Multiplicative structural decomposition and attribution analysis of carbon emission intensity in China, 2002–2012.

Abstract Energy/emission intensity indicators measure the relationship between economic development and climate change. These intensity indicators are preferentially used in assessment criteria for mitigation goals in places such as China. This paper investigates the driving factors of changes in the national CO 2 emission intensity and their contributions to reductions at the sector level in China from 2002 to 2012 using multiplicative structural decomposition analysis (SDA) and attribution analysis. Both Leontief and Ghosh input-output models are used in the study. The empirical results indicate: 1) the energy intensity effect is the main driver that decreases the aggregate emission intensity from both the demand and supply sides; 2) structural effects, such as the energy structure effect and domestic Ghosh structure effect, promote the increase in aggregate emission intensity principally; and 3) to a large extent, sector "smelting and pressing of metals", "manufacture of non-metallic mineral products" and "chemical industry" are the top three sectors that contribute to the negative energy intensity effect. Ultimately, several discussions and conclusions associated with the empirical results, result stability and research extensibility are presented. Highlights • Both Leontief and Ghosh models were adopted to study China's CO 2 intensity. • Multiplicative decomposition was applied to study the intensity changes in 2002–2012. • Energy intensity effect was the major drivers to reduce China's emission intensity. • The structural effects as a whole contributed to the increase of emission intensity. • The domestic allocation structure can be adjusted and optimized preferentially. [ABSTRACT FROM AUTHOR]