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Multi-Dimensional Hypothetical Fuzzy Risk Simulation model for Greenhouse Gas mitigation policy development

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  • Liu, Lirong
  • Huang, Guohe
  • Baetz, Brian
  • Guan, Yuru
  • Zhang, Kaiqiang

Abstract

Changing climate is one of the most challenging environment issues worldwide. The objective of this paper is to develop a Multi-Dimensional Hypothetical Fuzzy Risk Simulation Model to facilitate the Greenhouse Gases mitigation policy development and multi-dimensional risk simulation. In detail, the comprehensive performances of various industries are evaluated and analyzed through Hypothetical Extraction Method. The preferences of decision-makers are considered through Analytic Hierarchy Process and Fuzzy Technique for Order Preference by Similarities to Ideal Solution method to develop the optimized Greenhouse Gases mitigation policies. The multi-dimensional risks of optimized Greenhouse Gases mitigation policies are simulated through RAS method. A detailed case study of the Province of Saskatchewan, Canada, is conducted to illustrate the potential benefits of the proposed model and support the Greenhouse Gases mitigation policy development. It is found that Electric power generation, transmission and distribution sector is the key industry in Saskatchewan. The government supports are suggested to be allocated to the Electric power generation, transmission and distribution sector, since it will benefit the province from environmental, economic, and urban metabolic perspectives.

Suggested Citation

  • Liu, Lirong & Huang, Guohe & Baetz, Brian & Guan, Yuru & Zhang, Kaiqiang, 2020. "Multi-Dimensional Hypothetical Fuzzy Risk Simulation model for Greenhouse Gas mitigation policy development," Applied Energy, Elsevier, vol. 261(C).
    • Handle: RePEc:eee:appene:v:261:y:2020:i:c:s0306261919320355
    DOI: 10.1016/j.apenergy.2019.114348
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    as
    1. Zubelzu, Sergio & Álvarez, Roberto, 2015. "Urban planning and industry in Spain: A novel methodology for calculating industrial carbon footprints," Energy Policy, Elsevier, vol. 83(C), pages 57-68.
    2. Elzen, Michel den & Fekete, Hanna & Höhne, Niklas & Admiraal, Annemiek & Forsell, Nicklas & Hof, Andries F. & Olivier, Jos G.J. & Roelfsema, Mark & van Soest, Heleen, 2016. "Greenhouse gas emissions from current and enhanced policies of China until 2030: Can emissions peak before 2030?," Energy Policy, Elsevier, vol. 89(C), pages 224-236.
    3. Du, W.C. & Xia, X.H., 2018. "How does urbanization affect GHG emissions? A cross-country panel threshold data analysis," Applied Energy, Elsevier, vol. 229(C), pages 872-883.
    4. Wang, Ke & Wang, Jiayu & Wei, Yi-Ming & Zhang, Chi, 2018. "A novel dataset of emission abatement sector extended input-output table for environmental policy analysis," Applied Energy, Elsevier, vol. 231(C), pages 1259-1267.
    5. Manfred Lenzen & Richard Wood & Blanca Gallego, 2007. "Some Comments on the GRAS Method," Economic Systems Research, Taylor & Francis Journals, vol. 19(4), pages 461-465.
    6. Liu, Lirong & Huang, Charley Z. & Huang, Guohe & Baetz, Brian & Pittendrigh, Scott M., 2018. "How a carbon tax will affect an emission-intensive economy: A case study of the Province of Saskatchewan, Canada," Energy, Elsevier, vol. 159(C), pages 817-826.
    7. Lomax, Guy & Workman, Mark & Lenton, Timothy & Shah, Nilay, 2015. "Reframing the policy approach to greenhouse gas removal technologies," Energy Policy, Elsevier, vol. 78(C), pages 125-136.
    8. Liu, Lirong & Huang, Guohe & Baetz, Brian & Zhang, Kaiqiang, 2018. "Environmentally-extended input-output simulation for analyzing production-based and consumption-based industrial greenhouse gas mitigation policies," Applied Energy, Elsevier, vol. 232(C), pages 69-78.
    9. Su, Bin & Ang, B.W. & Li, Yingzhu, 2017. "Input-output and structural decomposition analysis of Singapore's carbon emissions," Energy Policy, Elsevier, vol. 105(C), pages 484-492.
    10. Wolsky, Alan Martin, 1984. "Disaggregating Input-Output Models," The Review of Economics and Statistics, MIT Press, vol. 66(2), pages 283-291, May.
    11. Vaidya, Omkarprasad S. & Kumar, Sushil, 2006. "Analytic hierarchy process: An overview of applications," European Journal of Operational Research, Elsevier, vol. 169(1), pages 1-29, February.
    12. Cai, Bofeng & Cui, Can & Zhang, Da & Cao, Libin & Wu, Pengcheng & Pang, Lingyun & Zhang, Jihong & Dai, Chunyan, 2019. "China city-level greenhouse gas emissions inventory in 2015 and uncertainty analysis," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    13. Hua, Yaping & Oliphant, Monica & Hu, Eric Jing, 2016. "Development of renewable energy in Australia and China: A comparison of policies and status," Renewable Energy, Elsevier, vol. 85(C), pages 1044-1051.
    14. Brizga, Janis & Feng, Kuishuang & Hubacek, Klaus, 2017. "Household carbon footprints in the Baltic States: A global multi-regional input–output analysis from 1995 to 2011," Applied Energy, Elsevier, vol. 189(C), pages 780-788.
    15. Su, Bin & Ang, B.W., 2015. "Multiplicative decomposition of aggregate carbon intensity change using input–output analysis," Applied Energy, Elsevier, vol. 154(C), pages 13-20.
    16. Yang, Christopher & Yeh, Sonia & Zakerinia, Saleh & Ramea, Kalai & McCollum, David, 2015. "Achieving California's 80% greenhouse gas reduction target in 2050: Technology, policy and scenario analysis using CA-TIMES energy economic systems model," Energy Policy, Elsevier, vol. 77(C), pages 118-130.
    17. Liu, Lirong & Huang, Guohe & Baetz, Brian & Huang, Charley Z. & Zhang, Kaiqiang, 2019. "Integrated GHG emissions and emission relationships analysis through a disaggregated ecologically-extended input-output model; A case study for Saskatchewan, Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 97-109.
    18. Wu, Junnian & Pu, Guangying & Guo, Yan & Lv, Jingwen & Shang, Jiangwei, 2018. "Retrospective and prospective assessment of exergy, life cycle carbon emissions, and water footprint for coking network evolution in China," Applied Energy, Elsevier, vol. 218(C), pages 479-493.
    19. Alex Y. Lo, 2016. "Challenges to the development of carbon markets in China," Climate Policy, Taylor & Francis Journals, vol. 16(1), pages 109-124, January.
    20. Bi, Kexin & Huang, Ping & Ye, Hui, 2015. "Risk identification, evaluation and response of low-carbon technological innovation under the global value chain: A case of the Chinese manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 238-248.
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