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dc.contributor.authorDvorzhak, Allaes_ES
dc.contributor.authorMora, Juan Carloses_ES
dc.contributor.authorReal, Almudenaes_ES
dc.contributor.authorSainz Fernández, Carlos es_ES
dc.contributor.authorFuente Merino, Ismael es_ES
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2024-01-24T10:47:09Z
dc.date.available2024-01-24T10:47:09Z
dc.date.issued2021es_ES
dc.identifier.issn0944-1344es_ES
dc.identifier.issn1614-7499es_ES
dc.identifier.urihttps://hdl.handle.net/10902/31216
dc.description.abstractA 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.es_ES
dc.description.sponsorshipThis research was supported by the CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Environmental Department, Unit of Radiation Protection for the Public and the Environment.
dc.format.extent11 p.es_ES
dc.language.isoenges_ES
dc.publisherSpringer Science + Business Mediaes_ES
dc.rightsAlojado según Resolución CNEAI 5/12/23 (ANECA)es_ES
dc.rights© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021
dc.sourceEnvironmental Science and Pollution Research, 2021, 28(38), 54085-54095es_ES
dc.subject.otherRadon modelling
dc.subject.otherRadon in buildings
dc.subject.otherINDORAD
dc.titleGeneral model for estimation of indoor radon concentration dynamicses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1007/s11356-021-14422-3es_ES
dc.rights.accessRightsclosedAccess
dc.identifier.DOI10.1007/s11356-021-14422-3es_ES
dc.type.versionpublishedVersiones_ES


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