Department of Earth Science

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    Provenance And Source Area Weathering Of Sandstones From The Tarkwaian Group At The Northeastern Extent Of The Paleoproterozoic Ashanti Belt, Ghana: Constraints From Petrography And Geochemistry.
    (Elsevier Ltd, 2025-01-09) Song, Y.; Asiedu, K.; Anani, C.Y.; et al.
    An integrated geochemical and petrographic study was conducted on the Paleoproterozoic sandstones of the Tarkwaian Group exposed at the northeastern extent of the Ashanti Belt, Ghana. Recognizing the economic importance of the Tarkwaian Group, particularly owing to its extensive gold deposits, the primary objective was to investigate the provenance, tectonic setting, and crustal evolution of the Tarkwaian Group. The dominant quartz (polycrystalline and monocrystalline), together with minor muscovite, feldspar, hematite, and lithic fragments, characterize the sandstones and thus, the sandstones are classified as sublitharenite, and lith icsubarkose. Based on mineralogical composition and major element content, the sandstones can be classified as litharenite, sublitharenite, and minor greywacke. The high values of SiO2/Al2O3 (average: 12.74), relatively moderate values of K2O/NaO2 (average: 1.42), and high quartz content (average: 88%) suggest that the sedi ments are compositionally sub-mature to mature. The sandstones likely underwent low to moderate levels of sedimentary sorting and recycling owing to angular to sub-rounded grains and moderate Zr/Sc and Th/Sc values. The high Chemical Index of Alteration (CIA) signature (average: 76.79 wt%), Plagioclase Index of Alteration (PIA) values (average: 90.13 wt%), and Index of Compositional Variability (ICV) (average: 0.61 wt%) suggest moderate to intense chemical weathering within the region of origin. Overall, the mineralogical and geochemical features of the sandstones, such as a high proportion of quartz and feldspar, and elevated concentrations of elements such as Zr, Sc and Th, and moderate to high ratios of Al2O3/TiO2 and La/Sc indicate that they were likely sourced from felsic to intermediate igneous rocks and deposited in an active continental margin such as magmatic arc setting.
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    Mineral Prospectivity Modeling over Julie Tenement of Northwestern Ghana using Geophysical Datasets
    (Journal of Mining and Environment (JME), 2024) Amponsah, P.O.; Forson, E.D.
    This study was set out to delineate prospective zones of gold mineralization occurrence over the Julie tenement of Northwestern Ghana using two spatial statistical techniques, namely information value (IV) and weight of evidence (W of E) models. First, 110 locations, where gold (Au) mineralization has been observed, were identified by field survey results derived from highly anomalous geo-chemical assay datasets. Of these 110 locations, 77 (representing 70% of the known locations, where gold has been observed) were randomly selected for training the aforementioned models, and the remaining 33 (analogous to 30% of the known Au occurrence) were used for validation. Secondly, eleven mineral conditioning factors (evidential layers) comprising analytic signal, reduction-to-equator (RTE), lineament density (LD), porphyry density, potassium concentration, thorium concentration, uranium concentration, potassium-thorium ratio, uranium-thorium ratio, geology, and arsenic concentration layers were sourced from geophysical, geological, and geo-chemical datasets. Subsequently, by synthesizing these eleven evidential layers using the two spatial statistical techniques, two mineral prospectivity models were created in a geographic information system (GIS) environment. Finally, the mineral prospectivity models produced were validated using the area under the receiver operating characteristics curve (AUC). The results obtained showed that the IV model produced had a higher prediction accuracy in comparison with the mineral predictive model produced by the W of E with their AUC scores being 0.751 and 0.743, respectively
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    Exploring soil pollution patterns in Ghana’s northeastern mining zone using machine learning models
    (Journal of Hazardous Materials Advances, 2025) Kwayisi, D.; Kazapoe, R.W.; Alidu, S.; et al.
