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

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.