Modeling and control of global warming driven by transportation-induced carbon dioxide emissions through green economy investments

Global warming poses a significant threat to the environment and human well-being, necessitating urgent mitigation measures. This study develops a mathematical model to analyze the impact of fossil-fueled vehicle emissions on atmospheric carbon dioxide (CO2) concentrations and global warming. The model assumes that global warming is driven by rising atmospheric CO2 levels, which are influenced by vehicle population growth. System parameters are calibrated using global datasets on atmospheric CO2 concentration, human population, vehicle production, global temperature, and Gross Domestic Product (GDP). Model validation against global data demonstrates excellent predictive performance, as confirmed by statistical metrics. Sensitivity analysis reveals that vehicle growth rate, CO2-induced global warming, and population-driven temperature increases are key contributors to rising global temperatures. To stabilize the system, investment in the green economy, transitioning from fossil-fueled to clean energy vehicles, and implementing economic policies to curb temperature rise are essential, as confirmed by the numerical simulation of an optimal control problem. Numerical simulations further validate the analytical findings and explore the impact of parameter variations on system behavior. This article integrates an optimal control framework into a dynamic system to formulate data-driven strategies for minimizing global warming while ensuring sustainable economic growth.