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Workplace Dust Monitoring Strategies in Industrial Environments: Case Studies and Categorisation

Explore comprehensive industry case studies for effective workplace dust monitoring strategies, emphasizing air sampling techniques and ALARA implementation. Conclusions from studies highlight the importance of monitoring techniques and exposure categorisation.

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Workplace Dust Monitoring Strategies in Industrial Environments: Case Studies and Categorisation

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  1. Peter Shaw, HPA-RPD, UK SMOPIE - Work packages 2 and 3Industry case studies and workplace categorisation

  2. SMOPIE: Case Studies and Partners

  3. Process materials: Bq/g

  4. Industry Characteristics • Large scale processes • Dusty (in parts) • Many process steps • mechanical plant • manual tasks • multi-tasking • All have workplace/individual monitoring • all do air sampling (personal and/or static)

  5. Air sampling • Personal air sampling (PAS) • for dose estimates - UK1, UK2 and N1 (and F1) • shift and task sampling • radiometric and gravimetric • Static air sampling (SAS) • for dose estimates - F1 and N2 • reassurance monitoring and particle size (N1) • radiometric and gravimetric • Real-time dust sampling (RTDM) • SMOPIE surveys (not dose assessment) • gravimetric and optical (particle counting)

  6. Annual internal doses - Inhalation

  7. Results and conclusions from different case studies • Each case study is different • Annex 2 to Main Report • A lot of information • strategies and methods • results • advantages and limitations • practical tips • Just a small selection in this presentation

  8. UK1 - Zircon sand, grinding and milling • Existing dust monitoring programme for many years (PAS) • UK industrial hygiene regulations • accepted by workers • Results used to assess radiation doses • Provided limited ALARA information • dusty areas and tasks • long terms trends • More sampling recommended

  9. UK1 - Real-time dust monitoring • Specifically for the SMOPIE project • 200 measurements in 2 days • complete “map” of workplace • day-to-day changes • short-term variations • localised dust levels • dust sources • tasks • leaking pipes/vessels • exhaust air from extractors • cleaning machine!

  10. UK1 R-T dust results - by location

  11. UK1 R-T dust results - time variations

  12. F1. Case Study - U concentrate conversion • Comhurex, Malvési • Different to other case studies • activity concentration much higher • radiation protection (nuclear) background rather than industrial hygiene • Extensive monitoring programme • SAS, urine and lung • Focus on first step in the process • sampling drums of U concentrates

  13. F1. PAS campaign - sampling stage • Drum unbanding/rebanding • SAS v PAS • both produce same rankings of dusty areas • PAS doses 30-100 times higher • important factors • sampler location • time profile of dust • source of dust

  14. F1 Case study • Improvements to filling station • hopper modified to prevent over-filling • containment installed • Effectiveness demonstrated by PAS (task) • Problems with 1 drum type (from PAS/SAS) • Real-time (optical) particle counting • showing contamination peaks • Further improvements at filling station • drum handling equipment • new (confined) rebanding station

  15. F1. RT sampling inside filling station

  16. N1 - phosphorus production

  17. N1. Monitoring programme • Focus on precipitator dust • Leaching tests • lung class S • PAS (on 2% of shifts) • alpha/beta counting • 3 week delay • 5 day count • 245 results from 1998-2001

  18. N1 - PAS results • Doses categorised according to type of work • 0.1 to 2.8 mSv/y • mean = 1.2 mSv/y • Statistical uncertainties are important • worker variation is greater than task variation • varied work patterns • changing air concentrations • Only cleaners (2.8 mSv/y) and control room (0.1-0.2 mSv/y) show significant difference

  19. Conclusions from WP2 Case StudiesCategorisation of workplaces • A strict categorisation is not helpful • Instead focus on characteristics common to ALL case studies • multiple dust sources, from machinery and workers • airborne dust is always present • dust levels always varying with space and time • working patterns are complex and often change

  20. Conclusions from WP2 Case StudiesMonitoring strategies • To implement ALARA • assessment of internal dose, and • information on how/where doses arise • requires a combination of monitoring techniques • Air sampling is better than other methods • dose assessment and ALARA information • Sampling uncertainties • are significant • are not considered enough in practice

  21. Conclusions from WP2 Case StudiesMonitoring strategies • PAS • provides best estimate of worker doses • SAS • to check doses are low (reassurance) • underestimates, always compare with PAS • Real-time • not for dose assessment • only suitable in certain workplaces • can provide best ALARA information

  22. SMOPIE - WP3Categorisation of exposure situations • Case studies indicated that categorisation was not helpful • Same conclusions apply in all cases • Some other factors to consider • gravimetric analysis requires constant Bq/g • alpha/beta counting requires contant radionuclide ratios • Bq/g and dose coefficent influence choice of analysis method (sensitivity)

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