Abstract. Advancements in near-explicit chemical reaction mechanisms, such as the Master Chemical Mechanism (MCM) or the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A), have enabled highly detailed simulations of atmospheric chemistry. Such simulations offer a bottom-up approach to accompany and inform laboratory chamber experiments of organic aerosol formation or to model the complex chemistry of mixtures of volatile aerosol precursors for specific tropospheric conditions. These chemical reaction mechanisms, while comprehensive, generate hundreds to millions of organic components, creating computational challenges for subsequent applications in multiphase equilibrium gas–particle partitioning models to predict secondary organic aerosol (SOA) mass concentrations, phase compositions, and hygroscopicity. The wealth of simulated reactions and components also requires substantial simplifications for reduced-complexity representations in large-scale atmospheric models. This study introduces a suite of software tools to automate relevant pure-component property predictions as well as a 2-dimensional (2D) polarity–volatility lumping framework to systematically reduce the complexity of chemical mechanism outputs. We introduce a new polarity metric for use in the 2D framework, a ratio of a component's activity coefficients in water and an organic solvent (hexanediol). This ratio is computed using the Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model. The 2D framework offers grid-based and cluster-based methods to select an adjustable number of surrogate species and offers flexibility in the choice of polarity axis. Our methods utilize the Simplified Molecular Input Line Entry System (SMILES) description of molecular structures. A new tool, SMILES to AIOMFAC subgroups (S2AS), is introduced to automatically generate AIOMFAC-model input files and to handle exception cases consistently. We demonstrate the application of our framework using systems of hundreds to thousands of components generated by near-explicit chemical mechanisms. The new framework enables tailored reduced-complexity representations of gas–particle systems.

The phase state of fine particles (PM2.5) critically governs gas-particle partitioning and multiphase chemical reactivity, yet remains poorly constrained under real-world conditions. In this study, optical microscopy, poke-and-flow experiments, and thermodynamic modeling were combined to examine the phase behavior of wintertime urban PM2.5 collected in Ansan, South Korea. Morphological analyses revealed humidity- and composition-dependent transitions, with liquid-liquid and liquid-liquid-solid states frequently observed in individual particles. Polluted, nitrate-rich aerosols predominantly exhibited liquid-like morphology and followed near-equilibrium partitioning of nitrate and ammonium. In contrast, cleaner, organic-rich particles likely exhibited higher viscosity and nonliquid characteristics, which may have led to partial deviation from equilibrium predictions. These results provide direct experimental evidence of phase complexity in ambient PM2.5 and demonstrate that the particle phase state, modulated by relative humidity and composition, plays a critical role in determining thermodynamic behavior and atmospheric reactivity of urban aerosols.

Atmospheric aerosol droplets have large surface-area-to-volume ratios, leading to bulk-to-surface partitioning. This partitioning affects both the surface tension and water activity of aerosol when strong surfactants are present. The Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model predicts the water activity of solutions containing mixtures of inorganic ions and organic species using a group contribution approach. However, AIOMFAC predictions for the water activity of solutions containing strong surfactants have not been validated against experimental measurements. Here, the water activities of solutions containing strong, nonionic surfactants and their mixtures with NaCl are compared against AIOMFAC model predictions. For molecules with a polyethylene glycol (PEG)-like tail, using the oxyethylene subgroup outperforms an alternative ether and alkyl subgroup approach for representing the repeating molecular substructure. This model-measurement comparison shows the importance of selecting appropriate subgroup descriptions to provide the most accurate predictions of water activity, which could improve predictions of cloud droplet activation.

