AAAR 35th Annual Conference October 17 - October 21, 2016 Oregon Convention Center Portland, Oregon, USA
Abstract View
Scanning DMA Data Inversion
HUAJUN MAI, Rebecca Schwantes, Kelvin Bates, Weimeng Kong, John Seinfeld, Richard Flagan, California Institute of Technology
Abstract Number: 427 Working Group: Instrumentation and Methods
Abstract By scanning the voltage applied to a differential mobility analyzer (DMA) through an exponential ramp, the scanning differential mobility particle sizer (SMPS) enables rapid size distribution measurements. The inversion of SMPS data is more complex than for stepping-mode operation of the DMA (DMPS) due to the finite time response of the condensation particle counter (CPC) or aerosol electrometer (AE) that is used as a detector. Moreover, the transfer function that is most commonly used in data inversion was derived for operation of the DMA at constant voltage. While each of these factors that complicate SMPS data inversion relative to stepping-mode DMA measurements, most SMPS data inversion employs instrument static transfer and response functions for these dynamic measurements. Here we report on full characterization of a scanning DMA/laminar flow CPC measurement system, specifically an SMPS system comprised of a TSI long column DMA and a TSI model 3010 CPC.
Several studies have reported on the scanning DMA transfer function using idealized, coaxial models of the classification channel. We have determined the full scanning DMA transfer function by combining COMSOL Multiphysics$^(TM) finite element modeling of the flow and electric fields within the instrument with Monte Carlo simulations of particle transport and classification within the DMA. Mixing within the CPC introduces a residence time distribution that distributes particles that enter it over several seconds. That residence time distribution has been measured experimentally using an aerosol pulse at the instrument entrance. The data produced by the combined SMPS system has been inverted by combining deconvolution to correct the CPC data smearing effects and nonlinear least squares inversion of the scanning DMA response function. Experimental and simulation-based validation of the instrument model and data analysis procedures will be presented. Differences between the detailed analysis and either data analysis using static models or prior, simplified models of the scanning DMA will be discussed.