Multi-objective optimization of environmental tax for mitigating air pollution and greenhouse gas

Abstract

Government macro-control through various policies is an important way to mitigate air pollution and greenhouse gases. Therefore, environmental tax is used worldwide as an important measure. However, few studies have considered the interaction between carbon and environmental protection taxes. Additionally, different sectors differ in their energy structure, pollution emission intensity, and economic status, and previous studies rarely proposed differentiated environmental tax rates based at the sectoral level. A model framework combining the computable general equilibrium (CGE) model and Bayesian optimization (BO) algorithm is proposed to maximize GDP, meet environmental planning objectives, and explore the optimal environmental taxation scheme to realize the multi-objective optimization of the economy and environment. Meanwhile, this study compares the different impact mechanisms of environmental protection tax and carbon tax. It discusses the impacts of differentiated environmental tax rates in different sectors on the environment and economy. For example, the results show that the coordinated implementation of environmental protection and carbon tax policies and the sectoral differentiated environmental tax rates in China could better balance economic development and environmental governance. Additionally, the optimal taxation scheme could mitigate air pollution and greenhouse gases, promote economic growth, and realize sustainable economic and environmental development. Furthermore, the optimized taxation scheme positively affects the energy and industrial structures.

Keywords

• Computable general equilibrium
• Bayesian optimization algorithm
• Environmental tax
• Multi-objective optimization
• Air pollution
• Greenhouse gas