A Study On The Driving Factors And Route Selection Of Carbon Intensity Target In China

In 2009, the Chinese government announced its carbon intensity target（CO₂ emission per unit of GDP）, the carbon intensity in 2020 should be reduced by 40%-45% compared with that in 2005. Moreover, this target has been upgraded to a national strategy. Using theories and methods from multi-disciplinary, this paper explores the links among economic growth, energy consumption and CO₂ emission in China, driving factors of China’s CO₂ emission in different stages and pathway choice of achieving the carbon intensity target. It’s contributions are as follows:1. The causal relationships among economic growth（GDP）, energy consumption（EC） and CO₂ emission（CE） are clarified. Linear granger causality test, nonlinear Diks-Panchenko causality test and co-integration test are employed to examine the links among GDP, EC and CE. Both linear and nonlinear causality test results show that CO₂ emission unidirectional causes economic growth, while there is a bi-directional causality between energy consumption and CO₂ emission. Under a linear analysis, energy consumption unidirectional causes economic growth, while from a nonlinear perspective, economic growth unidirectional causes energy consumption.2. The driving factors of CO₂ emission and their contribution in different stages are identified and evaluated. Based on the improved Kaya identical equation, a multi-sector logarithmic mean divisia decomposition index（LMDI） model with two layers has been built. Furthermore, the driving factors of CO₂ emission in five stages are identified and evaluated. Moreover, the 14 driving factors are divided into five effects according to their different properties, the contribution of each factor on the increment of CO₂ emission is evaluated. The results show that, there are some deep reasons of the short-term fluctuations of CO₂ emission in different stages, the contribution of each factor and effect on the increment of CO₂ emission is different in different periods.3. Combining multi-disciplinary methods, the pathway choice to achieve carbon intensity target while sustaining economic growth from the perspective of “double control” is investigated. Firstly, an extended Cobb-Douglas production function is applied to predict the energy consumption in 2020 under various economic growth scenarios. Secondly, the multidisciplinary methods including the Markov chain model and scenario analysis are employed to predict the energy structure in 2020. Furthermore, the CO₂ emission under various scenarios in 2020 is estimated. Thirdly, the LMDI method is utilized to determine the drivers of CO₂ emission, and to evaluate the effects of these drivers on the increment of CO₂ emission during 1978-2012. Fourthly, the completion degree of carbon intensity target under different scenarios is evaluated, the results find that the carbon intensity target can be achieved under all the combination scenarios, but the completion degree is not identical. Moreover, the path choice of achieving the target in different decision preferences are investigated by using a multiple attribute decision model from the perspective of “double control”- quantity control & intensity control,the results find that in case of no preference and quantity, the optimal path of decision making is slow economic growth and medium energy structure adjustment; in case of prefer intensity, the optimal path of decision making is baseline economic growth and substantial energy structure adjustment.