Migration mechanism of PTEs in polymetallic mines under pioneer phytoremediation: A Lanmuchang mercury-thallium mine perspective.

The establishment of pioneer plants in waste slag sites not only modifies the nutrient content of the waste, but also plays a significant role in regulating the pH and potentially toxic elements (PTEs), thereby providing favorable conditions for the quick introduction of other plants. However, the mechanisms by which pioneer plants impact the migration and transformation of PTEs in polymetallic mines have rarely been studied. In this study, we investigated the effects of pioneer phytoremediation on the migration and transformation of PTEs, specifically thallium (Tl), mercury (Hg), arsenic (As), and antimony (Sb), in mercury-thallium mine waste. The results showed that pioneer phytoremediation increased esters and ethers containing C-O and P-O groups in dissolved organic matter, which subsequently formed soluble complexes with Hg, As, and Sb. Nevertheless, pioneer phytoremediation reduced the migration of Tl in the waste, this was mainly because pioneer phytoremediation reduced Fe3+ in silicate minerals and iron-containing minerals to more reactive Fe2+, thereby increasing the electronegativity (El) of the waste and enhancing its adsorption capacity for metal cations, such as Hg and Tl, thus maintaining electrical neutrality. However, the increased El of the waste was detrimental to the adsorption of negatively charged oxygen-containing anions, such as As and Sb. At the same time, the dissolution of Fe2+ resulted in the release and mobility of As and Sb that had been adsorbed onto iron oxides. The results offer significant theoretical support for guiding the ecological restoration of PTEs in polymetallic mines.

Health risk assessment of heavy metals based on source analysis and Monte Carlo in the downstream basin of the Zishui.

In this study, stone coal mines in the lower reaches of the Zijiang River were adopted as the research object. To analyze the spatial distribution, sources, and health risks of heavy metals in the surrounding soil of stone coal mines, 82 topsoil samples were collected in the study area, and the contents of 8 heavy metals including Cd, Hg, As, Cr, Pb, Cu, Ni, and Zn were determined. The spatial distribution of heavy metals was analyzed using ArcGIS, and the pollution sources of heavy metals were identified using Positive matrix factorization (PMF). Then, Monte Carlo and health risk assessment models were used to evaluate the health risks of different populations. The results showed that the average content of heavy metals followed the order of Zn > Cr > Pb > Cu > Ni > As > Cd > Hg, and the contents of all heavy metals were higher than the soil background values of Hunan Province. The high-value areas of heavy metals content were mostly concentrated in the central region close to areas with a notable concentration of stone coal mines. PMF identified four pollution sources, namely, mining activities (26.9%), atmospheric deposition (18.8%), natural sources (32.8%) and agricultural sources (21.5%). The carcinogenic and non-carcinogenic risks for children were higher than those for adults, with As and Cd posing higher carcinogenic risks to children. Based on the source of health risks, it was determined that the health risks could be primarily attributed to agricultural sources, and As was the main heavy metal causing health risks. This study provides theoretical support for treating heavy metal pollution in mining basins.

Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review.

Deposition of potentially toxic elements (PTEs) in soils due to different types of mining activities has been an increasingly important concern worldwide. Quantitative differences of soil PTEs contamination and related health risk among typical mines remain unclear. Herein, data from 110 coal mines and 168 metal mines across China were analyzed based on 265 published literatures to evaluate pollution characteristics, spatial distribution, and probabilistic health risks of soil PTEs. The results showed that PTE levels in soil from both mine types significantly exceeded background values. The geoaccumulation index (Igeo) revealed metal-mine soil pollution levels exceeded those of coal mines, with average Igeo values for Cd, Hg, As, Pb, Cu, and Zn being 3.02-15.60 times higher. Spearman correlation and redundancy analysis identified natural and anthropogenic factors affecting soil PTE contamination in both mine types. Mining activities posed a significant carcinogenic risk, with metal-mine soils showing a total carcinogenic risk an order of magnitude higher than in coal-mine soils. This study provides policymakers a quantitative foundation for developing differentiated strategies for sustainable remediation and risk-based management of PTEs in typical mining soils.