Liquid–liquid phase separation (LLPS) of atmospheric aerosols can significantly impact climate, air quality, and human health. However, their complex composition, small size, and history-dependent properties result in great uncertainty in the modeling of aerosol phase state and atmospheric processes. Herein, using cryogenic transmission electron microscopy (cryo-TEM), we examined model submicron aerosols composed of organic compounds and ammonium sulfate, and established a parameterization for the separation relative humidity (SRH) that accounts for chemical composition, particle size, and equilibration time. We evaluated different variables that describe chemical composition: O/C ratio, partition coefficient, solubility, molar mass, and polarizability. The O/C ratio fits the SRH of micrometer droplets best, and by using a scaling factor to translate the micrometer SRH parameterization to submicron aerosols, we incorporate the effects of size and equilibration time. The measured scaling factor for the submicron mean SRH (30nm – 1𝜇m, 20 min equilibration times) is 0.80, the factor becomes 1 with equilibration time over 1 hour, and is equal to 0, meaning that SRH is absent, when the aerosol dry diameter is smaller than 30 nm. Our parameterization will aid in universal SRH modeling, potentially leading to more accurate predictions of aerosol mass, optical properties, hygroscopicity, and heterogeneous chemistry.

Atmospheric aerosol particles span orders of magnitude in size. In ultrafine particles, the energetic contributions of surfaces and interfaces to the Gibbs energy become significant and increase in importance as particle diameter decreases. For these particles, the thermodynamic equilibrium state depends on size, composition, and temperature. Various aerosol systems have been observed to undergo liquid–liquid phase separation (LLPS), impacting equilibrium gas–particle partitioning, modifying physicochemical properties of the particle phases, and influencing cloud droplet activation. Numerous laboratory experiments have characterized the onset relative humidity of LLPS in larger aerosol particles and macroscopic bulk systems. However, in sufficiently small particles, the interfacial tension between two liquid phases constitutes an energetic barrier that may prevent the formation of an additional liquid phase. Determining said small-size limit is a key question. We introduce a predictive droplet model based on the Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model. This model enables size-dependent computations of surface and interfacial tension effects on bulk–surface partitioning within phase-separated and single-phase particles. We evaluate four approaches for computing interfacial tension in multicomponent droplets, including a new method introduced in this work. Of the approaches tested, Antonov's rule best matches observed liquid–liquid interfacial tensions in highly immiscible mixtures, while a modified Butler equation fits well in more miscible systems. We find that two approaches substantially lower the onset relative humidity of LLPS for the studied systems.

Organosulfates (OS) are emerging as a prominent secondary organic aerosol component, which can significantly alter the physicochemical properties and thus broader impacts of atmospheric aerosols. Despite their importance, OS-containing mixtures have yet to be studied using a detailed thermodynamic model which can account for the nonideal mixing among all species. In this work, we have extended the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model, a robust thermodynamic model that predicts activity coefficients in aerosol mixtures, to support OS-containing mixtures, including solving for the partial dissociation of OS. Simultaneously, we have extended AIOMFAC to support the partial dissociation of dicarboxylic acids (DA). DA are a prevalent class of compounds in tropospheric aerosols, whose pH-dependent dissociation can significantly impact aerosol physicochemical properties. We show that, for simple OS-containing and DA-containing systems, AIOMFAC is able to predict water activity and acidity (pH) behaviors that are physically reasonable and agree well with measurements, including new water activity and pH measurements performed for this study. To date, partial dissociation support in AIOMFAC is limited to select OS (methyl sulfate, ethyl sulfate, isoprene-OS-3, and isoprene-OS-4) and select DA (malonic acid, succinic acid, and glutaric acid) in simple single-phase mixtures. However, as more thermodynamic data become available, AIOMFAC's treatment of organic acids can be further refined and expanded, enabling it to predict how the partial dissociation of organic acids affects the physicochemical properties of realistic multicomponent, multiphase aerosol systems.

