates that NRE increases monthly output at reduced stoping widths while maintaining ore grades and improving operational safety compared to conventional methods. Full article

The inherent complexity of the decision-making process in early-stage mining projects demands high-risk investments, often based on limited and low-confidence data. The geometallurgical approach offers an opportunity to mitigate uncertainties through the development of mathematical models to predict key process variables, such as recovery and specific energy. This research quantifies the economic and technical impact of incrementally increasing the number of variables in a geometallurgical model of a copper-gold-silver polymetallic deposit during the Pre-Feasibility Study (PFS) phase. Regression models were developed to correlate grades (copper, gold, and silver) and metallurgical variables (recovery and specific energy). The models were applied to eight geometallurgical block models, and technical and economic results were generated using Direct Block Sequencing (DBS). Across all scenarios, increased model complexity had a modest effect on production metrics but caused notable variation in Net Present Value (NPV), reaching a 6.92% difference between scenarios. Thus, adding more geometallurgical variables is justified not by higher production tonnage but by the potential to enhance and stabilize NPV through improved sequencing based on key value drivers (costs, recoveries and processing time). These findings highlight the value of early geometallurgical modeling, even with limited data, for producing a more integrated and improved economic assessment. Full article

Specific computational methods, such as machine learning algorithms, can assist mining professionals in quickly and consistently identifying and addressing classification issues related to mineralized horizons, as well as uncovering key variables that impact predictive outcomes, many of which were previously difficult to observe. The integration of numerical and categorical variables, which are part of a dataset for defining ore grades, is part of the daily routine of professionals who obtain the data and manipulate the various phases of analysis in a mining project. Several supervised and unsupervised machine learning methods and applications integrate a wide variety of algorithms that aim at the efficient recognition of patterns and similarities and the ability to make accurate and assertive decisions. The objective of this study is the classification of gold ore or gangue through supervised machine learning methods using numerical variables represented by grade and categorical variables obtained through drillholes descriptions. Four groups of variables were selected with different variable configurations. The application of classification algorithms to different groups of variables aimed to observe the variables of importance and the impact of each one on the classification, in addition to testing the best algorithm in terms of accuracy and precision. The datasets were subjected to training, validation, and testing using the decision tree, random forest, Adaboost, XGBoost, and logistic regression methods. The evaluation was randomly divided into training (60%) and testing (40%) with 10-fold cross-validation. The results revealed that the XGBoost algorithm obtained the best performance, with an accuracy of 0.96 for scenario C1. In the SHAP analysis, the variable As was prominent in the predictions, mainly in scenarios C1 and C3. The arsenic class (Class_As), present mainly in scenario C4, had a significant positive weight in the classification. In the Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC) curves, the results showed that XGBoost/scenario C1 obtained the highest AUC of 0.985, indicating that the algorithm had the best performance in ore/gangue classification of the sample set. The logistic regression algorithm together with AdaBoost had the worst performance, also varying between scenarios. Full article

Throughout the past four decades, most projects related to mercury in Artisanal Gold Mining (AGM) have been dedicated to monitoring the environmental and health impacts of the activity without actually proposing effective solutions to tackle the issue. Recently, the UN and a few NGOs have been dedicated to bringing solutions to artisanal gold miners, but the outcomes remain modest, given the funds expended and the considerable effort invested by interventionists. This commentary paper critiques some of the interventions observed in the last four decades and suggests some technical strategies to approach artisanal miners to reduce mercury losses. It is stressed that mercury elimination is a consequence of good engagement with miners that creates opportunities to show them how to produce more gold with cleaner methods. We recommend that academics educate a new generation of engineers working with AGM to adopt a more practical approach, ensuring they understand the needs, motivations, and skills of artisanal miners before proposing solutions. Full article

Deforestation caused by gold mining in the Ecuadorian Amazon has increased by 300% in the last decade, leading to severe environmental degradation of water and land resources. Effective remediation and revegetation technologies are still needed to address this issue. This study aimed to foster revegetation on 0.5 hectares of degraded land in Naranjalito, a mining site in the Ecuadorian Amazon, by applying plant-based biocompost and biochar and planting Ochroma pyramidale and Arachis pintoi, two pioneer species. The project’s objective was to evaluate the impact of these treatments on vegetation cover recovery through physicochemical and microbiological improvements in the soil. Four blocks and sixteen experimental plots were established: eight plots received treatments with varying doses of biocompost+biol (BIOC), four plots included plantations without biocompost (Not-BIOC), and four served as control plots (bare land). Over six months, dasometric characteristics of O. pyramidale and the expansion of A. pintoi were recorded. The data were analyzed using multivariate methods. The results revealed significant differences between treatments, with BIOC plots T4 and T1 showing greater improvements in vegetation development compared to Not-BIOC plots T3 and T2, confirming the positive influence of biocompost+biol. The BIOC treatment favored not only the planted species but also the secondary successional plant communities including certain grasses, leguminous plants, and other shrub and tree species, thus accelerating the revegetation process. This study demonstrates that biocompost application is an effective strategy to enhance plant recolonization on land severely degraded by gold mining in the Ecuadorian Amazon. Full article

