A mathematical model for optimizing global warming caused by carbon dioxide emissions from energy sector

Background: Carbon dioxide levels in the atmosphere are increasing day by day due to diverse sources leading to global warming. Meeting the energy demands of the growing human population results in large-scale carbon dioxide (CO2) production. Effective reduction of CO2 emissions from the energy sector and others through optimization is required to reduce global warming. Model: This paper presents a mathematical model that captures the dynamic relationship between carbon dioxide levels in the atmosphere, human population dynamics, energy use, and the progression of global warming as distinct sections. Real-time data from these sections are utilized to adjust model parameters. Methodology: First, the stability analysis of the proposed model is examined to determine whether solutions remain bounded or converge to specific states on the equilibrium points. Second, sensitivity analysis of the model is investigated and determines the behavior of the dynamic system on changes in parameters. Finally, an optimization technique is applied to the model to reduce global warming by optimizing the level of CO2 emissions from the energy sector. Results: The results of the optimization process show that global warming can be significantly reduced by decreasing CO2 emissions from the energy sector. Novelty: The comprehensive analysis and validation of the proposed model provide valuable insights for developing effective strategies to address climate change.