Atmospheric aerosols are complex mixtures of highly functionalized organic compounds, water, inorganic electrolytes, metals, and carbonaceous species. The surface properties of atmospheric aerosol particles can influence several of their chemical and physical impacts, including their hygroscopic growth, aerosol-cloud interactions, and heterogeneous chemical reactions. The effects of the various compounds within a particle on its surface tension depend in part on the pure-component surface tensions. For many of the myriad of organic compounds of interest, experimental pure-component surface tension data at tropospheric temperatures are lacking, thus, requiring the development and application of property estimation methods. In this work, a compiled database of experimental pure-component surface tension data, covering a wide range of organic compound classes and temperatures, is used to train four different types of machine learning models to predict the temperature-dependent pure-component surface tensions of atmospherically relevant organic compounds. The trained models process input information about the temperature and the molecular structure of an organic compound, initially in the form of a Simplified Molecular Input Line Entry System (SMILES) string, to enable predictions. Our quantitative model assessment shows that extreme gradient-boosted descent along with Molecular ACCess System (MACCS) key descriptors of molecular structure provided the best balance of derived input complexity and model performance, resulting in a root-mean-square error (RMSE) of ∼1 mJ m-2 in pure-component surface tension. Additionally, a simplified model based on molar mass, elemental ratios, and temperature as inputs was developed for use in applications for which molecular structure information is incomplete (RMSE of ∼2 mJ m-2). We demonstrate that including predicted pure-component surface tension values in thermodynamically rigorous bulk-surface partitioning calculations may substantially modify the critical supersaturations necessary for aerosol activation into cloud droplets.

Understanding the viscosity and phase state of biomass-burning organic aerosol (BBOA) from wildfires and pyrocumulonimbus (pyroCb) events in the stratosphere is critical for predicting their role in stratospheric multiphase chemistry and ozone depletion. However, the viscosity and phase state of BBOA under stratospheric conditions, including interactions with sulfuric acid (H₂SO₄), remain largely unquantified. In this study, we combine laboratory data with a thermodynamic model to predict the viscosity and phase state of BBOA under stratospheric conditions. Our results suggest that BBOA with a H₂SO₄-to-BBOA mass ratio of 0.37—an estimated upper limit for pyroCb smoke in the lower stratosphere after two months of aging— is highly viscous and frequently exists in a glassy state. Even at a higher H₂SO₄-to-BBOA mass ratio of 0.79 – an estimated upper limit after nine months of aging – BBOA can still transition to a glassy state under certain stratospheric conditions. In the glassy state, bulk reactions are suppressed, and multiphase chemistry may be limited to the particle surfaces. We also highlight key areas for future research needed to better constrain the viscosity and phase state of BBOA in the stratosphere and its subsequent impact on ozone.

Atmospheric organic aerosol (OA) mass concentrations can be affected by water uptake through its impact on the gas–particle partitioning of semi-volatile compounds. Current chemical transport models (CTMs) neglect this process. We have implemented the Binary Activity Thermodynamics model coupled to a volatility basis set partitioning scheme in the GEOS-Chem CTM, providing an efficient reduced-complexity OA model that predicts relative-humidity-dependent mixing and partitioning thermodynamics, while limiting the impact on computational efficiency. We provide a quantitative assessment of this water-sensitive OA treatment, focusing on a subdomain over North America. The updated OA scheme predicts a spatiotemporal mean enhancement in surface-level OA mass concentration of 145 % for January 2019 and 76 % for July 2019 compared to GEOS-Chem's most advanced OA scheme. The temporal mean surface-level OA organic mass concentration can increase by up to ∼590 % for January 2019 and ∼280 % for July 2019, with the greatest enhancements occurring over the ocean. The updated OA scheme also quantifies the OA-associated water content. The simulations show how different OA precursors and related OA surrogates contribute and respond to water uptake, including that due to changes in temperature and relative humidity over the diurnal cycle in selected winter and summer months. These results are independent of future CTM improvements involving updates to chemical reaction schemes and emission inventories. Our water-sensitive OA scheme allows for a better representation of the seasonal and regional variations in OA mass concentration in CTMs.

Accurate surface tension measurements are key to understanding and predicting the behavior of atmospheric aerosols, particularly their formation, growth, and phase transitions. In Earth's atmosphere, aerosols often exist in metastable states, such as being supercooled or supersaturated. Standard tensiometry instruments face challenges in accessing these states due to the large sample volumes they require and rapid phase changes near surfaces. We present an instrument that uses a strong electric field, nearing the dielectric strength of air, to deform aerosol microdroplets and measure surface tension in a contact-free, humidity-controlled environment. A dual-beam optical trap holds single microdroplets between two electrodes and excites Raman scattering. When a high voltage is applied, droplet deformations reach tens of nanometers. These small shape changes are precisely measured through the splitting of morphology-dependent resonances, seen as sharp peaks in Raman spectra. Our measurements cover water activities where droplets are supersaturated, a region with limited previous data, and show good agreement with existing data where comparisons are possible. Unlike prior levitation-based methods, this approach measures surface tension in systems with viscosities over 102 Pa s without relying on dynamic processes.

