Implementation of a parallel reduction algorithm in the GENerator of reduced Organic Aerosol mechanisms (GENOA v2.0): Application to multiple monoterpene aerosol precursors

Explicit gas-phase chemical mechanisms represent the state of knowledge regarding the chemistry of volatile organic compounds (VOCs), which are crucial in the formation of secondary organic aerosols (SOAs). However, these chemical mechanisms are computationally expensive, which limits their practical use in large-scale air quality modeling. Mechanism reduction is therefore required for computational efficiency while preserving the accuracy of the detailed gas-phase chemical mechanisms. This paper presents a new version of the Generator of Reduced Organic Aerosol Mechanisms (GENOA v2.0), which reduces mechanisms at a size suitable for three-dimensional (3-D) modeling while preserving the accuracy of detailed chemical mechanisms for simulating aerosol concentrations. GENOA v2.0 adopts a parallel reduction framework to identify the most optimal reductions from competitive candidates, and can reduce chemical mechanisms from multiple aerosol precursors. To demonstrate the reduction efficiency, GENOA v2.0 is applied to the reduction of monoterpene chemistry from the Master Chemical Mechanism (MCM) combined with the Peroxy Radical Autoxidation Mechanism (PRAM) mechanism. The original mechanism, consisting of 3 001 reactions and 1 227 species (including 738 condensable species), is reduced by 93% to 197 reactions and 110 species (including 23 condensable species), inducing an average error of only 3% in aerosol concentrations. Sensitivity tests showed that this reduced mechanism behaved similarly to the original mechanism in response to changes in environmental conditions such as temperature, relative humidity, and SOA mass loading. Moreover, if the error tolerance is increased to 20% — which can still be acceptable for 3-D air quality modeling — the mechanism can be further simplified to 40 reactions and 24 species (including 5 condensable species). Consequently, the GENOA-generated aerosol mechanism preserves the complexity of the detailed gas-phase chemical mechanisms on SOA formation while increasing computational efficiency, which makes it suitable for most environmental conditions encountered in the atmosphere.