| Year Funded: 2022 | Budget: | Funding Agency: IRSST |
|---|---|---|
| Title: | Development of a New Technique for Evaluating the Spatiotemporal Dispersion and Scrubbing Kinetics of Aerosols in the Workplace | |
| Category: | Occupational Disease, Injury and Health Services | |
| Subcategory: | Occupational Injury | |
| Keywords: | Spatiotemporal Dispersion, Kinetics of Aerosols, Workplaces | |
| Link to research website: | https://www.irsst.qc.ca/en/ohs-research/research-projects/project/i/5840/n/developpement-d-une-nouvelle-technique-d-evaluation-de-la-dispersion-spatio-temporelle-et-de-la-cinetique-d-epuration-des-aerosols-en-milieux-de-travail-2022-0007 | |
Issue:
In many areas of activity, workers are exposed to aerosols of different kinds and sizes: solid dust, airborne nanomaterials, liquid particles or bioaerosols. The effects of these various aerosols on health are well documented, particularly regarding the incidence of cancer, asthma, lung infections, organic dust toxic syndrome and contact dermatitis.
It is therefore very important to study and control workers’ exposure to aerosols. The research team is undertaking a study of the dynamics of aerosols – spatiotemporal dispersion and changes and scrubbing kinetics – in the workplace.
Different methods reveal that aerosols in the workplace can spread over several dozen metres, by ventilation systems and otherwise, but none of the methods identified allows one to track aerosol dynamics in real time.
Objectives:
The research team plans to develop an AEROsol dispersion Spatiotemporal Evaluation Technique (AERO-SET) based on a network of sensors and a data acquisition and processing tool. The device will measure aerosol dispersion, simultaneously and in real time, as affected by different disturbances, and will locally quantify the kinetics of air scrubbing for particles of various sizes.
Anticipated Results:
This standardized technique will increase the realism of evaluations of aerosol dynamics in the workplace and thus enhance their accuracy and effectiveness.
Investigators:
Loïc Wingert, Geneviève Marchand, IRSST; Maximilien Debia, Université de Montréal; Stéphane Hallé, ÉTS
