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- Title
Temporal and Spatial Variability of Carbon Emission Intensity of Urban Residential Buildings: Testing the Effect of Economics and Geographic Location in China.
- Authors
Shi, Qingwei; Gao, Jingxin; Wang, Xia; Ren, Hong; Cai, Weiguang; Wei, Haifeng
- Abstract
Highlights: A new method to calculate the URBCE is proposed for explore the influencing factors of carbon emission. The spatial econometric model solved the bias estimation caused by spatial correlation. The effect of regional factors on carbon emission is determined by an econometric model. Regional emission reduction policies are more scientific and effective than national ones. The role of urban residential buildings (URBs) in the carbon reduction goal of China is becoming increasingly important because of the rising energy consumption and carbon emission of such buildings in the region. Considering the increasing spatial interaction of the carbon emission of URBs (URBCE) in the region, this study investigates the influence of climate and economic factors on the URBCE in North and South China. First, the URBCE is calculated by using a decomposition energy balance table based on the carbon emission coefficient of electric and thermal power, thereby improving the estimation of the basic data of URBCE. Second, the influence of economic and climatic factors on the URBCE intensity in 30 provinces of China is explored by using a spatial econometric model. Results show that the URBCE intensity in China had a spatial autocorrelation from 2000 to 2016. Climatic and economic factors have great differences in the degree and direction of influencing the URBCE intensity in the country. Formulating emission reduction policies for climate or economic zones is more scientific and effective than developing national policies. Among these factors, urbanization rate, climate, and GDP per capita have a significant positive impact on the URBCE intensity in the region, whereas other factors have varying degrees of negative impact. In addition, climate, consumption level, and building area have significant spatial spillover effects on URBCE intensity, whereas other factors do not pass the significance test. Relevant conclusions should be given special attention by policymakers.
- Subjects
CHINA; DWELLINGS; HIGH strength steel; GOVERNMENT policy; ESTIMATION bias; ECONOMETRIC models; CARBON; ENERGY intensity (Economics)
- Publication
Sustainability (2071-1050), 2020, Vol 12, Issue 7, p2695
- ISSN
2071-1050
- Publication type
Article
- DOI
10.3390/su12072695