Modelling radioactivity in the Irish Sea: From discharge to dose

In order to support authorised discharges of low level radioactive liquid effluent into coastal regions, mathematical models are required to robustly predict radiological impacts on critical groups of current and proposed changes to liquid discharges. The grid model presented here simulates the long term dispersion and transport of radioactivity discharged from the Sellafield site in Cumbria, UK, and the subsequent exposure of critical groups in Cumbria and across the Irish Sea in Northern Ireland. The fine grid of the model allows a good resolution of the seabed sediment distribution. This benefits the predictions for the last decades of low discharge level, when bed sediment can become a source of contamination by bringing back the legacy of past high discharges. This is highlighted by the dose comparison, where the predicted dose to Cumbria critical group follows well the dose estimated from environmental data during the low discharge level period.     

Liquid discharges from the use of radionuclides in medicine (diagnosis)

The production and discharge of liquid radioactive wastes as excreta from patients undergoing Nuclear Medicine Diagnostic (NMD) in a hospital were studied. Instantaneous and accumulated activity, discharged from the hospital to the sewage system, has been estimated keeping in mind radionuclide decay. This study would enable estimation of the environmental impact due to NMD procedures. Annual accumulated activities of 2.2GBq ((131)I), 1.847GBq ((99m)Tc), 0.743GBq ((123)I), 0.337GBq ((67)Ga), 0.169GBq ((111)In) and 0.033GBq ((201)Tl) result from our model when applied to a European hospital. A comparison is made with calculations by other authors that do not consider the radionuclide decay and who overestimate by two orders of magnitude. Doses to critical people as sewage treatment workers are also significantly reduced. So, our results stress the importance of including the decay in the calculations.     

Investigations of Contaminated Fluvial Sediment Deposits: Merging of Statistical and Geomorphic Approaches

Concentrations of contaminants in sediment deposits can have large spatial variability resulting from geomorphic processes acting over long time periods. Thus, systematic (e.g., regularly spaced sample locations) or random sampling approaches might be inefficient and/or lead to highly biased results. We demonstrate the bias associated with systematic sampling and compare these results to those achieved by methods that merge a geomorphic approach to evaluating the physical system and stratified random sampling concepts. By combining these approaches, we achieve a more efficient and less biased characterization of sediment contamination in fluvial systems. These methods are applied using a phased sampling approach to characterize radiological contamination in sediment deposits in two semiarid canyons that have received historical releases from the Los Alamos National Laboratory. Uncertainty in contaminant inventory was used as a metric to evaluate the adequacy of sampling during these phased investigations. Simple, one-dimensional Monte Carlo simulations were used to estimate uncertainty in contaminant inventory. We also show how one can use stratified random sampling theory to help estimate uncertainty in mean contaminant concentrations.     

Health effects from the nuclear fuel cycle and other sources in perspective

The data base for each process of the nuclear fuel cycle has been updated as a part of the Committee on Nuclear and Alternative Energy Systems (CONAES) at Brookhaven National Laboratory (BNL). The BNL Energy System Network Simulator (ESNS) was modified to accommodate the new data, and methodology was developed for estimating population dose and health effects resulting from atmosphere releases of radioactive materials from the nuclear fuel cycle.Estimates of population dose and health effects were made using these new CONAES emission data and the new model for three scenarios out to the year 2000: (1) no reprocessing; (2) reprocessing, 1-year cooling; and (3) reprocessing, 5-year cooling. Results indicate that radon emissions from mining and milling of uranium bearing ores will have greater impacts than any other component in the open nuclear fuel cycle. The estimated number of health effects will depend, to a large extent, on the lung model mechanism assumed to induce cancer; i.e., either the smeared or the unsmeared model. The smear model and the linear relationship predict for scenario 1, 630; for scenario 2, 949; and for scenario 3, 854 lung cancers, respectively, using the new CONAES data.Epidemiologic data from six United States counties were correlated using a new statistical model (described in the text) in order to test the validity of the lung model and the linear relationship. Results do not support the high lung cancer correlations expected from the unsmear model and the linear relationship; therefore, it is concluded that low-dose mechanisms may be different from those developed from high-dose data. The best place to look for effects of low-dose radiation may be the less developed countries because of a reduction in the noise level caused by chemical pollutants.     

