Mining Region Research Articles

Recognizing Traces of Colonialism and Coloniality in a South African Mining Region: Surfacing the Past in Regional, Ethnographic and Well-Being Research

Recent discussions on colonialism and coloniality in academic and community contexts have not been fully informed, only understanding the past from a present-day context. This article provides a deeper, more experiential understanding of this culturally complex phenomenon by combining three research methodologies: structured regional research, ethnography informed research and multidisciplinary wellbeing research. The article examines traces of colonialism in the Far West Rand area of South Africa, at a time of expanding mining operations when it was rare for people to think of themselves as ‘colonists’ with a colonial vision. Yet, structured regional research points to a history of immense urbanisation, linked to immigration and strong, almost dominant, features of colonialism. Two other, totally different, research methods have also observed the same phenomenon, adopting a more experiential angle to communities in the Far West Rand. These community experiences relate more closely to a coloniality imagery manifested primarily in ideas and opinions about contemporary service delivery, poverty and land use issues.

Contamination, ecological, and human health risks of heavy metals in water from a Pb-Zn-F mining area, North Eastern Nigeria.

In Nigeria, artisanal mining has become a serious issue. In the Nigerian mining region of Arufu Pb-Zn-F, this study assessed the level of pollution, ecological hazards, and health risks related to the presence of metals in the water. In the dry and rainy seasons, 36 water samples (20 from the ground, 10 from the surface, and six from the mine) were gathered. Samples were examined for the presence of heavy metals such as Cr, Co, Ni, Cu, Zn, As, Cd, and Pb. Other than Cu, Zn, As, Cd, Sb, and Cd (surface water, dry season), which were below the acceptable norm, all water samples had metals over the suggested limits. Heavy metals from nearby mining activities polluted the water, according to contamination evaluations utilizing the contamination factor (CF). Metals in the water may pose very significant ecological dangers, according to ecological risk assessments. The evaluation of human health risks revealed that both adults and children in the region are susceptible to carcinogenic and non-carcinogenic health hazards since the hazard index (HI) values for both indices were above 1 × 10-5 and above 1, respectively. This report emphasizes the need for monitoring mining operations in the nation to safeguard public health.

High energy events as a combined effect of human impact and geoenvironmental factors - the case study based on GNSS data

In the Upper Silesian Coal Basin (USCB) mining region in Poland, coal production has been gradually reduced for many years. Nevertheless, the number of high-energy tremors remains at a similar level or decreases much slower than production. We analyze this problem in the aspect of geological setting and on the base of geodetic data. We explain the paradox by specific interaction between man-induced and natural tectonic stress as seasonal hydrological effects. Anomalous energies released during large seismic events exceeded the predetermined threshold, typical for mining tremors in the area. Further, the authors point out the seasonal occurrence of these events. Temporal variations of distances between continuously operating GNSS (Global Navigation Satellite Systems) reference stations were analyzed, and linear strain, inferred from these geodetic observations, corresponded to high-energy tremors in the area. Consequently, the seismic events usually occurred when the analyzed baseline performance demonstrated significant seasonal increases or decreases of evaluated temporal distribution of strain. The aim of the analysis was to evaluate the relationships between the characteristics of the time series of deformations and the occurrence of seismic tremors of energy E ≥ 3 x 107J occur. Seasonal occurrences of high-energy seismic events as the energy they released suggest the influence of environmental factors.

Silicosis and silicotuberculosis among respiratory hospital admissions: A cross-sectional survey in northern Tanzania.

