Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China
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 spatiote...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-06-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/14/13/3864 |
| _version_ | 1797528595307954176 |
|---|---|
| author | Qiucheng Li Jiang Hu Bolin Yu |
| author_facet | Qiucheng Li Jiang Hu Bolin Yu |
| author_sort | Qiucheng Li |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T10:00:37Z |
| format | Article |
| id | doaj.art-60e4bef1501e42968f3959904ca80308 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T10:00:37Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-60e4bef1501e42968f3959904ca803082023-11-22T01:56:14ZengMDPI AGEnergies1996-10732021-06-011413386410.3390/en14133864Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in ChinaQiucheng Li0Jiang Hu1Bolin Yu2School of Economics and Management, Wuhan University, Wuhan 430072, ChinaSchool of Economics and Management, Hubei University of Automotive Technology, Shiyan 442002, ChinaSchool of Economics and Management, Wuhan University, Wuhan 430072, ChinaThe 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.https://www.mdpi.com/1996-1073/14/13/3864spatiotemporal heterogeneityinequality measuresGeneralized Divisia Index Method (GDIM)urban residential energy consumptiondecoupling processChina |
| spellingShingle | Qiucheng Li Jiang Hu Bolin Yu Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China Energies spatiotemporal heterogeneity inequality measures Generalized Divisia Index Method (GDIM) urban residential energy consumption decoupling process China |
| title | Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China |
| title_full | Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China |
| title_fullStr | Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China |
| title_full_unstemmed | Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China |
| title_short | Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China |
| title_sort | spatiotemporal patterns and influencing mechanism of urban residential energy consumption in china |
| topic | spatiotemporal heterogeneity inequality measures Generalized Divisia Index Method (GDIM) urban residential energy consumption decoupling process China |
| url | https://www.mdpi.com/1996-1073/14/13/3864 |
| work_keys_str_mv | AT qiuchengli spatiotemporalpatternsandinfluencingmechanismofurbanresidentialenergyconsumptioninchina AT jianghu spatiotemporalpatternsandinfluencingmechanismofurbanresidentialenergyconsumptioninchina AT bolinyu spatiotemporalpatternsandinfluencingmechanismofurbanresidentialenergyconsumptioninchina |