An investigation and forecast on CO2 emission of China: Case studies of Beijing and Tianjin

  • Wen, Lei (The Academy of Baoding Low-Carbon Development) ;
  • Ma, Zeyang (Department of Economics and Management, North China Electric Power University) ;
  • Li, Yue (Department of Economics and Management, North China Electric Power University) ;
  • Li, Qiao (Department of Economics and Management, North China Electric Power University)
  • Received : 2017.02.22
  • Accepted : 2017.06.18
  • Published : 2017.12.31


$CO_2$ emission is increasingly focused by public. Beijing and Tianjin are conceived to be a new economic point of growth in China. However, both of them are suffering serious environmental stress. In order to seek for the effect of socioeconomic factors on the $CO_2$ emission of this region, a novel methodology -symbolic regression- is adopted to investigate the relationship between $CO_2$ emission and influential factors of Beijing and Tianjin. Based on this method, $CO_2$ emission models of Beijing and Tianjin are built respectively. The models results manifested that Beijing and Tianjin own different $CO_2$ emission indicators. The RMSE of models in Beijing and Tianjin are 255.39 and 603.99, respectively. Further analysis on indicators and forecast trend shows that $CO_2$ emission of Beijing expresses an inverted-U shaped curve, whilst Tianjin owns a monotonically increasing trend. From analytical results, it could be argued that the diversity rooted in different development orientation and the mixture of different natural and industrial environment. This research further expands the investigation on $CO_2$ emission of Beijing and Tianjin region, and can be used for reference in the study of carbon emissions in similar regions. Based on the investigation, several policy suggestions are presented.


Beijing and Tianjin;$CO_2$ emission;Driven factors;Genetic programming;Pareto front;Symbolic regression


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