carbon intensity target
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2019 ◽  
Vol 233-234 ◽  
pp. 196-207 ◽  
Author(s):  
Bangzhu Zhu ◽  
Shunxin Ye ◽  
Minxing Jiang ◽  
Ping Wang ◽  
Zhanchi Wu ◽  
...  

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2721 ◽  
Author(s):  
Ying Wang ◽  
Peipei Shang ◽  
Lichun He ◽  
Yingchun Zhang ◽  
Dandan Liu

To mitigate global warming, the Chinese government has successively set carbon intensity targets for 2020 and 2030. Energy restructuring is critical for achieving these targets. In this paper, a combined forecasting model is utilized to predict primary energy consumption in China. Subsequently, the Markov model and non-linear programming model are used to forecast China’s energy structure in 2020 and 2030 in three scenarios. Carbon intensities were forecasted by combining primary energy consumption, energy structure and economic forecasting. Finally, this paper analyzes the contribution potential of energy structure optimization in each scenario. Our main research conclusions are that in 2020, the optimal energy structure will enable China to achieve its carbon intensity target under the conditions of the unconstrained scenario, policy-constrained scenario and minimum external costs of carbon emissions scenario. Under the three scenarios, the carbon intensity will decrease by 42.39%, 43.74%, and 42.67%, respectively, relative to 2005 levels. However, in 2030, energy structure optimization cannot fully achieve China’s carbon intensity target under any of the three scenarios. It is necessary to undertake other types of energy-saving emission reduction measures. Thus, our paper concludes with some policy suggestions to further mitigate China’s carbon intensities.


Energy Policy ◽  
2018 ◽  
Vol 119 ◽  
pp. 377-387 ◽  
Author(s):  
Bangzhu Zhu ◽  
Minxing Jiang ◽  
Kefan Wang ◽  
Julien Chevallier ◽  
Ping Wang ◽  
...  

2017 ◽  
Vol 194 ◽  
pp. 765-773 ◽  
Author(s):  
Shibao Lu ◽  
Jianhua Wang ◽  
Yizi Shang ◽  
Haijun Bao ◽  
Huixiong Chen

2015 ◽  
Vol 119 ◽  
pp. 209-216 ◽  
Author(s):  
Bangzhu Zhu ◽  
Kefan Wang ◽  
Julien Chevallier ◽  
Ping Wang ◽  
Yi-Ming Wei

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