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Household Energy Consumption Patterns and Carbon Emissions for the Megacities—Evidence from Guangzhou, China

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  • Lu Jiang

    (Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province and Beijing Normal University, Xining 810016, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510030, China)

  • Bowenpeng Ding

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Xiaonan Shi

    (Northeast Institute of Geography and Agroecology, CAS, Jilin 130102, China)

  • Chunhua Li

    (Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province and Beijing Normal University, Xining 810016, China)

  • Yamei Chen

    (Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province and Beijing Normal University, Xining 810016, China)

Abstract

Over the last 20 years, energy consumption in the residential sector in China has grown rapidly, and the growth is faster than that of any other energy form. To assess the limitations of the spatial characteristics of household energy consumption in urban areas, this paper selected Guangzhou as the research area. Specifically, the old town, core area, central area and peri-urban areas, which best reflect the evolutionary characteristics and spatial differentiation of households, were assessed. Based on the surveyed database of community-scale household energy consumption (N = 1097), the spatial heterogeneity of household energy consumption and carbon emissions at the community scale were assessed through exploratory spatial data analysis and the standard deviation ellipse method. The results report that (1) the main sources of energy consumption in Guangzhou households were water heating equipment, kitchen equipment and refrigeration equipment, which were related to the climatic conditions and cultural traditions of the city. (2) There was significant spatial heterogeneity in the carbon emissions from household domestic energy use in Guangzhou. (3) The economic level, the effects of the Lingnan culture and the characteristics of residents are the main drivers influencing the spatial characteristics of household energy consumption and carbon emissions in Guangzhou. We propose that policy development should actively promote energy-efficient equipment, such as water heating and cooling equipment, in urban households and take full account of the basic household energy needs of residents in old urban and suburban areas while promoting the development of low-carbon buildings.

Suggested Citation

  • Lu Jiang & Bowenpeng Ding & Xiaonan Shi & Chunhua Li & Yamei Chen, 2022. "Household Energy Consumption Patterns and Carbon Emissions for the Megacities—Evidence from Guangzhou, China," Energies, MDPI, vol. 15(8), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2731-:d:789393
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    References listed on IDEAS

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    1. Zheng, Xinye & Wei, Chu & Qin, Ping & Guo, Jin & Yu, Yihua & Song, Feng & Chen, Zhanming, 2014. "Characteristics of residential energy consumption in China: Findings from a household survey," Energy Policy, Elsevier, vol. 75(C), pages 126-135.
    2. Zhifu Mi & Jiali Zheng & Jing Meng & Jiamin Ou & Klaus Hubacek & Zhu Liu & D’Maris Coffman & Nicholas Stern & Sai Liang & Yi-Ming Wei, 2020. "Economic development and converging household carbon footprints in China," Nature Sustainability, Nature, vol. 3(7), pages 529-537, July.
    3. De Lauretis, Simona & Ghersi, Frédéric & Cayla, Jean-Michel, 2017. "Energy consumption and activity patterns: An analysis extended to total time and energy use for French households," Applied Energy, Elsevier, vol. 206(C), pages 634-648.
    4. Golley, Jane & Meng, Xin, 2012. "Income inequality and carbon dioxide emissions: The case of Chinese urban households," Energy Economics, Elsevier, vol. 34(6), pages 1864-1872.
    5. Jihoon Min & Zeke Hausfather & Qi Feng Lin, 2010. "A High‐Resolution Statistical Model of Residential Energy End Use Characteristics for the United States," Journal of Industrial Ecology, Yale University, vol. 14(5), pages 791-807, October.
    6. Moshiri, Saeed, 2015. "The effects of the energy price reform on households consumption in Iran," Energy Policy, Elsevier, vol. 79(C), pages 177-188.
    7. Xie, Lunyu & Yan, Haosheng & Zhang, Shuhan & Wei, Chu, 2020. "Does urbanization increase residential energy use? Evidence from the Chinese residential energy consumption survey 2012," China Economic Review, Elsevier, vol. 59(C).
    8. Shimei Wu & Xinye Zheng & Chu Wei, 2017. "Measurement of inequality using household energy consumption data in rural China," Nature Energy, Nature, vol. 2(10), pages 795-803, October.
    9. Zaneta Simanaviciene & Virgilijus Dirma & Arturas Simanavicius, 2017. "Psychological Factors Influence On Energy Efficiency In Households," Working Papers 112/2017, Institute of Economic Research, revised May 2017.
    10. Li, Jiajia & Zhang, Jian & Zhang, Dayong & Ji, Qiang, 2019. "Does gender inequality affect household green consumption behaviour in China?," Energy Policy, Elsevier, vol. 135(C).
    11. Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
    12. Yang Wang & Xiaoli Yue & Hong’ou Zhang & Yongxian Su & Jing Qin, 2021. "Relationship between Urban Floating Population Distribution and Livability Environment: Evidence from Guangzhou’s Urban District, China," Sustainability, MDPI, vol. 13(23), pages 1-15, December.
    13. Jiang, Lu & Yu, Lu & Xue, Bing & Chen, Xingpeng & Mi, Zhifu, 2020. "Who is energy poor? Evidence from the least developed regions in China," Energy Policy, Elsevier, vol. 137(C).
    14. Zaneta Simanaviciene & Virgilijus Dirma & Arturas Simanavicius, 2017. "Psychological factors influence on energy efficiency in households," Oeconomia Copernicana, Institute of Economic Research, vol. 8(4), pages 671-684, December.
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    Cited by:

    1. Yamei Chen & Lu Jiang, 2022. "Influencing Factors of Direct Carbon Emissions of Households in Urban Villages in Guangzhou, China," IJERPH, MDPI, vol. 19(24), pages 1-14, December.
    2. Yanyi Zhu & Youpei Hu, 2023. "The Correlation between Urban Form and Carbon Emissions: A Bibliometric and Literature Review," Sustainability, MDPI, vol. 15(18), pages 1-28, September.
    3. Jingjing Chen & Yangyang Lin & Xiaojun Wang & Bingjing Mao & Lihong Peng, 2022. "Direct and Indirect Carbon Emission from Household Consumption Based on LMDI and SDA Model: A Decomposition and Comparison Analysis," Energies, MDPI, vol. 15(14), pages 1-22, July.

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