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Keywords = Bayan-Uul

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27 pages, 21070 KiB  
Article
Geochemistry, Mineralization, and Fluid Inclusion Study of the Bayan-Uul Porphyry Au-Cu-(Mo) Deposit, Central Mongolia
by Bolor-Erdene Bilegsaikhan, Kotaro Yonezu, Jargalan Sereenen, Oyungerel Sarantuya and Baasanjargal Borshigo
Minerals 2024, 14(3), 320; https://doi.org/10.3390/min14030320 - 20 Mar 2024
Viewed by 3031
Abstract
The Bayan-Uul porphyry Au-Cu-(Mo) deposit occurs within the Mongol–Okhotsk Orogenic Belt, which is a part of the Central Asian Orogenic Belt. To understand geotectonic, petrogenesis, mineralization, and ore-forming fluid evolution of the Bayan-Uul deposit, we report petrographic and geochemical analyses of host rocks, [...] Read more.
The Bayan-Uul porphyry Au-Cu-(Mo) deposit occurs within the Mongol–Okhotsk Orogenic Belt, which is a part of the Central Asian Orogenic Belt. To understand geotectonic, petrogenesis, mineralization, and ore-forming fluid evolution of the Bayan-Uul deposit, we report petrographic and geochemical analyses of host rocks, mineralogy of ores, and fluid inclusion characteristics. Based on petrographic and mineralogical analyses, Cu, Mo, and Au mineralization occurs as disseminated and sulfide-bearing quartz–tourmaline veins hosted within granodiorites, monzodiorites, and diorite porphyry and tourmaline breccia. Four main alteration assemblages are identified: potassic, phyllic, argillic, and quartz–tourmaline alteration. The ore mineralogy of quartz–tourmaline veinlets are classified into A-type veinlets (quartz + tourmaline + chalcopyrite + magnetite + pyrite ± electrum), B-type veinlets (quartz + tourmaline + molybdenum + chalcopyrite + pyrite), and C-type veinlets (quartz + tourmaline + pyrite ± chalcopyrite). Fluid inclusions are found in quartz–tourmaline veinlets consisting mainly of liquid-rich two-phase (L-type), vapor-rich two-phase (V-type), and solid-bearing multi-phase (S-type) inclusions. The homogenization temperatures for the fluid inclusions in A-type, B-type, and C-type veinlets range from 215 to 490°C, 215 to 500 °C, and 160 to 350 °C and their salinity varies from 5.4 to 43.5 wt.%, 16 to 51.1 wt.%, and 3.4 to 24.1 wt.% NaCl equivalent, respectively. Coexistance of (L-type), (V-type), and (S-type) inclusions support fluid boiling. The δ18O values of ore fluids from different mineralizing A-, B-, and C-type veins are 8.7‰, 10.9‰, and 8.4‰, respectively, and the δ34S values of sulfide minerals range from −1.4‰ to 5.3‰, which indicates magmatic origin. Full article
(This article belongs to the Section Mineral Deposits)
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28 pages, 8805 KiB  
Article
Study on Numerical Simulation of Reactive-Transport of Groundwater Pollutants Caused by Acid Leaching of Uranium: A Case Study in Bayan-Uul Area, Northern China
by Haibo Li, Zhonghua Tang and Dongjin Xiang
Water 2024, 16(3), 500; https://doi.org/10.3390/w16030500 - 4 Feb 2024
Cited by 4 | Viewed by 1858
Abstract
Acid in situ leaching (ISL) is a common approach to the recovery of uranium in the subsurface. In acid ISL, there are numerous of chemical reactions among the injected sulfuric acid, groundwater, and porous media containing ore layers. A substantial amount of radioactive [...] Read more.
