Modeling Ambient Oxidation of Aerosol Oleic Acid with Bayesian Statistics.

The heterogeneous oxidation of organic aerosols (OA) is a critical atmospheric process, but predictive modeling is hindered by a lack of ambient decay kinetic data and an undefined quantitative relationship with environmental variables. Using unsaturated fatty acids (uFAs) as model OA compounds, we determined the ambient decay rates of oleic, elaidic, and linoleic acids from long-term measurements at two sites in Shanghai, China. The decay rates showed minimal seasonal variations despite significant shifts in temperature, ozone, and initial uFA concentrations and OA matrix. Analysis revealed a distinct temperature dependence of uFA decay rates that differed across temperature regimes, corroborating previous observations alongside a compound influence from other environmental parameters. By applying Bayesian statistical calibration, we derived quantitative parametrizations for oleic acid decay rates specific to each temperature regime. OC exerts a suppressive effect on reaction rates, especially at low temperatures, whereas the influence of reactant concentrations becomes increasingly important at higher temperatures. The results advance the mechanistic understanding of uFA heterogeneous oxidations and provide a robust, observationally constrained framework for improving model parametrizations of OA aging under realistic atmospheric conditions.