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A GIS-Based Methodology for Speedy Energy Efficiency Mapping: A Case Study in Bologna

Author

Listed:
  • Jacopo Gaspari

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

  • Michaela De Giglio

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

  • Ernesto Antonini

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

  • Vincenzo Vodola

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

Abstract

The paper reports a methodology developed to map energy consumption of the building stock at the urban scale on a GIS environment. Energy consumption has been investigated, focusing on the shift from the individual building scale to the district one with the purpose of identifying larger homogenous energy use areas for addressing policies and plans to improve the quality and the performance levels at the city scale. The urban planning zoning concept was extended to the energy issue to include the energy behavior of each zone that depends on the performance of its individual buildings. The methodology generates GIS maps providing a district scale visualization of energy consumption according to shared criteria. A case study in Bologna city (Italy) is provided. In the specific case, the last update of Emilia-Romagna regional urban planning regulation required a mapping action regarding energy efficiency of homogeneous urban portions defined by the General Urban Plan. The main achieved results are (a) a methodology to identify homogeneous areas for analyzing energy consumption; (b) an updated energy map of Bologna Municipality.

Suggested Citation

  • Jacopo Gaspari & Michaela De Giglio & Ernesto Antonini & Vincenzo Vodola, 2020. "A GIS-Based Methodology for Speedy Energy Efficiency Mapping: A Case Study in Bologna," Energies, MDPI, vol. 13(9), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2230-:d:353597
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    References listed on IDEAS

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    1. Cerezo Davila, Carlos & Reinhart, Christoph F. & Bemis, Jamie L., 2016. "Modeling Boston: A workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets," Energy, Elsevier, vol. 117(P1), pages 237-250.
    2. Ballarini, Ilaria & Corgnati, Stefano Paolo & Corrado, Vincenzo, 2014. "Use of reference buildings to assess the energy saving potentials of the residential building stock: The experience of TABULA project," Energy Policy, Elsevier, vol. 68(C), pages 273-284.
    3. Murphy, Lorraine, 2014. "The influence of the Energy Performance Certificate: The Dutch case," Energy Policy, Elsevier, vol. 67(C), pages 664-672.
    4. Fabbri, Kristian, 2015. "Building and fuel poverty, an index to measure fuel poverty: An Italian case study," Energy, Elsevier, vol. 89(C), pages 244-258.
    5. Theodoridou, Ifigeneia & Karteris, Marinos & Mallinis, Georgios & Papadopoulos, Agis M. & Hegger, Manfred, 2012. "Assessment of retrofitting measures and solar systems' potential in urban areas using Geographical Information Systems: Application to a Mediterranean city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 6239-6261.
    6. Parshall, Lily & Gurney, Kevin & Hammer, Stephen A. & Mendoza, Daniel & Zhou, Yuyu & Geethakumar, Sarath, 2010. "Modeling energy consumption and CO2 emissions at the urban scale: Methodological challenges and insights from the United States," Energy Policy, Elsevier, vol. 38(9), pages 4765-4782, September.
    7. Tronchin, Lamberto & Fabbri, Kristian, 2012. "Energy Performance Certificate of building and confidence interval in assessment: An Italian case study," Energy Policy, Elsevier, vol. 48(C), pages 176-184.
    8. Droutsa, Kalliopi G. & Kontoyiannidis, Simon & Dascalaki, Elena G. & Balaras, Constantinos A., 2016. "Mapping the energy performance of hellenic residential buildings from EPC (energy performance certificate) data," Energy, Elsevier, vol. 98(C), pages 284-295.
    9. Caputo, Paola & Costa, Gaia & Ferrari, Simone, 2013. "A supporting method for defining energy strategies in the building sector at urban scale," Energy Policy, Elsevier, vol. 55(C), pages 261-270.
    10. Van Hoesen, John & Letendre, Steven, 2010. "Evaluating potential renewable energy resources in Poultney, Vermont: A GIS-based approach to supporting rural community energy planning," Renewable Energy, Elsevier, vol. 35(9), pages 2114-2122.
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    Cited by:

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    2. Aleksandar S. Anđelković & Miroslav Kljajić & Dušan Macura & Vladimir Munćan & Igor Mujan & Mladen Tomić & Željko Vlaović & Borivoj Stepanov, 2021. "Building Energy Performance Certificate—A Relevant Indicator of Actual Energy Consumption and Savings?," Energies, MDPI, vol. 14(12), pages 1-19, June.
    3. Beril Alpagut & Arantza Lopez Romo & Patxi Hernández & Oya Tabanoğlu & Nekane Hermoso Martinez, 2021. "A GIS-Based Multicriteria Assessment for Identification of Positive Energy Districts Boundary in Cities," Energies, MDPI, vol. 14(22), pages 1-18, November.

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