IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i19p10511-d640540.html
   My bibliography  Save this article

Integrated Planning for Regional Development Planning with Low Carbon Development Constraint under Uncertainty: A Case Study of Qingpu District, Shanghai

Author

Listed:
  • Wentao Lu

    (School of Environment, Tsinghua University, Beijing 100084, China
    Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China
    The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing 100012, China)

  • Zhenghui Fu

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Yang Zhang

    (College of Environmental Science and Engineering, Peking University, Beijing 100871, China)

  • Yuxuan Qiao

    (School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China)

  • Lei Yu

    (Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China)

  • Yi Liu

    (School of Environment, Tsinghua University, Beijing 100084, China)

Abstract

Regional development planning systems contain multiple uncertainties which come from economic restructuring, resource management, carbon peak action, environmental protection, and other factors, it is difficulty to handle all of these uncertainties in one method. In order to solve this problem, a new model developed in this study combines an interval fuzzy program with an environmental quality model for regional development planning in order to provide optimal solutions. The interval fuzzy program is put forward based on interval parameter programming (IPP) and fuzzy programing (FP). The environmental quality model is used to calculate water environmental capacity and atmospheric capacity, which are set as constraint conditions in the model. In order to meet the requirements of carbon peak action, a low carbon development constraint is added to the model. In this model, decision makers can choose the satisfaction level of constraints based on their preferences. The results suggest that the methodology is applicable for the regional development planning system within the planning period. The developed model can be used to generate a series of optimization schema under multiple credibility levels, ensuring that the regional development planning system can meet both societal demands and environmental quality requirements, considering a proper balance between the expected system benefits and risks of violating the resource constraint and low carbon development constraint.

