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Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28

Author

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  • Andreas Müller

    (E-Think Energy Research, Zentrum für Energiewirtschaft und Umwelt, Argentinierstrasse 18, 1040 Vienna, Austria
    Institute of Energy Systems and Electrical Drives, Energy Economics Group, Technische Universität Wien, Gusshausstr. 25-27, 1040 Vienna, Austria)

  • Marcus Hummel

    (E-Think Energy Research, Zentrum für Energiewirtschaft und Umwelt, Argentinierstrasse 18, 1040 Vienna, Austria)

  • Lukas Kranzl

    (Institute of Energy Systems and Electrical Drives, Energy Economics Group, Technische Universität Wien, Gusshausstr. 25-27, 1040 Vienna, Austria)

  • Mostafa Fallahnejad

    (Institute of Energy Systems and Electrical Drives, Energy Economics Group, Technische Universität Wien, Gusshausstr. 25-27, 1040 Vienna, Austria)

  • Richard Büchele

    (Institute of Energy Systems and Electrical Drives, Energy Economics Group, Technische Universität Wien, Gusshausstr. 25-27, 1040 Vienna, Austria)

Abstract

The planning of heating and cooling supply and demand is key to reaching climate and sustainability targets. At the same time, data for planning are scarce for many places in Europe. In this study, we developed an open source dataset of gross floor area and energy demand for space heating and hot water in residential and tertiary buildings at the hectare level for EU28 + Norway, Iceland, and Switzerland. This methodology is based on a top-down approach, starting from a consistent dataset at the country level (NUTS 0), breaking this down to the NUTS 3 level and further to the hectare level by means of a series of regional indicators. We compare this dataset with data from other sources for 20 places in Europe. This process shows that the data for some places fit well, while for others, large differences up to 45% occur. The discussion of these results shows that the other data sources used for this comparison are also subject to considerable uncertainties. A comparison of the developed data with maps based on municipal building stock data for three cities shows that the developed dataset systematically overestimates the gross floor area and heat demand in low density areas and vice versa. We conclude that these data are useful for strategic purposes on aggregated level of larger regions and municipalities. It is especially valuable in locations where no detailed data is available. For detailed planning of heating and cooling infrastructure, local data should be used instead. We believe our work contributes towards a transparent, open source dataset for heating and cooling planning that can be regularly updated and is easily accessible and usable for further research and planning activities.

Suggested Citation

  • Andreas Müller & Marcus Hummel & Lukas Kranzl & Mostafa Fallahnejad & Richard Büchele, 2019. "Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28," Energies, MDPI, vol. 12(24), pages 1-25, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4789-:d:298413
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    References listed on IDEAS

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    2. Malte Schwanebeck & Marcus Krüger & Rainer Duttmann, 2021. "Improving GIS-Based Heat Demand Modelling and Mapping for Residential Buildings with Census Data Sets at Regional and Sub-Regional Scales," Energies, MDPI, vol. 14(4), pages 1-18, February.
    3. Sánchez-García, Luis & Averfalk, Helge & Möllerström, Erik & Persson, Urban, 2023. "Understanding effective width for district heating," Energy, Elsevier, vol. 277(C).
    4. Stoeglehner, G. & Abart-Heriszt, L., 2022. "Integrated spatial and energy planning in Styria – A role model for local and regional energy transition and climate protection policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    5. Axel Bruck & Luca Casamassima & Ardak Akhatova & Lukas Kranzl & Kostas Galanakis, 2022. "Creating Comparability among European Neighbourhoods to Enable the Transition of District Energy Infrastructures towards Positive Energy Districts," Energies, MDPI, vol. 15(13), pages 1-21, June.
    6. Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2020. "Open Data and Energy Analytics," Energies, MDPI, vol. 13(9), pages 1-3, May.
    7. Nis Bertelsen & Brian Vad Mathiesen, 2020. "EU-28 Residential Heat Supply and Consumption: Historical Development and Status," Energies, MDPI, vol. 13(8), pages 1-21, April.
    8. Zwickl-Bernhard, Sebastian & Auer, Hans, 2022. "Demystifying natural gas distribution grid decommissioning: An open-source approach to local deep decarbonization of urban neighborhoods," Energy, Elsevier, vol. 238(PB).
    9. Kleanthis Koupidis & Charalampos Bratsas & Christos Vlachokostas, 2022. "OpΕnergy: An Intelligent System for Monitoring EU Energy Strategy Using EU Open Data," Energies, MDPI, vol. 15(21), pages 1-15, November.
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    11. Stefan Pauliuk & Niko Heeren, 2021. "Material efficiency and its contribution to climate change mitigation in Germany: A deep decarbonization scenario analysis until 2060," Journal of Industrial Ecology, Yale University, vol. 25(2), pages 479-493, April.

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