Consequences of shifting to renewable energy on atmospheric carbon dioxide: a mathematical model

In recent years, there has been a notable increase in atmospheric carbon dioxide (\(\hbox {CO}_2\)) levels, primarily due to the burning of fossil fuels, which has led to heightened global warming and negative repercussions for human populations. As a result, governments are striving to diminish reliance on fossil fuels by promoting the adoption of renewable energy sources. This research introduces a nonlinear mathematical model that has been developed to examine the consequences of shifting the population from traditional energy sources, such as coal, oil, and gas to renewable alternatives like solar, wind, and hydropower. The concept revolves around governments encouraging the adoption of renewable energy by the public as \(\hbox {CO}_2\) levels increase, thereby enabling a phased transition away from conventional energy sources. The population is divided into two segments: those dependent on conventional energy and those opting for green alternatives due to their understanding of the environmental impact of fossil fuels and \(\hbox {CO}_2\) emission. Our analysis suggests that if the demand for energy from traditional sources surpasses a certain threshold, atmospheric \(\hbox {CO}_2\) levels may begin to fluctuate periodically. To maintain \(\hbox {CO}_2\) concentrations at a lower level, there must be a significant rate of transition from traditional to renewable energy sources within the population.