Acid in situ leaching (ISL) is a common approach to the recovery of uranium in the subsurface. In acid ISL, there are numerous of chemical reactions among the injected sulfuric acid, groundwater, and porous media containing ore layers. A substantial amount of radioactive elements including U, Ra, Rn, as well as conventional elements like K, Na, and Ca, and trace elements such as As, Cd, and Pb, are released into the groundwater. Thus, in acid ISL, understanding the transport and reactions of these substances and managing pollution control is crucial. In this study, a three-dimensional reactive transport modeling (RTM) using TOUGHREACT was built to investigate the dynamic reactive migration process of UO22+, H+, and SO42− at a typical uranium mine of Bayan-Uul. The model considering the partial penetration through wellbore in confined aquifer and complex chemical reactions among main minerals like uranium, K-feldspar, calcite, dolomite, anhydrite, gypsum, iron minerals, clay minerals, and other secondary minerals. The results show that after mining for one year, from the injection well to the extraction well, the spatial distribution of uranium volume fraction does not consistently increase or decrease, but it decreases initially and then increases. After mining for one year, the concentration front of UO22+ is about 20 m outside the mining area, the high concentration zone is mainly inside the mining area. The concentration front of H+ is no more than 50 m. SO42− is the index with the highest concentration among the three indexes, the concentration front of SO42− is no more than 100 m. The concentration breakthrough curve of the observation well 10 m from the mining area indicates that the concentrations of the three indicators began to significantly rise approximately after mining 0.05 years, reached the maximum value after mining 0.08 to 0.1 years, and then stabilized. The parameter sensitivity of absolute permeability and specific surface area of minerals shows that the concentration of H+ and SO42− is positively correlated with absolute permeability. The concentration of H+ is negatively correlated with the specific surface area of calcite, anhydrite, K-feldspar, gypsum, hematite, and dolomite. The concentration of SO42− is positively correlated with the specific surface area of K-feldspar and Hematite, and negatively correlated with the specific surface area of calcite, anhydrite, gypsum, and dolomite. The influence analysis of pumping ratio and non-uniform injection ratio shows that the non-uniform injection scheme has a more significant impact on pollution control. The water table, streamline, capture envelope, and the concentration breakthrough curve of five schemes with different pumping ratios and non-uniform injection ratio were obtained. The water table characteristics of five schemes shown that increase in the pumping ratio and the non-uniform injection ratio, the water table convex near the outer injection well is weakened and the groundwater depression cone near the pumping well is strengthened. This characteristic of water table exerts a notable retarding influence on the migration of pollutants from the mining area to the outside. For the scheme with a pumping ratio is 0 (the total pumping flow rate is equal to the total injection flow rate) and a non-uniform injection ratio is 0 (the flow rate of inner injection well Q1,Q2,Q3 is equal to the flow rate of outer injection well Q4,Q5,Q6), the streamline characteristics shown that a segment of the streamline of is diverging from inner region to the outer region. For other schemes, the streamline exhibits a convergent feature. It is indicated that by increasing the pumping ratio and non-uniform injection ratio, a closure flow field can be established, confining the groundwater pollutants resulting from mining within the capture envelope. Hence, the best scheme for preventing pollution migration is the scheme with a pumping ratio is 0 (the total pumping flow rate is equal to the total injection flow rate) and a non-uniform injection ratio is 0.1 (the flow rate of inner injection well Q1,Q2,Q3 is 10% more than the flow rate of outer injection well Q4,Q5,Q6). In this scheme, the optimal stable concentration of UO22+, H+, and SO42− at the observation well obtained by RTM is lower than other schemes, and the values are 0.00316 mol/kg, 2.792 (pH), and 0.0952 mol/kg. The inner well injection rate is 194.09 m3/d, the outer well injection rate is 158.89 m3/d, and the pumping rate is 264.00 m3/d. Numerical simulation analysis suggests that a scheme with a larger non-uniform injection ratio is more conducive to the formation of a strong hydraulic capture zone, thereby controlling the migration of pollutants in the acid ISL. A reasonable suggestion is to adopt non-uniform injection mining mode in acid ISL. Full article
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17 pages, 2909 KiB  
Article
Using Clustering, Geochemical Modeling, and a Decision Tree for the Hydrogeochemical Characterization of Groundwater in an In Situ Leaching Uranium Deposit in Bayan-Uul, Northern China
by Haibo Li, Mengqi Liu, Tian Jiao, Dongjin Xiang, Xiaofei Yan, Zhonghua Tang and Jing Yang
Water 2023, 15(24), 4234; https://doi.org/10.3390/w15244234 - 8 Dec 2023
Cited by 3 | Viewed by 1961
Abstract
Uranium extraction through the in situ leaching method stands as a pivotal approach in uranium mining. In an effort to comprehensively assess the repercussions of in situ uranium leaching on groundwater quality, this study collected 12 representative groundwater samples within the Bayan-Uul mining [...] Read more.
