1Engineering and Public Policy, Carnegie Mellon University, Pittsburgh PA, USA
2Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh PA, USA
3Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh PA, USA
4Mechanical Engineering, Carnegie Mellon University, Pittsburgh PA, USA
Abstract. We present a methodology to model secondary organic aerosol (SOA) formation from the photo-oxidation of low-volatility organics (semi-volatile and intermediate volatility organic compounds). The model is parameterized and tested using SOA data collected during two field campaigns that characterized the atmospheric evolution of dilute gas-turbine engine emissions using a smog chamber. Photo-oxidation formed a significant amount of SOA, much of which cannot be explained based on the emissions of traditional, speciated precursors; we refer to this as non-traditional SOA (NT-SOA). The NT-SOA can be explained by emissions of low-volatility organic vapors measured using sorbents. Since these vapors could not be speciated, we employ a volatility-based approach to model NT-SOA formation. We show that the method proposed by Robinson et al. (2007) is unable to explain the timing of NT-SOA formation because it assumes a very modest reduction in volatility of the precursors with every oxidation reaction. In contrast, a Hybrid method, similar to models of traditional SOA formation, assumes a larger reduction in volatility with each oxidation step and results in a better reproduction of NT-SOA formation. The NT-SOA yields estimated for the low-volatility organic vapor emissions are similar to literature data for large n-alkanes and other low-volatility organics. The yields vary with fuel composition (JP8 versus Fischer-Tropsch) and engine load (idle versus non-idle). These differences are consistent with the expected contribution of high (aromatics and n-alkanes) and low (branched alkanes and oxygenated species) SOA forming species to the exhaust.