Dose Estimation Model for Terminal Buds in Radioactively Contaminated Fir Trees

Abstract

Background: After the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, biological alterations in the natural biota, including morphological changes of fir trees in forests surrounding the power plant, have been reported. Focusing on the terminal buds involved in the morphological formation of fir trees, this study developed a method for estimating the absorbed radiation dose rate using radionuclide distribution measurements from tree organs.Materials and Methods: A phantom composed of three-dimensional (3D) tree organs was constructed for the three upper whorls of the fir tree. A terminal bud was evaluated using Monte Carlo simulations for the absorbed dose rate of radionuclides in the tree organs of the whorls. Evaluation of the absorbed dose targeted 131I, 134Cs, and 137Cs, the main radionuclides subsequent to the FDNPP accident. The dose contribution from each tree organ was calculated separately using dose coefficients (DC), which express the ratio between the average activity concentration of a radionuclide in each tree organ and the dose rate at the terminal bud.Results and Discussion: The dose estimation indicated that the radionuclides in the terminal bud and bud scale contributed to the absorbed dose rate mainly by beta rays, whereas those in 1-year-old trunk/branches and leaves were contributed by gamma rays. However, the dose contribution from radionuclides in the lower trunk/branches and leaves was negligible.Conclusion: The fir tree model provides organ-specific DC values, which are satisfactory for the practical calculation of the absorbed dose rate of radiation from inside the tree. These calculations are based on the measurement of radionuclide concentrations in tree organs on the 1-year-old leader shoots of fir trees. With the addition of direct gamma ray measurements of the absorbed dose rate from the tree environment, the total absorbed dose rate was estimated in the terminal bud of fir trees in contaminated forests.