Modelling the influence of biogenic SOA precursor volatility on aerosol forcing

Secondary organic aerosol (SOA) plays a significant role in atmospheric processes, influencing particulate matter, air quality, and global climate. The volatility basis set (VBS) framework facilitates simulating the large number of SOA species by grouping SOA precursors based on volatility, thus reducing computational challenges. However, volatilities of SOA forming vapors are inadequately constrained in global climate models, causing uncertainties in predicted aerosol mass loads and climate effects. Using a process-scale particle growth model and a global climate model, we analyse the sensitivity of simulated cloud condensation nuclei (CCN) and SOA mass concentrations to the volatility distribution of SOA precursor gases from monoterpenes emitted by boreal trees. Our findings reveal that uncertainties in the volatilities of condensing organic vapors significantly affect particle growth rates and CCN survival in the process-scale model. Global model simulations show less sensitivity in CCN and cloud droplet number concentration (CDNC). A one order of magnitude shifts in volatility results in a 13% increase or a 9% decrease in SOA mass concentration over the boreal region. Furthermore, the study compares a finely resolved 9-bin VBS setup and a coarser 3-bin VBS setup, highlighting the importance of accurately representing saturation concentration values for volatility bins, especially in global models with reduced bin numbers. In addition, the study found that the radiative forcing attributed to changes in SOA is notably more sensitive to the volatility distribution of semi-volatile compounds than low-volatile compounds. This underscores the need for improved representations of semi-volatile compounds in global scale models to accurately predict aerosol loads and subsequent climate effects.