Foliar transfer into the biosphere: review of translocation factors to cereal grains

A review of the published literature about foliar transfer radionuclides to cereal grains was carried out with a special interest for translocation factors. Translocation describes the distribution of radionuclides within the plant after foliar deposition and radionuclide absorption onto the surface of leaves. It mainly depends on elements and the plant growth stage. The collected data were derived from both in-field and greenhouse experiments. They were analysed in order to select those coming from a contamination simulating a sprinkling irrigation or a rain. The data set contains 307 values. For each radionuclide the translocation factor values were sorted according to 5 characteristic stages of the cereal vegetative cycle: leaf development-tillering, stem elongation, earing-flowering, grain growth and ripening. Wheat, barley and rye have been treated together, independently of rice. For mobile elements such as cesium, the translocation factor is maximum when the contamination occurred at the earing-flowering stage. For less mobile elements such as strontium this maximum occurred for a foliar contamination at the grain growth stage. This review enabled us to propose the most probable value as well as the range of variation of translocation factors for some radionuclides according to the cereal vegetative cycle. Moreover, from these results, a radionuclide classification is proposed according to three mobility groups.     

Multi-model approach and evaluation of the uncertainty of model results. Rationale and applications to predict the behaviour of contaminants in the abiotic components of the fresh water environment

This work aims at discussing some concepts pertaining to the theory and practice of environmental modelling in view of the results of several model validation exercises performed by the group “Model validation for radionuclide transport in the system watershed-river and in estuaries” of project EMRAS (Environmental Modelling for Radiation Safety) supported by the IAEA (International Atomic Energy Agency). The analyses here performed concern models applied to real scenarios of environmental contamination. In particular, the reasons for the uncertainty of the models and the EBUA (empirically based uncertainty analysis) methodology are discussed. The foundations of multi-model approach in environmental modelling are presented and motivated. An application of EBUA to the results of a multi-model exercise concerning three models aimed at predicting the wash-off of radionuclide deposits from the Pripyat floodplain (Ukraine) was described. Multi-model approach is, definitely, a tool for uncertainty analysis. EBUA offers the opportunity of an evaluation of the uncertainty levels of predictions in multi-model applications.     

Concentration ratios for small mammals collected from the exposed sediments of a 137Cs contaminated reservoir

(137)Cs concentration ratios were computed for small mammals collected from the dried sediments of a partially drained, contaminated reservoir. Soil (137)Cs activity concentrations were heterogeneous on small and large spatial scales and had a geometric mean of 253 (range 23-2110) Bq/kg dry weight. Mean (137)Cs activity concentrations in composite cotton rat Sigmodon hispidus and cotton mouse Peromyscus gossypinus samples averaged 2480 (range 556-6670) and 471 (range 96-1000) Bq/kg whole body dry weight, respectively. About 50% of the variance in cotton rat tissue (137)Cs activity was explained by variation in soil (137)Cs activity. Soil-to-animal dry weight concentration ratios averaged 6.0 for cotton rats and 1.2 for cotton mice and were generally similar to (137)Cs concentration ratios for herbivorous, homeothermic animals from other contaminated ecosystems. In the RESRAD-BIOTA dose model, the default wet-weight concentration ratio for (137)Cs in terrestrial animals is 110 resulting in an estimate of internal and external radiation doses to terrestrial biota that is 44 times more than the dose calculated with the actual measured wet-weight concentration ratio for cotton rats (1.6). These results show that site-specific concentration ratios can significantly affect the estimation of dose.