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Decomposition of Intensity and Sustainable Use Countermeasures for the Energy Resources of the Northwestern Five Provinces of China Using the Logarithmic Mean Divisia Index (LMDI) Method and Three Convergence Models

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  • Zhenxu Zhang

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Changbei Campus, Nanchang Normal University, Nanchang 330032, China)

  • Junsong Jia

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

  • Chenglin Zhong

    (School of Finance, Jiangxi Normal University, Nanchang 330022, China)

  • Chengfang Lu

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

  • Min Ju

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

Abstract

Energy resources are a material basis for regional sustainable development and ecological security. However, this issue has not been adequately studied in Northwest China. Here, we consider the five northwestern provinces of China and break down the change in energy use intensity. Results show that the total energy intensity in the five northwestern provinces decreased from 2.389 tons/10 4 Chinese yuan (CNY) in 2000 to 0.92 tons/10 4 CNY in 2021. The main influencing factors for the decline in energy intensity are the industrial energy intensity followed by the industrial structure and the energy structure. There are eight industrial sub-sectors that contributed to the decrease in industrial energy intensity. Conversely, there are seven sub-sectors that increased industrial energy intensity. In addition, there are six sub-sectors with an energy intensity of more than 1 ton/10 4 CNY. The convergence parameters demonstrate that the energy intensities of the five northwestern provinces did not converge to the same steady-state level, and their gap did not narrow in the short term. While the region’s overall energy intensity has shown a consistent downward trajectory, sectors heavily reliant on traditional fossil fuels—such as coal chemical processing, petroleum refining, and coking—have experienced a paradoxical upward trend in energy consumption. To address this, governments must implement targeted sector-specific measures, including upgrading technical capabilities through advanced coal gasification technologies, optimizing heat integration systems in petroleum refining processes, and streamlining intermediate production stages to minimize energy waste.

Suggested Citation

  • Zhenxu Zhang & Junsong Jia & Chenglin Zhong & Chengfang Lu & Min Ju, 2025. "Decomposition of Intensity and Sustainable Use Countermeasures for the Energy Resources of the Northwestern Five Provinces of China Using the Logarithmic Mean Divisia Index (LMDI) Method and Three Con," Energies, MDPI, vol. 18(6), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:6:p:1330-:d:1608097
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    References listed on IDEAS

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    1. Mussini, Mauro, 2020. "Inequality and convergence in energy intensity in the European Union," Applied Energy, Elsevier, vol. 261(C).
    2. Lin, Boqiang & Xu, Mengmeng, 2019. "Quantitative assessment of factors affecting energy intensity from sector, region and time perspectives using decomposition method: A case of China’s metallurgical industry," Energy, Elsevier, vol. 189(C).
    3. Sala-i-Martin, Xavier X, 1996. "The Classical Approach to Convergence Analysis," Economic Journal, Royal Economic Society, vol. 106(437), pages 1019-1036, July.
    4. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    5. Pesaran, M. Hashem, 2012. "On the interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 116(3), pages 545-546.
    6. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    7. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    8. Junsong Jia & Jing Lei & Chundi Chen & Xu Song & Yexi Zhong, 2021. "Contribution of Renewable Energy Consumption to CO 2 Emission Mitigation: A Comparative Analysis from a Global Geographic Perspective," Sustainability, MDPI, vol. 13(7), pages 1-23, March.
    9. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    10. Neil J. Hewitt, 2024. "Decarbonizing Energy of a City: Identifying Barriers and Pathways," Energies, MDPI, vol. 17(1), pages 1-13, January.
    11. Augutis, Juozas & Krikštolaitis, Ričardas & Martišauskas, Linas & Urbonienė, Sigita & Urbonas, Rolandas & Ušpurienė, Aistė Barbora, 2020. "Analysis of energy security level in the Baltic States based on indicator approach," Energy, Elsevier, vol. 199(C).
    12. Sirintip Juntueng & Sirintornthep Towprayoon & Siriluk Chiarakorn, 2021. "Assessment of energy saving potential and CO2 abatement cost curve in 2030 for steel industry in Thailand," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(2), pages 2630-2654, February.
    13. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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