Decoupling Relationship between Carbon Emissions and Land Mixed Use in Southwest Guangxi Karst-Beibu Gulf
The land mixed use to control carbon emissions is an important prerequisite for harmonizing regional low-carbon development and the ecological environment.The southwest Guangxi Karst-Beibu gulf was se-lected as the studied area.Based on the NPP-VIIRS night light and energy consumption data from 2005 to 2020,this paper inverted land-use carbon emissions in the southwest Guangxi Karst-Beibu gulf,and the spatio-temporal trajectory changes and decoupling effects of 50 counties in the southwest Guangxi Karst-Beibu gulf were studied by using methods such as information entropy,spatial autocorrelation analysis and decoupling model.The results are as follows.(1)There is regional variability of land-use mixed degree in the southwest Guangxi Karst-Beibu gulf,with different change magnitudes in each county,and the land-use mixed degree of some counties is"growing viscous",showing a spatial distribution of"high in the center and low around the periphery".(2)Net carbon emissions of the southwest Guangxi Karst-Beibu gulf show a significant increasing trend of 2.757×107 t.The carbon emission lev-el shows a distribution pattern of"high in the east and low in the west,high in the south and low in the north"in space and also shows that the regional difference in the southwest Guangxi Karst area is lower than that in the Beibu gulf.(3)The Moran Index shows that there is a significant positive spatial correlation between carbon emissions from the land use in each county,and there are two types of agglomeration:high-high agglomeration and low-low agglomeration.(4)The main relationship types between carbon emissions and land mixed use are strong decou-pling,strong negative decoupling and expansion negative decoupling with the expansion negative decoupling being dominant,and the increase of carbon emission level is greater than the land-use mixed degree,which leads to a di-lemma of how to efficiently use land and control carbon emissions.
万方数据
维普