There is little evidence describing respiratory disease among 40.5 million small-scale miners worldwide. To describe the prevalence and clinical characteristics of adult respiratory inpatients with silicosis and silicotuberculosis in a tertiary hospital in Tanzania that serves a small-scale mining region. In this retrospective, cross-sectional survey, patient files from admissions between 2010 and 2020 were opportunistically selected and included if a respiratory diagnosis had been made. Of 223 patients with respiratory conditions, 32 (14.3%; 95% confidence interval (CI) 10.0 - 19.6) were diagnosed with silicosis and 17 (7.6%; 95% CI 4.5 - 11.9) with silicotuberculosis. Mining was the most frequent occupation in those with silicosis (n=15/32; 46.9%) and silicotuberculosis (n=15/17; 88.2%). Of those with silicosis or silicotuberculosis, 26/49 (53.1%) were aged <45 years. Our study suggests that silicosis and silicotuberculosis are common among male and female respiratory inpatients with occupational exposure. The study highlights the role of occupational exposures in respiratory disease in developing economies. What the study adds. This retrospective, cross-sectional survey describes the prevalence of silicosis and silicotuberculosis among adult respiratory inpatients admitted to a tertiary hospital in northern Tanzania. It is the first study to describe the prevalence and characteristics of respiratory inpatients with silicosis and silicotuberculosis in a small-scale mining region of Africa. A high prevalence of silicosis (14.3%) and silicotuberculosis (7.6%) was found. Patients were often aged <45 years, and the majority required oxygen therapy.Implications of the findings. The high prevalence of advanced silicosis and silicotuberculosis in miners presenting at a young age raises concerns about high occupational silica exposures and, importantly, suggests a need for community-based research, which our team is planning to undertake.

An InSAR Deformation Phase Retrieval Method Combined with Reference Phase in Mining Areas

The acquisition of precise deformation data, including the entirety of the subsidence basin resulting from subterranean mining operations, assumes critical significance in the context of surface impairment monitoring during the course of mining activities. In light of the constraints associated with InSAR technology when applied to the surveillance of expansive deformation gradient mining regions, an innovative approach is advanced herein for InSAR deformation phase retrieval. This approach integrates a reference phase, derivable through a variety of means, including pre-existing models or measurements. Initially, the reference deformation phase is subjected to subtraction from the wrapped InSAR deformation phase, culminating in the derivation of the wrapped phase indicative of the residual phase. Notably, it is posited that the fringe density characterizing the wrapped phase of the residual phase is theoretically diminished in comparison to that of the InSAR wrapped phase. This reduction in complexity in phase unwrapping ensues as a direct consequence. Subsequent to this, the phase retrieval process is effectuated through the summation of the reference phase and the unwrapped phase pertaining to the residual phase. The study harnesses Sentinel-1A and ALOS PALSAR-2 data, employing the PIM-predicted outcomes and GNSS-RTK monitoring outcomes as reference phases for the execution of phase retrieval experiments in two designated study areas. The computation of subsidence is subsequently realized through the combination of the displacement vector depression angle model and the retrieved phase, with the accuracy thereof corroborated through the utilization of leveling data. The experimental findings underscore the efficacy of the reference phase retrieval methodology in securing a more precise deformation phase characterization within expansive deformation gradient mining regions, thereby demonstrating the suitability of this methodological approach.

Rheological mechanical properties and its constitutive relation of soft rock considering influence of clay mineral composition and content

Rheological mechanical properties of the soft rock are affected significantly by its main physical characteristics-clay mineral. In this study, taking the mudstone on the roof and floor in four typical mining regions as the research object, firstly, the clay mineral characteristic was analyzed by the X-ray diffraction test. Subsequently, rheological mechanical properties of mudstone samples under different confining pressures are studied through triaxial compression and creep tests. The results show that the clay mineral content of mudstone in different regions is different, which leads to significant differences in its rheological properties, and these differences have a good correlation with the content of montmorillonite and illite-montmorillonite mixed layer. Taking the montmorillonite content as an example, compared with the sample with 3.56% under the lower stress level, the initial creep deformation of the sample with 11.19% increased by 3.25 times, the viscosity coefficient and long-term strength decreased by 80.59% and 53.94%, respectively. Furthermore, based on the test results, the damage variation is constructed considering the montmorillonite content and stress level, and the M–S creep damage constitutive model of soft rock is established. Finally, the test results can be fitted with determination coefficients ranging from 0.9020 to 0.9741, which proves that the constitutive relation can reflect the influence of the clay mineral content in the samples preferably. This study has an important reference for revealing the long-term stability control mechanism of soft rock roadway rich in clay minerals.

