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Urban-rural disparities of household energy requirements and influence factors in China: Classification tree models

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  • Chen, Guangwu
  • Zhu, Yuhan
  • Wiedmann, Thomas
  • Yao, Lina
  • Xu, Lixiao
  • Wang, Yafei

Abstract

The United Nations Sustainable Development Goals have highlighted the challenges brought about by increasing energy consumption and climate change. Previous studies have concentrated on accounting for urban and rural household energy requirements in China at a macro-scale, which neglects the analysis of individuals and their socio-economic driving factors at the micro-scale. To fill this gap, this study began with an accounting of energy requirements for urban and rural households based on the provincial Multi-Regional Input-Output (MRIO) tables and household survey covering over 25,000 unique samples from 25 provinces in 2012. Multilinear Regression models were employed to estimate the average effect of various demographic and socioeconomic characteristics of samples, and Tree-based models were applied to classify energy requirement groups and identify the key individual characteristics. The results suggest that the energy requirements per capita on average range from 34 to 211 GJ for urban samples and 34 to 149 GJ for rural samples across different provinces, and that the gap between individuals can be over 100 times. Indirect energy requirements representing above 90% of the total is the focus of the study. Changes in lifestyle factors include eating out, drinking and smoking, were all correlated with indirect energy requirements. Furthermore, the one-child family has had a positive effect on indirect energy requirements, while the two or more children family has had a negative effect. In addition, an individual’s mental health plays a role in the level of indirect energy requirements for high-income rural residents, while geographic location plays a key role for urban residents.

