Towards automated inclusion of autoxidation chemistry in models: from precursors to atmospheric implications

In the last few decades, atmospheric formation of secondary organic aerosols (SOA) has gained increasing attention due to their impact on air quality and climate. However, methods to predict their abundance are mainly empirical and may fail under real atmospheric conditions. In this work, a close-to-mechanistic approach allowing SOA quantification is presented, with a focus on a chain-like chemical reaction called “autoxidation”. A novel framework is employed to (a) describe the gas-phase chemistry, (b) predict the products' molecular structures and (c) explore the contribution of autoxidation chemistry on SOA formation under various conditions. As a proof of concept, the method is applied to benzene, an important anthropogenic SOA precursor. Our results suggest autoxidation to explain up to 100% of the benzene-SOA formed under low-NO_x laboratory conditions. Under atmospheric-like day-time conditions, the calculated benzene-aerosol mass continuously forms, as expected based on prior work. Additionally, a prompt increase, driven by the NO₃ radical, is predicted by the model at dawn.