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 the glass transition temperature (Tg) of
an organic compound containing carbon, hydrogen, and oxygen. Based on
analysis of over 2400 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. This prediction method of Tg is applied to ambient
observations of volatility distributions at 11 field sites. The
predicted Tg values of OA under dry conditions vary mainly from 290 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 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 (AMS) data. The predicted viscosity of
oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived
from α-pinene, toluene, isoprene epoxydiol (IEPOX), and 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.