Decision-support tool for prioritizing retrofitting actions on Social Housing stock in Italy

Authors

  • Jacopo Gaspari University of Bologna, Department of Architecture, Viale del Risorgimento 2, 40136 Bologna, Italy
  • Ernesto Antonini University of Bologna, Department of Architecture, Viale del Risorgimento 2, 40136 Bologna, Italy
  • Lia Marchi University of Bologna, Department of Architecture, Viale del Risorgimento 2, 40136 Bologna, Italy

DOI:

https://doi.org/10.14311/APP.2022.38.0097

Keywords:

retrofitting, social housing, decision-support tool, energy efficiency

Abstract

Housing is the main environmental impact generator (62 %) of the whole building sector, but it also has the greatest reduction potential. Enhancing its performance is thus crucial to sustainable development. Social Housing (SH) represents a critical asset within the residential segment, due to the recurrent investment shortage and several environmental, social, and economic related implications. In Italy, SH is held by around one hundred public agencies facing endemic resource constraints for both maintenance and retrofitting, which are limited further by a diffused lack of information regarding the conditions and features of the buildings they manage. In cooperation with an Italian SH agency (ACER Bologna), we developed a speedy tool to compare the technical and economic effects of different refurbishment scenarios on a case-by-case basis. This is not a tool to manage retrofitting works, as the many already available, but a means to help large housing managers overcome the intention-action gap that limit their capacity to properly prioritize interventions based on reliable information. The research focuses on the validation of the fast procedure for estimating the baseline energy scenario, arguing that the relatively small inaccuracies are irrelevant for the scope of the tool and are compensated for by the time saved.

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Published

2022-12-21

How to Cite

Decision-support tool for prioritizing retrofitting actions on Social Housing stock in Italy. (2022). Acta Polytechnica CTU Proceedings, 38, 97-103. https://doi.org/10.14311/APP.2022.38.0097