University of Oulu

Vepsäläinen, S., Calderón, S. M., Malila, J., and Prisle, N. L.: Comparison of six approaches to predicting droplet activation of surface active aerosol – Part 1: moderately surface active organics​​​​​​​, Atmos. Chem. Phys., 22, 2669–2687, https://doi.org/10.5194/acp-22-2669-2022, 2022

Comparison of six approaches to predicting droplet activation of surface active aerosol : part 1: moderately surface active organics

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Author: Vepsäläinen, Sampo1; Calderón, Silvia M.1,2; Malila, Jussi1;
Organizations: 1Nano and Molecular Systems Research Unit, University of Oulu, P.O. Box 3000, 90014, Oulu, Finland
2Finnish Meteorological Institute, P.O. Box 1627, 70211, Kuopio, Finland
3Center for Atmospheric Research, University of Oulu, P.O. Box 4500, 90014, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022051836466
Language: English
Published: Copernicus Publications, 2022
Publish Date: 2022-05-18
Description:

Abstract

Surface active compounds (surfactants) are frequently found in atmospheric aerosols and droplets. As they adsorb to the surfaces of microscopic systems, surfactants can decrease aqueous surface tension and simultaneously deplete the bulk concentration. These processes may influence the activation of aerosols into cloud droplets and investigation of their role in cloud microphysics has been ongoing for decades. In this work, we have used six different models documented in the literature to represent surface activity in Köhler calculations of cloud droplet activation for particles consisting of one of three moderately surface active organics (malonic, succinic or glutaric acid) mixed with ammonium sulfate in varying mass ratios. For each of these organic acids, we find that the models predict comparable activation properties at small organic mass fractions in the dry particles, despite large differences in the predicted degree of bulk-to-surface partitioning. However, differences between the model predictions for the same dry particles regarding both the critical droplet diameters and supersaturations increase with the organic fraction in the particles. Comparison with available experimental data shows that models assuming complete bulk-to-surface partitioning of the moderately surface active component (total depletion of the bulk) do not adequately represent the droplet activation of particles with high organic mass fractions. When reduced droplet surface tension is also considered, these predictions somewhat improve. Models that consider partial bulk-to-surface partitioning of surface active components yield results comparable to experimental supersaturation data, even at high organic mass fractions in the particles, but predictions of the degree of organic bulk–surface partitioning strongly differ. This work highlights the need to use a thermodynamically consistent model framework to treat the surface activity of atmospheric aerosols and for firm experimental validation of model predictions across a wide range of droplet states relevant to the atmosphere.

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Series: Atmospheric chemistry and physics
ISSN: 1680-7316
ISSN-E: 1680-7324
ISSN-L: 1680-7316
Volume: 22
Pages: 2669 - 2687
DOI: 10.5194/acp-22-2669-2022
OADOI: https://oadoi.org/10.5194/acp-22-2669-2022
Type of Publication: A1 Journal article – refereed
Field of Science: 114 Physical sciences
1172 Environmental sciences
116 Chemical sciences
Subjects:
Funding: This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme, Project SURFACE (grant agreement no. 717022). The authors also gratefully acknowledge the financial contribution from the Academy of Finland (grant nos. 308238, 314175 and 335649).
EU Grant Number: (717022) SURFACE - The unexplored world of aerosol surfaces and their impacts.
Academy of Finland Grant Number: 308238
314175
335649
Detailed Information: 308238 (Academy of Finland Funding decision)
314175 (Academy of Finland Funding decision)
335649 (Academy of Finland Funding decision)
Copyright information: © Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.
  https://creativecommons.org/licenses/by/4.0/