Model-Measurement Comparisons for Surfactant-Containing Aerosol Droplets

Abstract

Surfactants are important components of atmospheric aerosols, potentially impacting their hygroscopic growth and eventual activation into cloud droplets. By adsorbing at the air−water interface, surfactants lower the surface tension of aqueous systems. However, in microscopic aerosol droplets, the bulk surfactant concentration can become depleted because of the droplets' high surfacearea-to-volume ratio, reducing the bulk surfactant concentration at equilibrium and increasing droplet surface tension. Partitioning models have been developed to account for the concentration-and size-dependencies of surface tension, but these models have rarely been assessed against experimentally measured droplet surface tensions. Here, we directly compare surface tension predictions made using a simple kinetic partitioning model and a thermodynamic monolayer partitioning model against experimentally measured picoliter droplet surface tensions for 12 surfactant− cosolute systems. Surface tension predictions were also made across 8 orders of magnitude in droplet radius. The largest differences between model predictions were associated with the predicted onset of bulk depletion. The quality of the isotherm or parametrization fit to the macroscopic data most strongly influenced a model's ability to accurately predict droplet surface tension. These results highlight the importance of validating partitioning models against droplet surface tension measurements in size ranges where bulk depletion is expected to occur and motivate collection of high-quality macroscopic surface tension data sets that serve as model inputs. The results also validate both models' abilities to predict aerosol surface tension across size and composition, which will facilitate their eventual incorporation into cloud parcel models to explore the impact of surface tension assumptions on cloud droplet number concentration.