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Decomposition Analysis of Global Water Supply-Demand Balances Focusing on Food Production and Consumption

Author

Listed:
  • Yohei Yamaguchi

    (Graduate School of Science and Engineering, Ritsumeikan University, Kusatsu 525-8577, Japan)

  • Naoki Yoshikawa

    (College of Science and Engineering, Ritsumeikan University, Kusatsu 525-8577, Japan)

  • Koji Amano

    (College of Gastronomy Management, Ritsumeikan University, Kusatsu 525-8577, Japan)

  • Seiji Hashimoto

    (College of Science and Engineering, Ritsumeikan University, Kusatsu 525-8577, Japan)

Abstract

Food production and consumption require large amounts of freshwater. There is no literature on the decomposition analysis of the intensities of water supply-demand balances (water balance intensities) for each country worldwide. The aim of this study is to evaluate the water balance intensities and elucidate the promoting factors and offset factors of water balance intensities for each country worldwide, focusing on food supply-demand balances and considering food trade balances on a global scale. The modified Laspeyres index method is applied to both a production-based water balance index ( WBI PB ) and a consumption-based water balance index ( WBI CB ). The major promoting factor for the WBI PB is the renewable freshwater resources, whereas the major offset factor is the produced item preference. The major promoting factor for the WBI CB is the consumed item preference, whereas the major offset factor is the producing area preference. Improving irrigation efficiencies of rice and cereals is effective because rice requires the largest blue water footprint intensities, considering irrigation efficiency on a calorie content basis in all of the items, whereas cereals are the largest share of calorie-based production quantities in all of the items worldwide. This study provides the foundation for decreasing water balance intensities regarding food production and consumption.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7586-:d:589870
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    References listed on IDEAS

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    1. Hoekstra, Rutger & van den Bergh, Jeroen C. J. M., 2003. "Comparing structural decomposition analysis and index," Energy Economics, Elsevier, vol. 25(1), pages 39-64, January.
    2. 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.
    3. Sun, J.W. & Malaska, P., 1998. "CO2 emission intensities in developed countries 1980–1994," Energy, Elsevier, vol. 23(2), pages 105-112.
    4. 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.
    5. Zhang, Chenjun & Wu, Yusi & Yu, Yu, 2020. "Spatial decomposition analysis of water intensity in China," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    6. Ang, B. W. & Liu, F. L. & Chew, E. P., 2003. "Perfect decomposition techniques in energy and environmental analysis," Energy Policy, Elsevier, vol. 31(14), pages 1561-1566, November.
    7. Sun, J. W., 1998. "Changes in energy consumption and energy intensity: A complete decomposition model," Energy Economics, Elsevier, vol. 20(1), pages 85-100, February.
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