Carbon tax serves as a tool to discourage carbon dioxide ( \(\text {CO}_2\) ) emissions, which are a root cause of climate change. A well-designed tax policy could reduce the risk of climate change, promote innovation in carbon-reducing technologies, and increase public revenue. In this research work, the model formulation is based on dynamic interactions among variables, namely the atmospheric concentration of \(\text {CO}_2\) , human population, forestry biomass, and the levied carbon tax. We assume that the collected revenue is used to control anthropogenic emissions of \(\text {CO}_2\) and fund reforestation/afforestation programs. We have derived sufficient conditions under which the considered dynamical variables settle to their equilibrium levels. The model analysis reveals that the atmospheric level of \(\text {CO}_2\) decreases as the levied tax rate increases, indicating that the atmospheric \(\text {CO}_2\) level can be reversed from its present state through the imposition of a carbon tax. Additionally, the formulated system undergoes Hopf-bifurcation concerning the growth of the levied tax and deforestation rate. Furthermore, through simulations, we have demonstrated that utilizing tax revenues for technologies that limit human-induced \(\text {CO}_2\) emissions and reforestation/afforestation programs is a promising strategy for mitigating the increased levels of \(\text {CO}_2\) .