Chronic effects of metal releases from historical mining on threatened crayfish in Madison County Missouri, USA.

The Little St. Francis River and its tributaries drain metals-contaminated areas of the Madison County Mines National Priority List Superfund site (MCM) which was designated in 2003 to facilitate remediation of metals contamination within the MCM. One concern for natural resource trustees in the MCM is the potential effects of elevated metals concentrations on the federally threatened St. Francis River crayfish, Faxonius quadruncus, which has a geographic range that is limited to the St. Francis River watershed. A survey of riffle-dwelling crayfish, in-situ cage study, and laboratory toxicity tests were conducted to assess the effects of mining-derived metals on F. quadruncus and other crayfish species in the MCM. Crayfish densities were significantly greater at sites upstream of metals releases from historical mining (henceforth mining releases) compared to densities at sites downstream of mining releases, and metals concentrations in whole-body crayfish, surface water, sediments, macroinvertebrates, fish, and plant material were greater at sites downstream of mining releases compared to sites upstream of mining releases. Crayfish densities were also negatively correlated with consensus-based adverse effects indices, expressed as surface-water toxic units and sediment probable effects quotients. Decreased growth and increased mortality during cage and laboratory studies were likely due to exposure to, and subsequently uptake of, elevated concentrations of metals. Crayfish in all studies were found to bioaccumulate metals, which supports their utility as bioindicators of metals contamination. Study results show that elevated metals concentrations associated with mining releases in the MCM continue to adversely affect biota, including the federally threatened F. quadruncus.

Stone mining work and dust pollution in Birbhum district, West Bengal, India.

Dust pollution is common in Indian roads and several industrial settings (including mines) that affects human health. Identification and characterization of the dust particles in the mining area is essential for knowing the properties of the dust that effectively causes ailments to humans, particularly among workers those who are working in unorganized industrial settings. The present study aimed to determine the level of dust pollution and to know the size and characterize the dust particles in the Pachami-Hatgacha stone mine areas of Birbhum district, West Bengal, India. Dust samples were collected and analysed for Dynamic Light Scattering (DLS) to determine the size and shape of the particles, Fourier Transform Infrared Spectroscopy (FT-IR) to determine the free silica content, and X-ray Florence (XRF) analysis for quantitative estimation of components in the sample. All the analyses were done following standard instrumentation and techniques. The size of the dust particles was much less (ranges 101-298 nm) than the size of respirable particles (2500 nm). Those were mostly generated as well as precipitated during peak working hours of the day. Presence of considerable amounts of silica was confirmed by the FT-IR (strong and broad band at 1000 cm-1) and XRF analysis (76.85% SiO2). Exposure to these dust particles may cause severe health impairments. Therefore, interventions like wet drilling and blasting, sprinkling of water during peak working hours, and awareness of use of personal protective devices among workers are required to reduce the risk and hazards associated with dust pollution to the health of miners and inhabitants around the mines.

An Image Dehazing Algorithm for Underground Coal Mines Based on gUNet.

Aiming at the problems of incomplete dehazing, color distortion, and loss of detail and edge information encountered by existing algorithms when processing images of underground coal mines, an image dehazing algorithm for underground coal mines, named CAB CA DSConv Fusion gUNet (CCDF-gUNet), is proposed. First, Dynamic Snake Convolution (DSConv) is introduced to replace traditional convolutions, enhancing the feature extraction capability. Second, residual attention convolution blocks are constructed to simultaneously focus on both local and global information in images. Additionally, the Coordinate Attention (CA) module is utilized to learn the coordinate information of features so that the model can better capture the key information in images. Furthermore, to simultaneously focus on the detail and structural consistency of images, a fusion loss function is introduced. Finally, based on the test verification of the public dataset Haze-4K, the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and Mean Squared Error (MSE) are 30.72 dB, 0.976, and 55.04, respectively, and on a self-made underground coal mine dataset, they are 31.18 dB, 0.971, and 49.66, respectively. The experimental results show that the algorithm performs well in dehazing, effectively avoids color distortion, and retains image details and edge information, providing some theoretical references for image processing in coal mine surveillance videos.

