Study On The New Methods Of Measurement And Calculation Of Cloud Condensation Nuclei Based On The Field Observation

Cloud condensation nuclei(CCN)are the aerosol particles that can be activated to form cloud droplets under certain supersaturated conditions.The aerosol CCN activity and CCN number concentration are important factors in the study of aerosolcloud interactions(ACI)and play an important role in the indirect radiative effects of aerosols and the radiative balance of the atmosphere.Since the traditional methods of direct measurement and indirect estimation of CCN number concentration still had some defects,it is significantly important to apply new estimation methods and instrumental measurements to CCN research.In recent studies,the machine learning techniques have been applied to estimate CCN number concentration under single supersaturation,while Aerodynamic Aerosol Classifier(AAC)can be applied to measure the hygroscopic activation properties of low hygroscopic aerosol such as black carbon aerosols(BC).In this study,these two methods will be further discussed based on the field campaigns.In this study,machine learning(ML)method is applied to estimate CCN activation spectra based on four field campaigns in the North China Plain.The results show that,for the ML model trained based on the conventional observational data of aerosols,there may be systematic deviations in estimating CCN spectra parameters.The reason for the deviations including the differences of aerosol physicochemical properties and the measurement uncertainties among campaigns,and the overfit of ML model.Among the input aerosol properties variables of the ML model,the mass concentration of black carbon and aerosol hemispheric backscattering fraction at the wavelength of 450 nm are the most important variables.In addition,the aerosol optical properties dataset is more applicable than aerosol chemical properties dataset in ML model training for estimate CCN spectra.In addition,AAC is applied to the CCN size-resolved measurement of the low concentration in the Mount Hua alpine site in this study.Results show that AAC can be effectively applied to the size-resolved CCN measurement at alpine site.The observations in the autumn and winter of Mount Hua show that the diurnal variation of aerosol hygroscopicity properties and mixing state are not obvious.The main factor affecting the diurnal variation of CCN number concentration are the variations in aerosol particle number-size distribution.In addition,the total CCN number concentration calculated based on the particle size-resolved data measured by AAC is in good agreement with the directly measured total CCN concentration.