4.4 Article

Multivariate statistical analysis of radiological data of building materials used in Tiruvannamalai, Tamilnadu, India

Journal

APPLIED RADIATION AND ISOTOPES
Volume 85, Issue -, Pages 114-127

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.apradiso.2013.12.005

Keywords

Natural radioactivity; Building materials; Gamma-ray spectrometry; Radiological hazard; Statistical approach

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Using gamma spectrometry, the concentration of the naturally occurring radionuclides Ra-226, Th-232 and K-40 has been measured in soil, sand, cement, clay and bricks, which are used as building materials in Tiruvannamalai, Tamilnadu, India. The radium equivalent activity (Ra-eq), the criterion formula (CF), indoor gamma absorbed dose rate (D-R), annual effective dose (H-R), activity utilization index (AUI), alpha index (I-alpha) gamma index (I-gamma), external radiation hazard index (H-ex), internal radiation hazard index (H-in), representative level index (RLI), excess lifetime cancer risk (ELCR) and annual gonadal dose equivalent (AGDE) associated with the natural radionuclides are calculated to assess the radiation hazard of the natural radioactivity in the building materials. From the analysis, it is found that these materials used for the construction of dwellings are safe for the inhabitants. The radiological data were processed using multivariate statistical methods to determine the similarities and correlation among the various samples. The frequency distributions for all radionuclides were analyzed. The data set consisted of 15 measured variables. The Pearson correlation coefficient reveals that the Ra-226 distribution in building materials is controlled by the variation of the K-40 concentration. Principal component analysis (PCA) yields a two-component representation of the acquired data from the building materials in Tiruvannamalai, wherein 94.9% of the total variance is explained. The resulting dendrogram of hierarchical cluster analysis (HCA) classified the 30 building materials into four major groups using 15 variables. (C) 2013 Elsevier Ltd. All rights reserved.

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