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A Multi-Objective Input–Output Linear Model for Water Supply, Economic Growth and Environmental Planning in Resource-Based Cities

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  • Wenlan Ke

    (School of Humanities and Economic Management, China University of Geosciences, Beijing 100083, China
    Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resource, Beijing 100083, China)

  • Jinghua Sha

    (School of Humanities and Economic Management, China University of Geosciences, Beijing 100083, China
    Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resource, Beijing 100083, China)

  • Jingjing Yan

    (School of Humanities and Economic Management, China University of Geosciences, Beijing 100083, China
    Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resource, Beijing 100083, China)

  • Guofeng Zhang

    (Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resource, Beijing 100083, China
    Institute of Economic and Trade, Shijiazhuang University of Economics, Shijiazhuang 050031, China)

  • Rongrong Wu

    (Department of Finance and Accounting, Yango College, Fuzhou 350015, China)

Abstract

Water resource and environment capacity have become two of the most important restrictions for sustainable development in resource-based cities whose leading industries are the exploitation and processing of resources. Taking Ordos in China as an example, this article constructs an integrated model combining a multi-objective optimization model with input–output analysis to achieve the tradeoffs between economic growth, water utilization and environmental protection. This dynamic model includes socioeconomic, water supply–demand, water quality control, air quality control, energy consumption control and integrated policy sub-models. These six sub-models interact with each other. After simulation, this article proposes efficient solutions on industrial restructuring by maximizing the Gross Regional Product of Ordos from 394.3 in 2012 to 785.1 billion RMB in 2025 with a growth rate of 6.4% annually; and presents a water supply plan by maximizing the proportion of reclaimed water from 2% to 6.3% through sewage treatment technology selection and introduction, and effective water allocation. Meanwhile, the environmental impacts are all in line with the planning targets. This study illustrates that the integrated modeling is generic and can be applied to any region suffering uncoordinated development issues and can serve as a pre-evaluation approach for conducting early warning research to offer suggestions for government decision-making.

Suggested Citation

  • Wenlan Ke & Jinghua Sha & Jingjing Yan & Guofeng Zhang & Rongrong Wu, 2016. "A Multi-Objective Input–Output Linear Model for Water Supply, Economic Growth and Environmental Planning in Resource-Based Cities," Sustainability, MDPI, vol. 8(2), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:2:p:160-:d:63664
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    References listed on IDEAS

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    Cited by:

    1. Xinkui Wang & Zengchuan Dong & Wei Xu & Yun Luo & Tao Zhou & Wenzhuo Wang, 2019. "Study on Spatial and Temporal Distribution Characteristics of Coordinated Development Degree among Regional Water Resources, Social Economy, and Ecological Environment Systems," IJERPH, MDPI, vol. 16(21), pages 1-20, October.
    2. Zhang, Qian & Shen, Juqin & Sun, Fuhua, 2021. "Spatiotemporal differentiation of coupling coordination degree between economic development and water environment and its influencing factors using GWR in China's province," Ecological Modelling, Elsevier, vol. 462(C).
    3. Willem K. M. Brauers, 2018. "Location Theory and Multi-Criteria Decision Making: An Application of the MOORA Method," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(3), September.
    4. Liu, Er-na & Wang, Yanan & Chen, Wei & Chen, Wenjun & Ning, Siyin, 2021. "Evaluating the transformation of China's resource-based cities: An integrated sequential weight and TOPSIS approach," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).

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