Uranium Mining Research Articles

Comprehensive Study on Hydrogeological Conditions and Suitability Evaluation of In Situ Leaching for Sandstone-Hosted Uranium Deposit in Erlian Basin

As a strategic mineral and energy resource, the enrichment and metallogenic mechanism of sandstone-hosted uranium deposits are highly dependent on hydrogeological conditions. However, the relationship between sandstone uranium mineralization and hydrogeological conditions has not received sufficient attention yet. The pumping test, hydrogeological parameters and hydrochemical characteristics were employed to analyze the change characteristics of hydrogeological conditions and evaluate the suitability of in situ leaching (ISL). The results showed that the study area in the Inner Mongolia Autonomous Region could be divided into two groundwater subsystems, namely Quanzha-Engeriyin and Luhai-Zhendai. The latter with relatively high water richness is confined and a main ore-bearing aquifer, which consists of four orebodies. The well discharge (Q) and hydraulic conductivity (K) of Orebody II ranged from 98.40 to 867.36 m3/d and 0.25 to 5.64 m/d, respectively, indicating the aquifer is suitable for the migration, enrichment and mineralization of uranium due to relatively high permeability and fast flow rate. The water storage of Orebodies III-IV gradually deteriorated from east to west in a stepped pattern. And the highest values of Q and K in Orebodies III-IV decreased from 1200 m3/d to 120 m3/d and 1.75 m/d to 0.035 m/d, respectively, suggesting these were conducive to a reduction in and accumulation of uranium under poor hydrodynamic conditions. Additionally, the study area would be defined as three grades, including favorable, relatively favorable and unfavorable areas of ISL according to a comprehensive evaluation. This study provided a scientific basis for evaluating the possibility of in situ leaching for sandstone-hosted uranium deposit.

A hydration model of actinide complexes by exploring their multiple minima hypersurface: The case of uranyl cation

The multiple minima hypersurface (MMH) approach is a reliable theoretical model for characterizing uranyl-water complexes in aqueous media. It provides insights into probable conformations, solubility, and reactivity through accurate exploration of the local energy landscape via quantum calculations. The approach predicts equilibria and populations of local minima, identifying pre-reactive sites and hydrolyzed ligands. By applying MMH to a wider range of molecular species, a robust theoretical framework is established for understanding the complex chemistry of environmental and nuclear materials. The approach here aims to predict the behavior of weathered uranium mining waste and enhance the study of actinide compounds.

Study in Laboratory of Aqueous Solutions Representing the Acidity of a Uranium Mine Under Decommissioning

Study in Laboratory of Aqueous Solutions Representing the Acidity of a Uranium Mine Under Decommissioning

Kinetic Study and Process Optimization of Plutonium Barrier Units for Enhanced Plutonium Stripping in the PUREX Process

In the PUREX (the plutonium uranium reduction extraction) process, a plutonium barrier unit (1BXX) is used to achieve deep plutonium stripping. According to the operating experience of the French reprocessing plant, after the separation of uranium and plutonium in the first cycle (1B + 1BXX), the plutonium barrier unit has excellent stripping effect, such that the removal of plutonium from uranium can already be achieved in the first cycle, and the second cycle only needs to focus on the removal of neptunium from uranium in order to obtain a qualified uranium product. In recent decades, China has also been actively conducting research on the plutonium barrier unit process to reduce the plutonium concentration in the primary uranium product in the first cycle to avoid the need to remove neptunium and plutonium at the same time in the second cycle, and to improve the efficiency and feasibility of reprocessing. Due to the lack of design basis for plutonium barriers to achieve deep plutonium stripping at present, this study conducts a basic study on the plutonium barrier unit, aiming to provide data for the optimization of plutonium barriers in the actual reprocessing process at a later date. In this work, a kinetic study on the reduction and stripping of trace plutonium from dibutyl phosphate-containing organic phases was carried out first, and the kinetic equations for the reduction and stripping of Pu(IV) by U(IV) under flow process conditions were obtained. The effects of U(IV) addition on the extraction loss of U(IV) and the concentration distribution of U(IV) at various stages were investigated by process simulation. Additionally, the oxidation of U(IV) under process conditions was investigated to clarify the process chemistry of U(IV) oxidation and to provide a reference for the oxidation consumption of U(IV). Finally, the process parameters of the plutonium barrier unit were preliminarily designed based on the above research.

