Preprints
https://doi.org/10.5194/egusphere-2022-1188
https://doi.org/10.5194/egusphere-2022-1188
02 Jan 2023
 | 02 Jan 2023

Comparison of six approaches to predicting droplet activation of surface active aerosol – Part 2: strong surfactants

Sampo Vepsäläinen, Silvia M. Calderón, and Nønne L. Prisle

Abstract. Surfactants have been a focus of investigation in atmospheric sciences for decades due to their ability to modify the water uptake and cloud formation potential of aerosols. Surfactants adsorb to the air–solution interface and can decrease the surface tension, while in microscopic aqueous droplets simultaneously depleting the droplet bulk. While this mechanism is now broadly accepted, the representation in atmospheric and cloud droplet models is still not well constrained. We compare the predictions of five bulk–surface partitioning models and a general bulk solution model documented in the literature to represent aerosol surface activity in Köhler calculations of cloud droplet activation. The models are applied to a suite of common aerosol particle systems, consisting of strong surfactants (sodium myristate or myristic acid) and sodium chloride in a wide range of relative mixing ratios. The partitioning models predict comparable critical droplet properties at small surfactant mass fractions, but differences between the model predictions for identical particles increase significantly with the surfactant mass fraction in the particles. For the same particles and simulation conditions, the partitioning models also predict significantly different surface compositions and surface tensions for growing droplets along the Köhler curves. The inter-model variation is furthermore different for these particles comprising strongly surface active organics, than for moderately surface active atmospheric aerosol components. Our results show that experimental validation across a range of atmospherically relevant aerosol compositions, surface active properties, and droplet states is necessary before a given model can be generally applied in atmospheric predictions.

Sampo Vepsäläinen et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1188', Anonymous Referee #2, 21 Mar 2023
  • RC2: 'Comment on egusphere-2022-1188', Anonymous Referee #3, 24 Mar 2023
  • AC1: 'Author response to reviewers’ comments: egusphere-2022-1188', Sampo Vepsäläinen, 30 May 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1188', Anonymous Referee #2, 21 Mar 2023
  • RC2: 'Comment on egusphere-2022-1188', Anonymous Referee #3, 24 Mar 2023
  • AC1: 'Author response to reviewers’ comments: egusphere-2022-1188', Sampo Vepsäläinen, 30 May 2023

Sampo Vepsäläinen et al.

Sampo Vepsäläinen et al.

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Latest update: 29 Nov 2023
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Short summary
Atmospheric aerosols act as seeds for cloud formation. Many aerosols contain surface active material that accumulates at the surface of growing droplets. This can affect cloud droplet activation, but the broad significance of the effect and the best way to model it are still debated. We compare predictions of six models to surface activity of strongly surface active aerosol and find significant differences between the models, especially with large fractions of surfactant in the dry particles.