Measurement report: The influence of particle number size distribution and hygroscopicity on the microphysical properties of cloud droplets at a mountain site - Shen, Xiaojing; Liu, Quan; Sun, Junying; Kong, Wanlin; Ma, Qianli; Qi, Bing; Han, Lujie; Zhang, Yangmei; Liang, Linlin; Liu, Lei; Liu, Shuo; Hu, Xinyao; et al. (Atmospheric chemistry and physics, 2025)
An automatic switched inlet system, incorporating a ground-based counterflow virtual impactor (GCVI) and a PM2.5 impactor, was developed and employed to investigate the particle number size distributions (PNSDs) and chemical composition for cloud-free (CF), cloud interstitial (CI), and cloud residual (CR) particles at Mt. Daming in the Yangtze River Delta, China, throughout a 1-month period in spring 2023. The PNSDs of CF particles were primarily characterized by a significant Aitken mode alongside a secondary accumulation mode. In contrast, CI and CR particles exhibited unimodal distribution with Aitken and accumulation modes, peaking at 56 and 220 nm, respectively. With the fast changes of PNSDs during the onset stage of the observed four typical cloud processes, it can be inferred that the critical diameters activated as cloud droplets ranging from 133–325 nm. Particularly noteworthy was the higher hygroscopicity parameter, κ value observed in CR particles (0.32±0.06), associated with a larger mass fraction of nitrate, compared to the lower κ value in CI particles (0.23±0.08), with higher fraction of black carbon. For a typical cloud process, the hygroscopicity of CI particles was found to influence cloud droplet properties, with higher κ values corresponding to lower droplet number concentration, reduced liquid water content, and smaller effective cloud droplet diameters. This suggests that these CI particles are capable of absorbing ambient water vapour, thereby restricting further droplet growth. This investigation contributes to understanding aerosol–cloud interactions by assessing the impact of aerosol particles on cloud microphysics, thus enhancing overall comprehension of these complex atmospheric dynamics. However, it is noted that long-term observations are necessary to capture more cloud processes and yield statistically significant findings.