Designing a qualitative pre-diagnosis model for the evaluation of radon potential in indoor environments

• Main Author: Silva, Joaquim P.
• Publication Date: 2023
• Other Authors: Lopes, Nuno, Curado, António, Nunes, Leonel J R, Lopes, Sérgio I
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/11110/3211; https://doi.org/Silva, J.P., Lopes, N., Curado, A., Nunes, L.J.R., Lopes, S.I. (2023). Designing a Qualitative Pre-diagnosis Model for the Evaluation of Radon Potential in Indoor Environments. In: Caetano, N.S., Felgueiras, M.C. (eds) The 9th International Conference on Energy and Environment Research. ICEER 2022. Environmental Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-43559-1_9
• topic: Indoor radon assessment; Radon performance indicator; Radon potential; Energy efficiency

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. Hence, a practical methodology for variable selection based on an analysis of historic data plays a key role concerning radon potential assessment. 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 Indoor Air Quality (IAQ), mainly concerning local geology, built environment performance, 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.