Mining knowledge: Nineteenth-century Cornish electrical science and the controversies of clay.

Michael Faraday's laboratory experiments have dominated traditional histories of the electrical sciences in 1820s and 1830s Britain. However, as this article demonstrates, in the mining region of Cornwall, Robert Were Fox fashioned a very different approach to the study of electromagnetic phenomena. Here, it was the mine that provided the foremost site of scientific experimentation, with Fox employing these underground locations to measure the Earth's heat and make claims over the existence of subterranean electrical currents. Yet securing philosophical claims cultivated in mines proved challenging for Fox, with metropolitan audiences, including Faraday, loath to give credit to the results of these underground experiments. This article explores how Fox developed a way of modeling his mine experiments, using clay samples, to communicate knowledge from industrial Cornwall to urban centers of elite science. It argues that the mine was an epistemologically complex venue of scientific activity, at once seeming to provide a way of examining nature directly, without recourse to laboratory contrivance, while simultaneously being a place where knowledge claims were hard to verify without access to these physically challenging locations. In exploring Fox's work, this study contributes to a growing literature of spatial investigation that takes the vertical as its unit of analysis.

Micro-Factors-Aware Scheduling of Multiple Autonomous Trucks in Open-Pit Mining via Enhanced Metaheuristics

Traditional open-pit mineral transportation systems are typically subject to manual command, frequently leading to vehicular delays and traffic congestion. With the advancement of automation and electrification technologies, this study proposes a highly accurate scheduling method for multiple autonomous trucks in an open-pit mine. This model considers micro-level temporal and spatial factors to tackle the task of scheduling autonomous trucks within open-pit mines. The cost function of the concerned scheduling problem is a comprehensive evaluation of energy consumption, time, and output. Beyond the loading and unloading activities, the model also factors in the charging requirements of autonomous trucks in mining regions. The scheduling model integrates a Voronoi diagram search and optimal spatial path time matching, aiming to provide superior mission planning and decision-making solutions for autonomous trucks in mining regions. For an efficient solution to the scheduling problem, we propose an improved-evolution artificial bee colony (IE-ABC) algorithm. This algorithm improves the global search and re-initialization processes and conducts algorithm ablation experiments to closely examine their impact on optimization. Simulation results across various algorithms, cost function definition strategy, and encoding strategy show that our method can improve scheduling performance in energy consumption and time. Experimental results demonstrate that the proposed model and algorithm can effectively solve the scheduling decision-making problem in an unmanned open-pit mine.

