Modeling the formation and evolution of secondary organic aerosol during Calnex 2010

Field studies in polluted areas over the last decade have observed large formation of secondary organic aerosol (SOA) that is often poorly captured by models. Four parameterizations for urban secondary organic aerosol (SOA), frequently used in 3D models, are evaluated using a box model representing the Los Angeles Region during the CalNex 2010 field campaign. The model SOA formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA, even with parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or with increased yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (v.5.0.1) underestimates the observed SOA mass by a factor of 25, which is consistent with many previous model-measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate volatility organic compounds (P-S/IVOCs) improves model/measurement agreement for mass concentration. The results from 3 parameterizations show large differences and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (~3 days). Reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16 – 27%, 35 – 61%, and 19 – 35%, respectively, consistent with the observed fossil fraction of urban SOA, 71(±3)%. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA, while there is likely a substantial contribution from regional biogenic SOA to the OA background. The percentage of SOA from diesel vehicle emissions is consistent with previous studies of the weekly cycle. However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies, and which is higher on weekends. A simple two-parameter model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA. An Oxidation Flow Reactor (OFR) was also deployed during CalNex. The reactor achieved equivalent atmospheric aging from hours up to several weeks. Enhancement of OA from aging showed a maximum net SOA production between 0.8–6 days of aging with net OA mass loss beyond 2 weeks. Reactor SOA mass peaked at night, in the absence of ambient photochemistry and correlated with trimethylbenzene concentrations. Reactor SOA formation was inversely correlated with ambient SOA and Ox, which along with the short-lived VOC correlation, indicates the importance of relatively reactive (OH ~0.3 day) SOA precursors in the LA-Basin. Evolution of the elemental composition in the reactor was similar to trends observed in the atmosphere (O:C vs. H:C slope ~ -0.65). The ratio of OA in the reactor output to excess CO (CO, ambient CO above regional background) vs. photochemical age is similar to previous studies at low to moderate ages and also extends to higher ages where OA loss dominates. A comparison of urban SOA formation in this study with a similar study of vehicle SOA in a tunnel supports the dominance of vehicle emissions in urban SOA. Pre-2007 SOA models underpredict SOA formation by an order of magnitude, while a more recent model performs better but overpredicts at higher ages.