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Published March 9, 2016 | Supplemental Material + Published
Journal Article Open

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses


The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the University of California at Davis / California Institute of Technology (UCD/CIT) regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall-loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with "low" and one with "high" vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from volatile organic compounds (VOCs) in both domains, by factors of  ∼  2–5 for the low and  ∼  5–10 for the high scenarios. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total organic aerosol (OA) increases from  ∼  0.2 (no) to  ∼  0.5 (low) and to  ∼  0.7 (high), with the high vapor wall-loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA ∕ ΔCO ratio captures the influence of dilution on SOA concentrations. The simulated OA ∕ ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall-loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O : C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H : C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O : C and H : C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model–measurement discrepancies.

Additional Information

© Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 License. Received: 02 Nov 2015 – Published in Atmos. Chem. Phys. Discuss.: 25 Nov 2015. Revised: 17 Feb 2016 – Accepted: 23 Feb 2016 – Published: 04 Mar 2016. The authors thank Pedro Campuzano-Jost for the SEAC4RS data. This study was funded by the California Air Resources Board, contract 12-312 and NOAA grant NA13OAR4310058. Jose L. Jimenez was supported by CARB 11-305 and EPA STAR 83587701-0. This manuscript has not been reviewed by the funding agencies and no endorsement should be inferred. Author contributions. The manuscript was written through contributions of all authors. Christopher D. Cappa, Shantanu H. Jathar, Michael J. Kleeman, John H. Seinfeld and Anthony S. Wexler designed the project. Shantanu H. Jathar and Michael J. Kleeman carried out the simulations. Christopher D. Cappa determined model parameters using laboratory data collected by John H. Seinfeld. Kenneth S. Docherty and Jose L. Jimenez collected and processed the SOAR data. All authors have given approval to the final version of the manuscript.

Attached Files

Published - acp-16-3041-2016.pdf

Supplemental Material - acp-16-3041-2016-supplement.pdf


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