Spatial-temporal analysis of China's carbon intensity: a ST-IDA decomposition based on energy input-output table.

Abstract

It is of crucial importance to identify the driving factors for emission changes since China's commitment to reduce carbon intensity in 2009. Hence, the spatial-temporal variation of carbon intensity of China's 30 provinces from 2010 to 2017 is explored by applying a Spatial-temporal Index decomposition analysis (ST-IDA) model combined with energy input-output analysis. Industrial structure, energy intensity, energy structure, and carbon emission coefficient are identified as driving factors; simultaneously, a new factor, energy conversion efficiency, is also introduced based on the energy input-output analysis, which is of significance as China is vigourously pushing electricitification. The results show that the carbon intensity of economic sectors in most provinces declined from 2010 to 2017. Energy intensity is the biggest contributor to both the temporal decline of carbon intensity and its spatial difference for economic sectors, followed by industrial structure, energy conversion efficiency, energy structure and carbon emission coefficient, while the rank of inhibition of each factor is the same as above. Meanwhile, the carbon intensity of the residential sector is mainly affected by per capita GDP and per capita energy consumption. Related policy suggestions are given.