Statistical analysis for 134Cs and 137Cs radioactivity risk levels modeling

After the Fukushima Dai-Ichi Nuclear Power Plant (FDNPP) accident, 134 Cs and 137 Cs were spread widely into the environment. Spatial distribution maps giving radiocesium activities in contaminated soils for post-accident risk modeling were obtained using the Kriging method. We used Generalized extr...

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Bibliographic Details
Published inJournal of radioanalytical and nuclear chemistry Vol. 326; no. 2; pp. 1047 - 1064
Main Authors Bilici, Ahmet, Bilici, Sevim, Külahcı, Fatih
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 2020
Springer Nature B.V
Subjects
Cesium 134
Cesium 137
Cesium isotopes
Chemistry
Chemistry and Materials Science
Diagnostic Radiology
Distribution functions
Extreme values
Hadrons
Heavy Ions
Inorganic Chemistry
Modelling
Nuclear accidents
Nuclear Chemistry
Nuclear Physics
Nuclear power plants
Physical Chemistry
Radioactivity
Risk assessment
Risk levels
Soil contamination
Spatial distribution
Statistical analysis
Probability distribution function
Risk analysis
Modeling
Kriging
Distribution functions
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Summary:After the Fukushima Dai-Ichi Nuclear Power Plant (FDNPP) accident, 134 Cs and 137 Cs were spread widely into the environment. Spatial distribution maps giving radiocesium activities in contaminated soils for post-accident risk modeling were obtained using the Kriging method. We used Generalized extreme-value distribution, Lognormal probability distribution (PDF) and Weibull PDFs for risk assessment of the data. Root mean square error values and coefficient of determination ( R 2 ) were calculated for each distribution function. Weibull PDF was found to be more successful in modeling 134 Cs and 137 Cs activities. Graphic abstract
ISSN:0236-5731
1588-2780
DOI:10.1007/s10967-020-07399-9