Investigating the spatiotemporal variability and driving factors of China's building embodied carbon emissions

Rapid and large scale construction activities consume significant resources and make impacts on the environment. To support policy for emission reduction and route of low-carbon society development, this paper estimated building stocks and building embodied carbon emissions (BECEs) in China's 31 provinces from 1997 to 2016 by material flow analysis (MFA). Furthermore, global and local Moran's indices were employed to investigate the geographical clustering patterns, and temporal and spatial decomposition models were proposed to identify the driving forces. The results reveal the total BECEs has boomed from 9.67 billion tons in 1997 to 28.99 billion tons in 2016. BECEs in 31 provinces have experienced consistent increase but obvious differences in growth rate, and are spatially inclined to decrease from eastern coastal regions to western inland regions. The change of spatial agglomeration pattern is complex and variable. It presents that a long and narrow H-L agglomeration is located in the two northernmost provinces and the other 29 provinces enforce a sequence arrangement with an order of H-H, L-H, H-L, and L-L from east to west. Temporal decomposition results show that investment scale, economic level, and population density are the main driving forces for the increase of BECEs from both national and provincial levels, while the main reasons for the decrease are technical level and return on investment. Spatial decomposition results demonstrate that population density and provincial area are the main driving forces for the difference between provincial and national average, and others cause the difference among provinces.

Automated summary

The paper estimated building stocks and building embodied carbon emissions in China's 31 provinces from 1997 to 2016 using material flow analysis. The results showed a significant increase in total emissions, with noticeable differences in growth rates between provinces and a spatial inclination of emissions decreasing from eastern coastal regions to western inland regions. The spatial agglomeration patterns were found to be complex and variable, with different driving forces identified for the increase and decrease in emissions.