Characteristics of Scanning Flow Condensation Particle Counter (SFCPC): A rapid approach for retrieving hygroscopicity and chemical composition of sub-10 nm aerosol particles

Abstract

Chemical composition of sub-10 nm particles is crucial for understanding the atmospheric new particle formation (NPF) and subsequent particle growth. However, very limited chemical information is available in this diameter range due to the high technical requirements. In this work, we proposed a new operation mode of water-based condensation particle counter, which was termed as Scanning Flow Condensation Particle Counter (SFCPC). By altering the aerosol flow rate (Q_a), this method could change supersaturation (S) rapidly. The inner S of SFCPC was evaluated by ammonium sulfate (AS) and tungsten oxide particles. It decreased more and more sharp when Q_a varied from 400 to 80 cm³ min⁻¹, corresponding to the S in the range of 14.02%–26.39%, which could activate AS in 3.6–5.4 nm. Hygroscopicity parameter κ was obtained directly from the selected particle diameter and measured counting efficiency. For AS-levoglucosan/sucrose mixtures, linear relationship between κ and organic mass fraction f_org was successfully established down to 3.5 nm. We also measured κ of several NPF relevant organics in 5–8 nm (0.121 ± 0.055, 0.123 ± 0.035, 0.132 ± 0.032, 0.129 ± 0.023 and 0.142 ± 0.023 for cis-pinonic acid, benzoic acid, malonic acid, succinic acid, and glutaric acid, respectively). This new method has been evaluated in lab for the capability of measuring κ. The size-resolved linear relationship indicated that SFCPC could be used to infer f_org. The rapid S change and activated diameter range make this method suitable for field measurements. The provided κ and f_org of sub-10 nm particles is an important complement for the understanding of new particle formation.

Copyright © 2023 American Association for Aerosol Research

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (41805100, 91844301, 42005086), the Fundamental Research Funds for Central Universities of China (2018QNA6008), and the Key Research and Development Program of Zhejiang Province (2021C03165 and 2022C03084).