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Contributors and drivers of Chinese energy use and intensity from regional and demand perspectives, 2012-2015-2017

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  • Yan, Junna
  • Li, Yingzhu
  • Su, Bin
  • Ng, Tsan Sheng

Abstract

China has been experiencing significant energy use transition accompanied by emphasizing on dual control of energy (e.g. energy consumption and energy intensity). Energy use was expected to present obvious spatial characteristics and differentiated contributions across regions. A systematic energy analysis was carried out to 31 regions (including Tibet) in China for investigating the contributors to national achievements and key drivers of regional energy use. With the help of multi-region input-output model (MRIO) and structural decomposition analysis (SDA) techniques, we found that the aggregate energy use in China has been advanced effectively with a declined increasing total energy consumption and accelerated decreasing total aggregate energy intensity. From regional perspective, Eastern region contributed the most characterized by greater total embodied energy consumption and lower aggregate embodied energy intensity, such as Shandong, Hebei and Jiangsu. From demand perspective, regional energy use has been dramatically determined by investment, consumption and exports in sequence. The changes in regional energy use have been tremendously influenced by the sectoral energy intensity and domestic production structure with differentiated performance across regions. According to additive and multiplicative SDA results, two different regional energy conservation paths, i.e. efficiency- and structure-oriented improvements, were identified for China.

