Currently, people spend most of their time inside their homes. However, poor conditions in terms of comfort and quality of the indoor environment can pose high risks to the inhabitants’ health. Therefore, a good quality environment is essential, since, in addition to the
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Currently, people spend most of their time inside their homes. However, poor conditions in terms of comfort and quality of the indoor environment can pose high risks to the inhabitants’ health. Therefore, a good quality environment is essential, since, in addition to the hazards present in indoor air (e.g., particles, (S)VOCs, CO, radon and tobacco smoke), extreme temperatures, relative humidity levels, pests (e.g., mold, dust mites and bioaerosols), noise, airborne infectious agents (e.g., SARS-CoV-2) and contamination through water and soil can cause physical injuries, respiratory diseases, damage to multiple organ systems as well as harmful effects on the mental health of the occupants. Faced with this requirement, housing evaluation models were studied together with the main types of risk that could affect the health of the inhabitants, with the objective of proposing a new evaluation model for housing health and safety risks, fitted to the occupants, and especially suitable for Portuguese dwellings, although applicable in other geographical contexts. As a result of this analysis, this article proposes a new model for evaluating health and safety risks in housing, applicable in Portugal, supported by an inspection form and, as the main difference from the existing models, parameter measurements, providing complementary data for the evaluation. This model was created based on a set of functional and regulatory requirements that were identified for the healthy use of living spaces. Twenty-eight hazards were identified, and the respective risk factors were assessed using different processes and target demographics, including visual inspection, parameter measurements, occupants’ age and location and age of housing. In order to validate the model and determine its usefulness, it was applied to a set of houses with different construction dates, locations and occupants. This exercise enabled the identification of hazard classes and the calibration and fine tuning of the model application. Finally, proposals for future work are presented in order to create a base of evolution for the model.