    This study assessed the pollution status and effectiveness of machine learning models in predicting pollution indices in soils from a mining area in Northeastern Ghana. 552 soil samples were analysed with an Energy Dispersive X-ray Fluorescence (ED-XRF) spectrometer for their elemental concentrations. Four pollution indices; Nemerow Integrated Pollution Index (NIPI), degree of contamination (Cdeg), modified degree of contamination (mCdeg) and Pollution Load Index (PLI). Additionally, the Multivariate Adaptive Regression Splines (MARS) machine learning approach were used. The high CV%, skewness, and kurtosis values show a high degree of variability and uneven distribution patterns which denotes dispersed hotspots that can be interpreted as an influence of gold anomalies and illegal mining activities in the area. V (120.86 mg/L), Cr (242.42 mg/L), Co (30.92 mg/L) Ba (337.62 mg/L), and Zn (35.42 mg/L) recorded values higher than the global and regional contaminant thresholds. The NIPI shows that 46.74% and 26.81% of samples are slightly and moderately polluted respectively. The Cdeg analysis supports these findings, with 36.96% and 41.49% of samples classified as having “moderate” to “considerable” contamination, respectively. The PLI indicates progressive soil quality deterioration (43.84%) of samples reflecting substantial environmental disturbance. The pollution indices show the effect of illegal mining on Shaega, Buin and other areas in the eastern boundary of the study. The MARS models developed for the study demonstrated high predictive capabilities with an R2 value of 0.9665 for model 1 (NIPI), and RMSE and MAE values of 0.8227 and 0.4287 respectively. For model 2 (Cdeg), R2 value of 0.9863, RMSE and MAE of 1.0416 and 0.6181, respectively. Model 3 (mCdeg) produced an R2 value of 0.9844, RMSE and MAE of 0.1225 and 0.0670. These findings suggest MARS models can be an integral tool for soil quality analysis in cooperation with pollution indices. The study suggests that remedial and legislative measures be implemented to address the issue of illegal mining in the area.
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    Exploring soil pollution patterns in Ghana’s northeastern mining zone using machine learning models
    (Journal of Hazardous Materials Advances, 2024) Kwayisi, D.; Kazapoe, R.W.; Alidu, S.; et al.
    This study assessed the pollution status and effectiveness of machine learning models in predicting pollution indices in soils from a mining area in Northeastern Ghana. 552 soil samples were analysed with an Energy Dispersive X-ray Fluorescence (ED-XRF) spectrometer for their elemental concentrations. Four pollution indices; Nemerow Integrated Pollution Index (NIPI), degree of contamination (Cdeg), modified degree of contamination (mCdeg) and Pollution Load Index (PLI). Additionally, the Multivariate Adaptive Regression Splines (MARS) machine learning approach were used. The high CV%, skewness, and kurtosis values show a high degree of variability and uneven distribution patterns which denotes dispersed hotspots that can be interpreted as an influence of gold anomalies and illegal mining activities in the area. V (120.86 mg/L), Cr (242.42 mg/L), Co (30.92 mg/L) Ba (337.62 mg/L), and Zn (35.42 mg/L) recorded values higher than the global and regional contaminant thresholds. The NIPI shows that 46.74% and 26.81% of samples are slightly and moderately polluted respectively. The Cdeg analysis supports these findings, with 36.96% and 41.49% of samples classified as having “moderate” to “considerable” contamination, respectively. The PLI indicates progressive soil quality deterioration (43.84%) of samples reflecting substantial environmental disturbance. The pollution indices show the effect of illegal mining on Shaega, Buin and other areas in the eastern boundary of the study. The MARS models developed for the study demonstrated high predictive capabilities with an R2 value of 0.9665 for model 1 (NIPI), and RMSE and MAE values of 0.8227 and 0.4287 respectively. For model 2 (Cdeg), R2 value of 0.9863, RMSE and MAE of 1.0416 and 0.6181, respectively. Model 3 (mCdeg) produced an R2 value of 0.9844, RMSE and MAE of 0.1225 and 0.0670. These findings suggest MARS models can be an integral tool for soil quality analysis in cooperation with pollution indices. The study suggests that remedial and legislative measures be implemented to address the issue of illegal mining in the area.
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    Crustal evolution of alternating Paleoproterozoic belts and basins in the Birimian terrane in southeastern West African Craton
    (Journal of African Earth Sciences, 2024) Sakyi, P.A.; Kwayisi, D.; Nunoo, S.; et al.
    We present a comprehensive review of available geochemical, geochronological and isotopic data on granitoids from the Paleoproterozoic Birimian terrane of Ghana, aimed at providing an in-depth understanding of the geodynamic evolution of southeastern West African Craton. The focus is on plutonic magmatism, crustal recy cling and tectonic setting of the granitoids. The granitoids are mainly TTG suites, calc-alkaline granites, diorites, monzonites, two-mica granites and leucogranites. They are characterized by enrichments in LILE and LREE relative to HREE and HFSE. Their variable positive and negative Eu and Sr anomalies and depletions in Nb-Ta and Ti suggest the presence of residual minerals like hornblende and Fe-Ti oxides (e.g., rutile and ilmenite). The plutons probably formed by partial melting of hydrous basaltic/mafic crust metasomatized by slab-derived melts at different depths. The εHf (− 14.5 to +7.6) and εNd (− 5.3 to +3.5) values and Nd model ages (2.21–2.53 Ga) indicate their crystallization from juvenile magmas derived from a depleted mantle with significant recycling of older crustal material. The older (≥2200 Ma) and younger (<2100 Ma) ages recorded in both belt- and basin type granitoids indicate that magmatism in both types was contemporaneous. Nonetheless, the basins recorded younger peak emplacement ages compared to adjacent belts. The presence of inherited older zircon grains (Archean zircon cores?), is widespread in southeastern WAC. The granitoids formed in a continental arc setting via subduction–accretion processes. Furthermore, the magmatic time-span is more prolonged in southern Ghana, with the sedimentary basins recording the longest intervals of magma emplacement. The sub-chondritic εHf data and Hf model ages strongly suggest the existence of Neoarchean to Mesoarchean crustal material in eastern Ghana during the Birimian crust formation. We propose that the subduction-accretion processes during the Paleoproterozoic Eburnean orogeny in the WAC contributed to the formation of the Columbia supercontinent in the Late Paleoproterozoic-Mesoproterozoic.
