Spatio-temporal Variation And Influencing Factors Of Carbon Emissions From Urban Civil Buildings

China has embarked on a new journey of development during the 14 th Five-Year Plan period.The goal of achieving a carbon peak by 2030 and a carbon-neutral vision by2060 has been listed as one of the key tasks to be promoted during the 14 th Five-Year Plan period.As the biggest developing country.China is in an important period of strategic opportunities of development,unbalanced development,the problem of inadequate is obvious,there are some deficiency in response to climate change and short board,combined with the increasingly complex international situation,to achieve "carbon target of peak" and "carbon neutral vision",needs to make arduous efforts.Therefore,in order to achieve the national overall emission reduction target,it is necessary not only to pay attention to the overall transformation of the national economy and industrial structure,but also to base on the energy conservation and emission reduction work in different industries and regions.As an important area of energy consumption in addition to industry and transportation,the construction industry has great energy saving potential,and its importance is becoming increasingly prominent.It has become an effective starting point to achieve energy saving and emission reduction targets.At the same time,the basic data of building energy has also become a key basis for measuring carbon emissions,analyzing energy saving potential and setting energy saving targets.However,at present,the basic data of domestic building energy is not available enough and the level of refinement is not high,which not only hinders the in-depth understanding of building energy consumption and carbon emissions,but also brings some difficulties to the classification,stratification and zoning of building energy conservation and emission reduction.In this context,the thesis introduced the light remote sensing image data,extracted the light brightness values of 30 provinces,360 cities and 2778 counties in China,and explored to establish the relationship model between building carbon emissions and light brightness values.Secondly,on the basis of model to measure the provincial,municipal,county three dimensions of building carbon emissions,by means of exploratory analysis and statistical analysis method of geography,space analysis from the dimension of time and space scales change characteristics of carbon emissions,visualization of building carbon emissions time change trend,spatial distribution pattern evolvement and center of gravity.Finally,using geographically weighted regression GTWR model of time and space in different provinces and cities in affect building spatial and temporal variation of the key factors and the effect of the carbon emissions,and for different area from the aspects of technology,management related emission reduction strategies and Suggestions,for national and local government adjust measures to local conditions,provide a scientific basis for effective energy saving policy,Promote the coordinated and balanced development of energy conservation work in different regions.The main conclusions of this thesis are as follows:(1)There is a balanced and stable relationship between building carbon emissions and lighting brightness value.The panel data sets of carbon emissions and light brightness in the eastern,central and western regions all passed the stationarity test,and were all one-order integrated stationary series,indicating that there is a long-term equilibrium and stable relationship between building carbon emissions and light brightness.(2)Although the total carbon emissions from China’s civil buildings are on the rise,the average annual growth rate is slowing down.From 2000 to 2003,the average annual growth rate of carbon emissions from buildings in China was about 9.61%.After 2003,the growth rate of carbon emissions from buildings gradually accelerated.The average annual growth rate was about 11.82% from 2003 to 2007 and 10.09% from 2007 to2012.After 2012,the growth of carbon emissions gradually slowed down.By 2018,the average annual growth rate of total carbon emissions was only 4.60 percent.(3)The spatial and temporal development direction of building carbon emissions at provincial,municipal and county scales in China is basically the same,and all of them show a trend of shifting to the east.From building carbon emissions directional analysis results of space and time,province,city,county scale building carbon emissions are showing a strong spatial correlation and spatial distribution characteristics of different scales at the same time of building carbon emissions standard deviation ellipse area were similar,the result was consistent,various scale architectural spatial distribution pattern of stability of the carbon emissions,As a whole,the ellipse distribution showed a changing trend to the east.(4)The effects of different factors on the carbon emissions of buildings in different periods and different Spaces show alienation effect.After establishing the GTWR regression model of the influencing factors of carbon emissions,it is found that:The regression coefficients of the six influencing factors,urbanization level,population density,proportion of the tertiary industry,residents’ consumption level,electrical appliance ownership per 100 households,and building area,are different in different Spaces in the same period,and in different periods in the same space.