Articles | Volume 19, issue 11
https://doi.org/10.5194/nhess-19-2451-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-19-2451-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
05 Nov 2019
Research article | Highlight paper |
| 05 Nov 2019
| 05 Nov 2019
The first version of the Pan-European Indoor Radon Map
Javier Elío
Centre for the Environment, Trinity College, Dublin, Ireland
Giorgia Cinelli
CORRESPONDING AUTHOR
European Commission, Joint Research Centre (JRC), Ispra, Italy
Peter Bossew
German Federal Office for Radiation Protection, Berlin, Germany
José Luis Gutiérrez-Villanueva
Radonova Laboratories AB, Uppsala, Sweden
Tore Tollefsen
European Commission, Joint Research Centre (JRC), Ispra, Italy
Marc De Cort
European Commission, Joint Research Centre (JRC), Ispra, Italy
Alessio Nogarotto
Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Università di Bologna, Bologna, Italy
Roberto Braga
Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Università di Bologna, Bologna, Italy
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Cited
21 citations as recorded by crossref.
- Estimation of the Radon Risk Under Different European Climates and Soil Textures S. Gil-Oncina et al. 10.3389/fpubh.2022.794557
- Estimated versus field measured soil gas radon concentration and soil gas permeability S. Beltrán-Torres et al. 10.1016/j.jenvrad.2023.107224
- Radon risk mapping: A new geostatistical method based on Lorenz Curve and Gini index F. Loffredo et al. 10.1016/j.jenvrad.2021.106612
- Radon prevalence in domestic water in the Ría de Vigo coastal basin (NW Iberian Peninsula) J. Ibánhez et al. 10.1007/s11356-023-27305-6
- Mapping indoor radon hazard in Germany: The geogenic component E. Petermann & P. Bossew 10.1016/j.scitotenv.2021.146601
- Machine learning in environmental radon science J. Elío et al. 10.1016/j.apradiso.2023.110684
- Predictive Geogenic Radon Potential (P-GRP): A novel approach for comprehensive hazard assessment and risk modeling in subsurface environment Y. Choi et al. 10.1016/j.scitotenv.2024.173721
- Radon variability due to floor level in two typical residential buildings in Serbia V. Udovicic et al. 10.2478/nuka-2020-0019
- Determination of optimal ventilation rates in educational environment in terms of radon dosimetry M. Dovjak et al. 10.1016/j.ijheh.2021.113742
- Radon Adsorption in Charcoal A. Maier et al. 10.3390/ijerph18094454
- Methodology for determination of radon prone areas combining the definition of a representative building enclosure and measurements of terrestrial gamma radiation C. Briones et al. 10.1016/j.scitotenv.2021.147709
- Development of a Geogenic Radon Hazard Index—Concept, History, Experiences P. Bossew et al. 10.3390/ijerph17114134
- Applying machine learning to model radon using topsoil geochemistry M. Banríon et al. 10.1016/j.apgeochem.2023.105790
- Estimation of Indoor 222Rn Concentration in Lima, Peru Using LR-115 Nuclear Track Detectors Exposed in Different Modes P. Pereyra et al. 10.3390/atmos14060952
- Distribution of soil gas radon concentration in north-eastern Sicily (Italy): hazard evaluation and tectonic implications D. Romano et al. 10.1007/s12665-023-10956-6
- Indoor radon interval prediction in the Swedish building stock using machine learning P. Wu et al. 10.1016/j.buildenv.2023.110879
- Weather control in radon flux time series from Schleswig-Holstein, Germany M. Mudelsee et al. 10.1007/s13137-020-00156-w
- Comparative analysis of water condensate porosity using mercury intrusion porosimetry and nitrogen and water adsorption techniques in porous building stones D. Benavente et al. 10.1016/j.conbuildmat.2021.123131
- Overview of Radon Flux Characteristics, Measurements, Models and Its Potential Use for the Estimation of Radon Priority Areas I. Čeliković et al. 10.3390/atmos13122005
- RadonPotential: An interactive web application for radon potential prediction under different climates and soil textures J. Galiana-Merino et al. 10.1007/s12145-024-01311-9
- The Geographical Pattern of Local Statistical Dispersion of Environmental Radon in Europe P. Bossew 10.1007/s11004-023-10073-x
20 citations as recorded by crossref.