Numerous research studies have long established the causes and consequences of the depopulation of certain regions in Europe, but it seems that there are no systematic approaches to implementing the policy of managing abandoned areas. Following years of demographic decline in settlements, the 2022 census revealed depopulated clusters in Serbia—regions with 20 or fewer residents or even no inhabitants at all. The areas of depopulated settlements are growing territorially from the south towards the north. This paper adopts a broader interpretation of brownfield land, defining it as any previously used land that is no longer employed for commercial purposes, serving as the theoretical foundation. Although they seem economically hopeless, some depopulated clusters have become the subject of research for the exploitation of mineral resources such as gold, copper, zinc, uranium, lithium and coal. The main problem is that depopulated clusters have acquired an ecological stability that would be disrupted by the opening of mines and massive construction. The changes in land use were analyzed using time series data and a formal database of natural resources from these communities. The primary methodological framework was based on the correlation between population size, utilized areas, and the ecological stability coefficient. This study aimed to explore the relationship between the proportion of arable land within a spatial unit and its depopulation rate while also examining how arable land and mineral resources could influence the potential revitalization of rural wastelands in Serbia’s depopulated areas. The primary findings indicate a significant correlation between population decline and changes in the natural environment of abandoned clusters, as well as the significant potential of clusters as rural brownfields. While it is natural to continue with ecological and green space projects, the current liberal and centralized mining management policy can create major problems for the remaining population. Full article

A scientific and reasonable microseismic monitoring sensor network is crucial for the prevention and control of rockmass instability disasters. In this study, three feasible sensor network layout schemes for the microseismic monitoring of Sanshandao Gold Mine were proposed, comprehensively considering factors such as orebody orientation, tunnel and stope distributions, blasting excavation areas, construction difficulty, and maintenance costs. To evaluate and validate the monitoring effectiveness of the sensor networks, three layers of seismic sources were randomly generated within the network. Four levels of random errors were added to the calculated arrival time data, and the classical Geiger localization algorithm was used for locating validation. The distribution of localization errors within the monitoring area was analyzed. The results indicate that when the arrival time data are accurate or the error is between 0% and 2%, scheme 3 is considered the most suitable layout; when the error of the arrival time data is between 2% and 10%, scheme 2 is considered the optimal layout. These research results can provide important theoretical and technical guidance for the reasonable design of microseismic monitoring systems in similar mines or projects. Full article

In mine planning, uncertainty assessment is essential to properly value a mining project. Geological, operational, and economical risks have to be considered to find the variable values that maximize the profit of the project. In this research, geological uncertainties are taken into account to assess the economic value of an underground gold mine. The scenarios considered are the tonnage-grade curves which are simulated by the Monte Carlo method. The decision variables are the cutoff grade (CoG), the Life of Mine (LoM), and operational variables, namely the mining and the processing capacity. In order to assess the economic value, we maximize the Net Present Value (NPV), which is carried out by a Genetic Algorithm (GA). This optimization, so-called implicit optimization, generates results of the probabilistic model which are compared with the deterministic one; the results found for a real underground gold mine show that, in the probabilistic case, the Net Present Value is higher and the time horizon is shorter than the results of the deterministic case, and the mining and the processing capacity are higher for the probabilistic case than the deterministic one. Full article

The extraction of mining resources, as well as processing processes such as ore beneficiation and smelting, generate large amounts of tailings that are difficult to directly utilize. Meanwhile, substantial filling materials are required for the voids formed after mining operations, and the environmental issues and safety hazards brought on by massive solid waste disposal cannot be ignored. By utilizing solid waste with alkaline and pozzolanic activity as the binder component and gold tailings as filler aggregate to prepare filler material to fill up the void areas, the purpose of waste treatment can be achieved. In this study, salt sludge, steel slag, ground granulated blast furnace slag, and gold tailings were used to prepare all-solid waste fluidized filling material for filling mine void areas, which not only solves the engineering safety problem of easy collapse of the mine airspace in the mining process but also ensures a backfill effect with high strength, which continuously guarantees the uninterrupted progress of the mining project. At the same time, the preparation of fluidized materials can consume a large amount of tailings and other solid waste, solving the problem of their stockpiling. The components of the solid wastes used are all general industrial solid wastes, so the preparation of the fluidized materials will not have an impact on the surrounding environment. The effects of binder ratios on the workability of the filling materials were investigated by means of the slump and slump flow tests. Combined with the unconfined compressive strength test, the change in backfill material strength with curing age and the water–binder ratio was studied. The experimental results showed that the slump and slump flow value of the filling material were positively correlated with the water–binder ratio. The water–binder ratio range satisfying a slump value of 180~260 mm and a slump flow value not less than 400 mm was 0.95~1.106. However, the strength decreased with the increase in the water–binder ratio, conforming to a hyperbolic relationship. The all-solid waste fluidized filling material had strengths not less than 0.22, 1.09, and 1.95 MPa at 3, 7, and 28 d, respectively, meeting the workability requirements. Finally, a method for determining the optimal range of water–binder ratio considering both workability performance and strength is proposed based on the relationship between slump value, slump flow value, unconfined compressive strength, and the water–binder ratio. Full article