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 1Department of Civil & Environmental Engineering, Portland State University, Portland, Oregon 2Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey 3Department of Civil & Environmental Engineering, Washington State University, Pullman, Washington
Abstract. Despite 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, a "best
available" set of SOA modeling parameters is selected by comparing
predicted SOA yields and mass concentrations with observed yields and mass
concentrations from a comprehensive list of published smog chamber studies.
Evaluated SOA model parameters include existing parameters for two product
(2p) and volatility basis set (VBS) modeling frameworks, and new 2p-VBS
parameters; 2p-VBS parameters are developed to exploit advantages of the VBS
approach within the computationally-economical and widely-used 2p framework.
Fine particulate matter (PM2.5) and SOA mass concentrations are
simulated for the continental United States using CMAQv.4.7.1; results are
compared for a base case (with default CMAQ parameters) and two best
available parameter cases to illustrate the high- and low-NOx limits of
biogenic SOA formation from monoterpenes. Results are discussed in terms of
implications for current chemical transport model simulations and
recommendations are provided for future modeling and measurement efforts.
The comparisons of SOA yield predictions with data from 22 published chamber
studies illustrate that: (1) SOA yields for naphthalene, and cyclic and
> C5 straight-chain/branched alkanes are not well represented
using either the newly developed or existing parameters for low-yield
aromatics and lumped alkanes, respectively; and (2) for four of seven
volatile organic compound+oxidant systems, the 2p-VBS parameters better
represent chamber data than do the default CMAQ v.4.7.1 parameters. 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 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. Percent bias between model-based and observationally-based
secondary organic carbon (SOC) improved from −63% for the base case to
−15% for the low-NOx case. The ability to robustly assign "best
available" parameters in all volatile organic compound+oxidant systems,
however, is critically limited due to insufficient data; particularly for
photo-oxidation of diverse monoterpenes, sesquiterpenes, and alkanes under a
range of atmospherically relevant conditions.
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., 13, 12073-12088, doi:10.5194/acp-13-12073-2013, 2013.