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Discussion papers | Copyright
https://doi.org/10.5194/acp-2018-339
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 Jun 2018

Research article | 04 Jun 2018

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Atmospheric Chemistry and Physics (ACP).

The size resolved cloud condensation nuclei (CCN) activity and its prediction based on aerosol hygroscopicity and composition in the Pearl Delta River (PRD) Region during wintertime 2014

Mingfu Cai1,2, Haobo Tan2, Chak K. Chan3, Yiming Qin4,5, Hanbing Xu1, Fei Li2, Misha I. Schurman4, Liu Li1, and Jun Zhao1 Mingfu Cai et al.
  • 1School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, and Institute of Earth Climate and Environment System, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
  • 2Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, CMA, Guangzhou 510640, China
  • 3School of Energy and Environment, City University of Hong Kong, Hong Kong, China
  • 4Hong Kong University of Science and Technology, Hong Kong, China
  • 5School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA

Abstract. A hygroscopicity-tandem differential mobility analyzer (H-TDMA), a scanning mobility CCN analyzer (SMCA), and an aerodyne high resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) were used to respectively measure the hygroscopicity, condensation nuclei activation, and chemical composition of aerosol particles at the Panyu site in the Pearl River Region during wintertime 2014. The distribution of the size-resolved cloud condensation nuclei (CCN) at four supersaturations (SS=0.1%, 0.2%, 0.4%, and 0.7%) and the aerosol particle size distribution were obtained by the SMCA. The hygroscopicity parameter κ (κCCN, κH-TDMA, and κAMS) was respectively calculated based upon the SMCA, H-TMDA, and AMS measurements. The results showed that the κH-TDMA value was slightly smaller than the κCCN one at all diameters and for particles larger than 100nm the κAMS value was significantly smaller than the others (κCCN, and κH-TDMA), which could be attributed to the underestimated hygroscopicity of the organics (κorg). The activation ratio (AR) calculated from the growth factor – probability density function (Gf-PDF) without surface tension correction was found to be lower than that from the H-TDMA measurement, due most likely to the uncorrected surface tension (σs/a) that did not consider the surfactant effects of the organic compounds. We demonstrated that better agreement between the calculated and measured AR could be obtained by adjusting σs/a. Various schemes were proposed to predict the CCN number concentration (NCCN) based on H-TDMA and AMS measurements. In general, the predicted NCCN agreed reasonably well with the corresponding measured ones using different schemes. For H-TDMA measurements, the NCCN value predicted from the real time AR measurements was slightly smaller (~6.8%) than that from the activation diameter (D50) method due to the assumed internal mixing in the D50 prediction. The NCCN values predicted from bulk PM1 were higher (~11.5%) than those from size-resolved composition measured by the AMS because a significant fraction of PM1 was composed of inorganic matter. The NCCN calculated from AMS measurement were under-predicted at 0.1% and 0.2% supersaturations, which could be due to underestimate of κorg and overestimate of σs/a. For SS=0.4% and 0.7%, slight over-predicted NCCN was found because of the internal mixing assumption. Our results highlight the need for accurately evaluating the effects of organics on both the hygroscopic parameter κ and the surface tension σ in order to accurately predict CCN activity.

Mingfu Cai et al.
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Cloud condensation nuclei (CCN) play a critical role in cloud formation which affects solar radiation and climate. We employed advanced instruments to measure aerosol hygroscopicity and chemical composition and used them to predict CCN activity. Our results found that the CCN activity was largely dependent on the hygroscopicity parameter and the surface tension of the particles. Our study highlights the need for evaluating the effects of organics in order to accurately predict CCN activity.
Cloud condensation nuclei (CCN) play a critical role in cloud formation which affects solar...
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