Study on Carbon Emission Peak Path of China's Civil Aviation Based on PSO-ELM-Markov Model
Under the Paris Agreement,China pledged to peak its CO2 emissions by 2030.Civil aviation,as an important part of transportation,accounts for an increasing propor-tion of carbon emissions.Therefore,it is of great significance to accurately evaluate the current carbon emission reduction effect of civil aviation,predict the path to the peak of car-bon emissions of Chinese civil aviation,and explore more effective environmental protection and emission reduction strategies.According to the calculation standard of civil aviation carbon emission issued by IPCC,the paper calculates the historical civil aviation carbon emission.By combing domestic and foreign literatures,five influencing factors of civil avi-ation carbon emissions are selected.Based on the Extreme Learning Machine,multi-level improvements are made to build a multivariable combined prediction model of civil aviation carbon emissions based on the PSO-ELM-Markov model.Scenario analysis is introduced to scientifically divide development scenarios and predict the peak path of carbon emissions of China's civil aviation under different development scenarios.The empirical results show that the multivariate combination prediction is the fastest and accurate,and is suitable for the prediction of civil aviation carbon emissions.Simulation results of different scenarios show that under the current emission reduction measures and intensity,it is difficult for CAAC to make its due contribution to the Chinese government's emission reduction commitment,but the fulfillment of its emission reduction commitment can be realized in the technological breakthrough scenario.It is suggested that civil aviation administrative departments con-trol the increase of impact factors to improve the quality of civil aviation development.We will explore advanced manufacturing processes and efficient flight management,improve fuel efficiency,and maintain adequate and orderly operation of civil aviation.
the carbon emission of civil aviationparticle swarms optimizationextreme learning machineMarkov modelscenario analysis
NETL
NSTL
万方数据
