Research On Carbon Emissions Prediction Of Energy Consumption In Beijing-Tianjin-Hebei Based On Scenario Analysis Method

With the continuous growth of energy demand,the use of fossil fuels makes environmental problems such as global warming,carbon emissions increasingly prominent,and the environmental problems gradually become important factors restricting economic development.With the gradual implementation of Beijing-Tianjin-Hebei collaborative strategy,the total economy in Beijing-TianjinHebei region is growing rapidly,but there are also many problems,such as the increment of the industrial energy consumption,carbon emissions,the haze weather,environmental pollution and other issues.The carbon emissions are mostly from fossil energy consumption because of the structure of China’s coal dominated energy consumption,therefore,the measurement,decomposition and prediction research of the Beijing-Tianjin-Hebei energy consumption carbon emissions is conducive to make the collaborative development planning and promote the optimization of energy structure,which has important practical significance,the following research work is carried out in this paper:(1)Summarizes the domestic and foreign research situation from the aspects of carbon emission influencing factors and carbon emission forecasting.On this basis,put forward the research contents and research ideas,summarize the basic theory and research methods of carbon emission,and then determine the research method of this paper,which lays the foundation for the empirical research.(2)Based on the data of energy consumption and carbon emission in the Beijing-Tianjin-Hebei region from 1995 to 2015,the present situation of energy consumption and carbon emissions in the Beijing-Tianjin-Hebei region was analyzed comprehensively from three aspects: energy consumption status,energy consumption carbon emission characteristics and the influencing factors of energy consumption carbon emission Based on GFI model and IPSO-BP neural network model,the decomposition model of energy consumption carbon emission and carbon emission scenario prediction model of Beijing-Tianjin-Hebei energy consumption were constructed.(3)The factors influencing the energy consumption of the energy consumption in the Beijing-Tianjin-Hebei region are decomposed into the per capita GDP effect,the population size effect,the energy structure effect and the energy intensity effect,and the effect of each factor was analyzed by the GFI carbon emission factor decomposition model.Based on the high carbon scenario,the baseline scenario and the low carbon scenario,the IPSO-BP neural network carbon emission prediction model was used to forecast the energy consumption carbon emissions in the Beijing-Tianjin-Hebei region from 2016 to 2030,and its prediction results were analyzed.The results of GFI decomposition show that the contribution rate of per capitaGDP,population size,energy structure and energy intensity are 70.75%,14.73%,10.89% and 3.63% respectively.The per capita GDP is the most important driving factor,and the energy intensity is the inhibition of carbon emissions;the prediction results show that in different scenarios,the peak time of Beijing-Tianjin-Hebei energy consumption carbon emission emerges in the year of 2028,2025 and 2030,and the peak carbon emission respectively is 40280 million tons,38892 million tons and 36158 million tons.And then taking the above analysis and forecast results into account,the corresponding energy-saving emission reduction measures are put forward.