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    Geological evaluation of black shale as a suitable Supplementary Cementitious Material (SCM) to optimize the use of clinker in cement production
    (Heliyon, 2024) Nunoo, S.; Owusu-Sasu, T.A.; Amponsah, P. O.; et al.
    Faced with challenges like resource depletion and climate change, the cement industry needs sustainable solutions. This study explores the potential of geologically-delinaeated black shale from Apersua, Ghana, as a supplementary cementitious material (SCM) to reduce reliance on traditional methods. The researchers analysed the shale’s chemical composition and mineralogy, then created laboratory cement formulations with varying black shale content. These were compared to standard formulations without shale. The results show cement with black shale has comparable compressive strength, meeting standard requirements. Even a formulation with only black shale (excluding limestone, a common ingredient) passed strength tests. Overall, the black shale demonstrated good potential as a SCM based on strength, chemical makeup, setting time, and its possible contribution to durability. This research suggests that black shales from Apersua are worth exploring further as a sustainable and potentially cost-effective alternative in cement production.
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    Multi-method machine learning techniques in gold pathfinder elements prediction in central parts of Tanzania using stream sediment geochemical data
    (Physics and Chemistry of the Earth, 2024) Nunoo, S.; Abu, M.; Ayitey, E.; Mvile, B. N.; Kalimenze, J. D.
    Prediction models using machine learning techniques have proven to be a reliable technique in mineral explo ration. A combination of these techniques is very robust and reliable in exploration targeting and much dependable as an approach in greenfield. In this study, multi-machine learning methods: random forest (RF), support vector machine (SVM), and artificial neural network (ANN) were employed to conduct a data-driven gold (Au) prospectivity modelling in the Central parts of the Tanzania Craton (TC). A total of 166 samples with Au concentrations from stream sediment samples were considered. Based on the modeling results, the RF model demonstrates superior prediction accuracy compared to the SVM (MSE of 0.89) and ANN models (MSE of 1.21), achieving an MSE of less than 0.82. In terms of overall predictive performance and efficiency, the RF model outperforms other ML models deployed in this research. Therefore, it is deemed the suitable model for gold (Au) prediction in the TC catchments. According to the geological interpretation derived from the model, anomalies in arsenic (As), nickel (Ni), and tungsten (W) now emerge as significant predictors in the quest for gold. This implies that the association of As–Ni–W are potential pathfinder elements in the exploration of gold in the central part of the TC.
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    Mineral Prospectivity Modeling over Julie Tenement of Northwestern Ghana using Geophysical Datasets
    (Journal of Mining and Environment (JME), 2024) Amponsah, P.O.; Forson, E.D.
    This study was set out to delineate prospective zones of gold mineralization occurrence over the Julie tenement of Northwestern Ghana using two spatial statistical techniques, namely information value (IV) and weight of evidence (W of E) models. First, 110 locations, where gold (Au) mineralization has been observed, were identified by field survey results derived from highly anomalous geo-chemical assay datasets. Of these 110 locations, 77 (representing 70% of the known locations, where gold has been observed) were randomly selected for training the aforementioned models, and the remaining 33 (analogous to 30% of the known Au occurrence) were used for validation. Secondly, eleven mineral conditioning factors (evidential layers) comprising analytic signal, reduction-to-equator (RTE), lineament density (LD), porphyry density, potassium concentration, thorium concentration, uranium concentration, potassium-thorium ratio, uranium-thorium ratio, geology, and arsenic concentration layers were sourced from geophysical, geological, and geo-chemical datasets. Subsequently, by synthesizing these eleven evidential layers using the two spatial statistical techniques, two mineral prospectivity models were created in a geographic information system (GIS) environment. Finally, the mineral prospectivity models produced were validated using the area under the receiver operating characteristics curve (AUC). The results obtained showed that the IV model produced had a higher prediction accuracy in comparison with the mineral predictive model produced by the W of E with their AUC scores being 0.751 and 0.743, respectively
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    Estimation of natural background and source identification of nitrate-nitrogen in groundwater in parts of the Bono, Ahafo and Bono East regions of Ghana
    (Groundwater for Sustainable Development, 2021) Manu, E.; Afrifa, G.Y.; Loh, Y.S.A.; et al.
