Due to the COVID-19 pandemic, universities in Ghana instituted drastic interventions to support large-scale online teaching and learning. This study, therefore, examines student's participation, level of satisfaction, and related challenges in teaching and learning delivery during the Coronavirus pandemic. The study also selects significant predictors of student's e-learning perceptions. Data was collected via an online structured survey based on students from the Kumasi Technical University. In all 2000 complete responses were received and formed the basis for our analysis. The study results reveal that 197 (9.85% of the sample) were unable to fully participate due to challenges such as lack of access devices, unreliable internet connectivity, and inability to afford the cost of internet data. It is again clear from the results that about 90.1% of students are not satisfied with e-learning and its associated challenges. From the positive perception model, students held the view that e-learning technology in the COVID-19 era is positive regardless of the challenges. On the other hand, level 300 students, and Moodle VClass platform users express a high negative perception over the use of e-learning technology. It is clear from this study that further investments and contingency plans are needed to develop a resilient education system that supports electronic and distance learning and shapes the perception and acceptance of students. University managers and the Education Ministry should formulate post-COVID-19 strategies to promote e-learning in a developing country like Ghana.

Dust levels around the Tema industrial area of the Greater Accra Region have seen no reduction in recent years. Even though at some periods in time a natural drop in dust pollution levels is assured, the overall variation characteristics of the concentration of PM2.5, PM10, and Total Suspended Particles (TSP) have not been studied in recent years. This paper examines the levels of dust pollution across four (4) locations within the Tema metropolitan area with a specific interest in selecting locations and periods (weeks) significantly affected by dust pollution within the study area. Data collection was done over a nine-month period using the Casella 712 Microdust Pro Kit equipment. Measurements were done day and night at sampling points about 100 m apart in a given location. Monitoring was conducted once a week during the day and at night with a sampling period of 24 h per location, for thirty-six weeks. The generalized linear models were explored in selecting locations and weeks significantly affected by dust pollution. The study results showed no significant difference between pollution levels across the four selected locations. Eight, eleven, and five weeks out of the 36 weeks recorded significantly high concentrations of PM2.5, PM10, and TSP respectively. In addition, two out of the selected four areas (the oil jetty area and the VALCO hospital area) were found to have significantly high concentrations of dust pollution. The study recommends that an urgent air quality control policy intervention be put in place to control the highly alarming levels of dust pollution concentrations to guarantee and protect human health within the study area and beyond.

Increase in crop yield in many parts of Africa is largely the result of increase in cultivated land. This trend, if allowed to remain, will increase the already high levels of forest depletion. This study attempts to formulate a model useful in examining support systems that influence crop yield in Northern Ghana. Comparison of the Classical Generalized linear model to the Joint Generalized linear models and selection of the very best factors that influence crop yield based on the best of the two models are the points of interest for this study. Data from the regional Monitoring and evaluation office of the linking farmers to market (FtM) project in Tamale Ghana was analysed and discussed. Crop type, Financial Credit, Training, Study tour, Demonstrative Practical, Networking Event, Post-harvest Equipment, number of farmers in the FBO and Size of plot cultivated were our measured fixed effects variables with Total Crop Yield as our response. We settle on the Joint GLM for inference and selects access to credit facility, Crop type, Networking among farmer groups, access to equipment used in post-harvest, the number of farmers on site and size of plot as the most important physical support factors that influence crop yield in Northern Ghana. Stakeholders in the Food and Agricultural sector are advised to give these listed factors the needed attention in the midst of resource scarcity and our quest to increasing yield while minimizing the conversion of our forest lands into farm lands.