Research On Spatio-temporal Characteristics Of Multi-region And Multi-sector CO₂ Emissions And Their Driving Mechanism Based On Decreasing Total Emissions And Improving Emission Efficiency

Total emission control and emission efficiency improvement of CO₂ represent emission reduction in absolute and relative sense respectively.The effective implementation of these two kinds of policies is the key to the green and low-carbon development of China's economy in the development stage of the new normal.China has a vast territory,and there are differences in natural resources,human environment,geographical features and economic development models among different regions.As a result,there are significant differences in spatio-temporal characteristics of carbon emissions among different regions.It is necessary to achieve differentiated and inclusive low-carbon development according to their respective characteristics.China has scientific accumulation in natural science research of regional carbon emission pattern,including the provincial level carbon productivity comparative study of the regional difference and the research of city level carbon emission pattern.However,in terms of emission efficiency,it is still relatively weak in the assessment of impacts on differences in carbon productivity of multi-region and multi-sector.Moreover,in this thesis of city level carbon emission patterns,due to the limitations of the availability of city-scale data and other factors,there is a lack of city level emission inventory that meets the spatial and temporal continuity of the region.Therefore,city level carbon emission inventory needs to be further expanded,and the relationship between regional structure and carbon emission at the city level still needs to be further studied.Towards the national strategic demands of low carbon emission development transition and research frontiers of regional coordinated development and differentiated low carbon transition,this thesis focused on the influence mechanism of regional carbon emission and efficiency.Applying multi-disciplinary knowledge of management,energy economics and environmental economics,this thesis developed the influence mechanism of regional carbon emission and efficiency at the provincial,city,and sectoral levels to analyze the complex relationship among economy,energy and environment by using decomposition analysis.Some innovative results were acheived as follows,(1)Based on provincial-level carbon emission inventories,the provincial industrial carbon productivity(ICP)was measured.Employing spatial production-theoretical decomposition analysis and data from the industrial sector in each province of China,this thesis investigated the regional disparities in ICP and the driving factors at the provincial and sectoral levels.In 2016,the provinces with the highest total industrial carbon emissions in China were Shandong,Hebei and Jiangsu,with an industrial carbon productivity of 3.54 yuan/Kg.The results indicate that the ICP discrepancies across different regions are obvious:the eastern region had the highest ICP,followed by the northeastern,central,and western regions.12 key industrial subsectors,including electricity generation sector,five energy-intensive manufacturing sectors and six nonenergy intensive manufacturing sectors,in 13 provinces(including Hebei,Liaoning,Heilongjiang,Anhui,and all the other western provinces)were identified as the main drivers of the lower than average ICP in these 13 provinces.The capital-energy substitution effect and CO₂ emission performance were two principal contributors to increasing the regional disparities for most provinces.By contrast,the labor-energy substitution effect and energy consumption structure remained relatively backward and resulted in lower ICP than the average level in most provinces.For the12industrial sectors in the 13 provinces,industrial structure,and CO₂ emission performance were the main causes of their backward carbon productivity.(2)Energy consumption and carbon emission inventories were compiled for analysis of city level carbon emission patterns.Shandong province was selected as a case study because it has the largest carbon emissions and has a high similarity with the national economic structure.Energy consumption and carbon emission inventories of16 cities in Shandong Province by sectors and energy types were compiled from 2010to 2018.This expanded spatial and temporal carbon emission samples of cities.During the study period,the overall carbon dioxide emissions in Shandong Province showed an upward trend.Carbon emissions were mainly from energy,non-metal and metal industry,petroleum and chemical industry.In terms of energy types,the carbon emissions from coal combustion accounted for the largest proportion,followed by oil and natural gas.Spatially,Shandong Province is divided into three major economic circles.Among them,the carbon emissions in provincial economic circle(PEC)account for the largest proportion of total emissions in Shandong Province and show an increasing trend,while the carbon emissions in Jiaodong economic circle(JEC)and Lunan economic circle(LEC)show an overall decreasing trend.In addition,the top five cities in terms of cumulative emissions include Dongying,Zibo,Binzhou,Qingdao and Jinan.This shows that the provincial capital economic circle has a larger space to reduce emissions.(3)This thesis for the first time includes regional structure into the influence mechanism of regional development on city level carbon emissions.Based on the spatial strategic layout of economic development in Shandong Province,it is divided into three major economic circles:the PEC,JEC,and LEC.The Logarithmic Mean Divisia Index(LMDI)was used to measure the contributing factors CO₂ emissions across 16 cities in Shandong Province during 2010-2018.The contributing factors mainly included GDP,population,energy structure,industry structure,energy intensity,emissions intensity and regional structure.The results show that Shandong Province's GDP per capita and population size promote energy-related CO₂ emissions from 2010to 2018.The other influencing factors show different dynamic effects in different economic circles and different development stages.Energy intensity is the main driving force behind Shandong's significant CO₂ emission growth,followed by the energy consumption structure.Emission intensity and regional structure partly offset the CO₂emission increase.Industrial structure is the most important driving factor in reducing emissions.In addition,taking Dongying,the city with the highest cumulative emissions in Shandong Province,as a special example,its emission pattern and dynamic influence mechanism of carbon emission were explored.The energy intensity of Dongying City mainly contributes to its carbon emission increment,while the industrial structure mainly contributes to its emission reduction.(4)Further detailed analysis was made on the carbon emission pattern of different sectors at the city level.It mainly evaluated the contribution of industrial structure,energy structure and emission intensity to sectoral carbon emissions in each city.At the sectoral level,carbon emissions from nonmetal and metal industry,petroleum and chemical industry,and energy sector accounted for a large proportion in most cities,and showed a growth trend from 2010 to 2018.In terms of energy types,the increase in carbon dioxide emissions is mainly due to the increase in energy consumption of raw coal,crude oil and fuel oil.Among them,the emissions caused by coal show a decreasing trend,while the emissions caused by oil consumption increase sharply.Moreover,industrial structure's emission reduction effect was not stable in some cities and sectors.Therefore,the formulation of regional emission reduction policy should be based on its phased development characteristics.In addition,the overall analysis conclusion for a province does not fully represent the carbon emission mechanism of each city within the province.Taking Jinan as an example,it provided a detailed research paradigm for the industrial carbon emission pattern from the provincial level to city level,then to cities'sectoral level,and provided an effective reference for the precise emission reduction of the city.