Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28
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 wa...
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fttuwien:oai:repositum.tuwien.at:20.500.12708/772 2023-05-15T16:52:31+02:00 Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 Müller, Andreas Hummel, Marcus Kranzl, Lukas Fallahnejad, Mostafa Büchele, Richard 2020-06-27T17:50:55Z https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-8212 https://hdl.handle.net/20.500.12708/772 en eng MDPI Energies HotMaps: 723677 1996-1073 https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-8212 http://hdl.handle.net/20.500.12708/772 AC15549325 urn:nbn:at:at-ubtuw:3-8212 open open data heating building stock heat map spatial analysis heat density map Article Artikel 2020 fttuwien https://doi.org/20.500.12708/772 2022-04-15T12:23:46Z 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. European Union's Horizon 2020 Article in Journal/Newspaper Iceland TU Wien: reposiTUm Norway |
institution |
Open Polar |
collection |
TU Wien: reposiTUm |
op_collection_id |
fttuwien |
language |
English |
topic |
open data heating building stock heat map spatial analysis heat density map |
spellingShingle |
open data heating building stock heat map spatial analysis heat density map Müller, Andreas Hummel, Marcus Kranzl, Lukas Fallahnejad, Mostafa Büchele, Richard Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 |
topic_facet |
open data heating building stock heat map spatial analysis heat density map |
description |
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. European Union's Horizon 2020 |
format |
Article in Journal/Newspaper |
author |
Müller, Andreas Hummel, Marcus Kranzl, Lukas Fallahnejad, Mostafa Büchele, Richard |
author_facet |
Müller, Andreas Hummel, Marcus Kranzl, Lukas Fallahnejad, Mostafa Büchele, Richard |
author_sort |
Müller, Andreas |
title |
Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 |
title_short |
Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 |
title_full |
Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 |
title_fullStr |
Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 |
title_full_unstemmed |
Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28 |
title_sort |
open source data for gross floor area and heat demand density on the hectare level for eu 28 |
publisher |
MDPI |
publishDate |
2020 |
url |
https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-8212 https://hdl.handle.net/20.500.12708/772 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Iceland |
genre_facet |
Iceland |
op_relation |
Energies HotMaps: 723677 1996-1073 https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-8212 http://hdl.handle.net/20.500.12708/772 AC15549325 urn:nbn:at:at-ubtuw:3-8212 |
op_rights |
open |
op_doi |
https://doi.org/20.500.12708/772 |
_version_ |
1766042845021470720 |