Uranium extraction through the in situ leaching method stands as a pivotal approach in uranium mining. In an effort to comprehensively assess the repercussions of in situ uranium leaching on groundwater quality, this study collected 12 representative groundwater samples within the Bayan-Uul mining area. The basic statistical characteristics of the water samples showed that the concentrations of SO42− and total dissolved solids (TDS) were relatively high. Through the use of cluster analysis, the water samples were categorized into two distinct clusters. Seven samples from wells W-d, W-u, N01, W10-2, W08-1, W10-1, and W13-1, situated at a considerable distance from the mining area, were grouped together. Conversely, five samples from wells W08-2, W13-2, W01-1, W02-2, and the pumping well located in closer proximity to the mining area, formed a separate cluster. A decision tree-based machine learning approach was employed to discern the influence of various hydrochemical indicators in forming these clusters, with results indicating that SO42− exerts the most substantial influence, followed by Ca2+. The mineral saturation indices from geochemical modeling indicated that, as the distance from the mining area increased, the trend of calcium minerals changed from dissolution to precipitation; iron minerals were in a precipitation state, and the precipitation trend was gradually weakening. In light of these findings, it is clear that in situ uranium leaching significantly impacted the groundwater in the vicinity of the mining area. The prolonged consumption of groundwater sourced near the study area, or its use for animal husbandry, poses potential health risks that demand heightened attention. Full article
(This article belongs to the Special Issue Application of Machine Learning to Water Resource Modeling)
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17 pages, 6732 KiB  
Article
Assessment of Burn Severity and Monitoring of the Wildfire Recovery Process in Mongolia
by Battsengel Vandansambuu, Byambakhuu Gantumur, Falin Wu, Oyunsanaa Byambasuren, Sainbuyan Bayarsaikhan, Narantsetseg Chantsal, Nyamdavaa Batsaikhan, Yuhai Bao, Batbayar Vandansambuu and Munkh-Erdene Jimseekhuu
Fire 2023, 6(10), 373; https://doi.org/10.3390/fire6100373 - 26 Sep 2023
Cited by 4 | Viewed by 3820
Abstract
Due to the intensification of climate change around the world, the incidence of natural disasters is increasing year by year, and monitoring, forecasting, and detecting evolution using satellite imaging technology are important methods for remote sensing. This study aimed to monitor the occurrence [...] Read more.
Due to the intensification of climate change around the world, the incidence of natural disasters is increasing year by year, and monitoring, forecasting, and detecting evolution using satellite imaging technology are important methods for remote sensing. This study aimed to monitor the occurrence of fire disasters using Sentinel-2 satellite imaging technology to determine the burned-severity area via classification and to study the recovery process to observe extraordinary natural phenomena. The study area that was sampled was in the southeastern part of Mongolia, where most wildfires occur each year, near the Shiliin Bogd Mountain in the natural steppe zone and in the Bayan-Uul sub-province in the forest-steppe natural zone. The normalized burn ratio (NBR) method was used to map the area of the fire site and determine the classification of the burned area. The Normalized Difference Vegetation Index (NDVI) was used to determine the recovery process in a timely series in the summer from April to October. The results of the burn severity were demonstrated in the distribution maps from the satellite images, where it can be seen that the total burned area of the steppe natural zone was 1164.27 km2, of which 757.34 km2 (65.00 percent) was classified as low, 404.57 km2 (34.70 percent) was moderate-low, and the remaining 2.36 km2 (0.30 percent) was moderate-high, and the total burned area of the forest-steppe natural zone was 588.35 km2, of which 158.75 km2 (26.98 percent) was classified as low, 297.75 km2 (50.61 percent) was moderate-low, 131.25 km2 (22.31 percent) was moderate-high, and the remaining 0.60 km2 (0.10 percent) was high. Finally, we believe that this research is most helpful for emergency workers, researchers, and environmental specialists. Full article
(This article belongs to the Special Issue Vegetation Fires and Biomass Burning in Asia)
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