Identification and Characterization of Reclaimed and Underclaimed Mine Features Using Lidar and Temporal Remote Sensing Methods within the Coastal Plain Uranium Mining Region of Texas

We developed a spatiotemporal mapping approach utilizing multiple techniques for distinguishing and mapping known reclaimed mine sites from “unreclaimed” mine sites in a historic uranium mining district along the South Texas Coastal Plains. Lidar laser scanning penetrates the vegetation canopy to expose anthropogenic modifications to the landscape. The Lidar analysis (bare earth elevation surface, slope, topographic contours, topographic textures, and overland-flow hydrography) revealed mine features. Visual interpretation of Landsat imagery and time-series analysis augmented the Lidar analysis revealing the temporal life cycle of mining. The combination of bare earth texture with time-lapse and time-series analyses revealed areas of disturbance for reclaimed mines. The spatiotemporal mapping approach proved to be most useful in identifying and characterizing the known mine pit and pile features, reclamation status, and areas of disturbance due to mining. Two mine waste volume estimation methods resulted in a 21% difference indicating that although the approach helps to map mine features and areas of mining disturbance for the purposes of mine land inventory, additional information is needed to improve the estimation of buried mine waste at reclaimed mine sites.

Quantifying element mass transfer in the Jiling Na-metasomatic hydrothermal uranium deposit, Northwest China

The Na-metasomatic hydrothermal uranium deposits are relatively widespread, low in grade (less than 1 % U3O8) but high in tonnage. Although it has been considered that this type of deposit was formed due to hydrothermal alteration unrelated to magmatic activity, the detailed evolution of fluids and ore-forming process are still not well understood. Through element-mass-balance calculation and geochemical mapping of regional rocks, we investigated the Jiling uranium deposit in northwestern China and evaluated the composition and source of fluids and element-transfer behavior through Na-metasomatism and uranium mineralization. The findings show that, in the early Na-metasomatism stage, the Na-, HFSE- and REE-rich late-magmatic hydrothermal fluids caused Na-metasomatism of wall rocks, enriching Na2O (>53 %) while removing K2O (<-78 %), depleting SiO2 (30 % in granite and 3 % in diorite), and massively mass-transferring Fe, Ti, P and some incompatible elements. With increased rock permeability and the formation of partial Fe2+-bearing minerals, the Na-metasomatic alteration produced reducing agents and migration channels for ore-forming fluids, as well as the creation of ∼ 15 vol% porosity in the altered granite for metallogenic space. In the late uranium mineralization stage, CO2-rich fluids extracted uranium and HREEs, converted Fe2+ to Fe3+, and subsequently precipitated uranium to form pitchblende with apatite, calcite and chlorite. Thus, the Na-metasomatic alteration caused by late-magmatic hydrothermal fluids is critical for the production of large Na-metasomatic hydrothermal uranium deposits. Our new geochemical mapping reveals that the mass-concentration changes of Na, K and Si are more credible to defining Na-metasomatic alteration, while Fe, Ti, P, ∑(Zr-Hf-Nb-Ta) and ∑LREE/∑HREE vary strikingly during the uranium mineralization process.

The genesis of intersection-type uranium deposits in south China: Insights from zircon and pitchblende U-Pb geochronology and pyrite sulfur isotopes of the Egongtang uranium deposit, southern Jiangxi

