Stakeholders believe what they can see and measure. To prove dust control works, collect defensible data before, during, and after interventions, and present it simply. Focus on metrics that reflect health risk and work reality.

Choose the right metrics

• Use particulate measurements for PM10/PM2.5/PM1 to capture fine airborne particulate.
• For silica tasks, align with RCS exposure; the UK WEL is 0.1 mg/m³ (8-hr TWA).
• Log airflow under load on LEV and air scrubbers, not free-air figures.

Set a clear baseline

• Run air monitoring for representative shifts, capturing task notes and timestamps.
• Record normal housekeeping and maintenance states to avoid favourable bias.
• Identify spikes and link them to specific tools, materials, or locations.

Test interventions

• A/B compare: one shift with existing controls, one with added capture at source or an extra air cleaner.
• Confirm negative air holds with a simple smoke test at doorways.
• Track filter loading; note when counts creep up as filters blind.

Report to convince

• Show before/after peak levels and time above thresholds, not just averages.
• Overlay task logs on PM graphs; highlight which changes cut peaks fastest.
• Summarise actions, costs (time/materials), and the exposure reduction achieved.

Common pitfalls

• Short trials that miss worst-case tasks.
• Relying on one sensor location; use at least source, breathing zone proxy, and boundary.
• Ignoring maintenance; clogged filters ruin the demo.

Good data makes decisions easy: invest where peaks fall the most, document compliance with COSHH, and keep a simple dashboard to show progress over time.