Tracing acid mine drainage and estuarine Zn attenuation using Cd and Zn isotopes

It has been estimated that the acid mine drainage (AMD) impacted Odiel river basin in southern Spain supplies 0.37% and 15% of the global riverine fluxes of Cd and Zn to the oceans, respectively (Sarmiento et al., 2009). However, the behaviour of Cd and Zn in the Ria of Huelva estuary, which connects the Odiel and Tinto watersheds with the Gulf of Cadiz, has yet to be fully investigated. Furthermore, very few studies have investigated Cd and Zn isotope behaviour in estuaries worldwide. This study presents Cd and Zn concentrations and isotopic compositions for the Ria of Huelva estuary and surrounding watersheds, sampled in 2017 and 2019. Sulfide-rich rock samples extracted from three mines yield Cd and Zn isotope compositions that range from –0.14‰ to +0.07‰ (n = 4) for δ114Cd and –0.01‰ to +0.29‰ (n = 4) for δ66Zn. However, a uniform riverine signal of about +0.02‰ for Cd and +0.17‰ for Zn indicates that tracing of individual mining regions using Cd and Zn isotopes is challenging. Limited variability was observed in dissolved δ114Cd values throughout the watershed, including AMD, the estuary, and the Gulf of Cadiz, with a mean value of ±0.00 ± 0.13‰ (n = 25, 2 SD; excludes one AMD outlier, at +0.48‰), including both 2017 and 2019 data. By contrast, δ66Zn values ranged from –0.12‰ to +0.35‰ (n = 28) for the same geographical and temporal scope. In May 2017, a large spill from an abandoned mine, La Zarza, resulted in a drastic increase in the concentrations of trace metals reaching the estuary compared to 2019, but no impact of this mine spill on Cd or Zn isotope compositions is observed. In 2019, an increase in δ66Zn values in the estuary coincided with high pH values (up to pH = 8.8) and chloride concentrations (2.73%), which may reflect an alkaline anthropogenic input from the active neighbouring industrial complex. Overall, Cd concentrations and isotope compositions in the estuary are largely consistent with conservative mixing behaviour. By contrast, Zn behaviour is non-conservative, with removal of 49–97% of dissolved riverine Zn in the estuary during the period 2017–2019, associated with a relatively small isotopic shift to lighter Zn isotope compositions. Removal of Zn to the particulate phase in the Ria of Huelva estuary therefore largely attenuates high riverine Zn fluxes from AMD, indicating that previously estimated Odiel river basin Zn fluxes were overestimated. Nevertheless, the variable but generally light AMD Cd and Zn isotope compositions, coupled with high dissolved metal concentrations, suggest that Cd and Zn isotopes may be useful tracers of regionally averaged AMD inputs to the Gulf of Cadiz and beyond.

Geostatistical based optimization of groundwater monitoring well network design

Monitoring groundwater quality in economically important and other aquifers is carried out regularly as part of regulatory processes for water and other resource development. Many water quality parameters are measured as part of baseline monitoring around mining and onshore gas resource development regions to develop improved understanding of the hydrogeological system as well as to inform managerial decisions to assess and manage contamination risks and health hazards. Water quality distribution in an aquifer is most often inferred from point measurements from limited number of bores drilled at arbitrary locations. Estimating the distribution of water quality parameters in the aquifer based on these point measurements is often a challenging task and results in high uncertainty in the estimates due to limited data availability. Minimizing uncertainty can be achieved by drilling more bores to collect water quality data and several approaches are available to identify optimal bore hole locations to minimize estimation uncertainty. However, optimization of borehole locations is difficult when multiple water quality parameters are of interest and have different spatial distributions in the aquifer. In this study we use geostatistical kriging to interpolate a large number of groundwater quality parameters. Then we integrate these predicted values and use the Differential Evolution algorithm to determine optimal locations for bores that would simultaneously reduce spatial prediction uncertainty of all parameters. The method is applied for designing a groundwater monitoring network in the Namoi region of Australia for monitoring groundwater quality in an economically important aquifer of the Great Artesian Basin. Optimal locations for 10 new monitoring bores are identified using this approach.

A comparative evaluation of deep convolutional neural network and deep neural network-based land use/land cover classifications of mining regions using fused multi-sensor satellite data

