A predictive group-contribution model for the viscosity of aqueous organic aerosol

Abstract

<p><strong>Abstract.</strong> The viscosity of primary and secondary organic aerosol (SOA) has important implications for the processing of aqueous organic aerosol phases in the atmosphere, their involvement in climate forcing, and transboundary pollution. Here we introduce a new thermodynamics-based group-contribution model, which is capable of accurately predicting the dynamic viscosity of a mixture over several orders of magnitude (~ 10<sup>−3</sup> to > 10<sup>12</sup> Pa s) as a function of temperature and mixture composition, accounting for the effect of relative humidity on aerosol water content. The mixture viscosity modelling framework builds on the thermodynamic activity coefficient model AIOMFAC (Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients) for predictions of liquid mixture non-ideality, including liquid–liquid phase separation, and the calorimetric glass transition temperature model by DeRieux et al. (2018) for pure-component viscosity values of organic components. Comparing this new model with simplified modelling approaches reveals that the group-contribution method is the most accurate in predicting mixture viscosity, although accurate pure-component viscosity predictions (and associated experimental data) are key and one of the main sources of uncertainties in current models, including the model presented here. Nonetheless, we find excellent agreement between the viscosity predictions and measurements for systems in which mixture constituents have a molar mass below 350 g mol<sup>−1</sup>. As such, we demonstrate the validity of the model in quantifying mixture viscosity for aqueous binary mixtures (glycerol, citric acid, sucrose, and trehalose), aqueous multicomponent mixtures (citric acid + sucrose and a mixture of nine dicarboxylic acids), and aqueous SOA surrogate mixtures derived from the oxidation of α-pinene, toluene, or isoprene. We also use the model to assess the expected change in SOA particle viscosity during idealized adiabatic air parcel transport from the surface to higher altitudes within the troposphere. This work demonstrates the capability and flexibility of our model in predicting the viscosity for organic mixtures of varying degrees of complexity and its applicability for modelling SOA viscosity over a wide range of temperatures and relative humidities.</p>

Kinetic modelling of formation and evaporation of SOA from NO<sub>3</sub> oxidation of pure and mixed monoterpenes

“…5). These viscosities are in the typical range for SOA under dry conditions and fall into the semi-solid phase state region (Koop et al, 2011;Shiraiwa et al, 2011;Abramson et al, 2013;Zhang et al, 2015b;Grayson et al, 2016;Gervasi et al, 2019). Using the Stokes-Einstein relation (Einstein, 1905) and an effective molecular radius of 2 nm, these viscosities correspond to bulk diffusion coefficients of 5×10 −16 to 5×10 −18 cm 2 /s at 298 K. The effective radius is approximated from geometric considerations assuming spherical molecular shape, a molar mass of 250 g/mol and density of 1.55 g/cm 3 .…”

“…The high viscosity caused by limonene oxidation products might in turn affect evaporation in the mixed precursor experiments and cause the observed non-linear effects. In a first approximation, viscosities of mixtures can be assumed to be a linear combination of the individual viscosities and follow a logarithmic mixing rule (Gervasi et al, 2019). This entails that the change in the rate of mass transport between pure compounds and their mixtures can reach orders of magnitudes.…”

Treatment of non-ideality in the multiphase model SPACCIM-Part2: Impacts on the multiphase chemical processing in deliquesced aerosol particles

“…Additionally, adequate consideration of liquid-liquid separations as well as salt formation (crystallization) in deliquesced aerosol particles is also necessary, which can potentially alter the ionic strength and acidity, and thus influence non-ideality. Moreover, model advancements are necessary by extending the database with new organic and inorganic AIOMFAC interaction parameters (Ganbavale et al, 2015;Gervasi et al, 2019).…”

“…Lastly, it has to be noted that the current version of SpactMod does not consider the latest development stage of the AIOMFAC model (Ganbavale et al, 2015;Gervasi et al, 2019). Nevertheless, it has also been observed that SPACCIM-SpactMod allows for model simulations with and without consideration of non-ideality by treating molarities as concentrations and activities, respectively.…”

Predictions of the glass transition temperature and viscosity of organic aerosols by volatility distributions

“…(1) was developed based on the training dataset containing a large number of compounds with measured C 0 (Table S1 in Supplement) and aimed to be applied in the 2D-VBS framework to predict the viscosity of SOA mixtures. For pure organic compounds with known molecular structure, viscosity can be predicted by group contribution approaches (Cao et al, 1993;Bosse, 2005;Song et al, 2016b;Gervasi et al, 2019;Rovelli et al, 2019).…”