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

被引:10
|
作者
Bai, Jing [1 ]
Qu, Jiansheng [2 ]
机构
[1] Northwest Normal Univ, Coll Geog & Environm Sci, Lanzhou 730030, Peoples R China
[2] Chinese Acad Sci, Lanzhou Informat Ctr, Informat Ctr Global Change Studies, Lanzhou 730000, Peoples R China
关键词
Building; Embodied carbon emissions; Spatial and temporal distribution; Driving forces decomposition analysis; DECOMPOSITION ANALYSIS; CO2; EMISSIONS; MATERIALS DEMAND; STOCK DYNAMICS; ENERGY DEMAND; LIFE-CYCLE; CONSTRUCTION; PERFORMANCE; MODEL;
D O I
10.1007/s11356-020-11971-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:19186 / 19201
页数:16
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