Analysis of the demographic impacts of nuclear fuel cycle facilities
Advisors: Aditi Verma, Gabrielle Hoelzle, and Todd Allen
Project Description: The Fastest Path to Zero Initiative is seeking a motivated undergraduate research assistant to build on an ongoing analysis of the demographic impacts of nuclear fuel cycle facilities in the US.
Preliminary analysis carried out by the Fastest Path team shows the differential impacts of extractive facilities (uranium mills and mines) on host communities of these facilities. For example, this analysis shows that extractive facilities have typically been sited in counties that have high percentages of Native American, Latino, and Hispanic populations at the time of siting and the percentage of white populations in these communities have fallen in the decades following facility siting, while the percentages of Native American, Hispanic, Latino, and Black populations have increased over time in these same counties. This trend, as well as others revealed through this analysis, indicate that the siting of both extractive and energy generation facilities may have heightened existing inequities along racial and socioeconomic lines within and across communities over time. We aim to build on this initial analysis to include waste management facilities, research facilities such as the national labs, as well as cleanup sites.
Nuclear reactor developers as well as policymakers are actively considering where and how to site future nuclear energy and fuel cycle facilities, and the results of such an analysis can not only inform siting policy decisions in this pivotal moment for the nuclear energy sector but also identify and repair existing inequities unintentionally created by the nuclear energy sector over its trajectory of development. Further, the results may also provide guidance to renewable energy technology companies who are embarking on a major energy transition with significant extraction requirements.
Prerequisites: A strong interest in the technology-policy intersection and interest in interdisciplinary research is ideal. Familiarity with programming and statistical analysis is desirable but not required. Students in any year of study are encouraged to apply. This is a paid position for up to forty hours per week for 12 weeks over the summer.
If interested, please reach out to Prof. Aditi Verma directly at: email@example.com.