Abstract. Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2300 organic compounds including oxygenated organic compounds as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. The prediction method of Tg and viscosity is applied to ambient observations of volatility distributions at eleven field sites. The predicted Tg varies mainly from 290 K to 339 K and the predicted viscosities are consistent with the results of ambient particle phase state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would be helpful to improve predictions of viscosity especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of SOA derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and of diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.;