Accurate land use/land cover (LULC) classifications using satellite data is a challenging task due to the limited spatial and spectral resolutions of different satellite data. Moreover, the challenge is more severe for LULC classification of mining regions as no standardized spectral signature is available for the detection of coal mining regions. Thus, the current study aims to design deep learning algorithms using fused data of three satellite sensors (LISS-IV, Landsat-8, and Sentinel-2A) for LULC classification of mining regions. The fused image was derived from three satellite sensors using a discrete cosine transform (DCT) with a spatial correlation approach. A comparative evaluation of deep convolutional neural network (DCNN) and deep neural network (DNN) models in LULC classification of mining regions is conducted. Moreover, the performances of the models with fused data are compared with the performance of the same model with individual sensor data. The study area chosen to execute the work is Jharia Coalfield, which comprises five key LULC types, viz. barren land, coal mining region, built-up area, water body, and vegetation. A total of 6000 image samples of 6 × 6 sizes and 216,000 pixels were used to train and validate the DCNN and DNN models, respectively. That is, the DCNN model uses the object dataset and DNN uses the pixel dataset for model training and validation. The DCNN model achieved high training and validation accuracies (99.8% and 99.2%), while the DNN model achieved relatively lower accuracies (85.3% and 81.8%). The study evaluates the performance of both models further by employing confusion matrix parameters to measure accuracy, error, precision, and recall for each class. The results reveal that the DCNN model consistently outperforms the DNN model, showcasing accuracy, error rates, precision, and recall ranging from 99.83% to 99.99%, 0.01% to 0.17%, 99.52% to 99.99%, and 99.40% to 99.99% on the training dataset, and 99.50% to 99.99%, 0.01% to 0.50%, 98.35% to 99.99%, and 98.33% to 99.99% on the validation dataset, respectively. In comparison, the DNN model demonstrates values ranging from 90.36% to 99.90%, 0.01% to 9.64%, 75.10% to 99.53%, and 66.99% to 99.99% on the training dataset, and 88.50% to 99.94%, 0.06% to 11.50%, 72.25% to 99.66%, and 62.50% to 99.99% on the validation dataset. These findings showed that the DCNN classification algorithm outperforms the DNN classification algorithm. Moreover, the comparative performances of the DCNN model with different datasets indicate that the model with fused images outperformed the model with individual sensor images.

Of hopeful narratives and historical injustices – An analysis of just transition narratives in European coal regions

In recent years, the public discourse on the phase-out of carbon-intensive technologies and practices has come to a near consensus that a “just transition” is required. Yet, this term seems to have as many meanings as there are stakeholders using it. The purpose of this paper is to unpack the different meanings that regional stakeholders assign to it and the underlying dimensions of in(justice) that they invoke in their political communication.To this end, we employ a policy narrative analysis to study and compare the political discourse in four European coal and carbon-intensive mining regions: Ida-Virumaa (Estonia, oil shale), the Rhenish mining region (Germany, lignite), Upper Silesia (Poland, hard coal) and Western Macedonia (Greece, lignite). Specifically, we address the following research questions: Which narratives are characterising the political discourse around just transition? Which (in)justices are being invoked? Which patterns, similarities or differences are recognizable between regions?We found that hopeful narratives describing structural change as an opportunity to reinvent the region are prevalent in all regions. Strong narratives of resistance only prevail in Upper Silesia and Ida-Virumaa where a phase-out decision has not yet been adopted. In terms of injustices, we find surprisingly little evidence that injustices related to the immediate effects of the transformation (e.g. lay-offs and compensation for workers and companies) play an important role. Instead, the aspects related to the historical injustices produced by the legacy industrial system prevail. And perhaps most importantly, questions about access and allocation of the opportunities of the imminent transition are key and should be addressed more explicitly.

The impact of nickel mining on vegetation index in Molawe Sub-district, North Konawe District, Southeast Sulawesi, Indonesia

Abstract. Adidharma MA, Supriatna, Takarina ND. 2023. The impact of nickel mining on vegetation index in Molawe Sub-district, North Konawe District, Southeast Sulawesi, Indonesia. Biodiversitas 24: 4581-4588. Nickel mining activities in Molawe Sub-district, North Konawe District, Southeast Sulawesi, Indonesia have modified the land cover structure over time due to increased mining exploitation zones. This study intends to assess changes in land cover in the Molawe Sub-district, particularly around mining regions. The NDVI index was applied to Landsat 7 ETM+ satellite imagery data in 2001 to identify land cover conditions before mining activities, then to Landsat 8 OLI imagery data in 2015 and 2020 to identify land cover after mining activities. These data are then used to compute annual changes in the extent of each land cover. The NDVI classification produces four land cover types: non-vegetation, open soil, sparse vegetation, and moderate vegetation. The study shows that non-vegetation and open ground cover types experienced a significant increase in area from 2001 to 2015 and from 2015 to 2020. Meanwhile, sparse vegetation forest cover experienced a reduction in area from 2001 to 2015 and 2015 to 2020. In contrast to sparse vegetation, the moderate vegetation cover is experiencing a minor increase in area. Based on these results, relevant policymakers need to formulate policies to mitigate environmental impacts that may arise in the future.

