Hybrid process improvement framework to reduce the eutrophication potential of in-situ leaching for uranium extraction: A qualitative study
Year: 2024
Type: article
Abstract: The UK government has embarked on a comprehensive revaluation of its investment in Nuclear Power (NP) in response to a confluence of factors, including rising oil and gas prices, the shift towards independent energy extraction, and mounting concerns about climate change. Central to this revaluation is the Hinkley Point C (HPC) Project, a new nuclear power station, which aligns with the UK’s decarbonisation and NetZero ambition but requires improvements highlighted by the Électricité de France’s (EDF) life cycle analysis, particularly in its Eutrophication Potential (EP). Eutrophication, a form of environmental damage stemming from excessive organism activity due to elevated nutrient loading remains is a key concern. Eutrophication is particularly relevant to nuclear power due to the nutrient emissions associated with uranium mining and milling processes. These processes contribute significantly to eutrophication, accounting for 58% of the EP per kilowatt-hour delivered. This study undertakes the development of a Hybrid Process Improvement Framework (HPIF) aimed at mitigating EP associated with uranium extraction in nuclear power plants and identifies diesel combustion in support of in-situ leaching (ISL) techniques for Uranium Extraction as the predominant contributor to EP impact. Consequently, the research underscores the necessity for a novel HPIF design aimed at reducing diesel combustion and, by extension, the overall EP value. By promoting sustainable practices, the research supports a broader move towards resource-efficient and low-impact industrial processes, crucial for the UK’s overall Net Zero strategy. Further, the study adopts the DMADV methodology for the design of the HPIF process, thus ensuring a well-structured and data-driven approach in managing the HPIF configuration process. For validation, we employ semi-structured open-ended qualitative interviews with a unique set of subject experts (n = 21) comprising nuclear industry practitioners, academic researchers, and policymakers. Insights from the analysed data from 21 subject experts indicate that the HPIF is a novel tool that can address the larger objective of responding to critical environmental concerns within the nuclear power industry. We conclude that the HPIF can mitigate EP reduction challenges associated with uranium extraction for nuclear power plants. The HPIF integrates and synthesises the methodologies of three established studies focused on reducing diesel fuel consumption in diesel generators. It systematically addresses key parameters, including load profiles, optimal generator type, number of generators, and scheduling strategies, tailored to specific load demands. By employing the advanced calculations derived from these three studies, HPIF effectively targets the fundamental issue contributing to EP value—namely, the diesel combustions of diesel generators. This framework specifically addresses the challenge of reducing EP values associated with diesel fuel usage. • Our study identifies the main contributor to Eutrophication Potential (EP) value utilising a comprehensive LCIA on In-Situ -Leaching (ISL), which is Diesel Combustions due Diesel Electric Generators. • Our paper shows how to reduce the Diesel Combustions, and consequently EP value. • Our paper applies a Six Sigma methodology validated by expert interviews to develop a Hybrid Process Improvement Framework (HPIF) to reduce EP of ISL for uranium extraction. • The HPIF addresses the root cause, by managing the load profile, power requirements and production parameters, thus eventually mitigating EP associated with uranium extraction in nuclear power plants.
Source: Journal of Cleaner Production
Authors: Kirim Yagmur, Okechukwu Okorie
Institutions: University of Exeter, University of Manchester
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,260
Funder: Royal Academy of Engineering
OpenAlex ID: W4404516036
