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The scattering of light by aerosol particles dictates atmospheric visibility, which is a straightforward indicator of air quality. It is affected by numerous factors, such as particle number size distribution, particle mass concentration (PM2.5), ambient relative humidity (RH), and chemical composition. The latter two factors jointly influence the aerosol liquid water content (ALWC). Here, the particle backscattering coefficient (βp) under ambient RH conditions is investigated to differentiate and quantify the contributions of aerosol properties and meteorology using comprehensive observational datasets acquired at three megacities in China, that is, Beijing (BJ), Nanjing (NJ), and Guangzhou (GZ). Overall, the temporal variations in βp under ambient RH conditions are consistent with those in ALWC at the three sites. The PM2.5 in BJ is systematically higher than in NJ and GZ, while ambient RH and aerosol hygroscopicity in NJ are much higher than in BJ and GZ. Notable differences in the variations of βp with related factors at the three sites are demonstrated. βp is more sensitive to particle hygroscopicity and mass in NJ and ambient RH in BJ. The relative contributions of these factors to βp at the three sites under different pollution conditions are differentiated and quantified. The factor with the largest impact on the variability in βp shifts from particle mass to ambient RH as air quality deteriorated to heavy pollution in BJ. The opposite is true in NJ. In GZ, the contributions of these factors to changes in βp under different pollution conditions are similar, both dominated by PM2.5. Plain Language Summary: Scattering of light by aerosol is a straightforward measure of air quality because of its close link to visibility. It is dictated primarily by aerosol mass loading, size distribution, chemical composition, and humidity. We used comprehensive observational datasets acquired at three sites in China to differentiate and quantify the contributions to the scattering of light by aerosol loading measured by aerosol particulate mass and aerosol properties, as well as humidity. The findings differ among the three cities due to differences in aerosol properties and meteorology. Scattering of light by aerosol is more sensitive to particle hygroscopicity and mass concentration in Nanjing and more sensitive to ambient humidity in Beijing. Local emission control measures can effectively reduce aerosol mass concentrations in Nanjing and Guangzhou. Weather conditions are more influential in Beijing due to the dominant influence of humidity. Key Points: This study differentially quantifies the impacts of aerosol loading and properties and meteorology on scattering at three sites in ChinaScattering of light by aerosol is most sensitive to particle hygroscopicity and mass in Nanjing and humidity in BeijingHumidity substantially affects scattering during heavy haze in Beijing, whereas particle mass is more impactful in Nanjing and Guangzhou [ABSTRACT FROM AUTHOR]

The evolution of haze, involving multiple processes such as nucleation, coagulation, and condensation, may exert complex effects on aerosols' cloud condensation nuclei (CCN) activity and number concentration (NCCN). Based on field campaigns carried out in the winters of 2014 and 2016 in Beijing, we show that NCCN was significantly enhanced by the evolution of haze, substantially driven by the nucleation process (or new particle formation). The enhancement factor of NCCN by such nucleation‐initiated haze episodes, E_NCCN, defined as the ratio of NCCN after haze events to NCCN prior to haze events, ranged from 2.2 to 6.5 at a supersaturation (S) = 0.76% and from 4.2 to 17.3 at S = 0.23%, the magnitude of which partially depends on the severity of the haze event. The enhancements are much greater than those previously observed and those from model simulations of contribution from new particle formation. This suggests that CCN sources from new particle formation may be underestimated, needing reevaluation in polluted environments where the subsequent growth of newly formed particles can last 2–3 days, yielding more CCN‐sized particles. We further quantified that the changes in particle size and composition during the nucleation‐initiated evolution of haze are responsible for > 80% and 12–20%, respectively, of the enhancement in CCN activity. The changes in particle composition had a limited impact because most of the ambient particles were already hydrophilic, with hygroscopic parameters of 0.2–0.65. Key Points: Nucleation‐initiated haze events lead to more CCN‐sized particlesThe effects of changes in particle size and composition on CCN activity during the evolution of haze events are quantifiedThe source of CCN from new particle formation needs reevaluation in polluted regions where the subsequent growth of nucleated particles may last 2–3 days [ABSTRACT FROM AUTHOR]

In this study, we report the phenomenon of fast changes in aerosol hygroscopicity between clean and polluted periods observed frequently in urban Beijing during winter using a hygroscopicity tandem mobility analyzer. The cause of this phenomenon and the formation process of particles in different modes are discussed. During clean periods, ultrafine‐mode particles (i.e., nucleation and Aitken modes) stem mainly from nucleation events with subsequent growth. During heavily polluted periods, ultrafine‐mode particles originate chiefly from primary emissions. Larger‐mode particles like accumulation‐mode particles are mainly from primary emissions during clean periods and aqueous reactions during polluted periods. This finding based on hygroscopicity tandem mobility analyzer measurements can make up the deficiency of mass‐dependent instruments in analyzing sources and chemical processes of ultrafine‐mode particles. Plain Language Summary: The mass concentration of ultrafine‐mode particles in the atmosphere is extremely low, and their properties are rarely investigated using instruments specialized in measuring such things. The hygroscopicity tandem mobility analyzer makes it possible to study sources and chemical processes of ultrafine‐mode particles. They were measured in terms of aerosol number concentration, and aerosol hygroscopicity indirectly reflects aerosol chemical compositions. The properties of ultrafine‐ and accumulation‐mode particles differed considerably between clean and polluted urban environments. Investigated were their different formation processes. Key Points: Aerosol hygroscopicity changes quickly between clean and polluted periods in BeijingUltrafine‐mode particles stem chiefly from nucleation in clean environments and from primary emissions in polluted environmentsUltrafine‐ and accumulation‐mode particles have distinct properties in urban environments [ABSTRACT FROM AUTHOR]

This study investigates aerosol hygroscopicity, mixing state, and cloud condensation nucleation as part of the Atmosphere-Aerosol-Boundary Layer-Cloud Interaction Joint Experiment performed in the summer of 2016 at Xingtai (XT), a suburban site located in the center of the North China Plain (NCP). In general, the probability density function (PDF) of the hygroscopicity parameter (κ) for 40-200 nm particles had a unimodal distribution, and mean κ-PDF patterns for different sizes were similar, suggesting that the particles were highly aged and internally mixed because of strong photochemical reactions. The κ calculated from the hygroscopic growth factor in the daytime and at night suggests that photochemical reactions largely enhanced the aerosol hygroscopicity. This effect became weaker as the particle size increased. In addition, the aerosol hygroscopicity was much larger at XT than at other sites in the NCP. This is because new particle formation takes place much more frequently in the central NCP, which is heavily polluted from industrial activities, than elsewhere in the region. The evolution of the planetary boundary layer played a dominant role in dictating aerosol mass concentration. Particle size was the most important factor influencing the ability of aerosols to activate, whereas the effect of chemical composition was secondary, especially when supersaturation was high. Using a fixed value of κ D 0:31 to calculate the cloud condensation nuclei number concentration in this region suffices. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]