An analysis of the decoupling relationship between CO2 emission in power industry and GDP in China based on LMDI method

Abstract

China predominantly relies on thermal power generation to meet its power requirement, which has led to a major increase in total CO2 emission and poses a huge threat to the development of power industry. In order to reduce CO2 emission in power industry and develop economy simultaneously, it is necessary to study how to achieve the strong decoupling relationship between CO2 emission in power industry and GDP in China. However, such studies are relatively limited so far. Thus, this paper mainly inquiries the major driving factors on the decoupling during the period of 1985–2016. First, the decoupling state in China is quantified by using the Tapio decoupling indicator. Then, this paper carries out the decomposition of the decoupling index to explore the driving factors affecting the decoupling by the logarithmic mean divisia index (LMDI) method and Kaya identity equation. Finally, energy consumption in power generation, thermal power structure, power generation structure, transmission and distribution loss, electrification, energy intensity and economic scale are explored to discuss the decoupling relationship with respect to the CO2 emission reduction. The results show that the decoupling relationship is in an alternating state between weak decoupling and expansive negative decoupling in 1985–2016. And the influences of seven factors on the decoupling relationship are of difference. Wherein, energy intensity as well as energy consumption in power generation, promotes the decoupling while both the economic scale and electrification are the two main factors that inhibit the decoupling. The other three factors have relatively weak effects. Therefore, based on the empirical results, this paper puts forward some policy suggestions to effectively promote the decoupling between China’s electric CO2 emission and economic growth.