Refereed Journals

This study addresses the limitations of Ghana's road traffic crash database, which lacks geographical coordinates, making it difficult to conduct spatial analyses for effective road safety interventions. The research focuses on creating a spatial database and performing spatiotemporal and statistical analyses of road traffic crashes along the N6 and N10 highways in the Ashanti Region from 2018 to 2020. A combination of primary and secondary data sources was used, with crash location data geocoded using postmile linear referencing. Validation of geocoded data was conducted using ground truth points, and positional accuracy was assessed through Root Mean Square Error (RMSE) calculations. Various spatial statistical methods, including Kernel Density Estimation and Hotspot Analysis using Getis-Ord Gi*, were applied to identify crash clusters and high-risk locations. The results indicate that geocoded crash points were accurate, with RMSE values of ±15 m for northings and ± 14 m for eastings, aligning with the recommended 100m buffer for crash location accuracy. The findings highlight critical crash hotspots, particularly at major intersections, emphasizing the need for targeted road safety interventions. The study demonstrates the potential of integrating geospatial data with traditional crash databases to improve road safety planning in Ghana.

Modern sustainable agriculture often relies on pesticide application, which may unintentionally affect non-target soil microorganisms. This study assessed the effects of commonly used pesticides in cabbage cultivation on bacteria diversity, composition, and abundance in soils from some farming communities in Bosome Freho District, Ghana. The pesticides included a neonicotinoid (acetamiprid), microbial agents (Pieris rapae granulosis virus+ Bacillus thuringiensis), avermectin (emamectin benzoate), and pyrrole (chlorfenapyr). Soil samples were collected from non-contaminated (NCS), abandoned pesticide-contaminated (AB-PCS) and actively pesticide-contaminated (AC-PCS) soils. Bacteria communities were analysed in the soil at phylum, class, order, family, genus, and species levels using 16S rRNA gene sequencing. The soils were also analyzed for physicochemical properties. Our results showed a decrease in bacteria diversity and abundance in pesticide-contaminated soils in the following order: NCS > AB-PCS > AC-PCS. Sorensen’s coefficient of similarity indicated major shifts in bacteria taxa composition due to pesticide contamination. In NCS, Pseudomonas veronii, Bacillus sp., and Prevotella albensis were the most abundant species, while Rhodoplanes elegans and Nostocoida limicola dominated AB-PCS. In AC-PCS, R. elegans, Gemmata obscuriglobus, Nitrospira calida, and N. limicola were the most abundant species. The abundance of Bacillus sp., P. veronii, and P. albensis decreased in the contaminated soils, while the abundance of N. calida, Cystobacter sp., Pedomicrobium australicum and Byssovorax cruenta was higher in the contaminated soils. Key genera involved in nutrient cycling such as Clostridium, Bacillus, Prevotella, Pseudomonas, and Arthrobacter, declined in abundance in pesticide exposed soils. In contrast, an increase in abundance of various taxa such as Pedomicrobium, Hyphomicrobiaceae, Pirellulaceae, Comamonadaceae, Nitrospirales, Nitrospira, Anaerolineae, Planctomycetes, Acidobacteriaí and Nitrospirae was observed in the contaminated soils. These bacteria may possess bioremediation potential that could be exploited for environmental remediation. Soil physicochemical properties and nutrient levels varied across the three soil treatments, with potential implications for bacteria community structure.

Traffic congestion, mobility challenges, and CO₂ emissions are global issues that require innovative solutions. This study explores the potential of Advanced Traveler Information Systems (ATIS) to alleviate congestion in Kumasi, Ghana, by leveraging Information and Communication Technologies (ICT) to encourage voluntary travel behavior change. It also aims to assess road users' attitudes towards ATIS in Ghana. A cross-sectional design was used, with closed-ended questionnaires sampling 1206 respondents through a multi-stage technique. A binary logistic regression model identified significant factors influencing ATIS use, including driver type, sex, age, education, income, and length of stay in the city (P < 0.05). Despite 98 % of road users being aware of ATIS, actual usage remains low, with only 61 % utilizing the technology for trip planning. The study recommends building a robust ATIS infrastructure while ensuring data privacy. These findings emphasize the need to explore factors beyond awareness, such as usability, perceived benefits, and trust in the system.

Natural rubber (NR) in bituminous mixes is a great innovation in the production of sustainable and quality binders for mostly road and pavement construction. This chapter reviews some studies on the feasibility of NR in bituminous mixes for road and pavement construction. The nature, properties, and uses of NR, the modification of bitumen using NR, and the effect of NR on bituminous mixes are reviewed and discussed. The review has shown that NR can be used for sustainable construction of pavements and roads. The optimum proportion of NR was reported to be 4–8% of the bituminous mixes from various studies. The increase in viscoelasticity of the resulting binder may help improve the service life of pavements while reducing maintenance costs. However, the limited number of field studies on the performance of NR-modified bitumen suggests the need for further research in this regard to determine the costeffectiveness of its use as a binder for commercial purposes. Tropical countries, which are also producers of NR and yet rely on imported bitumen for the construction of roads, could boost their domestic consumption and make some savings by incorporating NR in the bituminous mixes for the construction of asphaltic roads.

The recurring upsurge of illegal mining activities in the Bole District has led to the rapid disruption of the existing biodiversity stemming from the absence of periodic studies in the area. Also, little attention has been paid to the performance evaluation of modern classification algorithms such as SVM and RF in African tropical regions, of which Ghana is no exception. This paper aims to assess the impact of mining activities in the Bole District (2005–2020) using LULC trend analysis and future impact predictions of 2030. The research further focuses on the performance evaluation of SVM and RF classifiers, showcasing how different machine learning algorithms capture LULC variations and contribute to the advancement of mapping techniques. The results indicate the superiority of the SVM in pixel-based image classification tasks. Notable changes in LULC between 2005 and 2020 include a significant increase in built-ups by 454.77%, attributed to an influx of people due to the growth of small-scale mining activities. Bare lands increased by 88.79% due to land clearance for farming purposes and small-scale illegal mining. This study will thus serve as a guide for individuals, developers, the government, and other stakeholders in biodiversity conservation for further research and decision making.