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A multi-objective interactive approach to assess economic-energy-environment trade-offs in Brazil

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Listed:
  • de Carvalho, Ariovaldo Lopes
  • Henggeler Antunes, Carlos
  • Freire, Fausto
  • Oliveira Henriques, Carla

Abstract

An interactive method devoted to multi-objective linear programming (MOLP) models is used to assess the trade-offs between economic, energy and environmental (E3) objectives in the Brazilian economic system. The MOLP model is based on a hybrid input–output (IO) framework, with monetary (R$) and physical (tons of oil equivalent) units, developed from the Brazilian IO table and the National Energy Balance. This framework is extended to assess different Greenhouse Gas (GHG) emissions, which are then aggregated into a single indicator (CO2eq). The model includes 444 variables, 597 constraints and 3 objective functions: maximization of Gross Domestic Product (GDP), minimization of energy consumption and minimization of GHG emissions. The interactive decision support tool enables a progressive and selective search of non-dominated solutions making the most of graphical displays, namely the parametric diagram associated with the objective function “weights”, to provide insightful information to the Decision Maker. A representative sample of non-dominated solutions has been computed in the interactive process, allowing to identify three main regions corresponding to solutions with different characteristics, i.e. different patterns of trade-offs between the conflicting objective functions. Illustrative results indicate that the maximization of GDP leads to an increase of both energy consumption and GHG emissions, while the minimization of either GHG emissions or energy consumption cause negative impacts on GDP.

Suggested Citation

  • de Carvalho, Ariovaldo Lopes & Henggeler Antunes, Carlos & Freire, Fausto & Oliveira Henriques, Carla, 2016. "A multi-objective interactive approach to assess economic-energy-environment trade-offs in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1429-1442.
  • Handle: RePEc:eee:rensus:v:54:y:2016:i:c:p:1429-1442
    DOI: 10.1016/j.rser.2015.10.064
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    References listed on IDEAS

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    Cited by:

    1. Yu, Shiwei & Zheng, Shuhong & Li, Xia, 2018. "The achievement of the carbon emissions peak in China: The role of energy consumption structure optimization," Energy Economics, Elsevier, vol. 74(C), pages 693-707.
    2. C. Oliveira & D. Coelho & C. H. Antunes, 2016. "Coupling input–output analysis with multiobjective linear programming models for the study of economy–energy–environment–social (E3S) trade-offs: a review," Annals of Operations Research, Springer, vol. 247(2), pages 471-502, December.
    3. Tian, Jing & Andraded, Celio & Lumbreras, Julio & Guan, Dabo & Wang, Fangzhi & Liao, Hua, 2018. "Integrating Sustainability Into City-level CO2 Accounting: Social Consumption Pattern and Income Distribution," Ecological Economics, Elsevier, vol. 153(C), pages 1-16.
    4. Soares, N. & Martins, A.G. & Carvalho, A.L. & Caldeira, C. & Du, C. & Castanheira, É. & Rodrigues, E. & Oliveira, G. & Pereira, G.I. & Bastos, J. & Ferreira, J.P. & Ribeiro, L.A. & Figueiredo, N.C. & , 2018. "The challenging paradigm of interrelated energy systems towards a more sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 171-193.
    5. Fuentes-Cortés, Luis Fabián & Ma, Yan & Ponce-Ortega, Jose María & Ruiz-Mercado, Gerardo & Zavala, Victor M., 2018. "Valuation of water and emissions in energy systems," Applied Energy, Elsevier, vol. 210(C), pages 518-528.
    6. de Carvalho, Ariovaldo Lopes & Antunes, Carlos Henggeler & Freire, Fausto, 2016. "Economic-energy-environment analysis of prospective sugarcane bioethanol production in Brazil," Applied Energy, Elsevier, vol. 181(C), pages 514-526.
    7. Yu, Shiwei & Zheng, Shuhong & Zhang, Xuejiao & Gong, Chengzhu & Cheng, Jinhua, 2018. "Realizing China's goals on energy saving and pollution reduction: Industrial structure multi-objective optimization approach," Energy Policy, Elsevier, vol. 122(C), pages 300-312.

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