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Radiological Monitoring: a Data Science Case Study

A Data Science case study made from 4 years of radiological monitoring data from the Food Standards Agency (FSA). The project was completed as coursework for the module "Programming for Data Science" and received a Distinction (>70%).

Summary

The Food Standards Agency (FSA) routinely test isotope levels in various consumables across the United Kingdom. Common examples include meat, fish, eggs, milk, grain, soil, air and water. A simple analysis found that significantly more readings are taken in or around Sellafield, a town in Cumbria. Research revealed that Sellafield is home to Sellafield nuclear site, previously known as Windscale. Windscale was victim to a significant nuclear disaster in 1957 (see more here).

An investigation was conducted on isotope levels at Sellafield; it was found that levels are significantly higher than in other areas of the UK. Despite this, these levels remain within the threshold, and the food and drink produced around Sellafield is safe for human consumption.

The project gave fascinating insights into the lingering effects of nuclear accidents, as well as the recovery strategy by Sellafield and the UK Government.

License & Citation

This project is licensed under the MIT License – feel free to use it to benefit future work. I would appreciate acknowledgement:

@misc{boydlyon2025sellafield,
  author       = {Connor Boyd-Lyon},
  title        = {Radiological Monitoring: a Data Science Case Study},
  year         = {2025},
  url          = {https://github.com/connorlyon10/RadiologicalMonitoring}
}

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A case study on UK radiology reports, revealing insights into the 1957 Windscale nuclear fire. Completed as coursework for MSc Data Science at The University of Birmingham.

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