Intersection-type uranium deposits refer to the uranium deposits that are located at the intersection of mafic dykes and silicified faults and are an important type of granite-related uranium deposits in South China. However, the genesis of these deposits still remain poorly understood. The Egongtang uranium deposit is a typical intersection-type uranium deposit in the Huangsha uranium ore district (southern Jiangxi) that bears a number of NWW-trending mafic dykes, thus providing an excellent opportunity to study the genesis of intersection-type uranium deposits. In this study, the mineralization age and genesis of this deposit were constrained using in situ zircon and pitchblende U-Pb geochronology, whole-rock geochemistry, and pyrite sulfur isotope data. The zircon U-Pb dating constrains the crystallization ages of 240.4 ± 1.3 Ma and 160.7 ± 1.6 Ma for granites in the Huangsha ore district. The samples (including altered and unaltered) of the granites are characterized by variable whole-rock U contents of 5.8–14.1 ppm and Th/U ratios of 2.4–7.7, which favor the crystallization of uraninite in the granites and suggest U leaching from the granites during alteration. In situ U-Pb dating on pitchblende from the Egongtang uranium deposit yielded a lower intercept age of 89.8 ± 1.1 Ma, indicating that the uranium mineralization took place at the Late Cretaceous. Pyrite associated with pitchblende has δ34S values ranging from 1.6‰ to 3.8‰, suggesting a magmatic source. This study indicates that granites in this area might have represented the source of uranium for the Egongtang deposit, and that the uranium mineralization was probably related to the Late Cretaceous crustal extension in South China.

Measurement and mapping of radon exhalation rate around the uranium mines in Sikar, Rajasthan, India

Measurement and mapping of radon exhalation rate around the uranium mines in Sikar, Rajasthan, India

Bayesian identification and estimation of radon-related increased hazard rates of cancer death in the updated French cohort of uranium miners (1946-2014).

A recent update of the French cohort of uranium miners added seven years of follow-up data. We use these new data to look for new possible radon-related increased risks and refine the estimation of the potential association between cumulative radon exposure and four cancer sites: lung cancer, kidney cancer, brain and central nervous system (CNS) cancer and leukemia (excluding chronic lymphocytic leukemia, which is not radiation-induced). Several parametric survival models are proposed, fitted and compared under the Bayesian paradigm, to perform new and original exposure-risk analyses. In line with recent UNSCEAR recommendations, we consider time-related effect modifiers and exposure rate as potential effect modifying factors. We use Bayesian model selection criteria to identify radon-related increased hazard rates. Under the assumption of a linear exposure-risk relationship, we found a substantial evidence for a strictly positive effect of cumulative radon exposure on the hazard rate of death by lung cancer among French uranium miners. Given the current available data under the assumptions of a linear or log-linear exposure-risk relationship, it is not possible to conclude in favour of the absence or the existence of a strictly positive effect of chronic exposure to radon on the hazard rate of death by kidney cancer. Regarding death by brain and CNS cancer, there is a substantial evidence for the absence of radon-related effect. Finally, under the assumption of a log-linear exposure-risk relationship, a small positive radon-related effect appears when looking at the risk of death by leukemia (excluding CLL). This study investigates the existence of radon-related increased risk of death by lung cancer, kidney cancer, brain and CNS cancer and leukemia under a Bayesian framework and assumptions of linear and log-linear exposure-risk relationships. If there is no doubt in the interpretation of the results for lung cancer and brain and CNS cancer, the conclusion is less clear-cut in the case of kidney cancer and leukemia (excluding CLL). A future update of the French cohort, increasing the follow-up time for miners, may help to reach a clearer conclusion for these two cancer sites.

Following the yellowcake road: exploring the colonial roots and routes of Australian radioactive minerals, 1900s–1950s

ABSTRACT Over the past 40 years, environmental justice activists and scholars have drawn greater attention to the disproportionate environmental burdens borne by marginalised communities. This includes the consequences of ‘nuclear colonialism’, a phenomenon defined as constituting ‘a system of domination through which governments and corporations target indigenous peoples and their lands to maintain the nuclear production process’. In this article, I seek to complicate this definition of nuclear colonialism by exploring the role of uranium mining in consolidating both British and Australian settler colonial power during the first half of the twentieth century. I will do so through an examination of Australian uranium’s roots and routes as both a manifestation and facilitator of settler colonialism in Australia between 1900 and 1955. Combining sources from both British and Australian archives, this article seeks to contribute to emergent scholarship on the colonial dimensions of mineral extraction in two ways. Firstly, by explicating the role uranium played in fuelling the extractive mentalities of settler colonial Australia. And secondly, by exploring uranium extraction’s contribution to the consolidation of the British Empire’s waning power in the mid-twentieth century.

