Predicting cloud condensation nuclei number concentration based on conventional measurements of aerosol properties in the North China Plain

Yanyan Zhang; Jiangchuan Tao; Nan Ma; Ye Kuang; Zhibin Wang; Peng Cheng; Wanyun Xu; Wenda Yang; Shaobin Zhang; Chun Xiong; Wenlin Dong; Linhong Xie; Yele Sun; Pingqing Fu; Guangsheng Zhou; Yafang Cheng; Hang Su

doi:10.1016/j.scitotenv.2020.137473

Predicting cloud condensation nuclei number concentration based on conventional measurements of aerosol properties in the North China Plain

Sci Total Environ. 2020 Jun 1:719:137473. doi: 10.1016/j.scitotenv.2020.137473. Epub 2020 Feb 20.

Authors

Yanyan Zhang¹, Jiangchuan Tao², Nan Ma¹, Ye Kuang¹, Zhibin Wang³, Peng Cheng⁴, Wanyun Xu⁵, Wenda Yang⁴, Shaobin Zhang¹, Chun Xiong³, Wenlin Dong¹, Linhong Xie¹, Yele Sun⁶, Pingqing Fu⁷, Guangsheng Zhou⁵, Yafang Cheng⁸, Hang Su⁸

Affiliations

¹ Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China.
² Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China. Electronic address: taojch@jnu.edu.cn.
³ Research Center for Air Pollution and Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
⁴ Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou, China.
⁵ State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
⁶ State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
⁷ Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China.
⁸ Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz 55128, Germany.

PMID: 32126407
DOI: 10.1016/j.scitotenv.2020.137473

Abstract

Cloud condensation nuclei (CCN) play an important role in the formation and evolution of cloud droplets. However, the dataset of global CCN number concentration (N_CCN) is still scarce due to the lack of direct CCN measurements, hindering an accurate evaluation of its climate effects. Alternative approaches to determine N_CCN have thus been proposed to calculate N_CCN based on measurements of other aerosol properties, such as particle number size distribution, bulk aerosol chemical composition and aerosol optical properties. To better understand the interaction between haze pollution and climate, we performed direct CCN measurements in the winter of 2018 at the Gucheng site, a typical polluted suburban site in North China Plain (NCP). The results show that the average CCN concentrations were 3.81 × 10³ cm^-3, 5.35 × 10³ cm^-3, 9.74 × 10³ cm^-3, 1.27 × 10⁴ cm^-3, 1.44 × 10⁴ cm^-3 at measured supersaturation levels of 0.114%, 0.148%, 0.273%, 0.492% and 0.864%, respectively. Based on these observational data, we have further investigated two methods of calculating N_CCN from: (1) bulk aerosol chemical composition and particle number size distribution; (2) bulk aerosol chemical composition and aerosol optical properties. Our results showed that both methods could well reproduce the observed concentration (R² > 0.88) and variability of N_CCN with a 9% to 23% difference in the mean value. Further error analysis shows that the estimated N_CCN tends to be underestimated by about 20% during the daytime while overestimated by <10% at night compared with the measured N_CCN. These results provide quantitative instructions for the N_CCN prediction based on conventional aerosol measurements in the NCP.

Keywords: Aerosol chemical composition; Aerosol optical properties; Cloud condensation nuclei; Particle number size distribution.