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  • Chen, Guangwu & Zhu, Yuhan & Wiedmann, Thomas & Yao, Lina & Xu, Lixiao & Wang, Yafei, 2019. "Urban-rural disparities of household energy requirements and influence factors in China: Classification tree models," Applied Energy, Elsevier, vol. 250(C), pages 1321-1335.
    • Handle: RePEc:eee:appene:v:250:y:2019:i:c:p:1321-1335
    DOI: 10.1016/j.apenergy.2019.04.170
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    as
    1. Leahy, Eimear & Lyons, Sean, 2010. "Energy use and appliance ownership in Ireland," Energy Policy, Elsevier, vol. 38(8), pages 4265-4279, August.
    2. Tso, Geoffrey K.F. & Yau, Kelvin K.W., 2007. "Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks," Energy, Elsevier, vol. 32(9), pages 1761-1768.
    3. Nair, Gireesh & Gustavsson, Leif & Mahapatra, Krushna, 2010. "Factors influencing energy efficiency investments in existing Swedish residential buildings," Energy Policy, Elsevier, vol. 38(6), pages 2956-2963, June.
    4. Zhang, Dahai & Wang, Jiaqi & Lin, Yonggang & Si, Yulin & Huang, Can & Yang, Jing & Huang, Bin & Li, Wei, 2017. "Present situation and future prospect of renewable energy in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 865-871.
    5. Huang, Jianhua & Gurney, Kevin Robert, 2016. "The variation of climate change impact on building energy consumption to building type and spatiotemporal scale," Energy, Elsevier, vol. 111(C), pages 137-153.
    6. Wiesmann, Daniel & Lima Azevedo, Inês & Ferrão, Paulo & Fernández, John E., 2011. "Residential electricity consumption in Portugal: Findings from top-down and bottom-up models," Energy Policy, Elsevier, vol. 39(5), pages 2772-2779, May.
    7. Zhou, Kaile & Yang, Shanlin, 2016. "Understanding household energy consumption behavior: The contribution of energy big data analytics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 810-819.
    8. Elisha R. Frederiks & Karen Stenner & Elizabeth V. Hobman, 2015. "The Socio-Demographic and Psychological Predictors of Residential Energy Consumption: A Comprehensive Review," Energies, MDPI, vol. 8(1), pages 1-37, January.
    9. Bin, Shui & Dowlatabadi, Hadi, 2005. "Corrigendum to "Consumer lifestyles approach to US energy use and the related CO2 emissions": [Energy Policy 33 (2005) 197-208]," Energy Policy, Elsevier, vol. 33(10), pages 1362-1363, July.
    10. Alobaidi, Mohammad H. & Chebana, Fateh & Meguid, Mohamed A., 2018. "Robust ensemble learning framework for day-ahead forecasting of household based energy consumption," Applied Energy, Elsevier, vol. 212(C), pages 997-1012.
    11. Feng, Zhen-Hua & Zou, Le-Le & Wei, Yi-Ming, 2011. "The impact of household consumption on energy use and CO2 emissions in China," Energy, Elsevier, vol. 36(1), pages 656-670.
    12. Sözen, Adnan & Arcaklioglu, Erol & Özkaymak, Mehmet, 2005. "Turkey's net energy consumption," Applied Energy, Elsevier, vol. 81(2), pages 209-221, June.
    13. Bin, Shui & Dowlatabadi, Hadi, 2005. "Consumer lifestyle approach to US energy use and the related CO2 emissions," Energy Policy, Elsevier, vol. 33(2), pages 197-208, January.
    14. Liu, Hong-Tao & Guo, Ju-E & Qian, Dong & Xi, You-Min, 2009. "Comprehensive evaluation of household indirect energy consumption and impacts of alternative energy policies in China by input-output analysis," Energy Policy, Elsevier, vol. 37(8), pages 3194-3204, August.
    15. Druckman, A. & Jackson, T., 2008. "Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model," Energy Policy, Elsevier, vol. 36(8), pages 3167-3182, August.
    16. Nie, Hongguang & Kemp, René, 2014. "Index decomposition analysis of residential energy consumption in China: 2002–2010," Applied Energy, Elsevier, vol. 121(C), pages 10-19.
    17. Vassileva, Iana & Wallin, Fredrik & Dahlquist, Erik, 2012. "Analytical comparison between electricity consumption and behavioral characteristics of Swedish households in rented apartments," Applied Energy, Elsevier, vol. 90(1), pages 182-188.
    18. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    19. Lenzen, Manfred & Wier, Mette & Cohen, Claude & Hayami, Hitoshi & Pachauri, Shonali & Schaeffer, Roberto, 2006. "A comparative multivariate analysis of household energy requirements in Australia, Brazil, Denmark, India and Japan," Energy, Elsevier, vol. 31(2), pages 181-207.
    20. Wiedenhofer, Dominik & Lenzen, Manfred & Steinberger, Julia K., 2013. "Energy requirements of consumption: Urban form, climatic and socio-economic factors, rebounds and their policy implications," Energy Policy, Elsevier, vol. 63(C), pages 696-707.
    21. Huo, Hong & Zhang, Qiang & He, Kebin & Yao, Zhiliang & Wang, Michael, 2012. "Vehicle-use intensity in China: Current status and future trend," Energy Policy, Elsevier, vol. 43(C), pages 6-16.
    22. Mansouri, Iman & Newborough, Marcus & Probert, Douglas, 1996. "Energy consumption in UK households: Impact of domestic electrical appliances," Applied Energy, Elsevier, vol. 54(3), pages 211-285, July.