Radiological characterisation of freshwater fish species from strategic locations in Bangladesh

A radiological assessment of inland freshwater fishes of wetland haor zones, near a uranium mine and Rooppur Nuclear Power Plant (RNPP) areas, was performed. Gamma spectrometric analysis showed the accumulation of 226Ra, 228Ra, and 40K in all studied fishes, with varying degree levels of concentrations. The average radioactivity levels of 226Ra, 228Ra and 40K in haor fish samples ranged from 2.76 ± 1.51 to 22.02 ± 3.81 Bq kg−1, 1.78 ± 0.69 to 21.53 ± 1.40 Bq kg−1 and 405.51 ± 22.04 to 749.80 ± 42.65 Bq kg−1, respectively. Conversely, the respective values for Bata fish samples of Rooppur Nuclear power plant sites varied from 2.66 ± 0.80 to 6.62 ± 0.81 Bq kg−1, 2.31 ± 0.62 to 5.18 ± 49.81 Bq kg−1 and 342.00 ± 4.98 to 461.45 ± 18.00 Bq kg−1, respectively. Activity levels of Taki fish (Channa punctatus) from haors zones were almost 3–4 times higher than the Meni fish (Nundus nundus) of the same locations and Bata fish (Labeo bata) of the RNPP site. The general public may attain doses of 244.54 µSv from the consumption of haor fish and 84.02 µSv from the fish of the RNPP sites yearly. The chance of an increase in cancer risk from intake of haor fish was higher than the ICRP values of 2.9 × 10−4. Univariate statistics showed that 226Ra and 228Ra radionuclides do not normally distribute, whereas 40K is normally distributed in the studied fish species. Multivariate statistical analysis demonstrated that the radioactivity and estimated radiological parameters are strongly positively correlated with 226Ra and 228Ra, and also positively correlated with 40K. Hence, it indicated that the contents in the freshwater fish species are usually controlled and influenced by similar geogenic sources and occur together. It is presumed that the radiological risk is mostly associated with and dominated by the uranium and thorium series and non-series 40K radionuclides in the freshwater fish species.

Classification of Logging Data Using Machine Learning Algorithms

A log data analysis plays an important role in the uranium mining process. Automating this analysis using machine learning methods improves the results and reduces the influence of the human factor. In particular, the identification of reservoir oxidation zones (ROZs) using machine learning allows a more accurate determination of ore reserves, and correct lithological classification allows the optimization of the mining process. However, training and tuning machine learning models requires labeled datasets, which are hardly available for uranium deposits. In addition, in problems of interpreting logging data using machine learning, data preprocessing is of great importance, in other words, a transformation of the original dataset that allows improving the classification or prediction result. This paper describes a uranium well log (UWL) dataset generated with the employment of floating data windows and designed to solve the problems of identifying ROZ and lithological classification (LC) on sandstone-type uranium deposits. Comparative results of the ways of solving these problems using classical machine learning methods and ensembles of machine learning algorithms are presented. It has been shown that an increase in the size of the floating data window can improve the quality of ROZ classification by 7–9% and LC by 6–12%. As a result, the best-quality indicators for solving these problems were obtained, f1_score_macro = 0.744 (ROZ) and accuracy = 0.694 (LC), using the light gradient boosting machine and extreme gradient boosting, respectively.

Using Electrical Resistivity Tomography to Understand the Hydrogeological Behavior of Acid Drainage Percolation in a Fractured Aquifer at a Uranium Mining Site

Using Electrical Resistivity Tomography to Understand the Hydrogeological Behavior of Acid Drainage Percolation in a Fractured Aquifer at a Uranium Mining Site

A model for operational risk of industrial facilities including ageing/test degradation effects and maintenance effectiveness

The paper presents a model for operational risk of industrial facilities with applications to nuclear power plants and uranium mining. The traditional models update the risk profile for specific operational conditions setting to one the failure probability of components which are known to be unavailable by failure or maintenance, while constant mean unavailability values from the original Probabilistic Safety Analysis (PSA) are kept for the rest. The proposed methodology considers the time dependency of standby failure probabilities through instantaneous unavailability models, depending on the specific standby time for each component at the given moment, instead of using the same constant values. It also incorporates ageing, testing degradation effects and maintenance effectiveness, not explicitly considered in traditional models, as well as the instantaneous reevaluation of common cause failure probabilities. The results show significant risk underestimations when components specific standby times, ageing, testing degradation effects and maintenance effectiveness are not considered.

