Explicit simulation of chemical composition, size distribution and cloud condensation nuclei of the secondary organic aerosol from α-pinene oxidation

Secondary organic aerosol (SOA), formed by oxidation of volatile organic compounds and gas-particle partitioning, account for a large proportion of atmospheric submicron aerosol mass, and hence have a significant impact on clouds and global climate. The impact depends on the concentration and the cloud condensation nuclei (CCN) activity of SOA. CCN activity of SOA is determined by its particle size and hygroscopicity parameter (κ) characterizing the properties of different chemical composition. Despite a number of chamber studies on SOA formation and its CCN activity, few studies have simulated particle size and chemical composition of SOA and thus CCN concentration based on explicit chemical mechanism. To bridge this gap, in this study we used the box model PyCHAM to explicitly simulate the α-pinene ozonolysis reaction in an atmospheric reaction chamber, and compared the simulated SOA mass and number concentrations, chemical composition, particle size distribution, κ and CCN concentration with experimental measurements. In general, the simulation underestimated SOA mass concentration  and overestimated oxygen-to-carbon (O:C) and hydrogen-to-carbon (H:C), indicating the potential role of particle-phase reactions in SOA formation. The simulated SOA number concentration, particle nucleation and subsequent growth agreed well with measurement, whereas the geometric mean diameter was slightly overestimated, which partly due to the simplified microphysical processes like coagulation in the model. Moreover, the simulated κ and CCN concentration were also in consistent with measurements. This study reveals the key chemical processes that may influence SOA formation, as well as the importance of considering detailed chemical composition and particle size distribution for CCN simulations based on the explicit chemical mechanism.