Identifying the key impact factors of carbon emission in China: Results from a largely expanded pool of potential impact factors

Abstract

Carbon emission reduction (CER) comes to be the principle in most countries particularly China, the largest carbon emitter. For finding an efficient solution, the priority is to find the key impact factors (KIFs) of carbon emission. Previous studies for identifying KIFs, which partially selected only a few potential impact factors (PIFs), are inconsistent in their findings. This study aims to explore the KIFs of carbon emission in China among 43 PIFs, which comprehensively covers 30 relevant studies. The KIFs in China are identified using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model with correlation analysis, partial correlation analysis and stepwise regression. The findings of this study are as follows: (1) China's carbon emission has five KIFs: the real GDP per capita, urbanization rate, ratio of tertiary to secondary industry, ratio of renewable energy, and fixed assets investment; (2) the most significant carbon emission contributor is real GDP per capita and the most significant carbon emission inhibitor is urbanization rate. This study provides the reliable KIFs for governors' targeted decision-making on CER, and policy implications from the identified KIFs are highlighted.