| dc.description.abstract | 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. | en_US |