Stability Assessment of Trackbed under New Railway Line Passing Abandoned Mine Region

Stability Assessment of Trackbed under New Railway Line Passing Abandoned Mine Region

Receptor model-based source-specific health risks of toxic metal(loid)s in coal basin-induced agricultural soil in northwest Bangladesh.

Toxic metal(loid)s (TMLs) in agricultural soils cause detrimental effects on ecosystem and human health. Therefore, source-specific health risk apportionment is very crucial for the prevention and control of TMLs in agricultural soils. In this study, 149 surface soil samples were taken from a coal mining region in northwest Bangladesh and analyzed for 12 TMLs (Pb, Cd, Ni, Cr, Mn, Fe, Co, Zn, Cu, As, Se, and Hg). Positive matrix factorization (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models were employed to quantify the pollution sources of soil TMLs. Both models identified five possible sources of pollution: agrochemical practice, industrial emissions, coal-power-plant, geogenic source, and atmospheric deposition, while the contribution rates of each source were calculated as 28.2%, 17.2%, 19.3%, 19% and 16.3% in APCS-MLR, 22.2%, 13.4%, 24.3%, 15.1% and 25.1% in PMF, respectively. Agrochemical practice was the major source of non-carcinogenic risk (NCR) (adults: 32.37%, children: 31.54%), while atmospheric deposition was the highest source of carcinogenic risk (CR) (adults: 48.83%, children: 50.11%). NCR and CR values for adults were slightly higher than for children. However, the trends in NCR and CR between children and adults were similar. As a result, among the sources of pollution, agrochemical practices and atmospheric deposition have been identified as the primary sources of soil TMLs, so prevention and control strategies should be applied primarily for these pollution sources in order to protect human health.

Investigating the Mechanism of Continuous–Discrete Coupled Destabilization of Roadway-Surrounding Rocks in Weakly Cemented Strata under Varying Levels of Moisture Content

This study examines frequent disasters, including large-scale deformation and collapse, caused by underground mining in weakly cemented strata in Western China. The weakly cemented rock’s unique characteristics, including low strength and easy disintegration, demonstrate a different damage pattern than that traditionally seen in the central and eastern regions. Using Fast Lagrangian Analysis of Continua-Particle Flow Code (FLAC2D-PFC2D) coupling, we model the strata, focusing on the 3-1 coal seam roadway at Hongqinghe mine. This study investigates the damage–rupture–destabilization progression in the peripheral rock under varying levels of moisture content. Our findings indicate that a water content of ω = 5.5% is the threshold for roadway damage, and moisture content &lt;5.5% yields minimal rock deformation. However, moisture content &gt;5.5% abruptly increases cracks and shifts the rock’s force chain, causing significant deformation and affecting the ceiling the most. Moreover, higher levels of moisture content weaken the anchor solid’s performance, with two primary failure modes: anchor interface slippage (comprising five stages: elasticity, elasticity–shear hardening, elasticity–shear hardening–decohesion, shear hardening–decohesion, and decohesion) and shear damage. These insights are vital for improving numerical simulations of underground mining, obtaining a more accurate understanding of mineral pressure disasters in weakly cemented strata mining regions in Western China, and developing a solid foundation for the better control of such strata.

Transplacental transfer of cobalt: Evidence from a study of mothers and their neonates in the African Copperbelt