    The identification of the chemical status of groundwater is a prerequisite for sustainable management and development of groundwater resources. A better assessment of the chemical status of the groundwater requires the knowledge and understanding of the natural background concentrations to establish threshold values of chemical pollutants in groundwater. The aim of this study is to estimate the natural background levels, the threshold value (TV) of nitrate-nitrogen (NO3) − -N) and to identify its source in the groundwater in the Bono, Ahafo and Bono East regions of Ghana. A total of 165 groundwater samples were taken from the crystalline and sedimentary aquifers in the study area. iterative outlier removal technique and a Gaussian mixture model were then used to assess the natural background and threshold nitrate-nitrogen concentrations in the groundwater. Chloride data was then used to trace the NO3 - source in the groundwater. The estimated NBL of NO3 − -N in the area ranges from [0.001–3.9] mg/L, with an expected value of 1.25 mg/L and calculated TV of 6.95 mg/L. The data suggest that NO3 − –N concentrations are homogeneous across all the lithologies underlying the study area. The results showed that agricultural, domestic, and denitrification contribute significantly to the loading of NO3 − –N concentration in the groundwater. The estimated threshold range of NO3 − –N provides the baselinenitrate-nitrogen concentration for future studies in the region. However, the results are inconclusive, and we recommend using isotopic detection. 15N-NO3 − and 18O-NO3 − ) in future studies through comprehensive and sustainable regional monitoring of the aquifer system in order to further limit the source of nitrate and nitrogen in the groundwater system.
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    Mineralizations of Nb-Ta-Rb-Zr and rare-earth elements in Boziguoer, South Tianshan, NW China: Geochronology and geochemistry of monazite and bastnasite
    (Ore Geology Reviews, 2024) Xie, M.; Fan, H.; Sakyi, P.A.; et al.
    The Boziguoer alkaline intrusion is located in the South Tianshan Orogenic Belt on the northern margin of the Tarim Craton. The intrusion is entirely mineralized and forms a super-large rare metal (RM) and rare-earth element (REE) deposit dominated by Nb-Ta-Rb, accompanied by Zr-REE. The primary RM minerals include pyrochlore, astrophyllite, and zircon, while the main REE minerals consist of fluocerite, monazite, xenotime, and bastnasite, ¨ which are commonly present as granular aggregates or singularly filling the interstices between gangue minerals. Through a combination of geochronological and geochemical analyses of different types of monazite and bastn¨ asite in the mineralized alkaline rocks, this study elucidates the role of magmatic hydrothermal evolution on the Boziguoer RM-REE mineralization and reconstructs the geochronological framework of alkalic magmatic-hydrothermal evolution and mineralization processes, as well as establishing mechanisms responsible for RM-REE enrichment. Petrographic observations and back-scattered electron (BSE) imaging revealed several types of monazite and bastnasite ¨ with different characteristics as follows: (1) type Ia monazite (Mnz-Ia) experienced intense hydrothermal alteration, forming residual cores of monazite mantled by apatite and allanite coronas; (2) type Ib monazite (Mnz-Ib) was partially eroded, forming concentric zoning patterns with a core of monazite, a mantle of apatite, and an outer rim of allanite coronas; (3) type II monazite (Mnz-II) is slightly modified, and commonly associated with fluorite; (4) bastnasite ¨ and fluocerite exhibit a core rim structure, with the core of fluocerite being brighter than the rim of bastnasite ¨ in BSE images. According to the paragenetic relationships and compositional variations, all two types of monazite are of primary magmatic origin, while bastn¨ asite is of hydrothermal origin. In addition, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results indicate that Mnz-Ia and Mnz-Ib belong to the same group, different from Mnz-II. The latter has higher (Ce/Gd)N and (Th/U)N ratios, indicating relatively low-temperature crystallization of Mnz-II at late stages. In-situ LA-ICP-MS U-Th-Pb dating of monazite and bastn¨ asite show that Mnz-Ia and Mnz-Ib have ages of ca. 290 Ma, consistent with the zircon age of the intrusion, whereas the Mnz-II and bastnasite ¨ have younger ages of ca. 280 Ma, representing a post-magmatic hydrothermal mineralization event at Boziguoer. These new ages indicate that both magmatic and subsequent hydrothermal processes played critical roles in the RM-REE mineralization in this deposit. The latest findings also support the model that the formation of the alkaline belt where the Boziguoer ore-bearing intrusion was temporally and spatially linked to the Tarim Large Igneous Province that is genetically related to a mantle plume.