- Estimation of the Radon Risk Under Different European Climates and Soil Textures S. Gil-Oncina et al. 10.3389/fpubh.2022.794557
- Estimated versus field measured soil gas radon concentration and soil gas permeability S. Beltrán-Torres et al. 10.1016/j.jenvrad.2023.107224
- Radon risk mapping: A new geostatistical method based on Lorenz Curve and Gini index F. Loffredo et al. 10.1016/j.jenvrad.2021.106612
- Radon prevalence in domestic water in the Ría de Vigo coastal basin (NW Iberian Peninsula) J. Ibánhez et al. 10.1007/s11356-023-27305-6
- Mapping indoor radon hazard in Germany: The geogenic component E. Petermann & P. Bossew 10.1016/j.scitotenv.2021.146601
- Machine learning in environmental radon science J. Elío et al. 10.1016/j.apradiso.2023.110684
- Predictive Geogenic Radon Potential (P-GRP): A novel approach for comprehensive hazard assessment and risk modeling in subsurface environment Y. Choi et al. 10.1016/j.scitotenv.2024.173721
- Radon variability due to floor level in two typical residential buildings in Serbia V. Udovicic et al. 10.2478/nuka-2020-0019
- Determination of optimal ventilation rates in educational environment in terms of radon dosimetry M. Dovjak et al. 10.1016/j.ijheh.2021.113742
- Radon Adsorption in Charcoal A. Maier et al. 10.3390/ijerph18094454
- Methodology for determination of radon prone areas combining the definition of a representative building enclosure and measurements of terrestrial gamma radiation C. Briones et al. 10.1016/j.scitotenv.2021.147709
- Development of a Geogenic Radon Hazard Index—Concept, History, Experiences P. Bossew et al. 10.3390/ijerph17114134
- Applying machine learning to model radon using topsoil geochemistry M. Banríon et al. 10.1016/j.apgeochem.2023.105790
- Estimation of Indoor 222Rn Concentration in Lima, Peru Using LR-115 Nuclear Track Detectors Exposed in Different Modes P. Pereyra et al. 10.3390/atmos14060952
- Distribution of soil gas radon concentration in north-eastern Sicily (Italy): hazard evaluation and tectonic implications D. Romano et al. 10.1007/s12665-023-10956-6
- Indoor radon interval prediction in the Swedish building stock using machine learning P. Wu et al. 10.1016/j.buildenv.2023.110879
- Weather control in radon flux time series from Schleswig-Holstein, Germany M. Mudelsee et al. 10.1007/s13137-020-00156-w
- Comparative analysis of water condensate porosity using mercury intrusion porosimetry and nitrogen and water adsorption techniques in porous building stones D. Benavente et al. 10.1016/j.conbuildmat.2021.123131
- Overview of Radon Flux Characteristics, Measurements, Models and Its Potential Use for the Estimation of Radon Priority Areas I. Čeliković et al. 10.3390/atmos13122005
- RadonPotential: An interactive web application for radon potential prediction under different climates and soil textures J. Galiana-Merino et al. 10.1007/s12145-024-01311-9
1 citations as recorded by crossref.
Latest update: 14 Nov 2024
Short summary
The first version of the Pan-European Indoor Radon Map is presented in this article. The map has been developed using summary statistics estimated from 1.2 million samples. It represents an average radon concentration per 10 km x 10 km grid cell under the assumption that there are dwellings in the grid cell. It is a major contribution to the understanding of the exposure to ionizing radiation of Europeans and a first step towards a European radon exposure and, in the future, radon dose map.
The first version of the Pan-European Indoor Radon Map is presented in this article. The map has...
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