Spatial-temporal heterogeneity and driving factors of carbon emissions in China

Recently, exploring the driving factors behind carbon emission (CE) change in China has achieved increasing attention. As the determinants of CEs are likely to be affected by both spatial and temporal heterogeneities, we propose an extended production-theoretical decomposition analysis (PDA) approach based on global meta-frontier data envelopment analysis (DEA) to resolve heterogeneity problem. Then, by combing the extended PDA and index decomposition analysis (IDA) approaches, CE changes are decomposed into nine factors. And using panel data from China's 30 provinces during 2005-2015, the main results provide findings as follows. (1) The national total CEs are continuous increasing from 2005 to 2012, and then remain stable in 2012-2015. (2) Potential energy intensity and carbon emission temporal heterogeneity result in reduction of CEs. (3) Economic activity is the dominant driving factor for increasing the CEs, while temporal catch-up effect of carbon emission helps decrease the CEs in almost all provinces.

Automated summary

Recently, there has been increasing attention on exploring the driving factors behind carbon emission changes in China. A new approach combining extended production-theoretical decomposition analysis and index decomposition analysis is proposed to address spatial and temporal heterogeneities. The study found that economic activity plays a dominant role in increasing carbon emissions, while a temporal catch-up effect helps decrease emissions in most provinces.