Annual Carbon Footprint From Local Electricity Generation in Federal University of Technology, Owerri, Imo State, Nigeria.

The carbon di-oxide (CO2) emissions emanating from the consumption of fossil fuels for generation of electric power in order to sustain the smooth running of activities at the Federal University of Technology, Owerri (FUTO) has been investigated. With appropriate emission factors and the amount of fuel consumption by the generators per annum, the annual CO2 emissions from both diesel and PMS operated electricity generators were estimated. This emission amounted to ~1460.20 tons of CO2 per annum with the institution's diesel generators accounting for ~59%. The several gasoline generating sets scattered across the institution accounts for ~31% of the total CO2 emission. From literature, the result of this study shows that FUTO is one of the highest carbon emitters amongst other institutions were such studies have been carried out. There is a crucial need to control pollution and diversify into renewable sources of energy so as to reduce the carbon footprint emanating from generating power for the institution's use.

Analysis of COVID-19 and comorbidity co-infection model with optimal control.

In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 with re-infection in order to assess the impact of prior comorbidity (specifically, diabetes mellitus) on COVID-19 complications. The model is simulated using data relevant to the dynamics of the diseases in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection by comorbid susceptibles as well as the rate of reinfection by those who have recovered from a previous COVID-19 infection. Simulations of the cumulative number of active cases (including those with comorbidity), at different reinfection rates, show infection peaks reducing with decreasing reinfection of those who have recovered from a previous COVID-19 infection. In addition, optimal control and cost-effectiveness analysis of the model reveal that the strategy that prevents COVID-19 infection by comorbid susceptibles is the most cost-effective of all the control strategies for the prevention of COVID-19.