A digital platform for heatwave vulnerability assessment in non-air-conditioned residential buildings: Lyon Metropolis case study

Climate change is intensifying heat waves, making them longer, more frequent, and more severe In the dwellings that are not equipped with air conditioning, the risk of exposures to thermal stress in will increase, potentially leading to discomfort and even health issues.

The level of thermal stress experienced by occupants in residential buildings results from a multitude of factors, which can be categorized as apartment-specific, urban context-related, weather-induced, and occupant-behavior-dependent.

The very large number of factors induces a very large number of simulations if all the possible combinations have to be explored. Hence, it requires the implementation of an appropriate simulation platform and statistical tools to characterize risk situations, that is to say, to identify the factors having a major influence on exposure levels and their interactions. These platforms could also be used to evaluate the disparities in performance of passive cooling solutions on a varied building stock. Case studies in the literature always limit their scope by focusing on a narrow range of parameters, such as building typology, occupant behaviour, or weather conditions.

This contribution presents a digital platform, DEB (Design of Experiment for Building) designed to automate large numbers of simulations, varying many factors and the statistical methods for analysing the results. DEB leverages the Urban Thermal Tool Chain (Toesca et al., 2022a) to conduct simulations using Urban Weather Generator, Energy Plus, and UrbaWind. The digital platform is fed with a set of apartment samples, a set of urban contexts archetypes, a database of representative future heatwaves (Toesca et al., 2022b) and a collection of occupant behaviours. The set of apartment samples and the set of urban context archetypes should collectively represent a large majority of the real-world scenarios prevalent in the target area.

A small-scale case study was conducted to demonstrate the functionality of the platform and illustrate the types of results that can be achieved. The case describes the specific application of the platform to quantify the impact of non-compliance with recommended behavior during heat waves on night-time comfort. A set of 70 apartments was sampled, representative of the collective housing stock of the Grand Lyon Metropolis (France). 2 heatwaves and 4 occupant behaviours were tested. While the significance of night-time natural ventilation and day-time solar protection are evident, the substantial variation in occupant behavior’s influence across different apartment typologies is underscored.