Performance of real-time metrology applied to nanoparticle aerosols

Nanomaterials are full of promise in fields as varied as healthcare, agrifood, energy, materials, and transport. Research for developing them is therefore very active and the accompanying economic stakes are considerable. The data relating to characterising occupational exposure to nanoparticle aerosols remain limited; developing and validating methods making it possible to characterise them constitutes a major issue for research. Therefore, producing robust knowledge about instrumentation for use with airborne nanoparticles is essential before considering deploying it more widely in the industrial hygiene sector.
In addition to conventional sampling, various strategies for assessing occupational exposure to nanoparticle aerosols recommend implementing real-time measurement techniques that offer the possibilities of: (1) characterising the sources of airborne nanoparticles qualitatively or quantitatively in time and space; (2) highlighting the (specific) tasks associated with the emissions; (3) detecting malfunctioning of collective protection systems and thereby enabling alarms to be put in place; and (4) estimating worker exposure in real time, subject to various hypotheses.
The difficulties associated with the use of these techniques lie in particular in their non-selectivity (problem of background aerosols), in identifying and taking account of the sources of bias that are inherent to such instruments, or indeed in developing data processing tools.

This study is being conducted in response to the prospects stemming from the study EXPONANO (2008-2012) and within the framework of projects in which the laboratory is taking part (NANOCEN, NanoREG, EPINANO). The objective of the study is to assess real-time metrology performance for measuring airborne particle number size distribution as well as their number concentration.

Planned dissemination:
The knowledge acquired will be disseminated through presentations to conferences, and will be used in INRS training sessions.