After an accidental release of radioactivity to atmosphere, modelling assessments are needed to predict what the contamination levels are likely to be and what measures need to be taken to protect human health. These predictions will be imprecise due to lack of knowledge about the nature of the release and the weather, and also due to measurement inaccuracy. This thesis describes work to investigate this imprecision and to find better ways of including it in assessments and representing it in results. It starts by reviewing exposure pathways and the basic dose calculations in an emergency response assessment. The possible variability of key parameters in emergency dose calculations is considered, and ranges are developed for each. The imprecision typically associated with calculational endpoints is explored through a sensitivity study. This has been done using both a simple Gaussian atmospheric dispersion model and also real-time weather data in combination with a complex atmospheric dispersion model. The key parameters influencing assessment imprecision are identified. These are demonstrated to be factors relating to the release, arising from inevitable lack of knowledge in the early stages of an accident, and factors relating to meteorology and dispersion. An alternative improved approach to emergency response assessments is then outlined, which retains a simple and transparent assessment capability but which also indicates the imprecision associated with the results through incomplete knowledge. This tool uses input from real-time atmospheric dispersion and weather prediction tools. A prototype version of the tool has been created and this has been used to produce example results. The final stage of the thesis describes the use of the new tool to develop ways in which imprecise or uncertain information can be presented to decision makers. Alternative presentational techniques are demonstrated using example results
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