BackgroundTransfer of the trace metal cobalt (Co) from mother to foetus has not been documented in populations with high environmental exposure to Co, as is the case in the African Copperbelt mining region. We analysed data obtained from 246 mother-infant pairs included (at delivery) in a previously published case-control study on birth defects, done in Lubumbashi (Democratic Republic of Congo) between March 1, 2013, and Feb 28, 2015. Methods: Co was measured by Inductively Coupled Plasma Mass Spectrometry in maternal blood, maternal urine, umbilical cord blood and placental tissue, as available. ResultsThe Co concentrations [geometric mean (GM) with interquartile range (IQR)] in maternal blood (GM 1.77 µg/L, IQR 1.07–2.93) and urine (GM 7.42 µg/g creatinine, IQR 4.41–11.0) were highly correlated (Spearman r = 0.71, n = 166; p < 0.001) and considerably higher than reference values determined for general populations elsewhere in the world. The concentrations of Co in umbilical cord blood (GM 2.41 µg/L) were higher (Wilcoxon test, p < 0.001) than in maternal blood (GM 1.37 µg/L), with a correlation between both values (Spearman r = 0.34; n = 127, p < 0.001). Co concentrations in placental tissue (geometric mean 0.02 µg/g wet weight) correlated with concentrations in maternal blood (Spearman r = 0.50, n = 86, p < 0.001) and in neonatal blood (Spearman r = 0.23, n = 83, p = 0.039). ConclusionThis first study of maternal and neonatal Co concentrations in the African Copperbelt provides strong evidence of a high transfer of Co from mother to foetus.

Information Fusion and Metallogenic Prognosis of Gold Deposits in the Qixia Area, Northern Shandong Province, China

Analyzing and fusing information layers of exploratory parameters is a critical step for enhancing the accuracy of identifying mineral potential zones during the reconnaissance stage of mineral exploration. The Qixia area in Shandong Province is characterized by intricate geological structures and abundant mineral resources. Numerous gold polymetallic deposits have been discovered in this region, highlighting the potential for discovering more such deposits in the ore concentration zone and its adjacent areas. In this study, we focus on the Qixia area and employ the box dimension method to analyze the fractal dimension of fault structures. We investigate the relationship between orebody occurrence and fault incidence within the mining region. Furthermore, we combine fractal analysis with Fry analysis to comprehensively predict the metallogenic potential in the area. This study reveals the fractal dimension values of fault structures, demonstrating that fault structures govern the distribution of ore bodies, with NE and NW fault structures being the primary ore-hosting features. Based on thorough analysis, we hypothesize that gold deposits in this area are generally distributed along the northeastern direction. By considering mineral distribution characteristics, this study identifies five potential metallogenic prospect areas within the study region. Capitalizing on advancements in information technology and big data, digital geology has gained prominence in prospecting and prediction. To this end, we construct a multi-information comprehensive prospecting model based on the structure-geochemical anomaly-mineralization alteration, employing the convolutional neural network (CNN) model for quantitative estimation of regional gold mineral resources. The findings validate the CNN model’s robust prediction performance in this area, leading to the determination of five prediction prospects. We observe a notable congruence between the two methods, offering significant insights for subsequent exploration endeavors in the region.

Лесная промышленность горного региона: оценка территориальной организации и рисков развития (по материалам Республики Тыва)

Searching for ways to develop the territories along the eastern border of Russia, including mountainous areas, their manufacturing sectors, among them those in the forestry complex, becomes extremely relevant in current conditions due to the sanctions imposed by the Western countries. In keeping with the goals of this paper and based on studying the stages in the development of economic sectors, analysis and synthesis of data from official statistical sources and authorities as well as modeling of future processes in the mining region, it has been established that in such border mountainous regions of the country as the Republic of Tyva do not fully utilize the existing potential and opportunities for the development of manufacturing, exportoriented industries, especially in the timber industry. In particular, it is shown that in this region, half of the territory of which is covered with forests, there exists a significant potential to increase the volume of harvesting, treatment and deep processing of forest resources (including the volumes of timber up to 1500 thousand m³ per year) and the production of high-quality goods, including the export-oriented ones, provided that environmental protection measures are taken and the level of environmental risks is reduced. The formation of the necessary favorable legislative and legal conditions is proposed for the development of the forest industry in a depressive mountainous region.

Strategies for energy transition and regional development in European post-coal mining regions: Ústí Region, Czechia, and Lusatia, Germany

Strategies for energy transition and regional development in European post-coal mining regions: Ústí Region, Czechia, and Lusatia, Germany