The University for Development Studies, Tamale was established in 1992 by the government of Ghana with a view to accelerating the development of the then 3 Northern Regions of Ghana (the Northern, Upper East and Upper West Regions). The late President Jerry John Rawlings played a crucial role in its founding as he used his prized money from World Food Prize of $50,000 as seed money for its founding. It was set up as a multi-campus institution. It is the fifth public university to be established in Ghana. This deviates from the usual practice of having universities with central campuses and administrations. It was created with the three northern regions of North Ghana in mind. These are the Northern Region, Upper East Region and the Upper West Region. It has four campuses in all, eight Faculties, a Business School, one Medical School, one Graduate School, one Institute and three centres.
Illegal small-scale mining (galamsey) is a vital source of livelihood in Ghana. Its contribution to Ghana's national gold production is significant. However, galamsey is associated with many environmental challenges, posing serious threats to biodiversity and public health. Although extensive research has investigated the environmental impacts of galamsey, the scientific literature on potential remediation strategies remains relatively scarce. This study fills this gap in the literature by synthesising evidence of galamsey-related pollution pathways, pollutant profiles, and remediation techniques, including emerging low-cost and locally driven methods. The study found that galamsey has destroyed several hectares of forests, degraded land resources, caused biodiversity loss, reduced agricultural productivity, and polluted water bodies (including Pra, Birim, Ankobra, Tano, and Offin rivers) and soils, and rendered the air, especially in the mining areas, unsafe. The findings indicate that chemical pollution and high turbidity dominate water bodies in Southern Ghana, while Northern Ghana faces severe soil degradation and heightened desertification risks. This study explores various biological, physical, and chemical remediation techniques that can be applied, with recent advances highlighting phytoremediation and sorption as key approaches widely tested in galamsey-polluted environments over the past decades. To address the interwoven environmental challenges, this review highlights proposals for sustainable small-scale mining and ecological restoration. This paper is expected to advance environmental remediation strategies for addressing the galamsey challenge, in line with measures aligned with the attainment of the United Nations Sustainable Development Goals (SDGs).
Domestic cats and dogs are the most widely distributed animals associated with humans. They influence wildlife mortality through predation. Yet, little is known about their impacts in the protected landscapes of many African countries. We investigated the relationship between pet husbandry practices and wildlife predation within Ghanaian communities adjacent to protected areas to fill this knowledge gap using a mixed-methods approach. Descriptive statistics were used to summarise information on pet demography and husbandry practices, while generalised linear models were used to examine predictors of pet predation on wildlife. We found that most cats and dogs had unrestricted outdoor access, were provided rationed food, and were undewormed and unvaccinated. Predation on wildlife was significantly higher in cats than in dogs. Notably, pet age significantly influenced bird predation but showed no effect for reptiles. Pets fed rationed food were more likely to prey on wildlife than those fed ad libitum. Thus, poor feeding practices and unrestricted outdoor access increased the likelihood of predation and exposure to pathogens. Our findings underscore the need for integrated strategies (e.g. education and improved husbandry practices) under a One Health framework to mitigate impacts on wildlife and zoonotic diseases of public health concern in protected landscapes.
Artisanal and Small-Scale Mining (ASM) is a critical driver of soil contamination in West Africa, yet quantifying the relative contributions of natural and anthropogenic sources remains a major challenge. This study presents an integrated framework combining contamination indices, receptor modelling, and Machine Learning (ML) to evaluate Potentially Toxic Element (PTE) dynamics in soils from the Nangodi area, northern Ghana. A total of 552 grid-based soil samples were analysed for Cr, Co, Cu, Pb, V, and Zn using ED-XRF. Descriptive statistics revealed highly skewed distributions and elevated coefficients of variation for Cr, Co, and Cu, reflecting heterogeneous contamination patterns typical of ASM terrains. Pollution indices indicated divergent outcomes: the ecological Risk Index (RI) classified all samples as low risk (RI < 150), whereas the Nemerow Integrated Pollution Index (NIPI) identified 35.5
Access to improved sanitation remains essential for achieving the Sustainable Development Goals and promoting good health. Despite efforts to end open defecation, including through the adoption of community-led total sanitation, open defecation remains a significant challenge in developing countries. This study investigated predictors of open defecation in the Sagnarigu municipality of Ghana’s Northern Region. A cross-sectional design and a quantitative approach were adopted among households in sampled communities implementing the Community-Led Total Sanitation approach. Chi-square tests and binary logistic regression models were used to analyse the data at the bivariate and multivariate levels at a 95
Geochemical exploration has been an indispensable approach to mineral exploration and has been responsible for significant mineralization discoveries across the globe. With the increasingly difficult exploration targeting, there is a need for an add-on in the geochemical data processing techniques that has the qualities of enhancing exploration targeting even with the slightest of geochemical signatures. In recent years, machine learning methods coupled with multivariate statistical methods have gradually proven to be a good add-on to the geochemical data processing techniques, which are yielding positive exploration targeting results. Although similar studies aimed at enhancing exploration targeting have been conducted in some parts of the Tanzania Craton (TC) using the same approach, these earlier works did not include the sensitivity analysis of the mineralization characteristics within the TC. Hence, this study seeks to trace the potential source(s) of Au-Pt-Pd in stream sediments, their pathfinder elements, and the most sensitive elements to their occurrence in the study area. The study adopted multivariate statistics together with regression modeling, artificial neural network (ANN), and sensitivity analysis methods. The elemental association of Sr, Ba, Nb, and Rb suggests felsic igneous rocks, and Co, Ni, V, and Cr indicate mafic rock sources of the Au-Pd-Pt. The most sensitive elements to the Au occurrence in the area are Zn, Bi, Sr, Ca, K, Sn, Y, and Nb, while those for Pd are Au and Pt. The prediction model for Au performed better with RE values of 0.787 and 0.576 in training and testing stages, respectively. The geological complexity of the TC might have accounted for the variable pathfinder elements of Au within the different Au-bearing catchments. From the graphical illustration of the workflow, the study was conducted with the aim of elucidating the source of Au-Pd-Pt in stream sediments in the central parts of Tanzania. A total of 126 stream sediment samples were collected. This sample size includes 9 samples for QC and QA purposes. The samples were analyzed using the ICP-MS analytical method. The samples were processed using SPSS and ArcGIS to reveal trends, elemental associations and clusters, patterns, and spatial distribution. Multivariate statistics, multivariate linear regression modeling, and artificial neural networks were combined to bring out insight and hidden patterns and associations, as well as the sensitivity of the trace elements to the occurrences of the Au-Pd-Pt mineralization in the area. Exploration targeting is increasingly becoming difficult. Multimethod techniques are a reliable alternative to enhancing exploration targeting. Multi-techniques were adopted in the study to trace Au-Pd-Pt sources in stream sediments. The mineralization of Au-Pd-Pt in the area is associated with both felsic and mafic rocks. Zn, Bi, Sr, Ca, K, Sn, Y, and Nb are the most sensitive elements to Au occurrence in the area.
