Cleaning that ignores air data is guesswork. Using particulate readings to time and target housekeeping cuts re-suspension, keeps workflows moving and reduces PPE reliance.

Build a simple monitoring routine

Measure PM10/PM2.5 at fixed locations: near cutting, mixing and welfare thresholds. Log readings at start-up, mid-shift, after dusty tasks and before close. Note what was happening at each spike. Use these patterns to set cleaning windows when dust is settled but before it migrates.

Turn readings into schedules

Where peaks occur late morning, schedule a short vacuuming slot just after the spike. If levels rise steadily through the afternoon, add a mid-shift pass. Prioritise routes where people move from dirty to clean spaces. Keep high-traffic thresholds on a higher cadence than back-of-house areas.

Choose the right methods

Use industrial vacuums with appropriate M/H-Class filtration to remove settled dust without blowing it back. Avoid dry sweeping and compressed air. If sweepers are used for large floors or outdoor yards, ensure they capture rather than re-suspend dust and are supported by local vacuuming at edges.

Close the loop with verification

After cleaning, recheck PM. If levels rebound quickly, change the method (e.g., slower passes, different tools) or move to source control. Keep records to show that cleaning reduces airborne particulate and supports COSHH controls.

Practical takeaways

• Use air monitors at fixed points and times to identify spikes.
• Schedule housekeeping immediately after known peaks, not by habit.
• Vacuum with high-efficiency filtration; avoid re-suspension methods.
• Validate with post-clean readings and adjust frequency accordingly.
• Apply more frequent cleaning to thresholds and welfare approaches.

Consistent, data-led cleaning reduces exposure and disruption. Use air monitors to set the cadence, and support with appropriate tools, including sweepers where they truly capture dust.