Accelerated measurements of aerosol size distributions by continuously scanning the aerodynamic aerosol classifier

Abstract

Using an Aerodynamic Aerosol Classifier (AAC) upstream of a particle detector is a relatively new method for measuring the aerodynamic size distribution of an aerosol. This approach overcomes limitations of previous methodologies by leveraging the high transmission efficiency, independence from particle charging, and adjustable classification range and resolution of the AAC. However, the AAC setpoint must be stepped and stabilized before each measurement, which forces trade-offs between measurement time and step resolution. This study is the first to develop and validate theory which allows the speed of the AAC classifier to be continuously varied (following an exponential function), rather than stepped. This approach reduces measurement time, while increasing the resolution of the measured distribution. Assuming uniform axial flow, the transfer function of the scanning AAC and its inversion is determined. Limited trajectory theory is used to derive the idealized transfer function of the scanning AAC, while parameterized, particle streamline theory is used to develop the non-idealized transfer function, which accounts for nonidealized particle and flow behaviours within the classifier. This A c c e p t e d M a n u s c r i p t theory and the practical implementation of the scanning AAC are validated by the high agreement of its measurements of polystyrene latex (PSL) particles (within 8.7% for six sizes between 100 nm to 2.02 μm), and of size distributions of three aerosol sources (Bis(2-Ethylhexyl) sebacate, NaCl and soot) to those measured by the stepping AAC (within 2% or better if the source stability is considered). The validity of assuming uniform axial flow in the classifier and downstream plumbing/detector are also discussed.

Cloud condensation nuclei (CCN) activity analysis of low-hygroscopicity aerosols using the aerodynamic aerosol classifier (AAC)

“…In short, the AAC is increasing in popularity (e.g., but not limited to Johnson et al, 2020;Su et al, 2021;Johnson et al, 2021). However, the scientific knowledge of coupling an AAC with a CCNC is limited.…”

Cloud Condensation Nuclei (CCN) Activity Analysis of Low-hygroscopicity Aerosols Using the Aerodynamic Aerosol Classifier (AAC)

“…In short, the AAC is increasing in popularity (e.g. but not limited to Johnson et al (2020), Su et al (2021), Johnson et al (2021)). However, the scientific knowledge of coupling an AAC with a CCNC is limited.…”