Examining the Residual Radiological Footprint of a Former Colliery: An Industrial Nuclear Archaeology Investigation

Emily Parker, Matthew G Ryan Tucker, Ilemona C Okeme, Erin I Holland, Dean T Connor, Omer A H Mohamed, Peter George Martin*, Thomas Bligh Scott

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review


Nuclear industrial archaeology utilises radiation mapping and characterisation technologies to gain an insight into the radiological footprint of industrial heritage sites. Increased concentrations of naturally occurring radioactive materials at legacy mine sites are the result of elemental enrichment during coal mining and subsequent combustion. Public safety is of concern around these sites, and therefore, an increased understanding of their associated hazard is essential. Using coincident laser scanning and gamma detection technologies, this study sought to assess the radiological legacy of a coal mine located in Bristol, UK. From this, we can increase our understanding of the residual footprints associated with the local coal mining industry. Samples taken from inside the site were characterised using high resolution gamma spectrometry, wherein the radionuclide content and activities of samples were then quantified. An area of elevated low-level radioactivity was observed at and around buildings believed to belong to the colliery, while Th, U, and K are confirmed at the site from photopeak's of daughter radionuclides. Activities of the radionuclides K-40, U-238, and Th-232 were further quantified during subsequent laboratory analysis. Results highlight an enrichment of naturally occurring radionuclides when compared with global averages for unburned coal. Employing these techniques at further legacy sites would enable an increased understanding of the lasting traces of the coal mining industry, with a focus on NORM enrichment in residual fly ash.
Original languageEnglish
Article number107292
JournalJournal of Environmental Radioactivity
Early online date12 Sept 2023
Publication statusPublished - 1 Dec 2023

Bibliographical note

Funding Information:
The authors would like to thank UK Research and Innovation (UKRI) and the Engineering and Physical Sciences Research Council (EPSRC) for their support and funding for this work via the Robotics and Artificial Intelligence for Nuclear (RAIN) Hub ( EP/W001128/1 ) and NNUF-HR: National Nuclear User Facility for Hot Robotics ( EP/T011491/1 ).

Publisher Copyright:
© 2023 The Authors


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