Impact Of Population And Industrial Structure On Carbon Emissions And Emissions Trend Prediction In China

With the adoption of the Paris Agreement in 2015,China also plants to reach its CO2 peak in around 2030.As the largest carbon emission country in the world,China's emission reduction mission is very urgent now.As we all know,China has entered the aging society,and since there is a huge gap in economic development,structure of population and energy consumption among regions,it is necessary to analyze the impact factors of carbon emissions and take actions to reduce carbon emissions,which can help China achieve its goal.This paper considers the current status of the structure of population and industry and uses Ridge Regression Method and extended STIRPAT Model to analyze the impact factors of carbon emissions in China,which is based on data from year 1990 to 2015.The results show that population aging,industrial structure and per-capita wealth have a positive influence on carbon emissions,while energy intensity has an inhibiting and lowest effect on carbon emissions during the study period.Meanwhile,this paper also compares the impact factors by regions,and we find that industrial structure has a positive influence in east area and it has an inhibiting effect in middle and west area.In addition,this paper also uses GM(1,1)Model to predict future carbon emissions from year 2020 to 2030 in China.It concludes that carbon emissions have an upward trend in the future,but its growth rate will slow down,and the CO2 emissions in east area will occupy a large proportion.As a result,the government should focus more on the structure of population,adjust the industrial structure,speed up the supply-side reform and adopt differentiation strategy in different regions to control carbon emissions.