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Autoxidation is a 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 may appear 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 for constraining 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 data. Results show the ability to recover 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 to allow analysis of evolving systems is part of ongoing work.
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Pichelstorfer et al. (2025) studied this question.
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