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Activation of biomass burning aerosols (BBA) and fossil fuel combustion aerosols (FFA) in fogs and clouds significantly impact regional air quality through aqueous chemistry and climate by affecting cloud microphysics. However, we lack direct observations of how these aerosols behave in fogs and clouds. Using a newly developed aerosol‐cloud sampling system, we conducted observations during fog events and found that BBA, despite their high organic content, effectively contributed to super‐micron interstitial aerosols and fog droplets in low supersaturation fogs. In contrast, FFA, predominantly externally mixed organic, did not grow beyond the super‐micron size in fogs due to their near‐hydrophobic nature. Measurements conducted under supersaturations relevant for cloud formation revealed that portions of FFA could serve as cloud condensation nuclei, but only when supersaturation exceeded ∼0.14%. These findings have broad implications for future investigations into the influence of BBA and FFA on fog and cloud chemistry and their interactions with clouds. Plain Language Summary: Tiny particles, known as aerosols, emitted from combustion of biomass and fossil fuels, can impact air quality and global climate by interacting with fog and clouds. However, we lack direct observational evidence of how these aerosols behave in these conditions. In our study, we developed an advanced aerosol‐cloud sampling system to observe aerosol activation during fog events. Our findings highlight a crucial factor of aerosol activation: the mixing of these aerosols. Biomass burning aerosols with an internal mixture of organic and inorganic components activate more easily, even in conditions with low supersaturation like fog. In contrast, fossil fuel combustion aerosols are often externally mixed and almost water‐repellent, requiring higher supersaturation to become cloud condensation nuclei. Understanding these distinctions has significant implications for regional air quality and the intricate interactions between aerosols and clouds. By gaining insights into how various aerosols interact with fog and clouds, we can enhance our understanding of their impact on our environment and climate. Key Points: Advanced Aerosol‐Cloud sampling system was developed to characterize aerosol activation in fogsBiomass burning aerosols efficiently form fog droplets, while fossil fuel combustion aerosols are almost hydrophobic and don't contributeFossil fuel combustion organic aerosols can serve as CCN in high supersaturation conditions (>0.14%) [ABSTRACT FROM AUTHOR]

The commercial continuous‐flow streamwise thermal‐gradient cloud condensation nuclei (CCN) counter is widely used in aerosol CCN activity measurements which are critical for investigating aerosol‐cloud interactions. In CCN measurements, a critical threshold is needed for distinguishing interstitial aerosols and activated droplets, and a default threshold of 0.75 μm was set in CCN counter. Theoretically, interstitial aerosols could also grow larger than 0.75 μm in CCN counter at low supersaturations, thus theoretical thresholds derived from the Köhler theory were suggested. Here, we report that droplet growth in the CCN counter is kinetically limited and CCN‐active droplets does not reach their theoretical diameters under low supersaturations. Neglecting the kinetic growth limitation in CCN identification would count less CCN and underestimate the aerosol hygroscopicity parameter κ $\kappa $ by up to 50% for supersaturations lower than 0.1%. We recommend that thresholds considering kinetic limitations should be used as new criteria for CCN identification under low supersaturations. Plain Language Summary: Accurate Cloud Condensation Nuclei (CCN) predictions in climate and regional models are crucial for the assessment of climate effects of aerosol‐cloud interactions. Direct measurements of CCN activity, varied by aerosol size, hygroscopicity, and supersaturation, are important for model verifications and improvements. The commercial continuous‐flow streamwise thermal‐gradient CCN counter (CCNC) is widely used in CCN activity measurements. We found that the droplet growth in the CCNC is kinetically limited under low supersaturations (<0.14%), thus not reaching the theoretical critical activation diameter, which significantly affect CCN identification. Kinetic model results revealed that the wet diameter thresholds of CCN identification that took the kinetic limitations of droplet growth into account were independent of dry aerosol size and hygroscopicity thus could be directly used as new criteria for CCN identification. Neglecting the kinetic growth limitation in CCN identification would result in significant bias in CCN activity measurements and thus supersaturated aerosol hygroscopicity retrievals. Findings of this research have significant impacts on CCN activity measurements and supersaturated aerosol hygroscopicity investigations. Key Points: Limited hygroscopic growth of cloud condensation nuclei (CCN) in CCN counter is recognized and evaluated based on model analysisKinetic limitations in CCN counter impacts significantly on size‐resolved CCN activity measurementsKinetic limitations in CCN counter impacts significantly on aerosol hygroscopicity measurements under low supersaturation [ABSTRACT FROM AUTHOR]

Parameterization of the size-resolved particle activation ratio (AR) is useful for the prediction and analysis of the cloud condensation nuclei (CCN) number concentration ( N CCN ). Critical issues for the application of AR parameterizations in models are (1) the consistency of the different parameterization schemes in terms of fitting AR curves and (2) the applicability of the estimate of N CCN under different aerosol conditions. These issues are discussed in this study based on summertime measurements of the size-resolved AR in the North China Plain. By comparing parameterized AR curves, variations in the fitting parameters and application to N CCN calculations, the consistency of the three existing parameterization schemes is confirmed. Based on an analysis using representative AR fitting parameters, the method commonly used to calculate N CCN with a fixed AR was found to be accurate, except during periods affected by strong black carbon (BC) emissions or new particle formation (NPF) events. The N CCN value was overestimated by approximately 10% when BC aerosol emissions were abundant and deviated from the 1:1 line by 15% during NPF events. The bias of the calculated N CCN due to these significant emission or aerosol production events cannot be eliminated by using the appropriate representative fitting parameters. Under these circumstances, accurate prediction of N CCN requires real-time aerosol hygroscopicity data based on CCN measurements. This research furthers our understanding of the relationship between aerosol cloud activation and aerosol spectra. [ABSTRACT FROM AUTHOR]