Assessing the level of adaptation to heat waves in Parisian housing

The paper introduces an approach for assessing the resilience of buildings to both current heat waves and their recurrence in the future under the impact of climate change. The method, applied to the 60,000 dwellings of the RIVP (Régie Immobilière de la Ville de Paris), the second-largest social landlord in Paris, aims to provide reliable information to enable the buildings’ owner to assess the heat-related health risk for the tenants and the actions to be taken to decrease it. To this end, it provides them with a quantifiable indicator, the probability of risk occurrence, to enable them to decide which adaptation pathways are suitable based on a cost-benefit balance. 
Upon defining the study's scope, the method defines faultless performance criteria for dwellings, set here at operative temperatures below 27°C and 30°C at night-time and daytime respectively. Subsequently, it identifies the climatic sequences that make the dwellings faulty and finally quantifies their recurrence across present, near-future (2040), and distant-future (2080) scenarios. 
By applying the method, dwellings are classified into three categories based on the number of times the climatic sequences that deteriorate the apartments’ thermal performance are exceeded over a given period: those in which these boundary conditions are exceeded once every ten years or less, less than once a year, and more than once a year. 
In addition to this classification, the study highlights the substantial benefits of thermal insulation and window solar protection and emphasizes the critical importance of opening windows at night to reduce indoor temperature. Despite the significant impact of employing passive solutions, the results indicate that maintaining nighttime temperature thresholds remains challenging due to difficulties in heat evacuation exacerbated by rising outdoor temperatures caused by global warming. Looking ahead, this method may find application in diverse contexts and urban settings.