In Northeast Asia, the elevated levels of fine particulate matter (PM2.5) are an environmental concern, yet their physicochemical properties have been poorly characterized. Herein, we determined the phase states of PM2.5 in 92 filter samples collected from four different cities & horbar;Beijing, Seoul, Seosan, and Ulaanbaatar & horbar;during 2020-2022, within a temperature range of similar to 290-293 K. We noted a distinct trend in the boundary relative humidity (RH) of liquid and semisolid phases within these PM2.5 samples. As the inorganic fraction increased, the RH of the liquid phase decreased, whereas that of the semisolid phase increased. This behavior was strongly influenced by the chemical composition of PM2.5. By incorporating ambient RH data from each city, we estimated the prevalent PM2.5 phase states within the planetary boundary layer of Northeast Asia. Our findings revealed that the dominant phase states of PM2.5 in these urban areas were liquid and semisolid. Additionally, we showed a critical threshold based on the aerosol liquid water content (ALWC) in PM2.5: a primarily liquid phase for ALWC/PM2.5 ratios of >=similar to 0.5 and a predominantly semisolid phase for ALWC/PM2.5 ratios of <similar to 0.5. These insights could contribute to a better understanding of the mechanisms underlying aerosol pollution in Northeast Asia.

Abstract Aerosol water affects the physicochemical properties and mass concentration of organic aerosols (OA), but it is typically omitted by air quality, weather, and climate models. We compare two classes of simplified models to estimate the OA water uptake and gas–particle partitioning of organic compounds. One class uses a single‐hygroscopicity‐parameter (κ) approach while the other is based on the reduced‐complexity Binary Activity Thermodynamics (BAT) model. We show that a BAT‐based two‐dimensional volatility basis set (VBS) model always predicts a higher OA mass concentration at elevated relative humidity (RH), for example, ∼16% at 80% RH, than any variation of the κ‐based method considered—even when BAT‐VBS predicts a lower water uptake. The main reason being that the BAT‐VBS model captures variations in effective saturation mass concentration of organics (C*) with RH, a feature that other VBS methods lack. The BAT‐VBS framework offers an efficient, RH‐sensitive treatment for reduced‐complexity OA modeling.

Liquid–liquid phase separation (LLPS) is a thermodynamically driven process that occurs in mixtures of low miscibility material.

Direct Numerical Simulation (DNS) of turbulent cloud parcels are presented where particles evolve in response to the local values in supersaturation (s) led by turbulent fluctuations. A pseudo-spectral DNS is modified to incorporate aerosol particles and Cloud Condensation Nuclei (CCN) activation applying a droplet growth equation based on κ-Köhler theory that works for the whole range of warm cloud particles, from un-activated deliquesced aerosol particles to activated cloud droplets, that grow by condensation. The Lagrangian microphysics applied ensures that each particle experiences a supersaturation (fluctuations added to the mean) corresponding to its near-particle gas phase surroundings, which differs from the uniform parcel view where an average value of supersaturation, s¯, is applied to every particle in the domain. A non-turbulent Lagrangian parcel model with similar mean thermodynamics and CCN properties is compared with turbulent DNS parcels of varying fluctuation intensities to distinguish the impact of turbulence on CCN activation. It is shown that, in a given distribution, a subset of aerosols respond to fluctuations rather than the mean thermodynamics allowing particles of similar dry size to co-exist as un-activated haze particles as well as cloud droplets. The cloud microphysical properties are analysed in a series of DNS experiments with contrasting thermodynamic and aerosol properties. DNS results agrees with the general understanding of aerosol activation and cloud droplets evolution in response to various background conditions such as pristine and polluted aerosol distributions, composition of CCN with respect to organic - inorganic components and magnitude of vertical velocity. DNS considers turbulence-microphysics interactions in such problems providing additional knowledge on the role of turbulence in clouds. It is argued that incorporating turbulent fluctuations in simulating the CCN activation and droplet growth is well reasoned and a constructive way forward.

