Field evaluation of PM10 detectors in a quarry environment

This study is aimed to test and compare two different devices and methods to assess PM10 concentration at workplace. An analysis of data collected by Public Administration database on the main nuisance factors at workplaces revealed that in quarrying activities, PM10 concentration and airborne dust, in general, represent one of the most relevant hazards. Therefore, to provide a useful stress test for sampling devices, the location selected was a basalt quarry near Rome. Airborne dust tends to be unavoidable in quarries, as this industry necessarily causes ground disturbance. Drilling, blasting, loading, hauling, moving, crushing and screening rocks, as well as transporting the final product away from the quarry, are all dusty activities. To investigate this phenomenon, we carried out many outdoor sampling campaigns under various meteorological conditions during the period of 2012-2013. In each of them, two simultaneous samples were taken to assess PM10 airborne concentration: from one hand, a traditional device for long-Term sampling (gravimetric analysis) was employed, while on the other one, a photometric aerosol detection technology developed with a real-Time dust monitor was tested. The comparison of collected data revealed that optical readings, if not supported with a specific calibration against physical properties of the dust being measured, may overestimate PM10 concentration. In the second period of sampling campaign (2013), the calibration was realized taking into account particle size distribution and density and the samples were collected again. The following analysis showed an improvement in the correlation factor R2 by more than 20%. This result demonstrates that photometric aerosol detection technology using a nephelometer should be considered suitable for monitoring PM10 in dusty workplaces such as quarries or mines, especially when supported by a gravimetric sample to calibrate the optical device itself. This integrated approach seems to be the best option to reduce sampling time without reducing accuracy responses.