Suggested Citation

  • Wentao Lu & Zhenghui Fu & Yang Zhang & Yuxuan Qiao & Lei Yu & Yi Liu, 2021. "Integrated Planning for Regional Development Planning with Low Carbon Development Constraint under Uncertainty: A Case Study of Qingpu District, Shanghai," Sustainability, MDPI, vol. 13(19), pages 1-24, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10511-:d:640540
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/19/10511/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/19/10511/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Samimi, Abouzar & Nikzad, Mehdi & Siano, Pierluigi, 2017. "Scenario-based stochastic framework for coupled active and reactive power market in smart distribution systems with demand response programs," Renewable Energy, Elsevier, vol. 109(C), pages 22-40.
    2. Zhi-Fu Mi & Su-Yan Pan & Hao Yu & Yi-Ming Wei, 2014. "Potential impacts of industrial structure on energy consumption and CO2 emission: a case study of Beijing," CEEP-BIT Working Papers 51, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    3. Huang, G. H., 1998. "A hybrid inexact-stochastic water management model," European Journal of Operational Research, Elsevier, vol. 107(1), pages 137-158, May.
    4. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    5. Song Han & Changqing Lin & Baosheng Zhang & Arash Farnoosh, 2019. "Projections and Recommendations for Energy Structure and Industrial Structure Development in China through 2030: A System Dynamics Model," Sustainability, MDPI, vol. 11(18), pages 1-20, September.
    6. Song Han & Changqing Lin & Baosheng Zhang & Arash Farnoosh, 2019. "Projections and Recommendations for Energy Structure and Industrial Structure Development in China through 2030: A System Dynamics Model," Post-Print hal-02408957, HAL.
    7. Lu, W.T. & Dai, C. & Fu, Z.H. & Liang, Z.Y. & Guo, H.C., 2018. "An interval-fuzzy possibilistic programming model to optimize China energy management system with CO2 emission constraint," Energy, Elsevier, vol. 142(C), pages 1023-1039.
    8. Fahimnia, Behnam & Sarkis, Joseph & Choudhary, Alok & Eshragh, Ali, 2015. "Tactical supply chain planning under a carbon tax policy scheme: A case study," International Journal of Production Economics, Elsevier, vol. 164(C), pages 206-215.
    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. Lu, W.T. & Dai, C. & Fu, Z.H. & Liang, Z.Y. & Guo, H.C., 2018. "An interval-fuzzy possibilistic programming model to optimize China energy management system with CO2 emission constraint," Energy, Elsevier, vol. 142(C), pages 1023-1039.
    2. Honglei Shi & Guiling Wang & Wei Zhang & Feng Ma & Wenjing Lin & Menglei Ji, 2023. "Predicting the Potential of China’s Geothermal Energy in Industrial Development and Carbon Emission Reduction," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
    3. Cai, Mengting & Huang, Guohe & Chen, Jiapei & Li, Yunhuan & Fan, Yurui, 2018. "A generalized fuzzy chance-constrained energy systems planning model for Guangzhou, China," Energy, Elsevier, vol. 165(PA), pages 191-204.
    4. Kassim, Fatima & Isik, Abdurrahman, 2020. "The link between energy consumption and economic growth: Evidence from transition economies (1985-2017)," MPRA Paper 101601, University Library of Munich, Germany.
    5. X. Qin & G. Huang, 2009. "An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 661-695, March.
    6. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "An interval-valued minimax-regret analysis approach for the identification of optimal greenhouse-gas abatement strategies under uncertainty," Energy Policy, Elsevier, vol. 39(7), pages 4313-4324, July.
    7. Zhi-Fu Mi & Yi-Ming Wei & Chen-Qi He & Hua-Nan Li & Xiao-Chen Yuan & Hua Liao, 2017. "Regional efforts to mitigate climate change in China: a multi-criteria assessment approach," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(1), pages 45-66, January.
    8. Wang, Moran & Li, Xuerong & Wang, Shouyang, 2021. "Discovering research trends and opportunities of green finance and energy policy: A data-driven scientometric analysis," Energy Policy, Elsevier, vol. 154(C).
    9. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    10. Zhang, Yue-Jun & Liu, Zhao & Zhou, Si-Ming & Qin, Chang-Xiong & Zhang, Huan, 2018. "The impact of China's Central Rise Policy on carbon emissions at the stage of operation in road sector," Economic Modelling, Elsevier, vol. 71(C), pages 159-173.
    11. Wang, S. & Huang, G.H., 2014. "An integrated approach for water resources decision making under interactive and compound uncertainties," Omega, Elsevier, vol. 44(C), pages 32-40.
    12. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    13. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    14. Min Zhou & Shasha Lu & Shukui Tan & Danping Yan & Guoliang Ou & Dianfeng Liu & Xiang Luo & Yanan Li & Lu Zhang & Zuo Zhang & Xiangbo Zhu, 2017. "A stochastic equilibrium chance-constrained programming model for municipal solid waste management of the City of Dalian, China," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(1), pages 199-218, January.
    15. Yulei Xie & Linrui Wang & Guohe Huang & Dehong Xia & Ling Ji, 2018. "A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China," Energies, MDPI, vol. 11(8), pages 1-24, August.
    16. Yang, Yuxiang & Goodarzi, Shadi & Jabbarzadeh, Armin & Fahimnia, Behnam, 2022. "In-house production and outsourcing under different emissions reduction regulations: An equilibrium decision model for global supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    17. Wen-Hsien Tsai & Shang-Yu Lai & Chu-Lun Hsieh, 2023. "Exploring the impact of different carbon emission cost models on corporate profitability," Annals of Operations Research, Springer, vol. 322(1), pages 41-74, March.
    18. Changyu Zhou & Guohe Huang & Jiapei Chen, 2018. "A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China," Energies, MDPI, vol. 11(10), pages 1-21, October.
    19. Zhang, Xiaoyue & Huang, Guohe & Liu, Lirong & Li, Kailong, 2022. "Development of a stochastic multistage lifecycle programming model for electric power system planning – A case study for the Province of Saskatchewan, Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    20. Meng, Xiaoge & Yao, Zhong & Nie, Jiajia & Zhao, Yingxue & Li, Zenglu, 2018. "Low-carbon product selection with carbon tax and competition: Effects of the power structure," International Journal of Production Economics, Elsevier, vol. 200(C), pages 224-230.

    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:jsusta:v:13:y:2021:i:19:p:10511-:d:640540. 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.