Determinants of discomfort from combined exposure to noise and vibration in dumper operators of mining industry in India.

In the mining industry, dumper operators are exposed to combined noise and vibration, leading to discomfort. Dumpers are heavy earth-moving machines that are used for carrying bulky material in mining industries. Dumper operators are exposed to physical hazards such as vibration, noise, heat, and humidity, throughout their lifetime of work. Fifty-four dumper operators working in mines were selected for this study. Noise was measured as per the guidelines of the Directorate General Mining Safety, India, and whole-body vibration was measured as per the guidelines of ISO 2631-1::1997. Noise Pro DLX, Type 2 noise dosimeters were used for the measurement of personal noise exposure while SV-106 six channels vibration meters were used for whole body vibration (WBV) exposure measurement. Discomfort was calculated using the regression equation developed by Huang and Griffin (2014). The total discomfort level of mine operators was about 192. A predictive equation was derived by using a regression model to determine the contribution of individual variables causing discomfort. It was observed that for every unit increase in noise (LAeq), discomfort increased by 10.20 units, a one-unit increase in vibration (A (8)) led to a 51.7-unit increase in discomfort, while an increase of one unit of exposure time increased the discomfort level by 5.24 units.

Assessment of the ecological risk and mobility of arsenic and heavy metals in soils and mine tailings from the Carmina mine site (Asturias, NW Spain).

An evaluation of the pollution, distribution, and mobility of arsenic and heavy metals in spoil heaps and soils surrounding the abandoned Carmina lead-zinc mine (Asturias, northern Spain) was carried out. Fractionation of arsenic was performed by an arsenic-specific sequential extraction method; while, heavy metal fractionations was carried out using the protocol of the Bureau Community of Reference (BCR) (now renamed Standards, Measurements and Testing Programme). Arsenic appeared predominantly associated with amorphous iron oxyhydroxides. Among the heavy metals, lead and zinc showed high availability since significant amounts were extracted in the nonresidual fractions; whereas, chromium, copper and nickel showed very low availability, indicating their lithogenic origins. The results showed that the extractability of heavy metals in soils is influenced mainly by the presence of iron and manganese oxides as well as by pH and Eh. Multiple pollution indices, including the enrichment factor (EF), geoaccumulation index (Igeo), ecological risk index (Er) and potential ecological risk index (PERI), were used to assess the degree of soil pollution in the mine area. All results showed that lead was the key factor causing the pollution and ecological risk in the studied area, and copper, zinc and arsenic also had significant contributions. Notably, the sites at higher risk coincided with those with high availability of arsenic and heavy metals. This study provides an integrative approach that serves as a powerful tool to evaluate the metal pollution status and potential threats to the local environment of abandoned mining areas, and the results are useful for making management decisions in these areas.

Machine learning-assisted risk evaluation of heavy metals in the Hainan gold mining region, China.

This study employed machine learning (ML) to thoroughly investigate the impact of informal mining activities on the distribution and pollution status of heavy metals in soils near private gold mines in Hainan Province, southern China, a region known for its ecological sensitivity and economic importance. By systematically collecting surface soil samples and samples at depths of 0.5-1 m from 175 drilling sites, a comprehensive quantitative analysis was conducted on major heavy metal elements, including lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), mercury (Hg), chromium (Cr), arsenic (As), and zinc (Zn). Combined with evaluation methods such as the Pollution Load Index (PLI), Normalized Pollution Index (NIPI), and Ecological Risk Index (ERI), the study revealed a high level of soil pollution at informal mining sites. The findings indicated that the average concentrations of Pb, Cd, Hg, As, and Zn in surface soils significantly exceeded the background values for soils in China, with a pronounced positive correlation observed between these heavy metal elements in both surface and deep soil profiles (r > 0.5). Furthermore, leveraging the heavy metal content in surface soils and the constructed environmental indicators, the predictive accuracy for metal content in deep soils was found to range from R2 = 0.27 to 0.68, suggesting that informal mining activities have led to substantial variations in metal content across different soil profiles. Through the application of a random forest model for predictive analysis of the PLI, NIPI, and ERI, high prediction accuracy was achieved (R2 = 0.78, 0.86, and 0.60, respectively). The study demonstrates that informal mining activities not only elevate the risk of soil pollution but also alter the distribution patterns of heavy metals. Also, this study provides a crucial foundation for the scientific assessment of soil quality and potential environmental hazards, while also affirming the efficacy of ML techniques in forecasting soil quality parameters.

