Abstract: A known relationship exists between high radon concentrations and lung cancer, and therefore, the indoor radon quantification is important, and it is beneficial to have a model to estimate indoor concentration. The work is focused on the development of an INDORAD (INDOor RAdon Dynamic) model for estimation of indoor radon dynamics, with time-dependent meteorological parameters and adjustable soil and building properties being considered. This model is based on a systemic approach, where the flows of material between compartments are considered, without a spatial resolution. This approach allowed to simplify the mathematical processing and enabled to consider together all known sources of indoor radon. The developed model was put in use in a laboratory building where soil constitutes major source of radon. The results (radon concentrations) from the model were compared to an existing data set from Saelices el Chico in a soil with high concentration of 226Ra. The outcome of the validation implies that INDORAD could predict radon concentrations satisfactorily. Suggestions for future updates of the model to improve indoor radon estimations are provided.

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