Evaluation of one-dimensional model of C-14 atmospheric transport in vegetated canopies.

The evaluation of the previously developed one-dimensional model of radiocarbon atmospheric transport in vegetated canopies against C-14 concentration data collected at the site of SMEAR-II research station was presented. In most cases, the simulated vertical profiles of C-14 concentrations within the canopy layer agreed reasonably with measurements, the correlation coefficient of simulated vs. observed concentrations was 0.72. The developed model could be used to evaluate vertical variations of C-14 concentrations in vegetated canopy layers.

Adaptation of the RODOS system for analysis of possible sources of Ru-106 detected in 2017.

In this work, we present a method to use the European nuclear emergency response system RODOS for analysis of potential sources of airborne radioactivity of an unknown origin. The method is based on a solution of adjoint equations, without modification of the code of long-range atmospheric dispersion model MATCH used in RODOS. The method has been successfully applied to the Ru-106 accident of 2017. The obtained spatial distribution of the correlation between simulations and measurements which could be achieved with source located in a given place, is in a qualitative agreement with analogous results published in other works. The high correlation is centered on the Ural Mountains; this is explained by a very wide expansion of the plume. However, the location of the maximum correlation obtained in this work is in the northern part of Russia, close to a military test site on Novaya Zemlya. This location is far away from the reprocessing plant Mayak in the South-Eastern Urals mentioned in other investigations as the most probable location of the source. In the results presented here, the correlation at the source location corresponding to the Mayak plant is still quite high (0.49); release inventory from this source of about 300 TBq could explain the observed measurements.

Source reconstruction of airborne toxics based on acute health effects information.

The intentional or accidental release of airborne toxics poses great risk to the public health. During these incidents, the greatest factor of uncertainty is related to the location and rate of released substance, therefore, an information of high importance for emergency preparedness and response plans. A novel computational algorithm is proposed to estimate, efficiently, the location and release rate of an airborne toxic substance source based on health effects observations; data that can be readily available, in a real accident, contrary to actual measurements. The algorithm is demonstrated by deploying a semi-empirical dispersion model and Monte Carlo sampling on a simplified scenario. Input data are collected at varying receptor points for toxics concentrations (C; standard approach) and two new types: toxic load (TL) and health effects (HE; four levels). Estimated source characteristics are compared with scenario values. The use of TL required the least number of receptor points to estimate the release rate, and demonstrated the highest probability (>90%). HE required more receptor points, than C, but with lesser deviations while probability was comparable, if not better. Finally, the algorithm assessed very accurately the source location when using C and TL with comparable confidence, but HE demonstrated significantly lower confidence.

Atmospheric dispersion of radon around uranium mill tailings of the former Pridneprovsky Chemical Plant in Ukraine.

Simulations of atmospheric dispersion of radon around the uranium mill tailings of the former Pridneprovsky Chemical Plant (PChP) in Ukraine were carried out with the aid of two atmospheric dispersion models: the Airviro Grid Model and the CALMET/CALPUFF model chain. The available measurement data of radon emission rates taken in the territories and the close vicinity of tailings were used in simulations. The results of simulations were compared to the yearly averaged measurements of concentration data. Both models were able to reasonably reproduce average radon concentration at the Sukhachivske site using averaged measured emission rates as input together with the measured meteorological data. At the same time, both models significantly underestimated concentrations as compared to measurements collected at the PChP industrial site. According to the results of both dispersion models, it was shown that only addition of significant radon emission rate from the whole territory of PChP in addition to emission rates from the tailings could explain the observed concentration measurements. With the aid of the uncertainty analysis, the radon emission rate from the whole territory of PChP was estimated to be between 1.5 and 3.5 Bq·m-2s-1.