Literature DB >> 20022149

An approach to improve the Austrian Radon Potential Map by Bayesian statistics.

Harry Friedmann1, Joulieta Gröller.   

Abstract

A Radon Potential Map as well as a mean indoor Radon Concentration Map is available from the Austrian National Radon Project (1992-2002). These maps are based on the average Radon Potential/Concentration within every municipality and they sort municipalities into three radon 'risk' classes. This is a convenient way for the administration, but it does not describe the real radon risk distribution within a municipality because of the often inhomogeneous geological situation. Therefore, a combination of indoor radon data with all relevant parameters such as house type, storey and ventilation rates along with geological information should be used to improve the existing radon maps. The method, described here, uses Bayes' theory to combine the Radon Potential derived from indoor radon measurements with information from geology. The existing Radon Potential Map was improved by using available soil gas radon data at certain geological units and extrapolated transfer factors. The modifications of the map are shown and several problems arising with the application of this technique are discussed. Copyright 2009 Elsevier Ltd. All rights reserved.

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Year:  2009        PMID: 20022149     DOI: 10.1016/j.jenvrad.2009.11.008

Source DB:  PubMed          Journal:  J Environ Radioact        ISSN: 0265-931X            Impact factor:   2.674


  2 in total

1.  The use of gamma-survey measurements to better understand radon potential in urban areas.

Authors:  Andrew S Berens; Jeremy Diem; Christine Stauber; Dajun Dai; Stephanie Foster; Richard Rothenberg
Journal:  Sci Total Environ       Date:  2017-07-27       Impact factor: 7.963

2.  Mapping radon hazard areas using 238U measurements and geological units: a study in a high background radiation city of China.

Authors:  Hongtao Liu; Nanping Wang; Xingming Chu; Ting Li; Ling Zheng; Shouliang Yan; Shijun Li
Journal:  J Radioanal Nucl Chem       Date:  2016-02-23       Impact factor: 1.371

  2 in total

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