Radioecological modelling of Polonium-210 and Caesium-137 in lichen-reindeer-man and top predators

• Published in: Journal of Environmental Radioactivity
• Main Authors: Persson, Bertil R.R., Gjelsvik, Runhild, Holm, Elis
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2018
• Subjects: Environmental Sciences; Environmental Health and Occupational Health; Other Physics Topics; Caesium-137; Lichen; Lynx; Man; Modelling; Partial least square regression PLSR; Polonium-210; Principal component analysis PCA; Reindeer; Reindeer herder; Wolf; Wolverine; Reindeer lichen
• Online Access: https://lup.lub.lu.se/record/71ef50f4-fe33-4d4d-83cc-1297d8e15aee; https://doi.org/10.1016/j.jenvrad.2017.08.006

This work deals with analysis and modelling of the radionuclides 210Pb and210Po in the food-chain lichen-reindeer-man in addition to 210Po and 137Cs in top predators. By using the methods of Partial Least Square Regression (PLSR) the atmospheric deposition of 210Pb and 210Po is predicted at the sample locations. Dynamic modelling of the activity concentration with differential equations is fitted to the sample data. Reindeer lichen consumption, gastrointestinal absorption, organ distribution and elimination is derived from information in the literature. Dynamic modelling of transfer of 210Pb and 210Po to reindeer meat, liver and bone from lichen consumption, fitted well with data from Sweden and Finland from 1966 to 1971. The activity concentration of 210Pb in the skeleton in man is modelled by using the results of studying the kinetics of lead in skeleton and blood in lead-workers after end of occupational exposure. The result of modelling 210Pb and 210Po activity in skeleton matched well with concentrations of 210Pb and 210Po in teeth from reindeer-breeders and autopsy bone samples in Finland.The results of 210Po and 137Cs in different tissues of wolf, wolverine and lynx previously published, are analysed with multivariate data processing methods such as Principal Component Analysis PCA, and modelled with the method of Projection to Latent Structures, PLS, or Partial Least Square Regression PLSR.