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Policies to decarbonize the Swiss residential building stock: An agent-based building stock modeling assessment

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  • Nägeli, Claudio
  • Jakob, Martin
  • Catenazzi, Giacomo
  • Ostermeyer, York

Abstract

In light of the Swiss government's reduction targets for greenhouse gas (GHG) emissions under the Paris Agreement, this article investigates how and with which policy measures these reduction targets can be met for the Swiss residential building sector. The paper applies an agent-based building stock model to simulate the development of the Swiss residential building stock under three different policy scenarios. The scenario results until 2050 are compared against the reduction targets set by the Swiss government and with each other. The results indicate that while the current state of Swiss climate policy is effective in reducing energy demand and GHG emissions, it will not be enough to reach the ambitious emission-reduction targets. These targets can be reached only through an almost complete phase-out of fossil-fuel heating systems by 2050, which can be achieved through the introduction of further financial and/or regulatory measures. The results indicate that while financial measures such as an increase in the CO2 tax as well as subsidies are effective in speeding up the transition in the beginning, a complete phase-out of oil and gas by 2050 is reached only through additional regulatory measures such as a CO2 limit for new and existing buildings.

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  • Nägeli, Claudio & Jakob, Martin & Catenazzi, Giacomo & Ostermeyer, York, 2020. "Policies to decarbonize the Swiss residential building stock: An agent-based building stock modeling assessment," Energy Policy, Elsevier, vol. 146(C).
  • Handle: RePEc:eee:enepol:v:146:y:2020:i:c:s0301421520305322
    DOI: 10.1016/j.enpol.2020.111814
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    6. Hietaharju, Petri & Pulkkinen, Jari & Ruusunen, Mika & Louis, Jean-Nicolas, 2021. "A stochastic dynamic building stock model for determining long-term district heating demand under future climate change," Applied Energy, Elsevier, vol. 295(C).
    7. Streicher, Kai Nino & Berger, Matthias & Panos, Evangelos & Narula, Kapil & Soini, Martin Christoph & Patel, Martin K., 2021. "Optimal building retrofit pathways considering stock dynamics and climate change impacts," Energy Policy, Elsevier, vol. 152(C).
    8. Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof & Allan, James & Hoffmann, Volker H., 2022. "MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits," Applied Energy, Elsevier, vol. 314(C).
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    10. Delia D’Agostino & Danny Parker & Ilenia Epifani & Dru Crawley & Linda Lawrie, 2022. "Datasets on Energy Simulations of Standard and Optimized Buildings under Current and Future Weather Conditions across Europe," Data, MDPI, vol. 7(5), pages 1-18, May.

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