Study on Transition of Primary Energy Structure and Carbon Emission Reduction Targets in China Based on Markov Chain Model and GM (1, 1)

Feng Ren and Lihong Gu

Mathematical Problems in Engineering, 2016, vol. 2016, 1-8

Abstract:

The improvement of the primary energy structure has been considered as one of the important measures to achieve the carbon emissions reduction targets in China. This current paper constructed a Markov chain model, which was used to forecast the transition of primary energy structure. GM (1, 1) model and a linear regression model were used to predict the total energy consumption in 2020 and 2030. Then, the CO 2 emissions intensity was calculated, and the realization of carbon emissions reduction targets in China was analyzed. The findings indicated that (1) China’s nonfossil energy share in primary energy cannot be achieved naturally. (2) Part of the carbon emissions intensity in China’s commitments was not binding actually. (3) The realization of the carbon emissions peak and the reduction target of carbon emissions intensity in 2030 would need the policy intervention. In the last part of this paper, policy recommendations on carbon emissions reduction in China were provided.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:4912935

DOI: 10.1155/2016/4912935

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