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Experimental Protocol to Investigate Particle Aerosolization of a Product Under Abrasion and Under Environmental Weathering
Published on: September 16, 2016
Performance characteristics of respirable parallel particle impactors (PPI)
Gediminas Mainelis1, Taewon T Han1
1Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, New Jersey.
Parallel Particle Impactors (PPIs) accurately measure respirable aerosols, adhering to sampling conventions. Disposable PPI models demonstrate excellent performance, offering flexible options for exposure assessment.
Area of Science:
- Environmental Science
- Occupational Health
- Aerosol Science
Background:
- Parallel Particle Impactors (PPIs) are used for respirable aerosol sampling but lack published collection efficiency data.
- Existing PPI models are designed to align with the established convention for respiratory aerosol sampling.
Purpose of the Study:
- To investigate the collection efficiency curves and 50% cutoff sizes (d50) of disposable and reusable PPI models.
- To evaluate PPI performance at various flow rates (2, 4, and 8 L/min) against the respirable aerosol sampling convention.
Main Methods:
- Challenged PPI samplers with polydisperse sodium chloride (NaCl) and monodisperse polystyrene latex (PSL) particles.
- Calculated bias maps and Bias Performance Criterion (BPC) values for aerosols with varying mass median aerodynamic diameters (MMADs) and geometric standard deviations (GSDs).
Main Results:
- Disposable PPI models at 2, 4, and 8 L/min exhibited d50 values near 4 µm with BPC > 95%.
- Reusable 2 L/min PPI showed a d50 of 4.07 µm and 100% BPC; 4 and 8 L/min models had slightly higher d50 values.
- A 7% flow rate increase to 4.3 L/min maintained a d50 of ~4 µm with 100% BPC.
Conclusions:
- Respirable PPI samplers, especially disposable models, demonstrate strong adherence to the respirable aerosol sampling convention.
- PPI samplers provide a flexible tool for estimating respirable particle exposures, with various models suited for different sampling scenarios.
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