Preprints
https://doi.org/10.5194/ar-2024-40
https://doi.org/10.5194/ar-2024-40
16 Dec 2024
 | 16 Dec 2024
Status: this preprint is currently under review for the journal AR.

Theory informed, experiment based, constraint on the rate of autoxidation chemistry – An analytical approach

Lukas Pichelstorfer, Simon P. O'Meara, and Gordon B. McFiggans

Abstract. Autoxidation is key process that transforms volatile organic compounds into condensable species, thereby significantly contributing to the formation and growth of airborne particles. Given the enormous complexity of this chemistry, explicit reaction mechanisms describing autoxidation of the multitude of atmospherically relevant precursors seem out of reach.

The present work suggests an alternative solution path: based on theoretically suggested key reaction types and the recent advances in mass spectroscopy, an analytically-based approach to constrain lumped autoxidation reaction schemes is presented. Here, the method is used to equip an autoxidation reaction scheme for α-pinene with rate coefficients based on the interpretation of simulated mass-spectral data. Results show the capability of recovering the rate coefficients with a maximum error of less than 1 % for all reaction types. The process is automated and capable of determining roughly 103 rate coefficients per second when run on a PC. Currently, the method is applicable to chemical systems in a steady state, which can be established in flow reactors. However, extending the concept allowing to analyse evolving systems is part of ongoing work.

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Lukas Pichelstorfer, Simon P. O'Meara, and Gordon B. McFiggans

Status: open (until 27 Jan 2025)

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Lukas Pichelstorfer, Simon P. O'Meara, and Gordon B. McFiggans

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data for article "Theory informed, experiment based, constraint on the rate of autoxidation chemistry – An analytical approach" Lukas Pichelstorfer https://doi.org/10.5281/zenodo.14223708

Lukas Pichelstorfer, Simon P. O'Meara, and Gordon B. McFiggans
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Short summary
Quantification of autoxidation chemistry is a complex task, essential to our understanding of atmospheric secondary aerosol formation and its impact on climate. In this work, we introduce the autoCONSTRAINT module, a semi-empirical method to deduce reaction rate coefficients for lumped autoxidation chemistry schemes based on experimental data. The theoretical approach is analytical and provides mathematically correct, though non-unique, solutions with low computational cost.
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