Liquid–liquid phase separation (LLPS) in aerosol particles is important for the climate system due to its potential to impact heterogeneous chemistry, cloud condensation nuclei, and new particle growth. Our group and others have shown a lower separation relative humidity for submicron particles, but whether the suppression is due to thermodynamics or kinetics is unclear. Herein, we characterize the experimental LLPS phase diagram of submicron 2-methylglutaric acid and ammonium sulfate aerosol particles and compare it to that of supermicron-sized particles. Surprisingly, as the equilibration time of submicron-sized aerosol particles was increased to 60 min, the experimental phase diagram converges with the results for supermicron-sized particles. Our findings indicate that nucleation kinetics are responsible for the observed lower separation relative humidities in submicron aerosol particles. Therefore, experiments and models that investigate atmospheric processes of Aitken and accumulation mode organic aerosol particles may need to consider the temporal evolution of aerosol LLPS.

Biomass burning (BB) is a major source of aerosols and black carbon, thereby exerting an important impact on climate and air quality. Levoglucosan is the most well-recognized organic marker compound of BB and has been used to quantitatively assess BB's contribution to ambient aerosols. However, little is known about levoglucosan's evaporation under atmospheric conditions, primarily due to the uncertainty of its effective saturation vapor concentration (C*) and its unknown activity coefficient (gamma), in the complex BB emission matrix. Here, we utilized a thermodenuder to investigate the evaporation of levoglucosan from mixtures with polyethylene glycol (PEG) or BB primary organic aerosol (BBPOA) matrices, respectively. We estimate a pure component log10(C*/[mu g m-3]) of levoglucosan of 1.1 +/- 0.1 at 298 K. We reveal that levoglucosan mixed with PEG or BBPOA becomes more volatile than when treated as a single component due to nonideal molecular interactions. Considering that phase separation might occur in such systems, we term gamma apparent activity coefficient (gamma a ). We estimate log10 C* and gamma a of levoglucosan in BBPOA of 1.8 +/- 0.1 and 3.8 +/- 0.3, assuming a liquid phase state. Consequently, gamma a must be considered to avoid significant underestimation of levoglucosan evaporation via gas-particle partitioning during transport.

The viscosity of aerosol particles determines the critical mixing time of gas-particle partitioning of volatile compounds in the atmosphere. The partitioning of the semi-volatile ammonium nitrate (NH4NO3) might alter the viscosity of highly viscous secondary organic aerosol particles during their lifetimes. In contrast to the viscosity of organic particles, data on the viscosity of internally mixed inorganic-organic aerosol particles are scarce. We determined the viscosity of an aqueous ternary inorganic-organic system consisting of NH4NO3 and a proxy compound for a highly viscous organic, sucrose. Three techniques were applied to cover the atmospherically relevant humidity range: viscometry, fluorescence recovery after photobleaching, and the poke-flow technique. We show that the viscosity of NH4NO3-sucrose-H2O with an organic to inorganic dry mass ratio of 4:1 is 4 orders of magnitude lower than the viscosity of the aqueous sucrose under low-humidity conditions (30 % relative humidity (RH), 293 K). By comparing viscosity predictions of mixing rules with those of the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients Viscosity (AIOMFAC-VISC) model, we found that a mixing rule based on mole fractions performs similarly when data from corresponding binary aqueous subsystems are available. Applying this mixing rule, we estimated the characteristic internal mixing time of aerosol particles, indicating significantly faster mixing for inorganic-organic mixtures compared to electrolyte-free particles, especially at lower RH. Hence, the assumption in global atmospheric chemistry models of quasi-instantaneous equilibrium gas-particle partitioning is reasonable for internally mixed single-phase particles containing dissolved electrolytes (but not necessarily for phase-separated particles), for most conditions in the planetary boundary layer. Further data are needed to see whether this assumption holds for the entire troposphere at midlatitudes and at RH > 35 %.