Analysis of China’s Primary Energy Structure and Emissions Reduction Targets by 2030 Based on Multiobjective Programming

Abstract

China’s energy issues and carbon emissions have become important global concerns. The purpose of this paper is to analyze the fulfillment of China’s commitment to carbon emissions reduction by 2030. We establish the Markov chain model to analyze the transition of primary energy structure and carbon emissions in China by 2030 without artificial intervention and build three multiobjective optimization models to analyze China’s energy structure and emissions reduction targets by 2030 under three scenarios (scenario of energy structure optimization, scenario of energy intensity optimization, and scenario of energy structure-intensity optimization). The findings show that the proportions of coal, oil, natural gas, and nonfossil energy will reach 17.89%, 11.52%, 49.43%, and 21.16%, respectively; the total decreases in CO2 intensity reach 43.11%, 61.78%, and 60.64%, respectively; the CO2 emissions under these three scenarios are 25.092, 16.859, and 17.359 billion tons. In other words, China’s emissions reduction targets cannot be easily achieved. In order to keep pace with China’s overall mitigation agenda, we put forward the policy recommendations. Through these analyses and discussions, we hope to make contributions to policy stimulation in energy, carbon emissions, and ecological protection.