EGU23-13194
https://doi.org/10.5194/egusphere-egu23-13194
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

MultilayerPy: a tool for creating and optimising multi-layer models of aerosol and film processes

Adam Milsom1, Amy Lees2, Adam Squires3, and Christian Pfrang1
Adam Milsom et al.
  • 1University of Birmingham, Geography, Earth and Environmental Sciences, United Kingdom (a.milsom.2@bham.ac.uk)
  • 2University of York, York, United Kingdom
  • 3Department of Chemistry, University of Bath, Bath, United Kingdom

Heterogeneous processes such as aerosol-gas chemical reactions and vapour uptake are key to understanding the behaviour of aerosols in our environment. They contribute to their ability to take up water to form cloud droplets and determine the persistence of harmful particle-bound compounds, impacting the climate and human health.

Kinetic multi-layer models such as the kinetic multi-layer model for aerosol surface and bulk chemistry (KM-SUB) and gas-particle interactions (KM-GAP) are state-of-the-art models used to describe these processes on the particle and film level (Shiraiwa et al., 2010, 2012). KM-SUB and KM-GAP-based models have been used to determine the oxidative potential of particulate matter, the impact of surfactant self-organisation on aerosol chemical lifetimes, and the impact of aerosol phase state on the long-range transport of toxic chemicals. These models are useful but cumbersome to write and there is a need for an open-source tool to assist researchers in creating and optimising them.

We have developed MultilayerPy (Milsom et al., 2022), an open-source Python package which facilitates the creation and optimisation of kinetic multi-layer models. This software is written such that the user uses building blocks (i.e. reaction scheme, bulk diffusion parameterisations, and model components) to automatically generate model code which can then be ran and the output presented in a reproducible manner. This reduces the time needed to develop model descriptions of aerosol processes and allows the user to focus on the scientific issues rather than coding the models. I will present recent use cases of the software looking at the chemical lifetime of real aerosol material in the atmosphere, along with ongoing work extending the base package.

References:

Milsom, A., Lees, A., Squires, A. M. and Pfrang, C.: MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films, Geosci. Model Dev., 15(18), 7139–7151, doi:10.5194/gmd-15-7139-2022, 2022.

Shiraiwa, M., Pfrang, C. and Pöschl, U.: Kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB): The influence of interfacial transport and bulk diffusion on the oxidation of oleic acid by ozone, Atmos. Chem. Phys., 10, 3673–3691, doi:10.5194/acp-10-3673-2010, 2010.

Shiraiwa, M., Pfrang, C., Koop, T. and Pöschl, U.: Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): Linking condensation, evaporation and chemical reactions of organics, oxidants and water, Atmos. Chem. Phys., 12(5), 2777–2794, doi:10.5194/acp-12-2777-2012, 2012.

How to cite: Milsom, A., Lees, A., Squires, A., and Pfrang, C.: MultilayerPy: a tool for creating and optimising multi-layer models of aerosol and film processes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13194, https://doi.org/10.5194/egusphere-egu23-13194, 2023.

Supplementary materials

Supplementary material file