Abstract
China has become the largest CO2 emitter in the world for the rapid economic growth, and the large amount of CO2 emissions has caused worldwide concern. Based on the energy‐related data of CO2 emissions in eight economic zones from 2000 to 2012, this paper built a STIRPAT‐based multivariate linear model fitted by a ridge regression to examine the relationships between net CO2 emissions and a list of socioeconomic factors, including GDP per capita, population, energy intensity, and urbanization level. Regression results show that population, GDP per capita and urbanization level contribute to the increase of net CO2 emissions while energy intensity expresses an inhibitory effect. In addition, the elastic coefficients of different variables indicate that population scale and urbanization level play more important roles than GDP per capita and energy intensity in net CO2 emissions, where population scale contributes most significantly. Since the influence mechanisms of impact factors vary with scales of regional economy and characteristics of industry structure, some specific policy suggestions are also presented on how to mitigate the growth of CO2 emissions in each economic zone. This study have an important reference value for examining the impact factors of energy‐related CO2 emissions and the academic value in terms of enriching low carbon economy research systems in China. © 2017 American Institute of Chemical Engineers Environ Prog, 36: 1282–1289, 2017
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