[Show abstract][Hide abstract] ABSTRACT: Environmental assessment models are used as decision-aiding tools in the selection of remediation options for radioactively contaminated sites. In most cases, the effectiveness of the remedial actions in terms of dose savings cannot be demonstrated directly, but can be established with the help of environmental assessment models, through the assessment of future radiological impacts. It should be emphasized that, given the complexity of the processes involved and our current understanding of how they operate, these models are simplified descriptions of the behaviour of radionuclides in the environment and therefore imperfect. One way of testing and improving the reliability of the models is to compare their predictions with real data and/or the predictions of other models. Within the framework of the Remediation Assessment Working Group (RAWG) of the BIOMASS (BIOsphere Modelling and ASSessment) programme coordinated by IAEA, two scenarios were constructed and applied to test the reliability of environmental assessment models when remedial actions are involved. As a test site, an area of approximately 100 ha contaminated by the discharges of an old radium extraction plant in Olen (Belgium) has been considered. In the first scenario, a real situation was evaluated and model predictions were compared with measured data. In the second scenario the model predictions for specific hypothetical but realistic situations were compared. Most of the biosphere models were not developed to assess the performance of remedial actions and had to be modified for this purpose. It was demonstrated clearly that the modeller's experience and familiarity with the mathematical model, the site and with the scenario play a very important role in the outcome of the model calculations. More model testing studies, preferably for real situations, are needed in order to improve the models and modelling methods and to expand the areas in which the models are applicable.
Journal of Environmental Radioactivity 02/2005; 84(2):245-58. · 2.12 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: An important source of uncertainty in predictions of numerical simulation codes of environmental transport processes arises from the assumptions made by the user when interpreting the model and the scenario to be assessed. This type of uncertainty was examined systematically in this study and was compared with uncertainty due to varying parameter values in a code. Three terrestrial food chain codes that are driven by deposition of radionuclides from the atmosphere were used by up to ten participants to predict total deposition of 137Cs and concentrations on pasture and in milk for two release scenarios. Collective uncertainty among the predictions of the ten users for concentrations in milk calculated for one scenario by one code was a factor of 2000, while the largest individual uncertainty was 20 times lower. Choice of parameter values contributed most to user-induced uncertainty, followed by scenario interpretation. Due to the significant disparity in predictions, it is recommended that assessments should not be carried out alone by a single code user.
Journal of Environmental Radioactivity 01/1998; 42(2):177-190. · 2.12 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Two major areas of emphasis in the BIOMASS (Biosphere Modelling and Assessment Methods) programme were the improvement of the accuracy of model predictions and the improvement of modelling procedures within the general area of environmental assessment. Theme 2 of BIOMASS, Environmental Releases, focused specifically on issues of dose reconstruction and remediation assessment. Within Theme 2, the Dose Reconstruction Working Group was concerned with the evaluation of the reliability of methods and models used for dose reconstruction for specific individuals and members of specific population subgroups. The Dose Reconstruction Working Group of BIOMASS carried out model testing exercises. The present paper describes the first one, which was based on an accidental release of 131I from the Hanford Purex Chemical Separations Plant in the northwestern United States in September 1963 (BIOMASS, 1999). The scenario made use of monitoring data originally collected during the two months following the release (Soldat, 1965) and further evaluated as part of the Hanford Environmental Dose Reconstruction (HEDR) project in the 1990s (Farris et al., 1994). Radioiodine releases are important for many radiation accidents, and because data on the results of these releases are often incomplete, models for estimating 131I transport and exposure are essential in dose reconstruction efforts. The Hanford scenario therefore provided a valuable opportunity to intercompare modelling approaches and model predictions among several assessors, to compare model predictions with data, and to identify the most important sources of bias and uncertainty in the model results.