IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v146y2020ics0301421520305322.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421520305322
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2020.111814?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Schleich, Joachim & Gassmann, Xavier & Faure, Corinne & Meissner, Thomas, 2016. "Making the implicit explicit: A look inside the implicit discount rate," Energy Policy, Elsevier, vol. 97(C), pages 321-331.
    2. Michelsen, Carl Christian & Madlener, Reinhard, 2012. "Homeowners' preferences for adopting innovative residential heating systems: A discrete choice analysis for Germany," Energy Economics, Elsevier, vol. 34(5), pages 1271-1283.
    3. Kranzl, Lukas & Hummel, Marcus & Müller, Andreas & Steinbach, Jan, 2013. "Renewable heating: Perspectives and the impact of policy instruments," Energy Policy, Elsevier, vol. 59(C), pages 44-58.
    4. Pettifor, H. & Wilson, C. & Chryssochoidis, G., 2015. "The appeal of the green deal: Empirical evidence for the influence of energy efficiency policy on renovating homeowners," Energy Policy, Elsevier, vol. 79(C), pages 161-176.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    6. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
    7. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    8. Jonas Friege & Georg Holtz & Emile Chappin, 2016. "Exploring Homeowners’ Insulation Activity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-4.
    9. Heeren, Niko & Jakob, Martin & Martius, Gregor & Gross, Nadja & Wallbaum, Holger, 2013. "A component based bottom-up building stock model for comprehensive environmental impact assessment and target control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 45-56.
    10. Majcen, D. & Itard, L.C.M. & Visscher, H., 2013. "Theoretical vs. actual energy consumption of labelled dwellings in the Netherlands: Discrepancies and policy implications," Energy Policy, Elsevier, vol. 54(C), pages 125-136.
    11. Mastrucci, Alessio & Marvuglia, Antonino & Leopold, Ulrich & Benetto, Enrico, 2017. "Life Cycle Assessment of building stocks from urban to transnational scales: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 316-332.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    2. Claudio Nägeli & Liane Thuvander & Holger Wallbaum & Rebecca Cachia & Sebastian Stortecky & Ali Hainoun, 2022. "Methodologies for Synthetic Spatial Building Stock Modelling: Data-Availability-Adapted Approaches for the Spatial Analysis of Building Stock Energy Demand," Energies, MDPI, vol. 15(18), pages 1-18, September.
    3. Cremer, Leo & Weber, Christine, 2022. "Deep energy retrofits: How effective and robust are policy instruments?," Energy Policy, Elsevier, vol. 170(C).
    4. D'Agostino, D. & Parker, D. & Epifani, I. & Crawley, D. & Lawrie, L., 2022. "How will future climate impact the design and performance of nearly zero energy buildings (NZEBs)?," Energy, Elsevier, vol. 240(C).
    5. 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).
    6. 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).
    7. 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).
    8. Côté, Elizabeth & Pons-Seres de Brauwer, Cristian, 2023. "Preferences of homeowners for heat-pump leasing: Evidence from a choice experiment in France, Germany, and Switzerland," Energy Policy, Elsevier, vol. 183(C).
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Knobloch, Florian & Pollitt, Hector & Chewpreecha, Unnada & Lewney, Richard & Huijbregts, Mark A.J. & Mercure, Jean-Francois, 2021. "FTT:Heat — A simulation model for technological change in the European residential heating sector," Energy Policy, Elsevier, vol. 153(C).
    2. Yang, Xining & Hu, Mingming & Heeren, Niko & Zhang, Chunbo & Verhagen, Teun & Tukker, Arnold & Steubing, Bernhard, 2020. "A combined GIS-archetype approach to model residential space heating energy: A case study for the Netherlands including validation," Applied Energy, Elsevier, vol. 280(C).
