10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
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Modeling the Formation and Composition of Secondary Organic Aerosol in Oxidation Flow Reactors Using Simple and Detailed Chemistry and Thermodynamic Models
Sailaja Eluri, Christopher Cappa, Beth Friedman, Delphine Farmer, SHANTANU JATHAR, Colorado State University
Abstract Number: 1344 Working Group: Oxidation Flow Reactor: Development, Characterization, and Application to Aerosols
Abstract Oxidation flow reactors (OFRs) are being increasingly used to study the photochemical production of secondary organic aerosol from both anthropogenic and natural sources. Compared to environmental chambers, OFRs are smaller, easier to operate, allow for much longer photochemical exposures, and are less susceptible to gas and particle wall losses. Yet, there are concerns that high oxidant concentrations and kinetic limitations to gas/particle partitioning may affect the formation and composition of SOA in OFRs. Hence, there is a need to develop and use modeling tools to interpret OFR data and facilitate translation of OFR results to the real atmosphere.
Recently our group reported on experiments that used an OFR to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel) and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the volatility basis set (VBS) model and the statistical oxidation model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility and volatile organic compounds (SVOC, IVOC and VOC); multigenerational gas-phase chemistry; and kinetic gas/particle partitioning. Both models suggested that for model predictions of SOA mass to agree with measurements across all engine load-fuel-aftertreatment combinations, it was necessary to model the kinetically-limited gas-particle partitioning in OFRs as well as account for SOA formation from IVOCs. IVOCs were found to account for more than 90% of the model-predicted SOA but accounting for them resulted in an under-prediction of a factor of two for OA atomic oxygen-to-carbon ratios. Model predictions of the gas-phase organic compounds, resolved in carbon and oxygen space, from the SOM compared favorably to gas-phase measurements from a Chemical Ionization Mass Spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model-measurement comparisons were improved on using vapor wall-loss corrected SOA parameterizations but remained insensitive to OFR-specific parameters such as residence time distributions and spatial heterogeneity in oxidant concentrations.
As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret OFR data.