Research On Spatio-temporal Dynamics Of China’s Carbon Emissions Based On Spatial Stastics

Along with the development of the economy and progress of the society, theenergy consumption and carbon emissions will continue to grow in the comingdecades and even more over the long term. The phenomenon has aroused widespreadconcern of the state and society，the study of carbon emissions has gradually causedattention. Using the date of the carbon emissions in CDIAC, the paper mainly carriedout the work on two aspects below:（1）After the amount of carbon emissions each year in the provinces of Chinafrom1980to2011was calculated by using data of national carbon emissions andChinese provincial fossil energy consumption and cement output, which announcedby CDIAC，the author studied Spatio-temporal Distribution of carbon emissions,suchas carbon emissions of various provinces in the country, regional differences ofcarbon emissions, and global and local spatial autocorrelation of carbon intensity perland in China from1980to2011.The results showed that the carbon emissions ofnational and provincial presents obvious phase distribution characteristic, namelyslow growth phase from1980to1997, fluctuant growth phase from1997to2002andrapid growth phase from2002to2011; regional differences in carbon emissionsshows “high-low-high–low” trend. In other words, the difference is biggest in1980, gradually increasing after reaching the minimum level in1999, and decreasingafter reaching the maximum difference locally; global spatial autocorrelation ofcarbon intensity per unit area of land exists three distinct phases, namely fluctuantgrowth phase from1980to1994，fluctuant downward phase from1994to2001,andrapid growth phase from2001to2011;carbon intensity per land shows positive spatialautocorrelation mainly to the low concentration whose trend are changing andgradually stabilize after2006; Under the significance level of0.05, thecharacteristics of carbon intensity per land eventually shows the significant“high-high” cluster area in Bejing, Jiangsu and Zhejiang, the significant “low-low”cluster area in Gansu, Qinghai, Sichuan, Xinjiang, Ningxia and Yunnan, and a largemuch of non-significant areas which are stable distribution.（2）In order to further refine the research on carbon emissions in China, in thispaper we select NDVI vegetation index, DMSP/OLS, GDP, industrial output andpopulation, etc5influence factors of carbon emissions, which will be reassigned tothe5km5km grids with the carbon emissions, and establish the grid transformation layer of2000and2010in the study area. Based on the grid transformation layer, buildthe spatial lag model of carbon emissions, predicte the carbon emissions in each grid,and finally prove the accuracy of the model by testing the accuracy and error analysis.In order to make the research more accurate, the predicted value is correctedaccording to provincial statistics, ultimately, we got the spatial distribution of theintensity of carbon emissions unit area of land in2000and2010. The analysis foundthat: The intensity of carbon emissions unit area of land had significant regionaldifferences in distribution characteristics, which mainly showed that it becamesmaller from the eastern areas to the middle-western areas. There were few obvioushigh value hotspot areas and low value cold spots areas in the intensity of carbonemissions unit area of land, and as time went on, the features of regional differenceswere more obvious, and the distribution characteristics of hotspot areas and cold spotsareas were more significant. The intensity of carbon emissions unit area of land in2010was obviously greater than which in2000in different regions.