| 16 Sep 2025
Cloud droplet number enhancement from co-condensing NH3, HNO3, and organic vapours: sensitivity study
Abstract. Semi-volatile compounds such as organics, nitrate, chloride, and ammonium are ubiquitous in atmospheric aerosols. Their gaseous precursors (organics, HNO3, HCl, NH3) co-condense with water vapour when ambient relative humidity (RH) increases, thus enhancing hygroscopic growth under sub-saturated conditions and facilitating activation as cloud condensation nuclei (CCN) to cloud droplets. In this study, we investigate the co-condensation effect on CCN activation for inorganics, organics, and their combination in a boreal forest site in autumn with our cloud parcel model that includes non-ideality of organic-inorganic mixtures. The volatility distribution of organics is highly uncertain but critically important to estimate the co-condensation effect. We compare two distinct volatility basis sets (VBS) established from experimental and modelling data at 25 °C, which we amended with a volatility bin of saturation concentration C* = 104 μg m-3, which proved to be highly relevant for CCN activation. The combined co-condensation of organics and inorganics increases CDNC by up to 52 % in simulations initialized with RH of 80 %, depending on VBS and updraft velocity during the air parcel uplifts. Non-ideality of the system is important for considering the co-condensation effect realistically. For the ideal case, the maximum CDNC enhancement due to the combined co-condensation effect is 131 % while it is 52 % for the non-ideal case. The combined enhancement in CDNC of inorganic and organic species exceeds the sum of individual effects and should be further constrained in different environments in cloud parcel models as a basis for regional and global simulations.
This study investigates the impact of co-condensation of semi-volatile organic and inorganic compounds on cloud droplet formation in a boreal forest setting. Using a cloud parcel model that incorporates non-ideal mixing behavior, the authors demonstrate that combined co-condensation can enhance cloud droplet number concentration (CDNC) by up to 52% under realistic atmospheric conditions. Notably, the combined effect exceeds the sum of individual contributions, underscoring the critical role of organic volatility distributions and environmental parameters in cloud activation. While the study presents novel and compelling findings, the scope of conditions explored remains somewhat limited. Accounting for the non-ideality of organic compounds adds valuable realism to the simulations. Given the magnitude of the observed effect, it should be detectable through closure studies, and it is hoped that modelling efforts like this will inspire and guide such observational campaigns. I recommend the manuscript for acceptance, provided the detailed comments below are adequately addressed.
Title: The title may be slightly overstated. Since only one size distribution is used and temperature is not varied, the sensitivity analysis is limited, making it difficult to draw firm conclusions about the role of different co-condensing gases. This is more like a case study.
Line 20: Replace “VBS” with “VBS distribution” for clarity.
Line 35: Köhler (1936) is cited twice in the same sentence—consider revising to avoid redundancy.
Line 41: Note that Köhler theory has also been modified to include condensable gases. See: Laaksonen, A., Korhonen, P., Kulmala, M., and Charlson, R. J. (1998): Modification of the Köhler equation to include soluble trace gases and slightly soluble substances, J. Atmos. Sci., 55, 853–862.
Line 83: Why are only organics considered? Semivolatile inorganics are also likely to evaporate and should be addressed in a similar manner.
Line 136: Typo in “Hyyitälä” – should be corrected to “Hyytiälä”.
Line 137: Is there a reference to support this assumption? A significant fraction of the semivolatile mass originates from this bin, so the assumption has a notable impact on the manuscript’s conclusions.
Line 272: Does this assumption influence the results? Although the number of larger particles is small, their volume is substantial, which could affect the partitioning of semivolatile compounds.
Lines 275–280: Some semivolatiles are already partitioned into particles at 80% RH. It would be helpful to show the aerosol size distribution before and after initial equilibration—does it still match observations? Also, the choice of updraft velocity affects semivolatile partitioning. Why is a higher updraft used at RH below 98%? While the number of simulations is limited and computational cost is a factor, the model is a box model with parameterized thermodynamics and thus full simulations should be doable.
Line 332: “Dry radius” seems incorrect here—this appears to refer to the wet radius, as water cannot be part of the dry radius definition.
Figure 6: Is the observed change related to particle size before or after initial equilibration?
Line 362: Do simulations without co-condensation include the same initial equilibration step and after that the condensation is not allowed?
Line 397: “Interestingly…”—is this truly unexpected? The smallest (or nearly smallest) activating particles are also the most diluted, so this result seems intuitive.
Line 428: “Key factors”—in practice, the sensitivity analysis in this paper only considers updraft velocity and two VBS distributions. Aerosol size distribution is not varied. What about temperature?