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  • Yan, Junna & Li, Yingzhu & Su, Bin & Ng, Tsan Sheng, 2022. "Contributors and drivers of Chinese energy use and intensity from regional and demand perspectives, 2012-2015-2017," Energy Economics, Elsevier, vol. 115(C).
    • Handle: RePEc:eee:eneeco:v:115:y:2022:i:c:s0140988322004868
    DOI: 10.1016/j.eneco.2022.106357
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    as
    1. Su, Bin & Huang, H.C. & Ang, B.W. & Zhou, P., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of sector aggregation," Energy Economics, Elsevier, vol. 32(1), pages 166-175, January.
    2. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    3. He, He & Reynolds, Christian John & Li, Linyang & Boland, John, 2019. "Assessing net energy consumption of Australian economy from 2004–05 to 2014–15: Environmentally-extended input-output analysis, structural decomposition analysis, and linkage analysis," Applied Energy, Elsevier, vol. 240(C), pages 766-777.
    4. Duan, Cuncun & Chen, Bin & Feng, Kuishuang & Liu, Zhu & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2018. "Interregional carbon flows of China," Applied Energy, Elsevier, vol. 227(C), pages 342-352.
    5. Hao, Yu & Peng, Hui, 2017. "On the convergence in China's provincial per capita energy consumption: New evidence from a spatial econometric analysis," Energy Economics, Elsevier, vol. 68(C), pages 31-43.
    6. Su, Bin & Ang, B.W. & Sun, Ya-Fang, 2022. "Input-output analysis of embodied emissions: Impacts of imports data treatment on emission drivers," Energy Economics, Elsevier, vol. 107(C).
    7. Chong, ChinHao & Liu, Pei & Ma, Linwei & Li, Zheng & Ni, Weidou & Li, Xu & Song, Shizhong, 2017. "LMDI decomposition of energy consumption in Guangdong Province, China, based on an energy allocation diagram," Energy, Elsevier, vol. 133(C), pages 525-544.
    8. Su, Bin & Ang, B.W., 2014. "Attribution of changes in the generalized Fisher index with application to embodied emission studies," Energy, Elsevier, vol. 69(C), pages 778-786.
    9. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    10. Su, Bin & Ang, B.W., 2017. "Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 65(C), pages 137-147.
    11. Luo, Yulong & Zeng, Weiliang & Wang, Yueqiang & Li, Danzhou & Hu, Xianbiao & Zhang, Hua, 2021. "A hybrid approach for examining the drivers of energy consumption in Shanghai," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    12. Yan, Junna & Su, Bin, 2020. "What drive the changes in China's energy consumption and intensity during 12th Five-Year Plan period?," Energy Policy, Elsevier, vol. 140(C).
    13. Wang, Wenwen & Liu, Xiao & Zhang, Ming & Song, Xuefeng, 2014. "Using a new generalized LMDI (logarithmic mean Divisia index) method to analyze China's energy consumption," Energy, Elsevier, vol. 67(C), pages 617-622.
    14. Shahbaz, Muhammad & Chaudhary, A.R. & Ozturk, Ilhan, 2017. "Does urbanization cause increasing energy demand in Pakistan? Empirical evidence from STIRPAT model," Energy, Elsevier, vol. 122(C), pages 83-93.
    15. Dong, Kangyin & Sun, Renjin & Hochman, Gal & Li, Hui, 2018. "Energy intensity and energy conservation potential in China: A regional comparison perspective," Energy, Elsevier, vol. 155(C), pages 782-795.
    16. Liu, Hong & Wang, Chang & Tian, Meiyu & Wen, Fenghua, 2019. "Analysis of regional difference decomposition of changes in energy consumption in China during 1995–2015," Energy, Elsevier, vol. 171(C), pages 1139-1149.
    17. Zhu, Bangzhu & Su, Bin & Li, Yingzhu & Ng, Tsan Sheng, 2020. "Embodied energy and intensity in China’s (normal and processing) exports and their driving forces, 2005-2015," Energy Economics, Elsevier, vol. 91(C).
    18. Zhang, Xiaomei & Su, Bin & Yang, Jun & Cong, Jianhui, 2022. "Analysis of Shanxi Province's energy consumption and intensity using input-output framework (2002–2017)," Energy, Elsevier, vol. 250(C).
    19. Zhang, Haiyan & Lahr, Michael L., 2014. "China's energy consumption change from 1987 to 2007: A multi-regional structural decomposition analysis," Energy Policy, Elsevier, vol. 67(C), pages 682-693.
    20. Zhang, Ming & Su, Bin, 2016. "Assessing China's rural household energy sustainable development using improved grouped principal component method," Energy, Elsevier, vol. 113(C), pages 509-514.
    21. Su, Bin & Ang, B.W., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of spatial aggregation," Ecological Economics, Elsevier, vol. 70(1), pages 10-18, November.
    22. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    23. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei, 2018. "How does information and communication technology affect China's energy intensity? A three-tier structural decomposition analysis," Energy, Elsevier, vol. 151(C), pages 748-759.
    24. Tang, Zhipeng & Yu, Haojie & Zou, Jialing, 2022. "How does production substitution affect China's embodied carbon emissions in exports?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    25. Huang, Junbing & Lai, Yali & Wang, Yajun & Hao, Yu, 2020. "Energy-saving research and development activities and energy intensity in China: A regional comparison perspective," Energy, Elsevier, vol. 213(C).
    26. Zhang, Chi & Su, Bin & Zhou, Kaile & Sun, Yuan, 2020. "A multi-dimensional analysis on microeconomic factors of China's industrial energy intensity (2000–2017)," Energy Policy, Elsevier, vol. 147(C).
    27. Su, Bin & Ang, B.W., 2014. "Input–output analysis of CO2 emissions embodied in trade: A multi-region model for China," Applied Energy, Elsevier, vol. 114(C), pages 377-384.
    28. Su, Bin & Ang, B.W., 2022. "Improved granularity in input-output analysis of embodied energy and emissions: The use of monthly data," Energy Economics, Elsevier, vol. 113(C).
    29. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    30. Meng, Guanfei & Liu, Hongxun & Li, Jianglong & Sun, Chuanwang, 2022. "Determination of driving forces for China's energy consumption and regional disparities using a hybrid structural decomposition analysis," Energy, Elsevier, vol. 239(PC).
    31. Ma, Ben, 2015. "Does urbanization affect energy intensities across provinces in China?Long-run elasticities estimation using dynamic panels with heterogeneous slopes," Energy Economics, Elsevier, vol. 49(C), pages 390-401.
    32. Su, Bin & Ang, B.W., 2015. "Multiplicative decomposition of aggregate carbon intensity change using input–output analysis," Applied Energy, Elsevier, vol. 154(C), pages 13-20.
    33. Shi, Xiaohui & Chu, Junhui & Zhao, Changyi, 2021. "Exploring the spatiotemporal evolution of energy intensity in China by visual technology of the GIS," Energy, Elsevier, vol. 228(C).
    34. Amin, Sakib & Jamasb, Tooraj & Nepal, Rabindra, 2021. "Regulatory reform and the relative efficacy of government versus private investment on energy consumption in South Asia," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 421-433.
    35. Li, Aijun & Hu, Mingming & Wang, Mingjian & Cao, Yinxue, 2016. "Energy consumption and CO2 emissions in Eastern and Central China: A temporal and a cross-regional decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 284-297.
    36. Wu, Ya & Zhang, Wanying, 2016. "The driving factors behind coal demand in China from 1997 to 2012: An empirical study of input-output structural decomposition analysis," Energy Policy, Elsevier, vol. 95(C), pages 126-134.
    37. Gao, Cuixia & Su, Bin & Sun, Mei & Zhang, Xiaoling & Zhang, Zhonghua, 2018. "Interprovincial transfer of embodied primary energy in China: A complex network approach," Applied Energy, Elsevier, vol. 215(C), pages 792-807.
    38. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    39. Lei, Ming & Yin, Zihan & Yu, Xiaowen & Deng, Shijie, 2017. "Carbon-weighted economic development performance and driving force analysis: Evidence from China," Energy Policy, Elsevier, vol. 111(C), pages 179-192.
    40. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei & Su, Bin, 2020. "Who shapes China's carbon intensity and how? A demand-side decomposition analysis," Energy Economics, Elsevier, vol. 85(C).
    41. Yang, Mian & Hong, Yili & Yang, Fuxia, 2022. "The effects of Mandatory Energy Efficiency Policy on resource allocation efficiency: Evidence from Chinese industrial sector," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 513-524.
    42. Huang, He & Hong, Jingke & Wang, Xianzhu & Chang-Richards, Alice & Zhang, Jingxiao & Qiao, Bei, 2022. "A spatiotemporal analysis of the driving forces behind the energy interactions of the Chinese economy: Evidence from static and dynamic perspectives," Energy, Elsevier, vol. 239(PB).
    43. Zhang, Yue-Jun & Peng, Hua-Rong & Su, Bin, 2017. "Energy rebound effect in China's Industry: An aggregate and disaggregate analysis," Energy Economics, Elsevier, vol. 61(C), pages 199-208.
    44. Wang, S.S. & Zhou, D.Q. & Zhou, P. & Wang, Q.W., 2011. "CO2 emissions, energy consumption and economic growth in China: A panel data analysis," Energy Policy, Elsevier, vol. 39(9), pages 4870-4875, September.
    45. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    46. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    47. Yu, Xiaoman & Geng, Yong & Dong, Huijuan & Ulgiati, Sergio & Liu, Zhe & Liu, Zuoxi & Ma, Zhixiao & Tian, Xu & Sun, Lu, 2016. "Sustainability assessment of one industrial region: A combined method of emergy analysis and IPAT (Human Impact Population Affluence Technology)," Energy, Elsevier, vol. 107(C), pages 818-830.
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