Modeling the Formation and Composition of Secondary Organic Aerosol from Diesel Exhaust Using Parameterized and Semi-Explicit Chemistry and Thermodynamic Models

Abstract

11Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photo-oxidized in 12 the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary 13 organic aerosol (POA). Jathar et al. (2017) recently reported on experiments that used an oxidation flow reactor (OFR) to 14 measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel 15 types (diesel, biodiesel) and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In 16 this work, we used two different SOA models, the volatility basis set (VBS) model and the statistical oxidation model (SOM), 17 to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based 18 parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, 19intermediate-volatility and volatile organic compounds (SVOC, IVOC and VOC); multigenerational gas-phase chemistry; and 20 kinetic gas/particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with 21 measurements across all engine load-fuel-aftertreatment combinations, it was necessary to model the kinetically-limited gas-22 particle partitioning in OFRs as well as account for SOA formation from IVOCs, which were found to account for more than 23 90% of the model-predicted SOA. Accounting for IVOCs however resulted in an under-prediction of a factor of two for OA 24 atomic O:C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the 25 SOM compared favorably to gas-phase measurements from a Chemical Ionization Mass Spectrometer (CIMS), substantiating 26 the semi-explicit chemistry captured by the SOM. Model-measurement comparisons were improved on using vapor wall-loss 27 corrected SOA parameterizations. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field 28 environments, models such as those developed in this work can be used to interpret the OFR data. 29 30