Integrated Modeling and Monitoring Technologies for Environmental Resiliency in Nuclear Energy
Environmental concerns pose the biggest challenge for the development of the nuclear energy industry, often preventing or limiting the construction of new plants and radioactive waste disposal facilities. There are currently numerous sites in the world at which surface and groundwater are contaminated by nuclear weapon production and testing, as well as due to nuclear power plant accidents. Many of those sites remain unused or inhabited primarily due to public concern. Improving scientific and technical capabilities to develop environmental resiliency is critical not only to address existing contamination, but also to build public confidence and support for nuclear energy. One of the obstacles in remediation is to tackle a large volume of contaminated soil and groundwater with relatively low concentrations. Although many contaminant removal technologies have developed (e.g., pump-and-treat systems), they are often expensive and not cost-effective for low-concentration radionuclide contamination. Although soil removal is often the most effective, it produces a large amount of waste that has to be stored securely for a long period of time or treated at the special treatment facilities. Transporting a large amount of waste may also produce greenhouse gases and disrupt local communities. Recently, the concept of 'sustainable remediation' has been proposed to improve a remediation system as a whole, including the consideration of cost effectiveness, reduction of greenhouse emission, waste production and energy usage. Rather than just focusing on removing contaminants, the sustainable remediation highlights the use of passive remediation technologies to immobilize radionuclides along with the application of monitored natural attenuation and longer institutional control. However, such passive technologies and monitored natural attenuation require the increased burden of proof to ensure that those immobilized contaminants would not compromise the long-term public health. Although contaminant transport modeling and risk assessments are always performed, they sometimes fail due to the lack of understanding the contaminant transport proposes at the time of the risk assessment or due to some unexpected processes. Monitoring technologies are critical to ensure the long-term stability of such remediated sites, and also to address the public concerns. Recent advances in in situ sensor technologies and spatially-extensive mapping technologies (such as unmanned aerial vehicles, airborne mapping, geophysics) have improved monitoring of contamination over space and time. In addition to new sensing devices, data management and data analytics technologies have been expanded to manage and process large spatial and temporal datasets. Such technologies can be used to reduce monitoring cost significantly, and to facilitate long-term monitoring. In this study, we demonstrate our data analytics technologies for two nuclear-related contaminated sites: (1) air dose rate monitoring in Fukushima prefecture, and (2) groundwater monitoring at the Savannah River Site F-Area. We are developing the spatial and temporal data integration methodologies to integrate various spatially extensive data and time-series data for improving long-term monitoring. Such monitoring technologies and experiences at the existing contaminated sites can be transferred to build a better monitoring system for nuclear facilities, such as nuclear power plants or nuclear waste storages.