Potential Analysis Of Carbon Emission Reduction In Shanghai

The acceleration of industrialization and the deepening of informationization have brought about the general improvement of people’s quality of life,and also put pressure on the carrying capacity of the environment.Greenhouse effect has brought about global temperature rise,sea level rise,land desertification and other issues,which has aroused widespread concern of the whole society.As the largest developing country,China has a vast territory,a large population and a well-developed manufacturing industry.Its carbon emissions have attracted much attention.Transportation industry is one of the three major carbon emission industries in China.How to reasonably assess the factors affecting the carbon emission of transportation industry(hereinafter referred to as traffic carbon emissions)and the actual contribution rate of each factor,predict the total amount of traffic carbon emissions and reduce the total amount of traffic carbon emissions from the perspective of energy has become the focus of the research field of carbon emissions.In this paper,Shanghai is selected as the research object,and the year 2001-2015 is chosen as the time series.The total amount of traffic carbon emissions accounting,co-integration test,Tapio model decoupling analysis,decoupling elastic coefficient decoupling,influencing factors decomposition and carbon emission reduction prediction are carried out respectively.The results are as follows:(1)the total traffic carbon emission in Shanghai shows a rapid rising trend,from 399.43×10~4t to 1288.86×10~4t,with an increase of 889.43×10~4t,with an average annual growth rate of 8.73%.The research on traffic carbon emission intensity shows that during the research period,the traffic carbon emission intensity shows a fluctuating downward trend,reaching the lowest value of 1.14 tons/10,000 yuan in 2015.(2)co-integration test shows that there is a long-term co-integration relationship between the total traffic carbon emission and per capita GDP,and the granger causality test shows that there is a two-way long-term causality between the two.Decoupling analysis shows that the two experienced a transition from expansionary negative decoupling to weak negative decoupling.The GDP per capita effect and population effect are the main positive factors affecting the decoupling elasticity coefficient,while the carbon emission intensity effect and economic proportion are mainly negatively correlated,and the carbon emission coefficient effect turns from weak inhibition to weak promotion.(3)Only the proportion of tertiary industry is negatively correlated with total traffic carbon emissions.Population size,per capita GDP,freight turnover,passenger turnover and the proportion of secondary industry,energy terminal consumption of secondary industry and energy terminal consumption of tertiary industry are positively correlated with total traffic carbon emissions.Among them,per capita GDP is the main positive factor,and the proportion of tertiary industry is the only negative factor.(4)Total traffic carbon emissions in BAU scenario increased rapidly,rising by 27.82%,41.57%and 55.33%respectively at the end of 2025,2030 and 2035 compared with the end of 2015.Compared with BAU scenarios,mild low-carbon scenarios and moderate low-carbon scenarios show a trend of low-carbon.At the end of 2025,2030and 2035,the light low-carbon scenarios reduce emissions by 1.22%,2.95%and 4.97%compared with BAU scenarios,while the moderate low-carbon scenarios reduce emissions by 2.40%,5.70%and 9.47%compared with BAU scenarios at the end of 2025,2030 and 2035.