Uranium Mine Proposed Experimental Design for Natural Background Gross Gamma Exposure Rates, Post Remediation Final Status Survey Sampling Density, and Radiological Water Quality Modeling for a Worst-case Catastrophic Failure, Coles Hill, Virginia.

Completely randomized experimental design statistical modeling techniques were employed to analyze exposure rate measurements for evaluating hypothetical natural background post uranium mill operations at Coles Hill, Virginia uranium milling processes. The proposed Coles Hill Uranium Mine is situated upstream of the Banister River. This River is nearly homogenous throughout the reach length used in analysis and feeds into the mouth of Kerr Reservoir, Lake Gaston, which serves as the main drinking water source for cities in the Hampton Roads area including Norfolk, Virginia Beach, and Chesapeake. A critical scan value (=DCGLscan) was developed to flag anomalies of surface contamination during simulated post remediation final status surveys. The natural background was critical for meeting the Multi-Agency Radiation Survey and Site Investigation Manual guidance for post remediation final status surveys. The overarching null hypothesis suggested that the selected mean natural background is equal to the survey unit's mean natural background. Using SAS Procedures Shapiro-Wilk Test, ANOVA, and CR, it was decided the exposure rate data was normal, had no extreme outliers, and no collinearity between the number of samples (=treatment) and the areas (=block). Using the q-hyper (hypergeometric) distribution, the soil sampling density was decided for a final status survey unit. The most likely worst-case catastrophic failure analysis, 500-year event, such as the1969 Hurricane Camille of 69 centimeters of rain in Nelson County, Virginia was included in the model. The model showed impact was minimal at most to the Banister River's drinking water and likely less than the Virginia's Drinking Water Standards for gross alpha, 226Ra and 228Ra, and total uranium.

Radon an indoor risk: In the Urban Devarakonda, Telangana state, India

Natural background radiation risk owing to radon and its progeny at indoors to the general public is a significant issue. The concern about indoor radon risk has been increasing at national and international level since its role to the overall dose is well known. The current study aims to assess the 222Rn and its progeny in different type of indoors with a passive (SSNTD) and active technique (RAD-7). The area of investigation (urban Devarakonda), is located near the proposed uranium mineralization area. The estimated radon levels in the indoors were ranging from 20 to 437 Bq. m−3 and with a geometric mean of 66 Bq.m−3. The estimated EERC values are ranging from 22 to 82 Bq.m−3 and these are higher than the range limit prescribed by ICRP. The computed average EF value in the present study (0.58) is relatively higher than the world average value of 0.4. An effort has been made to comprehend the radon distribution among the representative locations. Annual effective inhalation dose was also estimated using the occupancy factor 0.8 and it is found in the range of 0.52–11.00 m Sv y−1 with geometric mean of 2.20 mSv.y−1. The diurnal variation of 222Rn levels was studied using RAD-7 in a dwelling and seasonal variation of radon levels was also to be discussed in this paper.

Calorimetry and structural analysis of uranyl sulfates with rare topologies

Abstract Uranyl sulfate minerals are the most rapidly expanding group of uranium minerals, with dozens of species described in the past decade from the localities of White Canyon, U.S.A. and Jáchymov, Czech Republic. Synthetic analogs of a suite of uranyl sulfate minerals were crystallized, characterized, and the standard-state enthalpies of formation (ΔHfo) were determined. Synthetic lussierite is monoclinic, space group Cc, a = 9.2896, b = 28.685, c = 9.6155 Å, β = 93.504°. Synthetic geschieberite is ortho-rhombic, space group Pna21, a = 13.7408, b = 7.2713, c = 11.5844 Å. The standard-state enthalpies of formation from the binary oxides for lussierite, péligotite, shumwayite, geschieberite, and bluelizardite are –3214 ± 78, –2026 ± 33, –587 ± 22, –966.1 ± 10.9, and –2084 ± 21 kJ/mol, respectively, while the standard-state enthalpies of formation of each phase from its elements are –9743 ± 78, –7220 ± 33, –5255 ± 22, –3916 ± 20, and –7117 ± 21 kJ/mol, respectively. The ΔHfo of péligotite was accurately estimated using the ΔHfo of lussierite, bluelizardite, and literature values of the oxide components of each phase. This implies that estimates can be made accurately of the ΔHfo of uranyl sulfates of minerals without synthetic analogs.

