Abstract. Molecular markers are organic compounds used to represent known sources of particulate matter (PM) in statistical source apportionment studies. The utility of molecular markers depends on, among other things, their ability to represent PM volatility under realistic atmospheric conditions. We measured the particle-phase concentrations and temperature-induced volatility of commonly-used molecular markers in California's heavily polluted San Joaqin Valley. Concentrations of elemental carbon, organic carbon, levoglucosan, and polycyclic aromatic hydrocarbons were not reduced by mild (~10 K) heating. In contrast, both hopane/sterane and n-alkane concentrations were reduced, especially during the summer sampling events at the urban site. These results suggest that hopanes and steranes have effective saturation concentrations ~1 μg m⁻³, and therefore can be considered semi-volatile. The volatility of an individual compound depends both on its inherent properties (primarily vapour pressure) and the interactions between itself and any potential absorbing phase. The volatility behavior of n-alkanes during the urban summer is consistent with that predicted for absorption by suberic acid (a C₈ diacid) using a group contribution modelling method. Observations can also be matched by an absorbent whose composition is based on recently-obtained high-resolution aerosol mass spectrometer factors (approximately 33% "hydrocarbon-like" and 67% oxygenated organic aerosol). The reduced evaporation of the n-alkanes, hopanes, and steranes with mild heating during rural and/or winter experiments could be explained by a more oxygenated absorbing phase along with a non-absorptive partitioning mechanism, such as adsorption to soot. This suggests that the temperature-induced volatility of large hydrocarbons in PM is most important if a relatively non-polar absorbing organic phase exists. While the activity coefficients of most organic aerosol compounds may be close to unity, the assumption of ideality for large hydrocarbons (e.g., hopanes) may result in large errors in partitioning calculations.