武汉居民建筑物碳排放反演计算和时空分析

doi:10.12082/dqxxkx.2020.190727

Abstract

Abstract:

Carbon emissions of residential buildings have an important impact on energy conservation policies, emission reduction strategies, and sustainable urban development. However, current studies mainly focus on carbon emission estimation for an entire city or a large region. There is a lack of consistent methods of carbon emission estimation for residential buildings. Thus, this paper proposes a method to calculate carbon emissions of residential buildings by the fusion of multiple datasets. Our method firstly uses a top-down based strategy to assign the total carbon emission to each urban block. Then it adopts a bottom-up strategy to establish an emission calculation model for each residential building by taking into account urban block planning factors, socioeconomic factors, and residential building morphological factors. This paper applies the proposed method to estimate carbon emissions of all residential buildings in Wuhan city. Our results show that: (1) Carbon emissions of residential buildings decreases from the central city to the suburbs, which is closely related to population distribution; (2) Carbon emissions of residential buildings are heterogeneous and exhibit a heavy-tailed distribution. For instance, there are 89% of residential buildings with carbon emission lower than the average of 1.28 ton and 11% of residential buildings with carbon emission higher than the average; (3) Residential buildings within the same urban block have slight difference in carbon emission with an average standard deviation of 7.66 ton, while residential buildings located in different urban blocks tend to have significantly different carbon emissions with an average standard deviation of 51.30 ton; and (4) Carbon emissions of residential buildings are more likely to be affected by plot ratios in planning factors, population density in socioeconomic factors, and shapes of residential buildings. Our method and experimental results can provide decision support for sustainable planning of urban residential areas.

Key words: residential building, carbon emission, nighttime light, spatiotemporal analysis, urban block, planning factor, socioeconomic factor, Wuhan

JIA Tao, YANG Shihao, LI Xin, YAN Penggao, YU Xuesong, LUO Xi, CHEN Kai. Computation of Carbon Emissions of Residential Buildings in Wuhan and Its Spatiotemporal Analysis[J].Journal of Geo-information Science, 2020, 22(5): 1063-1072.DOI:10.12082/dqxxkx.2020.190727

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References 22

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建筑物类值	建筑面积和/km²	建筑物数量/个	平均楼层数目/层	平均基底面积/m²	平均建筑面积/m²
1	130.0	1 845 285	2	35.8	70.3
2	12.3	8006	11	149.6	1531.4
3	14.1	6385	17	139.6	2370.0
4	29.8	7481	29	136.1	3987.0
5	3.9	600	45	142.0	6430.0

参数	值	参数	值	参数	值	参数	值	参数	值
k1	-18.8	b1	-0.5	c1	69.5	w2	13.0	w5	4.3
k2	15.6	b2	1.5	c2	-19.6	w3	6.5
k3	11.2	b3	2.5	w1	53.0	w4	12.5

Computation of Carbon Emissions of Residential Buildings in Wuhan and Its Spatiotemporal Analysis

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