The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy

Abstract

Abstract. Atmospheric aerosols influence the climate via cloud droplet nucleation and can facilitate the long-range transport of harmful pollutants. The lifetime of such aerosols can therefore determine their environmental impact. Fatty acids are found in organic aerosol emissions with oleic acid, an unsaturated fatty acid, being a large contributor to cooking emissions. As a surfactant, oleic acid can self-organise into nanostructured lamellar bilayers with its sodium salt, and this self-organisation can influence reaction kinetics. We developed a kinetic multi-layer model-based description of decay data we obtained from laboratory experiments of the ozonolysis of coated films of this self-organised system, demonstrating a decreased diffusivity for both oleic acid and ozone due to lamellar bilayer formation. Diffusivity was further inhibited by a viscous oligomer product forming in the surface layers of the film. Our results indicate that nanostructure formation can increase the reactive half-life of oleic acid by an order of days at typical indoor and outdoor atmospheric ozone concentrations. We are now able to place nanostructure formation in an atmospherically meaningful and quantifiable context. These results have implications for the transport of harmful pollutants and the climate.

The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy

“…The underlying experimental and model data are available at https://doi.org/10.5281/zenodo.6421940 (Milsom et al, 2022b).…”

The evolution of surface structure during simulated atmospheric ageing of nano-scale coatings of an organic surfactant aerosol proxy

“…23 Kinetic modelling of these experiments has shown that the chemical lifetime of oleic acid could increase by days upon selforganisation. 30 Many of these studies have suggested the persistence of reacted and/or unreacted organic materials aer chemical ageingsomething we observe and discuss here.…”

“…10,20,21 This makes it a suitable proxy compound for laboratory and model investigations into reactive organic aerosol systems. [22][23][24][25][26][27][28][29][30] The oleic acid-ozone heterogeneous oxidation system is well-studied and a simplied summary of the principal reaction and products is presented in Scheme 1. 28 As a surfactant, oleic acid can decrease the surface tension of an aqueous particle, affecting the ability of the particle to take up water and form a cloud droplet.…”

MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films

“…In particular, those based on the Pöschl-Rudich-Ammann (PRA) framework (Pöschl et al, 2007) such as the kinetic multi-layer model of surface and bulk chemistry (KM-SUB) (Shiraiwa et al, 2010) and the kinetic multilayer model of gas-particle interactions (KM-GAP) (Shiraiwa et al, 2012) have been applied in a wide range of studies, providing particle-level insights which are often not possible to obtain experimentally. For example, KM-SUB models have highlighted the impact of crust formation and viscosity on particle and film reaction kinetics, lengthening the chemical lifetime of particle and film constituents with potential impacts on the climate, air pollution and human health (Milsom et al, 2022b;Mu et al, 2018;Pfrang et al, 2011;Zhou et al, 2019). KM-GAP has been coupled with the aerosol inorganic-organic-mixture functional-group activity coefficients (AIOMFAC) thermodynamic model (Zuend et al, 2008(Zuend et al, , 2011 to calculate equilibration timescales be-A.…”

“…This paper describes MultilayerPy, a package written in Python, which is designed to facilitate the creation and optimisation of kinetic multi-layer models (namely KM-SUB and KM-GAP) in a modular and reproducible way. The key features are presented along with use cases focussing on the well-studied oleic-acid-ozone heterogeneous reaction system (Berkemeier et al, 2021;Gallimore et al, 2017;King et al, 2004King et al, , 2020Milsom et al, 2021bMilsom et al, , a, 2022bPfrang et al, 2011Pfrang et al, , 2017Woden et al, 2021;Zahardis and Petrucci, 2007). An educational tool has recently been created which creates and runs simple kinetic multi-layer models with two reactants (Hua et al, 2022).…”