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Vushe, A., & Amutenya, M. (2019). Investigating nitrate retention capacity, elementary and mineral composition of Kalahari sandy soils at Mashare farm in Namibia, Okavango river basin. Scientific African, 6, 00193.
Abstract: Kalahari sands which cover a large part of Southern Africa and extend into Central Africa are infertile and marginal soils for intensive agriculture. Therefore, high nitrogen fertilisation rates may degrade ecosystems of rivers with catchments covered by the Kalahari sands. A study on Mashare Farm located in the Okavango River basin showed that irrigated Kalahari sandy soils had a nitrate retention capacity, which enabled the soil to resist nitrate leaching in water saturated conditions. The irrigated soils were modified by agricultural activities; hence this study investigated if uncultivated and cultivated Kalahari sand soils had similar nitrate retention properties. The elementary composition of the soils was investigated for obtaining an insight into chemical properties that may be causing the nitrate retention capacity. A permeameter was used to leach out nitrates from irrigated and uncultivated soil samples, and nitrate concentrations were measured on the leaching effluent from the permeameter. Elemental analysis was done on the cultivated and the uncultivated soil samples using a Scanning Electron Microscope, a portable X-Ray Fluorescence analyzer, and an X-Ray Diffraction machine, and the later was also used for crystalline structure analyses. Sieve analyses confirmed that the Mashare’s cultivated and uncultivated topsoils were similar, and both were similar to Botswana Kalahari topsoil. The irrigated and cultivated subsoil had a higher average nitrate retention capacity of 76% compared to 73% for the uncultivated subsoil. Both samples had the same elements, although the proportions were different. Both soil samples were dominated by a quartz mineral, but the field soil had traces of palygorskite. The presence of aluminum and transition metals outside the minerals structure, but as coatings on the quartz sand grains enhanced nitrate retention capacity properties of the Kalahari sand soils.
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Merembayev, T., Yunussov, R., & Yedilkhan, A. (2019). Machine Learning Algorithms for Stratigraphy Classification on Uranium Deposits. Procedia Computer Science, 150, 46–52.
Abstract: Machine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words – it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost.
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Botha, R., Lindsay, R., Newman, R. T., Maleka, P. P., & Chimba, G. (2019). Radon in groundwater baseline study prior to unconventional shale gas development and hydraulic fracturing in the Karoo Basin (South Africa). Applied Radiation and Isotopes, 147, 7–13.
Abstract: The prospect of unconventional shale gas development in the semi-arid Karoo Basin (South Africa) has created the prerequisite to temporally characterise the natural radioactivity in associated groundwater which is solely depended on for drinking and agriculture purposes. Radon (222Rn) was the primary natural radionuclide of interest in this study; however, supplementary radium (226Ra and 228Ra) in-water measurements were also conducted. A total of 53 aquifers spanning three provinces were studied during three separate measurement campaigns from 2014 to 2016. The Karoo Basin’s natural radon-in-water levels can be characterised by a minimum of 1 ± 1 Bq/L (consistent with zero or below LLD), a maximum of 183 ± 18 Bq/L and mean of 41 ± 5 Bq/L. The mean radon-in-water levels for shallow aquifers were systematically higher (55 ± 10 Bq/L) compared to deep (14 ± 3 Bq/L) or mixed aquifers (20 ± 6 Bq/L). Radon-in-water activity concentration fluctuations were predominantly observed from shallow aquifers compared to the generally steady levels of deep aquifers. A collective seasonal mean radon-in-water levels increase from the winter of 2014 (44 ± 8 Bq/L) to winter of 2016 (61 ± 16 Bq/L) was noticed which could be related to the extreme national drought experienced in 2015. Radium-in-water (228Ra and 226Ra) levels ranged from below detection level to a maximum of 0.008 Bq/L (226Ra) and 0.015 Bq/L (228Ra). The 228Ra/226Ra ratio was characterised by a minimum of 0.93, a maximum of 6.5 and a mean value of 3.3 ± 1.3. Developing and improving baseline naturally occurring radionuclide groundwater databases is vital to study potential radiological environmental impacts attributed to industrial processes such as hydraulic fracturing or mining.
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Ruiz, O., Thomson, B., Cerrato, J. M., & Rodriguez-Freire, L. (2019). Groundwater restoration following in-situ recovery (ISR) mining of uranium. Applied Geochemistry, 109, 104418.
Abstract: From 1950 through the early 1980’s New Mexico accounted for roughly half of domestic uranium (U) production for the nuclear power industry and the nation’s weapon programs. Increased interest in nuclear energy has led to proposals for renewed development using both underground mining and uranium in situ recovery (ISR). When feasible, ISR greatly reduces waste generated by the mining and milling processes, however, the ability to restore ground water to acceptable quality after ISR ends is uncertain. This research investigated two methods of stabilizing an aquifer following ISR. Batch and column studies were performed to evaluate chemical and biological methods of stabilization. Columns packed with ore were first leached with an aerated NaHCO3 ground water solution to simulate ISR. Constituents present at elevated concentrations after leaching included molybdenum (Mo), selenium (Se), U, and vanadium (V). Chemical stabilization was studied by passing a phosphate (PO43-) amended solution through the ore to achieve passivation of mineral surfaces by P precipitates. Microbial stabilization was studied by passing a lactate solution through the ore to stimulate growth of anaerobic metal- and sulfate-reducing organisms to reduce U and other elements to less soluble phases. Analyses of the solids from the columns after completion of these experiments by X-ray photo electron spectroscopy (XPS) identified phosphate on samples near the column inlet of the chemically stabilized columns. Microbial populations were characterized by Illumina DNA sequencing and confirmed the presence of metal- and sulfate-reducing organisms. Neither chemical nor microbial stabilization method achieved contaminant immobilization, which is believed due to limited mixing of the stabilization solutions with the contaminated leach solutions. These results emphasize that ground water hydrodynamics, especially mixing, must be considered in aquifer restoration of soluble constituents.
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Mühr-Ebert, E. L., Wagner, F., & Walther, C. (2019). Speciation of uranium: Compilation of a thermodynamic database and its experimental evaluation using different analytical techniques. Applied Geochemistry, 100, 213–222.
Abstract: Environmental hazards are caused by uranium mining legacies and enhanced radioactivity in utilized groundwater and surface water resources. Knowledge of uranium speciation in these waters is essential for predicting radionuclide migration and for installing effective water purification technology. The validity of the thermodynamic data for the environmental media affected by uranium mining legacies is of utmost importance. Therefore, a comprehensive and consistent database was established according to current knowledge. The uranium data included in the database is based on the NEA TDB (Guillaumont et al., 2003) and is modified or supplemented as necessary e.g. for calcium and magnesium uranyl carbonates. The specific ion interaction theory (Brönsted, 1922) is used to estimate activity constants, which is sufficient for the considered low ionic strengths. The success of this approach was evaluated by comparative experimental investigations and model calculations (PHREEQC (Parkhurst and Appelo, 1999)) for several model systems. The waters differ in pH (2.7–9.8), uranium concentration (10−9-10−4 mol/L) and ionic strength (0.002–0.2 mol/L). We used chemical extraction experiments, ESI-Orbitrap-MS and time-resolved laser-induced fluorescence spectroscopy (TRLFS) to measure the uranium speciation. The latter method is nonintrusive and therefore does not change the chemical composition of the investigated waters. This is very important, because any change of the system under study may also change the speciation.
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