IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v69y2020ics0038012118301320.html
   My bibliography  Save this article

Spatial decomposition analysis of water intensity in China

Author

Listed:
  • Zhang, Chenjun
  • Wu, Yusi
  • Yu, Yu

Abstract

The shortage of water resources has become a burning issue constraining China's sustained development with significant differences in water intensity among regions and provinces. Quantifying the driving effect of spatial differences in the country's water intensity is very important to the dual implementation actions of water resources and intensity in each region. Spatial analysis reveals the variations among regions, identifies contributing factors, and helps us to better understand the scope for improvement compared to temporal analysis. This paper constructs a Spatial Index Decomposition Analysis (S-IDA) model based on the conventional IDA model referenced in the literature and divides China into six regions according to The 13th Five-Year Plan of Water-Saving Society Construction. We mainly examine the following four parts. First, the driving factors of the spatial difference of water intensity in the six regions are decomposed into intensity effect and structure effect. Second, we measure three industrial differences of the intensity effect and the structure effect in the six regions. Third, we decompose the drivers of the spatial differences of water intensity for provinces within the six regions into the intensity effect and the structure effect. Fourth, we select the results in 2015 to point out the key task of reducing water intensity in the six regions and in all provinces of those regions. The results underscore that each region should formulate and implement a sound water resource policy with differentiation and relevance according to actual conditions and provide a quantitative basis and support system so that regions can learn from each other about specific water-saving measures. These findings provide an insightful understanding of the spatial difference of water intensity and also a quantifiable justification for making building-specific water resources policies, which are discussed at the end of the study.

Suggested Citation

  • Zhang, Chenjun & Wu, Yusi & Yu, Yu, 2020. "Spatial decomposition analysis of water intensity in China," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
  • Handle: RePEc:eee:soceps:v:69:y:2020:i:c:s0038012118301320
    DOI: 10.1016/j.seps.2019.01.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012118301320
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2019.01.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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. Zhao, X. & Tillotson, M.R. & Liu, Y.W. & Guo, W. & Yang, A.H. & Li, Y.F., 2017. "Index decomposition analysis of urban crop water footprint," Ecological Modelling, Elsevier, vol. 348(C), pages 25-32.
    3. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    4. 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.
    5. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    6. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
    7. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    8. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    9. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    10. Luyanga, Shadrick & Miller, Richard & Stage, Jesper, 2006. "Index number analysis of Namibian water intensity," Ecological Economics, Elsevier, vol. 57(3), pages 374-381, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Edyta Sidorczuk-Pietraszko, 2020. "Spatial Differences in Carbon Intensity in Polish Households," Energies, MDPI, vol. 13(12), pages 1-21, June.
    2. Jiangtao Zhao & Xiaojin Zhang & Lijian Qi & Li Liu & Miao Huo, 2022. "A Comprehensive Post Evaluation of the Implementation of Water-Saving Measures in Xiangtan, Hunan Province, China," Sustainability, MDPI, vol. 14(8), pages 1-10, April.
    3. Yohei Yamaguchi & Naoki Yoshikawa & Koji Amano & Seiji Hashimoto, 2021. "Decomposition Analysis of Global Water Supply-Demand Balances Focusing on Food Production and Consumption," Sustainability, MDPI, vol. 13(14), pages 1-32, July.
    4. Shi, Zhen & She, Zhiyu & Chiu, Yung-ho & Qin, Shijiong & Zhang, Lina, 2021. "Assessment and improvement analysis of economic production, water pollution, and sewage treatment efficiency in China," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    5. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).

    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. Román-Collado, Rocío & Morales-Carrión, Any Viviana, 2018. "Towards a sustainable growth in Latin America: A multiregional spatial decomposition analysis of the driving forces behind CO2 emissions changes," Energy Policy, Elsevier, vol. 115(C), pages 273-280.
    2. Ang, B.W. & Goh, Tian, 2019. "Index decomposition analysis for comparing emission scenarios: Applications and challenges," Energy Economics, Elsevier, vol. 83(C), pages 74-87.
    3. Junghwan Lee & Jinsoo Kim, 2021. "A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs," Sustainability, MDPI, vol. 13(11), pages 1-13, May.
    4. 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.
    5. Linwei Ma & Chinhao Chong & Xi Zhang & Pei Liu & Weiqi Li & Zheng Li & Weidou Ni, 2018. "LMDI Decomposition of Energy-Related CO 2 Emissions Based on Energy and CO 2 Allocation Sankey Diagrams: The Method and an Application to China," Sustainability, MDPI, vol. 10(2), pages 1-37, January.
    6. van Megen, Bram & Bürer, Meinrad & Patel, Martin K., 2019. "Comparing electricity consumption trends: A multilevel index decomposition analysis of the Genevan and Swiss economy," Energy Economics, Elsevier, vol. 83(C), pages 1-25.
    7. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    8. Mariana Conte Grand, 2018. "Desacople y Descomposición del Consumo Final de Energía en Argentina," CEMA Working Papers: Serie Documentos de Trabajo. 678, Universidad del CEMA.
    9. Jaruwan Chontanawat & Paitoon Wiboonchutikula & Atinat Buddhivanich, 2020. "Decomposition Analysis of the Carbon Emissions of the Manufacturing and Industrial Sector in Thailand," Energies, MDPI, vol. 13(4), pages 1-23, February.
    10. Román-Collado, Rocío & Cansino, José M. & Colinet, María J. & Dugo, Víctor, 2020. "A tool proposal to detect operating anomalies in the Spanish wholesale electricity market," Energy Policy, Elsevier, vol. 142(C).
    11. Li, Hao & Zhao, Yuhuan & Qiao, Xiaoyong & Liu, Ya & Cao, Ye & Li, Yue & Wang, Song & Zhang, Zhonghua & Zhang, Yongfeng & Weng, Jianfeng, 2017. "Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models," Energy Economics, Elsevier, vol. 68(C), pages 522-538.
    12. Román-Collado, Rocío & Cansino, José M. & Botia, Camilo, 2018. "How far is Colombia from decoupling? Two-level decomposition analysis of energy consumption changes," Energy, Elsevier, vol. 148(C), pages 687-700.
    13. Lin, Yuancheng & Ma, Linwei & Li, Zheng & Ni, Weidou, 2023. "The carbon reduction potential by improving technical efficiency from energy sources to final services in China: An extended Kaya identity analysis," Energy, Elsevier, vol. 263(PE).
    14. Duran, Elisa & Aravena, Claudia & Aguilar, Renato, 2015. "Analysis and decomposition of energy consumption in the Chilean industry," Energy Policy, Elsevier, vol. 86(C), pages 552-561.
    15. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    16. Dong, Kangyin & Hochman, Gal & Timilsina, Govinda R., 2020. "Do drivers of CO2 emission growth alter overtime and by the stage of economic development?," Energy Policy, Elsevier, vol. 140(C).
    17. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    18. Maamar Traich & Amal Rahmane, 2022. "LMDI decomposition analysis of CO2 emissions in Algeria during 2000-2019 and the role of energy policy in reducing emission," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2022(2), pages 83-106.
    19. Wang, Qunwei & Hang, Ye & Su, Bin & Zhou, Peng, 2018. "Contributions to sector-level carbon intensity change: An integrated decomposition analysis," Energy Economics, Elsevier, vol. 70(C), pages 12-25.
    20. Lin, Boqiang & Kuang, Yunming, 2020. "Natural gas subsidies in the industrial sector in China: National and regional perspectives," Applied Energy, Elsevier, vol. 260(C).

    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:eee:soceps:v:69:y:2020:i:c:s0038012118301320. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.