Browsing by Author "Donald, Pita"

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Mathematical modeling of vehicle carbon dioxide emissions
(Cell Press, 2024-01-02) Mayengo, Maranya; Donald, Pita; Lambura, Aristide
The demand for transportation, driven by an increasing global population, is continuously rising. This has led to a higher number of vehicles on the road and an increased reliance on fossil fuels. Consequently, the rise in atmospheric carbon dioxide (𝐶𝑂2) levels has contributed to global warming. Therefore, it is important to consider sustainable transportation practices to meet climate change mitigation targets. In this research paper, a non-linear mathematical model is developed to study the dynamics of atmospheric 𝐶𝑂2 concentration in relation to human population, economic activities, forest biomass, and vehicle population. The developed model is analyzed qualitatively to understand the long-term behavior of the system’s dynamics. Model parameters are fitted to actual data of world population, human economic activities, atmospheric 𝐶𝑂2, forest biomass, and vehicle population. It is shown that increased vehicular 𝐶𝑂2 emissions have a potential contribution to the increase in atmospheric 𝐶𝑂2 and the decline of human population. Numerical simulations are carried out to verify the analytical findings and we performed global sensitivity analysis to explore the impacts of different sensitive parameters on the 𝐶𝑂2 dynamics.
Mathematical models for vehicular carbon dioxide emission
(NM-AIST, 2024-08) Donald, Pita
The increasing demand for transportation due to a growing global population has led to more vehicles on the road and increased use of fossil fuels, resulting in higher atmospheric carbon dioxide (CO2) levels and contributing to global warming. Thus, adopting sustainable trans portation practices is crucial for achieving climate change goals, specifically the reduction of greenhouse gas emissions to mitigate global warming. This study presents a nonlinear mathe matical model to analyze the dynamics and control of atmospheric CO2 concentration in rela tion to vehicle emissions. The model is qualitatively analyzed to understand long-term system behavior. Model parameters are calibrated using real-world data on world population, eco nomic activities, atmospheric CO2, forest biomass, and vehicle numbers. Results describes the dependence between vehicle CO2 emissions and atmospheric CO2 levels and impact human population decline. Numerical simulations validate analytical findings, and global sensitivity analysis explores the influence of various parameters on CO2 dynamics. An optimal control problem is formulated and solved by using Pontryagin’s principle, establishing optimality con ditions. Solving the problem reveals that reducing vehicle emissions, implementing reforesta tion efforts, adopting green economy practices, and curbing fossil-fueled vehicle production can cut atmosphericCO2 levels by 2.866%. Consequently, addressing climate change linked to increased atmospheric CO2 concentration is achievable through these measures.