AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
Finding the Right Mass: Comparing Measurements from a Differential Mobility Analyzer, Aerodynamic Aerosol Classifier and Aerosol Particle Mass Analyzer
QI YAO, James Radney, Akua Asa-Awuku, Christopher Zangmeister, National Institute of Standards and Technology
Abstract Number: 479 Working Group: Instrumentation and Methods
Abstract There now exists an instrumentation trifecta for aerosol separation and classification by mobility diameter (Dm), aerodynamic diameter (as Daero or the relaxation time, τ) and mass (mp) utilizing a differential mobility analyzer (DMA), aerodynamic aerosol classifier (AAC) or aerosol particle mass analyzer (APM), respectively. In principle, any combination of two measurements yields the third; i.e. relaxation time = mobility x mass. Here, we compare measurements of mp, effective density and mass-mobility scaling exponents (Dfm, a surrogate for particle shape) utilizing different combinations of tandem measurements – DMA-APM, AAC-DMA and AAC-APM – utilizing ammonium sulfate, soot from a Santoro diffusion flame and water-soluble carbon black; notably, these particles represent a solid, near-spherical particle, a lacey aggregate and a near-spherical collapsed aggregate. Preliminary data suggests that deviations in mp and Dfm between tandem measurements are low (on the order of 5 to 10 %) and that the largest uncertainty is the resolution of particles bearing multiple charges. While the AAC by itself does not require charge to classify particles, mp (and hence Dfm) determination requires a secondary instrument (i.e. DMA or APM) that does separate based upon charge. Results show that the deconvolution of multiply charged particles with classical charging theory works well for the spherical particles (AS and carbon black) but is especially problematic for lacey soot. Thus, measuring particle mass from the AAC may have resolution limitations. We will also present recommendations for data analysis and interpretation.