IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i6p1330-d1608097.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/6/1330/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/6/1330/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Mussini, Mauro, 2020. "Inequality and convergence in energy intensity in the European Union," Applied Energy, Elsevier, vol. 261(C).
    3. 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).
    4. Neil J. Hewitt, 2024. "Decarbonizing Energy of a City: Identifying Barriers and Pathways," Energies, MDPI, vol. 17(1), pages 1-13, January.
    5. Sala-i-Martin, Xavier X, 1996. "The Classical Approach to Convergence Analysis," Economic Journal, Royal Economic Society, vol. 106(437), pages 1019-1036, July.
    6. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    7. Pesaran, M. Hashem, 2012. "On the interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 116(3), pages 545-546.
    8. 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.
    9. 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).
    10. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    11. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kounetas, Konstantinos & Stergiou, Eirini, 2020. "European industrial eco-efficiency under different pollutants' scenarios and heterogeneity structures. Is there a definite direction?," MPRA Paper 98583, University Library of Munich, Germany.
    2. Mushtaq Ahmad Malik & Tariq Masood, 2020. "Analysis of Growth Accounting and Convergence in MENA Countries: Panel Cointegration Approach," South Asian Journal of Macroeconomics and Public Finance, , vol. 9(2), pages 237-262, December.
    3. Valérie Mignon & Christophe Hurlin, 2007. "Une synthèse des tests de cointégration sur données de panel," Économie et Prévision, Programme National Persée, vol. 180(4), pages 241-265.
    4. Tang, Kin-Boon, 2011. "The precise form of uncovered interest parity: A heterogeneous panel application in ASEAN-5 countries," Economic Modelling, Elsevier, vol. 28(1-2), pages 568-573, January.
    5. Ronald MacDonald & Flávio Vieira, "undated". "A panel data investigation of real exchange rate misalignment and growth," Working Papers 2010_13, Business School - Economics, University of Glasgow.
    6. Kurt Hafner, 2008. "The pattern of international patenting and technology diffusion," Applied Economics, Taylor & Francis Journals, vol. 40(21), pages 2819-2837.
    7. Iheonu, Chimere & Asongu, Simplice & Odo, Kingsley & Ojiem, Patrick, 2020. "Financial Sector Development and Investment in Selected ECOWAS Countries: Empirical Evidence using Heterogeneous Panel Data Method," MPRA Paper 107102, University Library of Munich, Germany.
    8. Jos Alberto Fuinhas & Ant nio Cardoso Marques & Alcino Pinto Couto, 2015. "Oil-Growth Nexus in Oil Producing Countries: Macro Panel Evidence," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 148-163.
    9. Atif Jahanger & Muhammad Usman & Daniel Balsalobre‐Lorente, 2022. "Linking institutional quality to environmental sustainability," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1749-1765, December.
    10. Pedroni, Peter L. & Vogelsang, Timothy J. & Wagner, Martin & Westerlund, Joakim, 2015. "Nonparametric rank tests for non-stationary panels," Journal of Econometrics, Elsevier, vol. 185(2), pages 378-391.
    11. Pao, Hsiao-Tien & Tsai, Chung-Ming, 2011. "Multivariate Granger causality between CO2 emissions, energy consumption, FDI (foreign direct investment) and GDP (gross domestic product): Evidence from a panel of BRIC (Brazil, Russian Federation, I," Energy, Elsevier, vol. 36(1), pages 685-693.
    12. Perevyshin, Yu. & Skrobotov, A., 2017. "The Price Convergence of Individual Goods in the Russian Regions," Journal of the New Economic Association, New Economic Association, vol. 35(3), pages 71-102.
    13. Ferreira, Cândida, 2020. "Globalisation and Economic Growth: A Panel Data Approach," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 73(2), pages 187-236.
    14. Kuan‐Min Wang, 2010. "Monetary Policy Impulses and Retail Interest Rate Pass‐Through in Asian Banking Markets," Asian Economic Journal, East Asian Economic Association, vol. 24(3), pages 253-287, September.
    15. Ibrahiem, Dalia M. & Hanafy, Shaimaa A., 2021. "Do energy security and environmental quality contribute to renewable energy? The role of trade openness and energy use in North African countries," Renewable Energy, Elsevier, vol. 179(C), pages 667-678.
    16. Cheng Hsiao, 2007. "Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-22, May.
    17. Acikgoz, Senay & Ben Ali, Mohamed Sami, 2019. "Where does economic growth in the Middle Eastern and North African countries come from?," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 172-183.
    18. Pedro Teles & Harald Uhlig & João Valle e Azevedo, 2016. "Is Quantity Theory Still Alive?," Economic Journal, Royal Economic Society, vol. 126(591), pages 442-464, March.
    19. M. Agovino, 2014. "What are the main explanations of occupational diseases and accidents at work in the agricultural sector? A panel analysis for Italian regional data," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(2), pages 1045-1073, March.
    20. Breitung, Jörg & Pesaran, Mohammad Hashem, 2005. "Unit roots and cointegration in panels," Discussion Paper Series 1: Economic Studies 2005,42, Deutsche Bundesbank.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:6:p:1330-:d:1608097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.