Analysis Of Carbon Emission Factors In Power Industry Based On STIRPAT And SVAR Model

Energy consumption,especially the massive consumption of fossil fuels,has led to global warming.It has become a consensus of all humankind.Global warming will bring about many environmental problems and cause huge losses to economic and social development.With the rapid socio-economic development,China's energy consumption and carbon dioxide emissions have risen sharply.Now it is the highest in the world and exerts tremendous pressure on the environment.According to the 2014 China Statistical Yearbook,China's carbon dioxide emissions exceeded 10 billion tons to 11.5 billion tons.However,rigid energy needs remain due to rapid industrialization and urbanization.This has led to difficulties in reducing carbon dioxide emissions.In all industries,the power sector is a key consumer of fuel energy and the industry with the highest CO2 emissions.In recent years,the power industry has achieved rapid growth.For example,generating capacity increased from 300 billion kwh in 1981 to 550 billion kwh in 2014,an average annual increase of 14.9%.In addition,China's electricity sector is also the largest country for energy consumption and carbon dioxide emissions.In 2014,it accounted for 44.56% of the national energy consumption and 48.79% of the carbon emission.It is well known that the energy consumption in the power industry mainly comes from highly polluting coal,which will remain the main source of energy consumption in China in the near future.Therefore,the power industry is undoubtedly the key sector affecting the country's emission reduction targets.based on the status of the power industry,this paper uses STIRPAT and SVAR methods to construct a carbon emission decomposition model for the power industry,studies the factor decomposition of the carbon intensity in China's power industry,and analyzes the influencing factors of carbon emissions in China's power industry.Based on the PATH-STIRPAT model,the power industry characteristics are added to the selection of the influencing factors of carbon emissions based on the existing research results.The energy efficiency,economic development level,industrial structure,energy structure and urbanization of the power industry are calculated directly Elasticity coefficient and indirect elasticity coefficient,the impact of each variable on carbon emissions and the interaction between selected variables are empirically analyzed.In order to eliminate the multicollinearity between the variables in the model,Two-factor method to calculate the elastic coefficient of each factor.The structure vector autoregression model is used to construct the overall SVAR model of carbon emissions,energy efficiency,energy structure and urbanization in the power industry.Using impulse response function to analyze the dynamic effect on carbon emissions;using variance decomposition technology,analysis of industrial structure,the level of urbanization impact on carbon emissions contributions and changes in law,variance decomposition results show that medium and long-term,economic growth in the power industry The proportion of explaining carbon emissions remained at between 10% and 12%.The proportion of urbanization and energy efficiency in explaining carbon emissions was between 6% and 7%.The improvement of economic level,urbanization and technological progress The proportion in the economic structure and the previous carbon emissions have an important contribution to the carbon emissions of the medium and long-term power industry.There is a strong interaction between the research variables.The volatility of one variable can be partly explained by the fluctuation of other variables Explanation.In the end,some countermeasures and suggestions are put forward for the possible problems of power emission reduction,which provide theoretical guidance and policy suggestions for the power industry in our country to complete the emission reduction targets in the "13th Five-Year Plan" period.