Research On Influencing Factors Of Carbon Emissions Based On Spatial Distribution Characteristics

Up to now,the economic development model at the cost of a large amount of carbon emissions has continued in China for many years,which gradually shows its clues and brings severe challenges to reality.Energy saving & emission reduction is one of the vital missons in China's ‘Thirteenth Five-Year Plan',which requires us to implement targeted measures based on the actual basis of carbon emissions.To this end,firstly,this paper analyzes the chronological change trend of the carbon emission level from 1980 to 2017,regarding the whole country as the research object,and shows that the total carbon emission and the per capita carbon emission index generally show a slow-fast-slow growth trend,as well as the intensity of carbon emissions is clearly showing a gradual decline.Secondly,based on the carbon emission related data of 30 provinces(excluding Tibet,Hong Kong,Macau,and Taiwan)from 2005 to 2017,the spatial characteristics of carbon emissions are analyzed,which is confirmed that space spillover effect and spatial differentiation characteristics among provinces do exist in China.Thirdly,based on the spatial characteristics of carbon emission levels,the 30 provinces are divided into four regions,and four types of emission reduction priorities are accordingly defined,including emission reduction priority areas,emission reduction key areas,emission reduction observation areas,and emission reduction slowdown areas.Fourthly,in order to offset the effect of spatial auto-correlation on the model estimation results,this paper builds a logarithmic model based on the data characteristics of 30 provinces from 2005 to 2017,and uses spatial measurement methods to optimize the modeling.The result shows that population density,economic development level,technological level,industrial structure,urban environment construction intensity,and foreign trade openness do have impacts on carbon emission intensity.However,the model results of the impact mechanism in the full sample and the sub-samples of each region are quite different,so that a semi-parametric regression model of GAM is used to supplement the explanation.Finally,according to the conclusions of spatial characteristics analysis and model results,this paper puts forward feasible pathsuggestions for carbon emission reduction,such as strengthening the joint emission reduction between the provinces within the region,rationally setting emission reduction targets that meet the actual situation of the provinces,improving the quality of economic development,and promoting Low-carbon industry development,etc.