Abstract
ABSTRACT Fast Mobility Particle Sizer (FMPS) size distribution measurements with different inversion matrices were compared with the Scanning Mobility Particle Sizer (SMPS) for ambient aerosols sampled from a background location in Riverside, CA in this study. The FMPS-compact matrix showed the best agreement with SMPS for particle concentration in the size ranges of 9–359 nm and 9–100 nm (for ultrafine particles). The FMPS-compact matrix also showed the best agreement with the SMPS for mode diameter. All FMPS inversion matrices showed size-dependent discrepancies compared with the SMPS. Measurement of the non-volatile fraction of ambient aerosol downstream of a catalytic stripper showed that the FMPS-compact matrix agreed best with the SMPS with the FMPS over SMPS linear regression slope of 0.99–1.00 for particle concentrations. This is likely due to the restructuring of soot during the removal of volatile coating. This study showed that the soot and compact matrices are insufficient for ambient aerosol measurement. Challenges remain for FMPS measurements when particle morphologies are not known a priori or when they are different from near spherical shape or aggregate structure.
Highlights
Ever since the algorithm for the Scanning Mobility Particle Sizer (SMPS) was first introduced by Wang and Flagan (1990), it has served as a standard for particle mobility size distribution measurement
A fast SMPS was introduced by Shah and Cocker (2005) using a radial differential mobility analyzer (DMA) and a mixing type condensation particle counter (CPC)
This study aims to evaluate the performance of the Fast Mobility Particle Sizer (FMPS) matrices for ambient aerosols in Riverside, CA
Summary
Ever since the algorithm for the Scanning Mobility Particle Sizer (SMPS) was first introduced by Wang and Flagan (1990), it has served as a standard for particle mobility size distribution measurement. It improves the accuracy of the data inversion from fast SMPS scans (Mai and Flagan, 2018; Mai et al, 2018) Another recently developed a fast integrated mobility spectrometer (FIMS) that uses an electric field to separate particles, subsequently grows particles by alcohol or water condensation, and measures size distributions using a high speed CCD camera (Olfert et al, 2008). Replacing the FMPS default matrix with the soot matrix improved the linear regression slopes of MIPSD/MGrav from 0.45–0.57 to 0.76–1.01 for gasoline direct injected (GDI) vehicles over transient driving cycles Performances of these inversion matrices have not been evaluated for ambient aerosols. Performance of the matrices was evaluated for ambient particles before and after removing the volatile fraction, using a catalytic stripper
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