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A novel spatial based approach for estimation of space heating demand saving potential and CO2 emissions reduction in urban areas

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  • Meha, Drilon
  • Dragusha, Bedri
  • Thakur, Jagruti
  • Novosel, Tomislav
  • Duić, Neven

Abstract

Space heating accounts for the most significant share of final energy demand in buildings in colder climatic regions contributing to greenhouse gas emission. In addition, there is a lack of data available to assess spatially, the potential of space heating demand reduction in different buildings when considering typical building refurbishment measures. Hence, in this paper, a robust information socket for urban building stock is developed to assess the impact of energy efficiency measures on space heating demand savings and CO2 emission reduction potential in the existing buildings based on a Geographical Information System tool. The model considers the topology and thermal performance of different building categories; houses with and without thermal insulation, apartments, commercial, public, office, and industrial buildings. Three scenarios, a reference and two additional scenarios using Prishtina city as a case study, have been created for standard (scenario 1), and advanced energy efficiency (scenario 2) measures based on the government’s proposed policies. The findings show that space heat demand saving potential for scenario 1 and 2 in comparison to the reference scenario was 50% and 68.5% respectively. Moreover, the CO2 emissions are reduced significantly from 502.3 mil kgCO2/year in reference scenario to 249.8 mil kgCO2/year for scenario 1 and 158.7 mil kgCO2/year in scenario 2 respectively.

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  • Meha, Drilon & Dragusha, Bedri & Thakur, Jagruti & Novosel, Tomislav & Duić, Neven, 2021. "A novel spatial based approach for estimation of space heating demand saving potential and CO2 emissions reduction in urban areas," Energy, Elsevier, vol. 225(C).
    • Handle: RePEc:eee:energy:v:225:y:2021:i:c:s0360544221005004
    DOI: 10.1016/j.energy.2021.120251
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    References listed on IDEAS

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    1. Nielsen, Steffen, 2014. "A geographic method for high resolution spatial heat planning," Energy, Elsevier, vol. 67(C), pages 351-362.
    2. Berger, Matthias & Worlitschek, Jörg, 2018. "A novel approach for estimating residential space heating demand," Energy, Elsevier, vol. 159(C), pages 294-301.
    3. Novosel, T. & Pukšec, T. & Duić, N. & Domac, J., 2020. "Heat demand mapping and district heating assessment in data-pour areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    4. Meha, Drilon & Novosel, Tomislav & Duić, Neven, 2020. "Bottom-up and top-down heat demand mapping methods for small municipalities, case Gllogoc," Energy, Elsevier, vol. 199(C).
    5. Connolly, D. & Lund, H. & Mathiesen, B.V. & Werner, S. & Möller, B. & Persson, U. & Boermans, T. & Trier, D. & Østergaard, P.A. & Nielsen, S., 2014. "Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system," Energy Policy, Elsevier, vol. 65(C), pages 475-489.
    6. Artur Wyrwa & Yi-kuang Chen, 2017. "Mapping Urban Heat Demand with the Use of GIS-Based Tools," Energies, MDPI, vol. 10(5), pages 1-15, May.
    7. Möller, Bernd & Wiechers, Eva & Persson, Urban & Grundahl, Lars & Connolly, David, 2018. "Heat Roadmap Europe: Identifying local heat demand and supply areas with a European thermal atlas," Energy, Elsevier, vol. 158(C), pages 281-292.
    8. Nielsen, Steffen & Möller, Bernd, 2013. "GIS based analysis of future district heating potential in Denmark," Energy, Elsevier, vol. 57(C), pages 458-468.
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