Comparison of the monitoring of surface deformations in open-pit mines with Sentinel-1A and TerraSAR-X satellite radar data.

In case necessary precautions are not taken in surface mines, serious accidents and loss of life may occur, particularly due to large mass displacements. It is extremely important to identify the early warning signs of these displacements and take the necessary precautions. In this study, free medium-resolution satellite radar images from the European Space Agency's (ESA) C-band Sentinel-1A satellite and commercial high-resolution satellite radar images (SAR, Synthetic Aperture Radar) from the Deutsches Zentrum für Luft- und Raumfahrt's (DLR) X-band TerraSAR-X satellite were obtained, and it was attempted to reveal the traceability and adequacy of monitoring of deformations and possible mass displacements in the dump site of an open-pit coal mine. The compatibility of the results obtained from the satellite radar data with two devices of Global Positioning System (GPS) which were installed in the field was evaluated. Furthermore, the velocity results in the Line Of Sight (LOS) direction and vertical deformation velocity results obtained with all three approaches (GPS/Sentinel-1A, GPS/TerraSAR-X, and Sentinel-1A/TerraSAR-X) were compared. It was observed that the results were statistically equal and the directions of movement were similar/compatible. The result of this study showed that deformations at mine sites can be monitored with sufficient accuracy for early warning with free Sentinel-1A satellite data, although the TerraSAR-X satellite offers a higher resolution.

Hydrogeochemical characteristics and agricultural suitability of shallow groundwater quality in a concentrated coalfield area of Huaibei Plain, China.

Groundwater is one of the chief water sources for agricultural activities in an aggregation of coal mines surrounded by agricultural areas in the Huaibei Plain. However, there have been few reports on whether mining-affected groundwater can be adopted for agricultural irrigation. We attempted to address this question through collecting 71 shallow groundwater samples from 12 coal mining locations. The Piper trilinear chart, the Gibbs diagram, the proportional coefficient of major ions, and principal component analysis were examined to characterize the source, origin, and formation process of groundwater chemical composition. The suitability for agricultural irrigation was evaluated by a final zonation map that establishes a comprehensive weighting model based on analytic hierarchy process and criteria importance though the intercriteria correlation (AHP-CRITIC). The results revealed that the groundwater was classified as marginally alkaline water with a predominant cation of HCO3- and anion of Na+. Total hardness, total dissolved solids, sulfate (SO42-), sodium (Na+), and fluoride (F-) were the primary ions that exceeded the standard. The results also indicated that the dominant hydrochemical facies were Ca-HCO3 and Na-Cl. The dissolution of carbonate, silicate, sulfate minerals, along with cation exchange, were the main natural drivers controlling the hydrogeochemical process of groundwater. The zonation map suggested that 43.17%, 18.85%, and 37.98% of the study area were high, mediate, and low suitability zones, respectively. These results from this study can support policymakers for better managing groundwater associated with a concentration of underground coal mines.

[Hierarchical fuzzy comprehensive evaluation of prevention and control level of occupational hazards in coal mines].

Objective: To establish an evaluation model for occupational hazard prevention and control levels in coal mines, to explore the combination of Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation, to evaluate the overall situation of occupational hazard prevention and control in coal mines. Methods: In November 2021, Collect information of occupational hazards and their prevention and control status in 30 coal mines. AHP model was first constructed for the elements of occupational hazard prevention and control in coal mines. Then, the AHP and fuzzy comprehensive evaluation method was applied to comprehensively evaluate and grade the occupational hazard prevention and control in coal mines, using the principles of maximum membership and weighted average. Results: The hierarchical fuzzy comprehensive evaluation results for typical coal mine were basically consistent with its occupational hazard prevention and control situation. The dust prevention and control situation was good, the noise prevention and control situation is average, the occupational health monitoring situation was good, the occupational health management situation was average, and the overall level of occupational hazard prevention and control was good. Conclusion: The hierarchical fuzzy comprehensive evaluation model for occupational hazard prevention and control levels, combined with the principles of maximum membership and weighted average, can objectively evaluate and reflect the overall situation of occupational hazard prevention and control in coal mines.

Yeasts associated with mines on tree leaves in the urban areas.

Mines on tree leaves and undamaged leaves were studied to investigate yeast complexes in urban areas (Aesculus hippocastanum, miner - Cameraria ohridella; Betula verrucosa, miner - Caloptilia betulicola; Populus nigra, miner - Lithocolletis populifoliella; Quercus robur, miner - Tischeria companella; Salix caprea, miner - Trachys minuta; Syringa vulgaris, miner - Caloptilia syringella; Tilia cordata, miner - Phyllonorycter issikii; Ulmus laevis, miner - Carpatolechia fugitivella). The abundance and taxonomic structure of yeasts were studied using a surface plating method on solid media (GPY agar). Identification of yeast species was based on the ITS rDNA nucleotide sequence. The average abundance of yeasts during the first stages of mine formation in the internal tissues of leaves was 103 cfu/g. After 23-25 days, during the last stage of larval metamorphosis before mine destruction, the abundance of yeasts in the mines increased by two orders of magnitude to 105 cfu/g. No significant differences were observed in the abundance of yeasts in mines formed by different insects on different trees. A total of twelve yeast species were observed. The fast-growing ascomycetous yeasts Hanseniaspora uvarum and H. occidentalis dominated the mines. On undamaged leaves, the basidiomycetous yeasts Papiliotrema flavescens and Rhodotorula mucilaginosa, typical in the phyllosphere, dominated. The opportunistic yeast Candida parapsilosis was detected in the yeast complexes of all mines examined and was not found on the surface of leaves. Comparison of the relative abundance of yeast species between the studied mines and undamaged leaves using principal component analysis showed that all studied yeast communities in the mines were significantly different from the epiphytic yeast complexes of the undamaged leaves. Thus, miners in urban environments provoke the formation of short-lived endophytic yeast complexes with high abundance of Hanseniaspora. For leaf miners, the yeasts serve primarily as a food source for insect larvae rich in vitamins and amino acids. The adult leaf miners, in turn, contribute to the reproduction of the yeasts and create favorable conditions for their development.

Exposure to dust and respiratory health among Australian miners.

PURPOSE: Occupational exposure to dust has been recognised as a significant health hazard to mine workers. This study aimed to investigate the association between exposure to inhalable (INH) and respirable (RES) dust and respiratory health among mine workers in Western Australia using an industry-wide exposure database. METHODS: The database comprised cross-sectional surveys conducted by mining companies for the period 2001-2012. The study population consisted of 12,797 workers who were monitored for exposure to INH and RES dust and undertook health assessments including a respiratory questionnaire and spirometry test. RESULTS: Despite the general trend of declining exposure to both INH and RES dust observed over the 12 years period, mine workers reported a higher prevalence of phlegm and cough when exposed to elevated concentrations of INH and RES dust. Logistic regression analysis further confirmed the positive association between INH dust exposure and the prevalence of phlegm with an adjusted odds ratio of 1.033 (95% CI 1.012-1.052). Overall, 6.3% of miners might have potential airway obstruction, and exposure to INH dust was associated with impaired lung function parameters. CONCLUSION: Exposure levels of INH and RES dust particles among mine workers have reduced considerably and were well below currently legislated occupational exposure limits. However, given the reported higher prevalence of phlegm and cough among those with elevated dust concentrations, there is a continued need for effective dust exposure monitoring and control in the mineral mining industry.

Effects of multi-heavy metal composite pollution on microorganisms around a lead-zinc mine in typical karst areas, southwest China.