Multi-source machine learning and spaceborne remote sensing data accurately predict three-dimensional soil moisture in an in-service uranium disposal cell

One reason arid and semi-arid environments have been used to store waste is due to low groundwater recharge, presumably limiting the potential for meteoric water to mobilize and transport contaminants into groundwater. The U.S. Department of Energy Office of Legacy Management (LM) is evaluating selected uranium mill tailings disposal cell covers to be managed as evapotranspiration (ET) covers, where vegetation is used to naturally remove water from the cover profile via transpiration, further reducing deep percolation. An important parameter in monitoring the performance of ET covers is soil moisture (SM). If SM is too high, water may drain into tailings material, potentially transporting contaminants into groundwater; if SM is too low, radon flux may increase through the cover. However, monitoring SM via traditional instrumentation is invasive, expensive, and may fail to account for spatial heterogeneity, especially over vegetated disposal cells. Here we investigated the potential for non-invasive SM monitoring using radar remote sensing and other geospatial data to see if this approach could provide a practical, accurate, and spatially comprehensive tool to monitor SM. We used theoretical simulations to analyze the sensitivity of multi-frequency radar backscatter to SM at different depths of a field-scale (3 ha) drainage lysimeter embedded within an in-service LM disposal cell. We then evaluated a shallow and deep form of machine learning (ML) using Google Earth Engine to integrate multi-source observations and estimate the SM profile across six soil layers from depths of 0–2 m. The ML models were trained using in situ SM measurements from 2019 and validated using data from 2014 to 2018 and 2020–2021. Model predictors included backscatter observations from satellite synthetic aperture radar, vegetation, temperature products from optical infrared sensors, and accumulated, gridded rainfall data. The radar simulations confirmed that the lower frequencies (L- and P-band) and smaller incidence angles show better sensitivity to deeper soil layers and an overall larger SM dynamic range relative to the higher frequencies (C- and X-band). The ML models produced accurate SM estimates throughout the soil profile (r values from 0.75 to 0.94; RMSE = 0.003–0.017 cm3/cm3; bias = 0.00 cm3/cm3), with the simpler shallow-learning approach outperforming a selected deep-learning model. The ML models we developed provide an accurate, cost-effective tool for monitoring SM within ET covers that could be applied to other vegetated disposal cell covers, potentially including those with rock-armored covers.

Characterization of mineral composition using PIXE and EXAFS analyses to elucidate the Barium adsorption mechanism

Ningyo-toge is a uranium (U) mine that was operative in Japan. Currently, the mining area retains a dump of mill tailings. Groundwater is contaminated with U ore, and mill tailings might contain radioactive elements, such as U and radium (Ra), which can negatively impact the human body. This study determined the soil composition at the tailings dumping site using particle-induced X-ray emission, scanning electron microscopy, and X-ray diffraction and observed the adsorption structure of barium (Ba), an analog of Ra, using X-ray absorption fine structure analysis. The results revealed the existence of silicate minerals, such as quartz and mica, and metal oxides, such as Fe and Mn, in the soil. Ningyo-toge soil is similar to montmorillonite and bentonite. In particular, it was proposed that the adsorption of Ba on Mn oxide is an inner-sphere complex that immobilizes Ba. These findings will provide valuable information for estimating the behavior of Ra in the environment. The results of this study will be helpful for safety assessment and evaluating the impacts on the surrounding environment.

MMs (metals and metalloids) based 238U, 226Ra, 232Th,40 K contamination and health risk assessments in different surface soils near an uranium mine of Southeast China

MMs (metals and metalloids) based 238U, 226Ra, 232Th,40 K contamination and health risk assessments in different surface soils near an uranium mine of Southeast China