LAPSE:2023.33292
Published Article
LAPSE:2023.33292
Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China
April 21, 2023
Abstract
The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007−2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007−2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.
Keywords
China, decoupling process, Generalized Divisia Index Method (GDIM), inequality measures, spatiotemporal heterogeneity, urban residential energy consumption
Suggested Citation
Li Q, Hu J, Yu B. Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China. (2023). LAPSE:2023.33292
Author Affiliations
Li Q: School of Economics and Management, Wuhan University, Wuhan 430072, China [ORCID]
Hu J: School of Economics and Management, Hubei University of Automotive Technology, Shiyan 442002, China
Yu B: School of Economics and Management, Wuhan University, Wuhan 430072, China [ORCID]
Journal Name
Energies
Volume
14
Issue
13
First Page
3864
Year
2021
Publication Date
2021-06-27
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14133864, Publication Type: Journal Article
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LAPSE:2023.33292
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https://doi.org/10.3390/en14133864
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