Heavy metal pollution poses a serious hazard to the soil bacterial community. The purpose of this study is to understand the characteristics of soil heavy metal pollution in lead-zinc mines in karst areas and the response of Pb, Zn, Cd, and As-induced composite pollution to soil microorganisms. This paper selected soil samples from the lead-zinc mining area of Xiangrong Mining Co., Ltd., Puding County, Guizhou Province, China. The soil in the mining area is contaminated by multiple heavy metals such as Pb, Zn, Cd and As. The average levels of Pb, Zn, Cd and As in the Pb-Zn mining soil were 14.5, 7.8, 5.5 and 4.4 times higher than the soil background in this area, respectively. Bacterial community structures and functions were analyzed using 16 S rRNA high-throughput sequencing technology and the PICRUSt method. A total of 19 bacterial phyla, 34 classes and 76 orders were detected in the tested soil. At the phylum level, the Proteobacteria are the dominant flora of the soil in the tailings reservoir area of the lead-zinc mine, respectively GWK1 (49.64%), GWK2 (81.89%), GWK3 (95.16%); and for the surrounding farmland soil, the Proteobacteria, Actinobacteriota, Acidobacteriota, Chloroflexi and Firmicutes are the most abundant in five bacterial groups. RDA analyses revealed that the heavy metal pollution of the lead-zinc mining area has a significant impact on the diversity of soil microorganisms. As the distance from the mining area increased, the heavy metal comprehensive pollution and potential risk value decreased, and the bacterial diversity increased. Additionally, various types of heavy metals have different effects on bacterial communities, and soil heavy metal content will also change the bacterial community structure. Proteobacteria positively related to Pb, Cd, and Zn, therefore, Proteobacteria were highly resistant to heavy metals. PICRUSt analysis suggested that heavy metals significantly affect the metabolic function of microorganisms. Microorganisms might generate resistance and enable themselves to survive by increasing the transport of metal ions and excreting metal ions. These results can be used as a basis for the microbial remediation of heavy metal-contaminated farmland in mining areas.

Robust Localization for Underground Mining Vehicles: An Application in a Room and Pillar Mine.

Most autonomous navigation systems used in underground mining vehicles such as load-haul-dump (LHD) vehicles and trucks use 2D light detection and ranging (LIDAR) sensors and 2D representations/maps of the environment. In this article, we propose the use of 3D LIDARs and existing 3D simultaneous localization and mapping (SLAM) jointly with 2D mapping methods to produce or update 2D grid maps of underground tunnels that may have significant elevation changes. Existing mapping methods that only use 2D LIDARs are shown to fail to produce accurate 2D grid maps of the environment. These maps can be used for robust localization and navigation in different mine types (e.g., sublevel stoping, block/panel caving, room and pillar), using only 2D LIDAR sensors. The proposed methodology was tested in the Werra Potash Mine located at Philippsthal, Germany, under real operational conditions. The obtained results show that the enhanced 2D map-building method produces a superior mapping performance compared with a 2D map generated without the use of the 3D LIDAR-based mapping solution. The 2D map generated enables robust 2D localization, which was tested during the operation of an autonomous LHD, performing autonomous navigation and autonomous loading over extended periods of time.

Relief Modeling in the Restoration of Extractive Activities Using Drone Imagery.

In the field of mine engineering, a cross-section topographic survey is usually carried out to perform volumetric calculations of earth movement in order to restore areas affected by extractive activities. Nowadays, Remote Sensing and Geographical Information System (GIS) technologies make it possible to perform the same work by using indirect methods such as images obtained by photogrammetric flights. In this context, Unmanned Aerial Systems (UAS) are considered a very convenient option to develop mapping projects in short periods of time and to provide quality geospatial information such as Digital Elevation Models (DEM) and orthophotos of centimetric spatial resolution. In the present study, this approach has been applied in a gravel extraction area to obtain data for estimating the filling volume of material required for the restoration of the relief (DEM(r)). The estimation of the DEM(r) is later used to calculate a difference of height values (DEM(r)-DEM) that will serve as a variable in the basic operation of volume calculation. The novelty of the presented method is the simulation of a relief adapted to the surrounding morphology, including the derived channel network and the visibility impact, improving what would be a simple clogging. Likewise, the generation of 3D models allows visualizing a new morphological structure of the relief. The proposed approach, based on GIS tools, allows analyzing water flow connectivity integration of the DEM(r) with the environment and estimating potential landscape impacts from the main focuses of a visual basin, both of which are key aspects of restoration modeling that are not always properly addressed.

