The Driving Factor Analysis And Prediction Research On China's CO₂ Emissions

In recent years,China is facing unprecedented challenges in maintaining sustained economic growth,reducing CO₂ emissions and tackling climate change.Therefore,the analysis and forecasting of the driving factors of CO₂ emissions in China will be of great significance to China's response to this challenge.Based on the previous theory,including the introduction of research methods and the reference of empirical data,this paper first uses the inventory method to estimate the CO₂ emissions in China from 1985 to 2015.Then,based on the extended STIRPAT model,from the aspects of population,economy and technology,China's CO₂ emissions driving factors are decomposed into eight representative indicators.And the ridge regression method is used to solve the multicollinearity problem between the variables.The results show that the population factor is still the important driving factor of China's CO₂ emissions,and the ratio of population and urbanization is 0.666 and 0.284 respectively.The energy consumption structure,which is dominated by coal consumption,has a large driving contribution,with coal consumption and oil consumption contributing 0.203 and 0.137 for CO₂ emissions.However,the contribution of real GDP per person and the amount of private car ownership on the basis of economic factors is relatively weak and the elasticity coefficient is 0.101 and 0.0404.In addition,this article also uses the scenario analysis method to forecast the future CO₂ emissions from 2016 to 2030,and then put forward the policy suggestions of energy conservation and emissions reduction,such as control population scale reasonably,improve the level of urbanization,optimize energy structure,improve the quality of economic growth or encourage residents' green consumption and so on,so that the study has theoretical and practical significance.