Modeling kinetic partitioning of secondary organic aerosol and size distribution dynamics: representing effects of volatility, phase state, and particle-phase reaction
- 1Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
- 2Division of Chemistry and Chemical Engineering and Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA
Abstract. This paper describes and evaluates a new framework for modeling kinetic gas-particle partitioning of secondary organic aerosol (SOA) that takes into account diffusion and chemical reaction within the particle phase. The framework uses a combination of (a) an analytical quasi-steady-state treatment for the diffusion–reaction process within the particle phase for fast-reacting organic solutes, and (b) a two-film theory approach for slow- and nonreacting solutes. The framework is amenable for use in regional and global atmospheric models, although it currently awaits specification of the various gas- and particle-phase chemistries and the related physicochemical properties that are important for SOA formation. Here, the new framework is implemented in the computationally efficient Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) to investigate the competitive growth dynamics of the Aitken and accumulation mode particles. Results show that the timescale of SOA partitioning and the associated size distribution dynamics depend on the complex interplay between organic solute volatility, particle-phase bulk diffusivity, and particle-phase reactivity (as exemplified by a pseudo-first-order reaction rate constant), each of which can vary over several orders of magnitude. In general, the timescale of SOA partitioning increases with increase in volatility and decrease in bulk diffusivity and rate constant. At the same time, the shape of the aerosol size distribution displays appreciable narrowing with decrease in volatility and bulk diffusivity and increase in rate constant. A proper representation of these physicochemical processes and parameters is needed in the next generation models to reliably predict not only the total SOA mass, but also its composition- and number-diameter distributions, all of which together determine the overall optical and cloud-nucleating properties.