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Sector decomposition of China’s national economic carbon emissions and its policy implication for national ETS development

Jingjing Jiang, Bin Ye, Dejun Xie, Ji Li, Lixin Miao and Peng Yang

Renewable and Sustainable Energy Reviews, 2017, vol. 75, issue C, 855-867

Abstract: Uncovering the contributions of each sector’s driving factors to the growth of national economic carbon emissions has great significance for China in developing its nationwide emission trading scheme (ETS). The paper applies the index decomposition analysis (IDA) and logarithmic mean divisia index (LMDI) model to discuss the underlying drivers behind China’s national economic carbon emissions during the period 1996–2012 from both sector and factor decomposition perspectives and accordingly offers policy proposals for China’s national ETS development. Major conclusions include: (1) Six heavy industry sectors, the transport & storage & post sector, and the construction sector are the largest contributors, and hence proposed for incorporation into the ETS’s coverage. (2) The rapid expansion of economic output dominantly increases carbon emissions. The design of cap on emissions should allow for a proper increment and establish a new entrant reserve to coordinate economic development. (3) As the dynamics of carbon emissions vary markedly across sectors, allowance allocation needs to consider the changing sectoral structure of emissions. (4) The combined effects of sectoral energy intensity and structure changes largely offset carbon emissions. Benchmarking is suggested as an ideal allocation mechanism, and the setup of sectoral carbon intensity benchmark should synthetically evaluate the potential impacts of related factors. (5) Manufacturer-based manner and carbon offset mechanism are respectively recommended for the initial implementation of carbon trading in the transport & storage & post sector and the construction sector.

Keywords: Carbon emissions; Sector decomposition; LMDI; Carbon trading; China (search for similar items in EconPapers)
Date: 2017
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