A pre-diagnosis model for radon potential evaluation in buildings: A tool for balancing ventilation, indoor air quality and energy efficiency

• Autor(a) principal: Silva, Joaquim
• Data de Publicação: 2022
• Outros Autores: Lopes, Nuno, Curado, António, Nunes, Leonel J R, Lopes, Sérgio Ivan
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/11110/3199; https://doi.org/Joaquim Silva, Nuno Lopes, António Curado, Leonel J.R. Nunes, Sérgio I. Lopes, A pre-diagnosis model for radon potential evaluation in buildings: A tool for balancing ventilation, indoor air quality and energy efficiency, Energy Reports, Volume 8, Supplement 3, 2022, Pages 539-546, ISSN 2352-4847, https://doi.org/10.1016/j.egyr.2022.02.100.
• topic: Indoor radon assessment; Radon performance indicator; Radon potential; Energy efficiency; Energy performance; Energy equipment; Ventilation; Indoor air quality

In a very early stage of implementation of a comprehensive experimental campaign for indoor radon assessment, a pre-evaluation selection of the variables that play a leading role in influencing expected results must be insightfully assessed, by stimulating compatibility between Indoor Air Quality (IAQ) and energy efficiency. Hence, a practical methodology for variable selection based on an analysis of historic data plays a key role concerning radon potential assessment, while never losing sight of the building energy performance. Given the circumstances, this work is focused on the design of a qualitative pre-diagnosis model for the evaluation of radon potential in indoor environments, for different energy efficiency scenarios, by considering a set of relevant variables carefully selected to characterize occupants’ risk exposure. A prior survey was done to identify all relevant characteristics that most affect both Indoor Air Quality (IAQ) and building energy efficiency, mainly concerning local geology, thermal insulation, ventilation schemes, energy equipment, renewable energy assets, and occupancy schedules. The selected parameters will be afterward weighted and combined into performance indicators through an evidence-based literature review. In the current early stage, the requirements to drive the software development are presented, together with a software architecture proposal. Finally, it is expected that this pre-diagnosis model will allow a more refined sample selection for indoor radon assessment, by choosing the most susceptible variables that influence radon potential in a given scenario and making it compatible with the building energy efficiency.