Atmos. Chem. Phys. Discuss., 13, 15907-15947, 2013
www.atmos-chem-phys-discuss.net/13/15907/2013/
doi:10.5194/acpd-13-15907-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Analyzing experimental data and model parameters: implications for predictions of SOA using chemical transport models
K. C. Barsanti1, A. G. Carlton2, and S. H. Chung3
1Portland State University, Portland, Oregon, USA
2Rutgers University, New Brunswick, New Jersey, USA
3Washington State University, Pullman, Washington, USA

Abstract. Despite the critical importance for air quality and climate predictions, accurate representation of secondary organic aerosol (SOA) formation remains elusive. An essential addition to the ongoing discussion of improving model predictions is an acknowledgement of the linkages between experimental conditions, parameter optimization and model output, as well as the linkage between empirically-derived partitioning parameters and the physicochemical properties of SOA they represent in models. In this work, advantages of the volatility basis set (VBS) modeling approach are exploited to develop parameters for use in the computationally-efficient and widely-used two product (2p) SOA modeling framework, standard in chemical transport models such as CMAQ (Community Multiscale Air Quality) and GEOS-Chem (Goddard Earth Observing System–Chemistry). Calculated SOA yields and mass loadings obtained using the newly-developed 2p-VBS parameters and existing 2p and VBS parameters are compared with observed yields and mass loadings from a comprehensive list of published smog chamber studies to determine a "best available" set of SOA modeling parameters. SOA and PM2.5 levels are simulated using CMAQv.4.7.1; results are compared for a base case (with default 2p CMAQ parameters) and two "best available" parameter cases chosen to illustrate the high- and low-NOx limits of biogenic SOA formation from monoterpenes. Comparisons of published smog chamber data with SOA yield predictions illustrate that: (1) SOA yields for naphthalene and cyclic and > C5 alkanes are not well represented using either newly developed (2p-VBS) or existing (2p and VBS) parameters for low-yield aromatics and lumped alkanes, respectively; and (2) for 4 of 7 volatile organic compound + oxidant systems, the 2p-VBS parameters better represent existing data. Using the "best available" parameters (combination of published 2p and newly derived 2p-VBS), predicted SOA mass and PM2.5 concentrations increase by up to 10–15% and 7%, respectively, for the high-NOx case and up to 215% (~ 3 μg m−3) and 55%, respectively, for the low-NOx case. The ability to robustly assign "best available" parameters, however, is limited due to insufficient data for photo-oxidation of diverse monoterpenes and sesquiterpenes under a variety of atmospherically relevant NOx conditions. These results are discussed in terms of implications for current chemical transport model simulations and recommendations are provided for future measurement and modeling efforts.

Citation: Barsanti, K. C., Carlton, A. G., and Chung, S. H.: Analyzing experimental data and model parameters: implications for predictions of SOA using chemical transport models, Atmos. Chem. Phys. Discuss., 13, 15907-15947, doi:10.5194/acpd-13-15907-2013, 2013.
 
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