Comparative analysis of the dispersion modeling and dose projection results performed under BARCO international project

Abstract

Radiological assessments on zones to take protective actions in case of a nuclear or radiological emergency involve a series of real-time forecasts of radiological impact on the public at various distances from the release point, using actual weather or forecast data, information on the source term or facility status, and primary radiation monitoring data. This practice is implemented during the operation of emergency centers around the world in order to promptly report the occurrence and possible consequences of radiological accidents in the country and abroad in the event of a possible transboundary impact. Since the Chornobyl disaster, a lot of emergency exercises, research programs and projects, in particular, benchmarking, have served as international platforms for improving modeling capacity in atmospheric dispersion. This activity is carried out both on the basis of past severe accidents with significant atmospheric releases and corresponding radiological consequences, and on the basis of specific conditional (hypothetical) events that are developed in accordance with the purpose of the study. The paper is focused on the comparison results performed under the international project “Benchmarking on Assessment of Radiological COnsequences” (BARCO) conducted in 2020–2021 between five technical support organisations – members of the European Technical Safety Organisations Network (ETSON). The work contains a short overview of relevant international activity conducted in the past, a description of the BARCO project and its objectives, a list of participants, project tasks, initial data (source term, meteorology, list of benchmarking quantities, approach to data exchange, codes used). The study presents some of comparative analysis results obtained via two techniques such as code-to-code analysis (CTCA) and matched-pair analysis (MPA). The results discussion concentrates on the overall recommendations for code users. Conclusions provide the main outputs of the project.