| dc.description.abstract | Major nuclear accidents such as Chernobyl and Fukushima-Daiichi have highlighted the need for robust consequence assessment and countermeasure (mitigation) plans. As such, FEMA provides several planning fundamentals such as ‘community-based planning’ and ‘considering all hazards and threats’. However, specific guidance on the implementation of these fundamentals was not found in the reviewed literature. Thus, a prototype DSS in line with these fundamentals was created to study the consequences of nuclear accidents and suggest countermeasures. A ‘receptor-centric’ framework was proposed to implement community-based planning. Similarly, a data-driven framework with stratified random sampling for release times throughout the year was applied to study a larger number of accident scenarios. This sampling approach was more robust than the wind rose approach in capturing a greater spectrum of possible impacts. The need for sufficient accident sampling was also demonstrated. Non-simultaneous individual accidents in regions with multiple nuclear plants were studied as no corresponding methodology was found in the literature. Time-dependent source terms were used to improve accuracy.
The DSS was tested on Qatar for hypothetical accidents at Barakah, Bushehr, and Umm Huwayd plants for the year 2017. All results were compared for 25 secondary receptors over seven categories. These accidents were determined to potentially cause both short-term and long-term health impacts, with ingestion exposure being the critical pathway. Thus, agricultural countermeasures were chosen as the core countermeasure strategy. Inhalation and groundshine exposure were also identified as pathways of concern. Mesaieed industrial area and Dukhan oil fields were determined to be disproportionately affected by nuclear accidents. Based on radioactive cloud spread, strategies for placement of early warning sensors were also proposed. Sheltering and food restrictions were chosen based on consequence assessment. A novel visualization method was used to guide food restrictions. An insufficient sampling rate hampered a complete comparison of the base case and countermeasure case. Nonetheless, the proposed countermeasure strategy was determined to be inadequate, requiring stricter measures to protect the population.
Various avenues for future research were identified, including further DSS development, module, and data improvements. The proposed design is expected to facilitate the development of similar DSS for harmful airborne releases. | en |