    23. Kialashaki, Arash & Reisel, John R., 2013. "Modeling of the energy demand of the residential sector in the United States using regression models and artificial neural networks," Applied Energy, Elsevier, vol. 108(C), pages 271-280.
    24. Longhi, Simonetta, 2015. "Residential energy expenditures and the relevance of changes in household circumstances," Energy Economics, Elsevier, vol. 49(C), pages 440-450.
    25. Selin Atalay & Margaret G. Meloy, 2011. "Retail therapy: A strategic effort to improve mood," Post-Print hal-00596836, HAL.
    26. Long, Yin & Yoshida, Yoshikuni & Fang, Kai & Zhang, Haoran & Dhondt, Maya, 2019. "City-level household carbon footprint from purchaser point of view by a modified input-output model," Applied Energy, Elsevier, vol. 236(C), pages 379-387.
    27. Kaza, Nikhil, 2010. "Understanding the spectrum of residential energy consumption: A quantile regression approach," Energy Policy, Elsevier, vol. 38(11), pages 6574-6585, November.
    28. Lenzen, Manfred, 1998. "Energy and greenhouse gas cost of living for Australia during 1993/94," Energy, Elsevier, vol. 23(6), pages 497-516.
    29. Henri C. Moll & Klaas Jan Noorman & Rixt Kok & Rebecka Engström & Harald Throne‐Holst & Charlotte Clark, 2005. "Pursuing More Sustainable Consumption by Analyzing Household Metabolism in European Countries and Cities," Journal of Industrial Ecology, Yale University, vol. 9(1‐2), pages 259-275, January.
    30. Wei, Yi-Ming & Liu, Lan-Cui & Fan, Ying & Wu, Gang, 2007. "The impact of lifestyle on energy use and CO2 emission: An empirical analysis of China's residents," Energy Policy, Elsevier, vol. 35(1), pages 247-257, January.
    31. Kok, Rixt & Benders, Rene M.J. & Moll, Henri C., 2006. "Measuring the environmental load of household consumption using some methods based on input-output energy analysis: A comparison of methods and a discussion of results," Energy Policy, Elsevier, vol. 34(17), pages 2744-2761, November.
    32. Yun, Geun Young & Steemers, Koen, 2011. "Behavioural, physical and socio-economic factors in household cooling energy consumption," Applied Energy, Elsevier, vol. 88(6), pages 2191-2200, June.
    33. Ding, Qun & Cai, Wenjia & Wang, Can & Sanwal, Mukul, 2017. "The relationships between household consumption activities and energy consumption in china— An input-output analysis from the lifestyle perspective," Applied Energy, Elsevier, vol. 207(C), pages 520-532.
    34. Ekonomou, L., 2010. "Greek long-term energy consumption prediction using artificial neural networks," Energy, Elsevier, vol. 35(2), pages 512-517.
    35. Krey, Volker & O'Neill, Brian C. & van Ruijven, Bas & Chaturvedi, Vaibhav & Daioglou, Vassilis & Eom, Jiyong & Jiang, Leiwen & Nagai, Yu & Pachauri, Shonali & Ren, Xiaolin, 2012. "Urban and rural energy use and carbon dioxide emissions in Asia," Energy Economics, Elsevier, vol. 34(S3), pages 272-283.
    36. Lan, Jun & Malik, Arunima & Lenzen, Manfred & McBain, Darian & Kanemoto, Keiichiro, 2016. "A structural decomposition analysis of global energy footprints," Applied Energy, Elsevier, vol. 163(C), pages 436-451.
    37. Owen, Anne & Brockway, Paul & Brand-Correa, Lina & Bunse, Lukas & Sakai, Marco & Barrett, John, 2017. "Energy consumption-based accounts: A comparison of results using different energy extension vectors," Applied Energy, Elsevier, vol. 190(C), pages 464-473.
    38. Tso, Geoffrey K.F. & Guan, Jingjing, 2014. "A multilevel regression approach to understand effects of environment indicators and household features on residential energy consumption," Energy, Elsevier, vol. 66(C), pages 722-731.
    39. Sozen, Adnan & Arcaklioglu, Erol, 2007. "Prediction of net energy consumption based on economic indicators (GNP and GDP) in Turkey," Energy Policy, Elsevier, vol. 35(10), pages 4981-4992, October.
    40. Jiansheng Qu & Tek Maraseni & Lina Liu & Zhiqiang Zhang & Talal Yusaf, 2015. "A Comparison of Household Carbon Emission Patterns of Urban and Rural China over the 17 Year Period (1995–2011)," Energies, MDPI, vol. 8(9), pages 1-21, September.
    41. Brounen, Dirk & Kok, Nils & Quigley, John M., 2012. "Residential energy use and conservation: Economics and demographics," European Economic Review, Elsevier, vol. 56(5), pages 931-945.
    42. Chen, Shaoqing & Chen, Bin, 2016. "Urban energy–water nexus: A network perspective," Applied Energy, Elsevier, vol. 184(C), pages 905-914.
    43. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    44. Chen, Shaoqing & Chen, Bin, 2017. "Coupling of carbon and energy flows in cities: A meta-analysis and nexus modelling," Applied Energy, Elsevier, vol. 194(C), pages 774-783.
    45. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    46. Edgar Hertwich, 2011. "The Life Cycle Environmental Impacts Of Consumption," Economic Systems Research, Taylor & Francis Journals, vol. 23(1), pages 27-47.
    Full references (including those not matched with items on IDEAS)

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