A receptor-centric decision support system for the mitigation of nuclear power atmospheric release incidents

The history of incidents involving nuclear power plants underscores the imperative for robust consequence assessment and countermeasure plans. Additionally, the recent energy crisis has reaffirmed the enduring necessity of nuclear energy. While a host of assessments, planning, and response fundamentals exist, the literature lacks specific directives for their implementation. Notably, despite a wealth of studies employing the entire suite of available tools (i.e., source release, atmospheric dispersion and deposition, food contamination, and human exposure) for hypothetical or actual cases, the majority tend to focus on the source and fate of nucleoids. Given these circumstances, we propose a receptor-centric and data-driven framework to guide the selection and evaluation of such planning. This framework, which utilizes time-dependent source terms and the JRODOS system, is exemplified within a region home to multiple nuclear plants. Significantly, this new approach proved more robust than traditional wind-rose and worst-case methodologies in capturing a broader spectrum of potential outcomes. Though it was possible to prioritize and validate certain countermeasures, such as sheltering and food restrictions, using the innovative visualization methods within the framework, we identified several limitations. These weaknesses, along with potential avenues for future research, are discussed in this study, contributing valuable insights to this crucial field.