The Future of Mine Safety: A Comprehensive Review of Anti-Collision Systems Based on Computer Vision in Underground Mines.

Underground mining operations present critical safety hazards due to limited visibility and blind areas, which can lead to collisions between mobile machines and vehicles or persons, causing accidents and fatalities. This paper aims to survey the existing literature on anti-collision systems based on computer vision for pedestrian detection in underground mines, categorize them based on the types of sensors used, and evaluate their effectiveness in deep underground environments. A systematic review of the literature was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify relevant research work on anti-collision systems for underground mining. The selected studies were analyzed and categorized based on the types of sensors used and their advantages and limitations in deep underground environments. This study provides an overview of the anti-collision systems used in underground mining, including cameras and lidar sensors, and their effectiveness in detecting pedestrians in deep underground environments. Anti-collision systems based on computer vision are effective in reducing accidents and fatalities in underground mining operations. However, their performance is influenced by factors, such as lighting conditions, sensor placement, and sensor range. The findings of this study have significant implications for the mining industry and could help improve safety in underground mining operations. This review and analysis of existing anti-collision systems can guide mining companies in selecting the most suitable system for their specific needs, ultimately reducing the risk of accidents and fatalities.

Distribution of heavy metals influenced by pumped storage hydropower in abandoned mines: Leaching test and modelling simulation.

Renewable energy generation varies frequently, making it difficult to match electricity demand. Pumped storage hydropower plants can alleviate this problem by reducing the unevenness of renewable energy generation. It is a new exploration of energy storage methods to construct pumped storage hydropower plants by using underground goaf of abandoned mines and mining subsidence water area. However, the construction of lower reservoirs using underground goaf areas of abandoned mines can lead to potential heavy metal pollution. To assess the impact of using abandoned mines for pumped storage hydropower on the downstream surface water environment, this work first analyzed the release characteristics of heavy metals from underground goaf and surface dump through field sampling and leaching tests, then constructed a water-environment model of the downstream surface water based on the experimental results and water environment theory, and finally simulated and analyzed the impact of underground pollutants pumped to the surface on downstream surface water-quality in typical hydrological years. The maximum error between the simulated values and measured values of the hydrodynamic model was 0.1, and the overall error was within a reasonable range (±0.2 m). The comparison between simulated values and measured values of heavy metal concentration in water quality model showed RMSE values ranged from 0.003 to 0.81, with an average of 0.4; the SI ranged from 0.84 to 0.95, with an average of 0.89. During the simulation of low, normal, and high flow years, pollution downstream was concentrated near the drainage outlet, and the underground pollutants pumped to the surface influenced the concentration of heavy metals there. After a period of drainage, the concentration of heavy metals decreased. Drainage volume was an important factor affecting the concentration of heavy metals downstream surface water. These results prove that the water environment model established based on MIKE21 is reliable and can provide guidance for the simulation and control of heavy metal pollution in the utilization of abandoned mines for pumped storage hydropower. This work provides a reproducible idea and method to assess the impact of using abandoned mines and mining subsidence water area for pumped storage hydropower on downstream surface water and ensure the safety of the ecological environment.

Radiological risk assessment of outdoor222Rn and220Rn around rare earth element and uranium mines from northern Vietnam.

The outdoor222Rn and220Rn concentrations at 320 sampling points at 1 m above the ground in different sites surrounding rare earth element (REE) and uranium mines from northern Vietnam were measured using the RAD7. Results showed that222Rn concentrations were always higher than220Rn concentrations with large variation ranges from 25.7 to 573 Bq m-3and from 18.5 to 385 Bq m-3, respectively. The high correlation between220Rn and228Ra concentrations in surface soil of the studied sites were observed. The highest220Rn and222Rn concentrations are found at the sampling points of the REE NX-Lai Chau site. The220Rn and222Rn activities surrounding the REE mines were found to be higher than those surrounding the uranium mines. The average annual committed effective doses originated from the inhalation of220Rn and222Rn outdoor concentrations is about five times higher than the worldwide average value.