Abstract
Abstract. Understanding the impacts of aerosol chemical composition and mixing state on cloud condensation nuclei (CCN) activity in polluted areas is crucial for accurately predicting CCN number concentrations (NCCN). In this study, we predict NCCN under five assumed schemes of aerosol chemical composition and mixing state based on field measurements in Beijing during the winter of 2016. Our results show that the best closure is achieved with the assumption of size dependent chemical composition for which sulfate, nitrate, secondary organic aerosols, and aged black carbon are internally mixed with each other but externally mixed with primary organic aerosol and fresh black carbon (external–internal size-resolved, abbreviated as EI–SR scheme). The resulting ratios of predicted-to-measured NCCN (RCCN_p∕m) were 0.90 – 0.98 under both clean and polluted conditions. Assumption of an internal mixture and bulk chemical composition (INT–BK scheme) shows good closure with RCCN_p∕m of 1.0 –1.16 under clean conditions, implying that it is adequate for CCN prediction in continental clean regions. On polluted days, assuming the aerosol is internally mixed and has a chemical composition that is size dependent (INT–SR scheme) achieves better closure than the INT–BK scheme due to the heterogeneity and variation in particle composition at different sizes. The improved closure achieved using the EI–SR and INT–SR assumptions highlight the importance of measuring size-resolved chemical composition for CCN predictions in polluted regions. NCCN is significantly underestimated (with RCCN_p∕m of 0.66 – 0.75) when using the schemes of external mixtures with bulk (EXT–BK scheme) or size-resolved composition (EXT–SR scheme), implying that primary particles experience rapid aging and physical mixing processes in urban Beijing. However, our results show that the aerosol mixing state plays a minor role in CCN prediction when the κorg exceeds 0.1.
Highlights
Atmospheric aerosol particles can serve as cloud condensation nuclei (CCN) and, in turn, affect the optical and microphysical properties of clouds (Twomey, 1977; Albrecht, 1989; Charlson et al, 1992)
The peak amplitude in the particle number size distribution (PNSD) that occurs from about 08:00 to 12:00 LT is probably associated with secondary formation processes, which is indicated by an apparent increase of nitrate, secondary organic aerosol (SOA), and f44 in the morning (08:00 LT) when photochemistry becomes significant
The PNSD amplitude and black carbon (BC) and primary organic aerosol (POA) concentrations are high at nighttime, suggesting an influence from the diurnal variation of the planetary boundary layer (PBL) height
Summary
Atmospheric aerosol particles can serve as cloud condensation nuclei (CCN) and, in turn, affect the optical and microphysical properties of clouds (Twomey, 1977; Albrecht, 1989; Charlson et al, 1992). Variations in mixing state impact NCCN prediction, with the effect dependent on the hygroscopicity of the organic component (Wang et al, 2010). Some studies have shown that detailed information about the chemical composition and the mixing state is required because of the complexity of the hygroscopicity of organics (Broekhuizen et al, 2006; Bhattu and Tripathi, 2015) and the differences in the CCN activity between fresh and aged aerosols (Gunthe et al, 2011). The impact of different assumptions concerning the mixing state and chemical composition on accurately quantifying CCN concentrations needs further investigation, especially in heavily polluted regions. The sensitivity of predicted NCCN to the particle mixing state and organic volume fraction with the aging of organic particles is presented in the last section of the study
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