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An empirical high-resolution geospatial model of future population distribution for assessing heat demands
Europa-Universität Flensburg, Flensburg, Germany.
Europa-Universität Flensburg, Flensburg, Germany.
Halmstad University, School of Business, Innovation and Sustainability.ORCID iD: 0000-0001-9118-4375
Halmstad University, School of Business, Innovation and Sustainability.ORCID iD: 0000-0002-6369-2222
2021 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

The future population distribution informs decisions on investment in district heating. Across Europe, demographic change has been associated with structural changes of the past. Trends towards urban or rural migration, urban sprawl or the depopulation of city centers will continue. Using gridded population data since 1990, past development is mapped using spatial disaggregation to grid cells by intensity of urban development. An empirical method proposed captures increment of population in each grid cell and relates it to the focal statistics of the cell neighbourhood. A positive population trend in populated cells leads to a future population increase and a spill over into new development areas, while a negative trend leads to lower future population. New areas are modelled based on the principles of proximity and similarity using neighbourhood trends and land cover suitability, adjusted to national and regional population trends. The result is a set of future 1-hectare population grids, which have been used to model the distribution of future heat demands. The distribution of heat demand densities, the zoning of heat supply, and the potential for individual heat pumps have been modelled. Results show that reductions of heat demands and demographic developments leave a window of opportunities to develop heating infrastructures with known technology in the present decade, after which 4th Generation District Heat technology is required to decarbonise the heating sector.

Place, publisher, year, edition, pages
2021.
Keywords [en]
Population modelling, heat demands, GIS
National Category
Energy Engineering Infrastructure Engineering Energy Systems Remote Sensing
Research subject
Smart Cities and Communities
Identifiers
URN: urn:nbn:se:hh:diva-48175OAI: oai:DiVA.org:hh-48175DiVA, id: diva2:1700011
Conference
7th International Conference on Smart Energy Systems, 21-22 September, Copenhagen, Denmark
Part of project
Quantification of synergies between Energy Efficiency first principle and renewable energy systems
Funder
EU, Horizon 2020, 846463Available from: 2022-09-29 Created: 2022-09-29 Last updated: 2023-02-27Bibliographically approved

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Persson, Urban

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf