- QUAN LIU, X. Shen, Lei Li, Junying Sun, Zirui Liu, Weibin Zhu, J. Zhong, Yangmei Zhang, Xinyao Hu, Shuo Liu, H. Che, Xiaoye Zhang. 2023. Impacts of Aerosol Chemical Composition on Cloud Condensation Nuclei (CCN) Activity during Wintertime in Beijing, China. Abstract: The cloud condensation nuclei (CCN) activity and aerosol chemical composition were concurrently measured via a scanning mobility CCN analyzer (SMCA) and an Aerodyne Time-of-Flight Aerosol Chemical Speciation Monitor (ACSM), respectively, during wintertime 2022 in Beijing, China. During the observation period, the mean CCN number concentrations ranged from 1345 ± 1270 cm−3 at SS = 0.1% to 3267 ± 2325 cm−3 at SS = 0.3%. The mean critical activation diameters (D50) at SS = 0.1%, 0.2%, and 0.3% were 172 ± 13 nm, 102 ± 8 nm, and 84 ± 7 nm, corresponding to the average hygroscopicity parameters (κCCN) of 0.34, 0.33, and 0.26, respectively. The diurnal variations in D50 suggested that the local primary emissions significantly enhanced D50 at SS = 0.2% and 0.3%, but had less influence on D50 at SS = 0.1% due to the limited size (<150 nm) of particles emitted from primary sources. As PM2.5 concentration increases, the dominant driver of CCN activity transitions from sulfate to nitrate. At a specific SS, D50 decreased with increases in the degree of internal mixing, implying that the elevated internal mixing degree during atmospheric aging was beneficial to CCN activation. In this study, the commonly used f44 (or O:C) was weakly correlated with κorg and failed to describe the variations in κorg. Instead, the variations in κorg can be well parameterized with the Org/BC ratio. The correlation between κ derived from bulk chemical compositions and CCN measurements was substantially improved when this κorg scheme was adopted, emphasizing the importance of considering κorg variations on deriving κchem from aerosol chemical composition.
