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A cross-country review on energy efficiency drivers

Author

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  • González-Torres, M.
  • Pérez-Lombard, L.
  • Coronel, J.F.
  • Maestre, I.R.

Abstract

Energy efficiency remains as the main mitigation factor to slow down the growth of energy consumption and related CO2 emissions, undoubtedly the major responsible for climate change. Gaining insights into the driving forces that make efficiency change is a keystone to define energy policies and examine pathways to sustainable development. To this aim, this paper proposes a pyramidal approach for the analysis and decomposition of energy intensity, the main global efficiency indicator, using the LMDI method. First, the effects related to supply and demand sides of the energy system are separated in Primary Energy Factor and final energy intensity, respectively. Then, supply side is further decomposed to progressively reveal structural effects associated to transformation processes and fuel types. The approach is applied to the most emitting and consuming nations (China, United States, European Union, India, Russia, Japan) to provide a meaningful cross-country analysis over the period 1995–2017. Results show that energy intensity gains have been mainly driven by widespread demand side efficiency improvements from 25% to 61%. Regarding the supply side, unfavourable structural changes due to electrification, up to 12% in China, have only been offset by transformation efficiency gains about 6% in developed countries. Consequently, emerging economies have worsened their energy sector efficiency as they thrive. Changes in fuel mixes have generally contributed to energy intensity reductions (up to 4%) mainly due to shifts from coal and nuclear power towards gas and renewables plants. The proposed methodology could help stakeholders to effectively analyse the energy system and to develop policies to reduce its environmental impact.

Suggested Citation

  • González-Torres, M. & Pérez-Lombard, L. & Coronel, J.F. & Maestre, I.R., 2021. "A cross-country review on energy efficiency drivers," Applied Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:appene:v:289:y:2021:i:c:s0306261921002105
    DOI: 10.1016/j.apenergy.2021.116681
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    Citations

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    Cited by:

    1. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(C).
    2. Komerath, Narayanan M. & Deepak, Ravi, 2023. "A reversible mid-stratospheric architecture to reduce insolation," Applied Energy, Elsevier, vol. 348(C).
    3. Kai Hu & Dandan Li & Daqian Shi & Wenli Xu, 2023. "Environmental regulation and energy efficiency: evidence from daily penalty policy in China," Journal of Regulatory Economics, Springer, vol. 63(1), pages 1-29, April.
    4. Zou, Chenchen & Ma, Minda & Zhou, Nan & Feng, Wei & You, Kairui & Zhang, Shufan, 2023. "Toward carbon free by 2060: A decarbonization roadmap of operational residential buildings in China," Energy, Elsevier, vol. 277(C).
    5. Ortega-Ruiz, G. & Mena-Nieto, A. & Golpe, A.A. & García-Ramos, J.E., 2022. "CO2 emissions and causal relationships in the six largest world emitters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    6. Kalina, Jacek, 2023. "The quest for game changers - Review of new trends and innovations in the design of large-scale energy systems," Energy, Elsevier, vol. 277(C).
    7. Alessandro Franco & Lorenzo Miserocchi & Daniele Testi, 2023. "Energy Indicators for Enabling Energy Transition in Industry," Energies, MDPI, vol. 16(2), pages 1-18, January.

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