TY - JOUR
T1 - Optimizing China's energy consumption structure under energy and carbon constraints
AU - Sun, Jiasen
AU - Li, Guo
AU - Wang, Zhaohua
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/12
Y1 - 2018/12
N2 - As the world's main energy consumer, China faces an increasingly prominent conflict between its growing energy consumption and its unreasonable energy consumption structure. To optimize China's energy consumption structure, while simultaneously controlling its carbon emissions, this study proposes two models for the analysis of China's energy configuration and energy consumption structure based on the data envelopment analysis (DEA) method. A fixed-sum input DEA model is proposed with which the energy input frontier is determined under consideration of China's energy shortage constraint. Furthermore, an energy consumption structure measurement model is developed to determine the adjustment direction and potential of the current energy consumption structure. The proposed models are further applied for the practical energy consumption structure evaluation in Chinese provinces. The obtained results show that almost all provinces suffer from an inefficient energy configuration and Eastern China experiences severe energy shortage. In addition, all provinces currently have unreasonable energy consumption structures. In particular, the proportion of gas consumption to total energy usage should be increased in all provinces. Furthermore, Chinese provinces with inefficient energy structures exhibit the geographical feature. The coal adjustment ratios in the central and western regions account for 70% of the total, which is much higher than the coal adjustment rate of the eastern region (50%). Based on these results, policies are also suggested to adjust China's energy consumption structure, such as reducing high carbon energy, implementing energy price reform, carbon tax, and clean energy subsidy.
AB - As the world's main energy consumer, China faces an increasingly prominent conflict between its growing energy consumption and its unreasonable energy consumption structure. To optimize China's energy consumption structure, while simultaneously controlling its carbon emissions, this study proposes two models for the analysis of China's energy configuration and energy consumption structure based on the data envelopment analysis (DEA) method. A fixed-sum input DEA model is proposed with which the energy input frontier is determined under consideration of China's energy shortage constraint. Furthermore, an energy consumption structure measurement model is developed to determine the adjustment direction and potential of the current energy consumption structure. The proposed models are further applied for the practical energy consumption structure evaluation in Chinese provinces. The obtained results show that almost all provinces suffer from an inefficient energy configuration and Eastern China experiences severe energy shortage. In addition, all provinces currently have unreasonable energy consumption structures. In particular, the proportion of gas consumption to total energy usage should be increased in all provinces. Furthermore, Chinese provinces with inefficient energy structures exhibit the geographical feature. The coal adjustment ratios in the central and western regions account for 70% of the total, which is much higher than the coal adjustment rate of the eastern region (50%). Based on these results, policies are also suggested to adjust China's energy consumption structure, such as reducing high carbon energy, implementing energy price reform, carbon tax, and clean energy subsidy.
KW - Carbon emission
KW - Energy configuration
KW - Energy consumption structure
KW - Energy shortage
KW - Structure adjustment
UR - http://www.scopus.com/inward/record.url?scp=85050981512&partnerID=8YFLogxK
U2 - 10.1016/j.strueco.2018.07.007
DO - 10.1016/j.strueco.2018.07.007
M3 - Article
AN - SCOPUS:85050981512
SN - 0954-349X
VL - 47
SP - 57
EP - 72
JO - Structural Change and Economic Dynamics
JF - Structural Change and Economic Dynamics
ER -