Forecast Of Carbon Emissions From Energy Consumption In China Based On IPSO-LSTM Model

Fossil energy carbon emissions as a result of climate warming is a common challenge facing all countries in the world.In 2020 the outbreak of the COVID-19 league short time to alleviate the pressure of global carbon emissions,but after the outbreak of governments will inevitably take a series of measures to stimulate economic growth,is likely to cause the rise of the global carbon emissions,bring certain pressure reduction process.As the largest developing country in the world and the largest carbon emitter,the Chinese government has made a commitment to reduce carbon emission intensity by 60-65%by 2030 compared with 2005,set the goal of reaching the peak of total carbon emission around 2030 and strive to reach the peak as soon as possible,and strive to achieve the vision of carbon neutrality by 2060.Facing the unprecedented pressure of emission reduction and economic transformation,it is very important to explore the strategy of energy conservation and emission reduction suitable for China’s current situation.Therefore,the calculation,decomposition and prediction of China’s energy consumption carbon emissions,and then put forward scientific and reasonable carbon emission reduction policy recommendations,for China’s energy conservation and emission reduction work and sustainable development has a very important practical significance.First of all,on the basis of grasping the research status at home and abroad and the related theories of carbon emissions,this paper compares the models of measuring,decompressing and predicting carbon emissions,and determines the corresponding research methods according to the content of the research.Secondly,based on the terminal consumption data of 26 types of energy in China,the total carbon emissions of energy consumption in China from 1990 to 2019 are calculated by using the carbon emission coefficient method,and the development trend is analyzed.On this basis,the decomposition model of influencing factors of China’s energy consumption carbon emission is established by using GDIM decomposition method.Using this model,the carbon emission of China’s energy consumption is divided into eight aspects,including GDP effect,output carbon intensity effect,energy consumption effect,energy consumption carbon intensity effect,population effect,per capita carbon emission effect,per capita GDP effect and energy intensity effect,and the quantitative analysis is carried out.It is concluded that the cumulative contribution of each factor from 1990 to 2019 is 92.06%,-49.61%,45.70%,15.27%,7.19%,42.86%,-3.52%and 3.09%respectively,the effect of each influencing factor and its degree of action were further analyzed,and the six influencing factors with higher contribution were selected as the basis for carbon emission prediction of energy consumption.The IPSO model is used to optimize the LSTM neural network model,and the IPSO-LSTM model for predicting China’s energy consumption carbon emissions is constructed.Combined with scenario analysis,the high-carbon scenario,baseline scenario and low carbon scenario of influencing factors are set,and the carbon emissions of China’s energy consumption during 2020-2050 under different scenarios are predicted.The forecast results show that under the high-carbon scenario,baseline scenario and low-carbon scenario,China’s energy consumption carbon emissions will reach the peak in 2041,2035 and 2029 respectively,with the peak amount of 7.218 billion tons of carbon,6.586 billion tons of carbon and 6.259 billion tons of carbon,respectively.At the same time,the carbon emission intensity and per capita carbon emissions of energy consumption in China from 2020 to 2050 are further analyzed.Finally,based on the results of factor decomposition and carbon emission prediction,targeted carbon emission reduction countermeasures are put forward to provide policy basis for China’s energy conservation and emission reduction work.