Modeling secondary organic aerosol using a dynamic partitioning approach incorporating particle aqueous-phase chemistry

Current air quality model (AQM) systems use either an Odum-type two-product or a volatility basis set (VBS) approach to predict secondary organic aerosol (SOA) formation from toluene oxidation. For the SOA module in AQM systems, the stoichiometric and partitioning coefficients used in both these approaches are typically developed from laboratory studies conducted in a single chamber, under a limited set of conditions (e.g., low humidity and initial (NH4)2SO4 seed), and with an implicit assumption of instantaneous thermodynamic equilibrium. In this study, we evaluated independent toluene laboratory studies that include experiments with different combinations of initial toluene, NOx, non-SOA-forming hydrocarbon mixture, initial seed type, and humidity. When evaluated against this observational data set both the Odum-type and VBS approaches fail to predict observed SOA when tested under dry conditions, in the presence of the hydrocarbon mixture, and with low initial seed mass, regardless of seed type. For wet experiments, predictions of temporal trends in aerosol mass growth from both approaches are inconsistent with observations; this is especially true earlier in the day under high humidity conditions. Based on these findings, a new SOA mechanism is developed that includes: 1) gas-phase reaction of semi-volatile products and a dynamic partitioning approach with accommodation coefficient as the principal transport parameter, 2) an additional pathway of SOA formation due to uptake of polar species into the particle aqueous-phase. The new mechanism improves predicted SOA mass reproducing observations from all experiments. Since these changes were made exclusively to existing algorithms in SOA modules, minimal modifications would be required to update air quality models to utilize this approach.