Author:
Liu Jing,Yang Tianjiao,Yang Tianyue,Liu Shanshan
Abstract
Abstract
Based on the statistical data of energy consumption of 30 provinces in China, the carbon emissions of urban civil buildings in China’s 30 provinces from 2006 to 2017 were calculated. Secondly, the tendency value method was used to analyse the changes in carbon emissions of buildings across the country. Spatial distribution of trends and growth rates, using ArcGIS10.5 to analyse the spatial correlation and spatial agglomeration of building carbon emissions across the country, calculating the Global Moran’s I and Local Moran’s I of building carbon emissions data, verifying there is a positive spatial correlation between the carbon emissions of urban civil buildings in 30 provinces in China, and distinguishing the four types of agglomeration of high-high agglomeration, low-low agglomeration, high-low agglomeration, low-high agglomeration types of regional distribution. Finally, this paper provides some emission reduction recommendations for different regions.
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