    3. Dieckhoener, Caroline & Hecking, Harald, 2012. "Greenhouse Gas Abatement Cost Curves of the Residential Heating Market – a Microeconomic Approach," EWI Working Papers 2012-16, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    4. Mastrucci, Alessio & Marvuglia, Antonino & Benetto, Enrico & Leopold, Ulrich, 2020. "A spatio-temporal life cycle assessment framework for building renovation scenarios at the urban scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    5. Caroline Löffler & Harald Hecking, 2017. "Greenhouse Gas Abatement Cost Curves of the Residential Heating Market: A Microeconomic Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(4), pages 915-947, December.
    6. Franceschinis, Cristiano & Thiene, Mara & Scarpa, Riccardo & Rose, John & Moretto, Michele & Cavalli, Raffaele, 2017. "Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory," Energy, Elsevier, vol. 125(C), pages 313-326.
    7. Bischof, Julian & Duffy, Aidan, 2022. "Life-cycle assessment of non-domestic building stocks: A meta-analysis of current modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    8. Chappin, Emile J.L. & Schleich, Joachim & Guetlein, Marie-Charlotte & Faure, Corinne & Bouwmans, Ivo, 2022. "Linking of a multi-country discrete choice experiment and an agent-based model to simulate the diffusion of smart thermostats," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    9. Michelsen, Carl Christian & Madlener, Reinhard, 2016. "Switching from fossil fuel to renewables in residential heating systems: An empirical study of homeowners' decisions in Germany," Energy Policy, Elsevier, vol. 89(C), pages 95-105.
    10. Florian Knobloch & Hector Pollitt & Unnada Chewpreecha & Vassilis Daioglou & Jean-Francois Mercure, 2017. "Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C," Papers 1710.11019, arXiv.org, revised May 2018.
    11. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
    12. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    13. Walker, Joan L. & Chatman, Daniel & Daziano, Ricardo & Erhardt, Gregory & Gao, Song & Mahmassani, Hani & Ory, David & Sall, Elizabeth & Bhat, Chandra & Chim, Nicholas & Daniels, Clint & Gardner, Brian, 2019. "Advancing the Science of Travel Demand Forecasting," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0v1906ts, Institute of Transportation Studies, UC Berkeley.
    14. Schleich, Joachim & Faure, Corinne & Meissner, Thomas, 2021. "Adoption of retrofit measures among homeowners in EU countries: The effects of access to capital and debt aversion," Energy Policy, Elsevier, vol. 149(C).
    15. Meles, Tensay Hadush & Ryan, Lisa & Mukherjee, Sanghamitra C., 2022. "Heterogeneity in preferences for renewable home heating systems among Irish households," Applied Energy, Elsevier, vol. 307(C).
    16. Mastrucci, Alessio & Marvuglia, Antonino & Leopold, Ulrich & Benetto, Enrico, 2017. "Life Cycle Assessment of building stocks from urban to transnational scales: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 316-332.
    17. Kaandorp, Chelsea & Miedema, Tes & Verhagen, Jeroen & van de Giesen, Nick & Abraham, Edo, 2022. "Reducing committed emissions of heating towards 2050: Analysis of scenarios for the insulation of buildings and the decarbonisation of electricity generation," Applied Energy, Elsevier, vol. 325(C).
    18. Olsthoorn, Mark & Schleich, Joachim & Faure, Corinne, 2019. "Exploring the diffusion of low-energy houses: An empirical study in the European Union," Energy Policy, Elsevier, vol. 129(C), pages 1382-1393.
    19. Zhu, Tong & Curtis, John & Clancy, Matthew, 2023. "Modelling barriers to low-carbon technologies in energy system analysis: The example of renewable heat in Ireland," Applied Energy, Elsevier, vol. 330(PA).
    20. Achtnicht, Martin & Madlener, Reinhard, 2014. "Factors influencing German house owners' preferences on energy retrofits," Energy Policy, Elsevier, vol. 68(C), pages 254-263.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:146:y:2020:i:c:s0301421520305322. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.