Aerosol hygroscopicity and cloud condensation nuclei (CCN) activity under clean conditions and polluted events during the Aerosol-CCN-Cloud Closure Experiment (AC3Exp) campaign

Monday, 15 December 2014
Fang Zhang1, Zhanqing Li2, Li Sun3, Chuanfeng Zhao1, Pucai Wang4, Yele Sun5, Yanan Li1, Junxia Li6 and Peiren Li6, (1)Beijing Normal University, College of Global Change and Earth System Science, Beijing, China, (2)Univ of Maryland College Park, College Park, MD, United States, (3)Institute of Atmospheric Physics, Beijing, China, (4)IAP Insititute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China, (5)IAP, CAS, Beijing, China, (6)Weather Modification Office of Shanxi Province, Taiyuan, China
Aerosol hygroscopicity and cloud condensation nuclei (CCN) activity under clean conditions and polluted events are investigated based on size-resolved CCN and aerosol chemical composition observations during the Aerosol-CCN-Cloud Closure Experiment (AC3Exp) campaign conducted at Xianghe, China in summer 2013. About 14-22% of aerosol particles during the campaign are of externally mixed CCN-inactive particles that cannot serve as CCN under atmospheric typical supersaturation (SS) of ~0.4%. A high sensitivity of Maximum activation fractions (MAF) to SS under polluted conditions has been observed. The pollutants can cause a maximum MAF decrease of 25%-30% (at SS=0.08%). Hygroscopicity parameter kappa (κ) are about 16%-35% lower under polluted conditions than under clean conditions for particles in accumulation size range (80-180 nm); however, for particles in nucleation or Aitken size range (30-60 nm), κ is slightly higher under polluted conditions. A non-parallel observation (NPO) CCN closure study shows low correlation coefficient between estimated and observed CCN number concentrations (NCCN). About 30%-40% uncertainties in NCCN prediction are associated with the changes of particle composition. A case study shows that CCN activation ratio (AR) increased with the increase of condensation nuclei (CN) number concentrations (NCN) in relatively clean days. In the case, AR exhibited good correlation with κchem, which is calculated from chemical volume fractions, due to particles mainly composed of soluble inorganics. On the contrary, AR declined with increase of NCN during polluted events when particles composed mostly of organics. Meanwhile, AR is closely related to f44, which is the fraction of total organic mass signal at m/z 44 and closely associated with particle organic oxidation level. Our study highlights the importance of aerosols chemical composition on determining the activation properties of aerosol particles, underlining the importance of long-term observation of CCN under different atmospheric environments, especially those with heavy pollution and high CN number concentrations.