Research On Carbon Emission Reduction Factors And Emission Reduction Paths Of Transportation Industry In China

In recent years,the instability of the global climate system has intensified,and extreme weather events have frequently occurred.The rainstorm in Henan,the desert flood in Xinjiang,the extremely cold weather in Texas,the flood in Europe and the 38-degree high temperature in the Arctic Circle have issued a new wave of warnings to human beings.Climate warming has moved from "behind the scenes" to "in front of the stage",which is a key issue that countries pay primary attention to and need to solve urgently.As the largest carbon emitter,China has put forward two-stage carbon emission reduction targets,namely,the carbon emission intensity level in 2030 will be reduced by 60%-65% compared with that in 2005(Paris Climate Conference 2015),the carbon emission peak target,and the carbon neutrality target in 2060.The realization of the first-stage goal is related to whether China can fulfill the commitments made at the Paris Climate Conference in 2015 and the progress of China’s carbon emission reduction strategy.To this end,the Chinese government has also issued a series of emission reduction policies to promote industry emission reduction,such as the carbon emissions trading policy.The carbon emissions trading policy is a government-led strategy,which aims to encourage industries that are included in the carbon trading market to reduce emissions.It is considered by most countries as one of the most effective means to reduce emission.Therefore,carbon emission reduction has become one of the most important tasks for the future development of China.The transportation industry is a key field under the background of carbon emission reduction in China,and it is also an industry with high oil consumption and high emission.According to the fifth assessment report of the IPCC,the transportation industry is one of the industries with the highest energy consumption and the fastest growth in carbon dioxide emissions.The high energy consumption,high carbon emissions and high carbon growth rate of the transportation industry pose a great challenge to China’s carbon emission reduction,and it is urgent to transform into green and low carbon transportation.The circular issued by the Ministry of Transport "Guidance on Accelerating the development of Green Recycling and low-carbon Transportation" clearly points out that the development of green and low-carbon transportation is an important measure for the transportation industry to strengthen the construction of ecological civilization,serve the national carbon-neutral target of peak carbon dioxide emissions and fight the battle of pollution prevention and control.Therefore,in order to achieve the goal of carbon emission reduction and the development of low-carbon transportation in China,it is necessary to clarify the influencing factors of emission reduction in the transportation industry and provide targeted and differentiated emission reduction direction and basis for transportation industry.Secondly,it is necessary to scientifically quantify the inter-provincial carbon emission quotas for the transportation industry to achieve the first-stage emission reduction targets,so as to help each province to clarify its own emission limits and emission reduction responsibilities,and thus formulate a reasonable transportation carbon emission reduction path,which is of great practical significance for achieving the national emission reduction targets and low-carbon transportation transformation.The detailed research and results are as follows.Firstly,discussion on the influencing factors of carbon intensity change in transportation industry.Carbon emission intensity is used to measure the relationship between regional economy and carbon emissions,and it is the most direct indicator to measure the development of low-carbon economy.The essence of low-carbon transportation is a way to achieve low-carbon economy in the transportation field.Therefore,it is of great significance to clarify the influencing factors of carbon intensity in the transportation industry for transportation to transform to low carbon and achieve the national carbon intensity reduction goal.Therefore,the STIRPAT-GTWR model is established to identify the spatio-temporal driving factors of carbon intensity on the basis of expounding the spatio-temporal variation characteristics and regional differences of carbon intensity.The results show that energy intensity is the main driving factor of carbon intensity in the transportation industry,which has a positive impact on the carbon intensity of transportation in all province and contributes the most.The energy structure,urbanization rate and population size of most provinces have a positive impact on the carbon emission intensity of transportation industry,while per capita GDP and industrial structure have a negative impact on the carbon emission intensity of transportation industry in most provinces.Secondly,This thesis studies the influencing factors of embodied carbon emissions change in transportation industry.Many international studies show that trade-related carbon emissions account for about a quarter of the total global carbon emissions.As a bridge of regional economic ties,the transportation industry needs to attach great importance to trade-related carbon emissions with the increasingly close trade between provinces.Most of the existing studies discuss the influencing factors of emission reduction in the transportation industry from the perspective of direct emissions,ignoring the impact of indirect carbon emissions,that is,embodied carbon emissions in bilateral trade.Therefore,a clear understanding of the influencing factors of carbon change in transportation trade can not only regulate industry emission reduction from the demand side,but also provide the government with another perspective of emission reduction strategy reference.Therefore,this thesis first discusses the characteristics of embodied carbon transfer and its unequal relationship with economic benefits,so as to provide reference for the division of government responsibility in air pollution control.In addition,the MRIO-SDA model is established,which divides the embodied carbon emission of transportation industry into four factors: technical effect,production structure,final demand per capita and population size,and discusses the influencing factors of embodied carbon emission of transportation industry from the national,regional and provincial levels.The results show that the influencing factors of carbon change are different in different periods and provinces,but the technology has the greatest influence,while the population size has the least influence.Thirdly,The influencing factors of carbon trading policies promoting traffic emission reduction are studied.The carbon emissions trading policy(CETP)is considered as the most effective means to reduce emissions.This thesis discusses the influencing factors of emission reduction in the transportation industry from a policy perspective,and can strengthen the emission reduction effect in transportation industry by regulating the influencing factors of policy-driven emission reduction.Therefore,this thesis first discusses the impact of carbon trading policy on the emission reduction of the transportation industry,and then discusses the impact mechanism of carbon trading policy on the emission reduction of the transportation industry,so as to clarify the factors that drive the emission reduction of the industry by policy,and further explores the spatial heterogeneity of the emission reduction effect of this influencing factor,so as to provide a reference for the transportation industry to strengthen the emission reduction effect of policy.The results show that the carbon trading policy can promote carbon emission reduction of transportation by optimizing energy consumption structure and improving technology research and development level.In addition,the emission reduction effect of energy consumption structure and technology level has regional heterogeneity.The emission reduction effect of energy structure is mainly reflected in the central region,and the emission reduction effect of technical level is mainly reflected in the eastern and central regions.Fourth,Scientifically quantified the provincial carbon emission quotas and emission reduction responsibilities of the transportation industry,and on this basis,combined with various influencing factors of transportation industry emission reduction,discussed the transportation carbon emission reduction path to achieve the national emission reduction target,with a view to provide scientific reference for the low-carbon transformation of transportation and the realization of the national emission reduction target.The STIRPAT-Ridge regression is used to establish a carbon emission prediction model for China’s transportation industry,and the fitting effect of the established model is tested.In addition,combining scenario analysis to simulate and predict the peak carbon emissions of the transport industry,it is found that the five scenarios can reach the peak in the specified time,and the technology emission reduction scenario can significantly reduce the peak carbon emissions value.Furthermore,considering the principles of fairness,efficiency and greenery,a multi-principle information entropy carbon quota allocation model is constructed.Combined with the ZSG-DEA model,this thesis scientifically quantifies the target allocation of carbon intensity decline in provincial transport industry,so that each province can clearly its own emission limit and reduction pressure under completing the carbon intensity decline target in year 2030.On this basis,combined with the main influencing factors of emission reduction in transport industry and the pressure of emission reduction faced by provinces in Chapters III,IV and V,further explore the carbon emission reduction path of transport industry in different provinces,in order to provide reference for the low-carbon transformation of transportation and the realization of national carbon emission reduction targets.