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Despite critical importance for air quality and climate predictions,accurate representation of secondary organic aerosol (SOA) formation remainselusive. An essential addition to the ongoing discussion of improving modelpredictions is an acknowledgement of the linkages between experimentalconditions, parameter optimization and model output, as well as the linkagebetween empirically-derived partitioning parameters and the physicochemicalproperties of SOA they represent in models. In this work, a "bestavailable" set of SOA modeling parameters is selected by comparingpredicted SOA yields and mass concentrations with observed yields and massconcentrations 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-VBSparameters; 2p-VBS parameters are developed to exploit advantages of the VBSapproach within the computationally-economical and widely-used 2p framework.Fine particulate matter (PM2.5) and SOA mass concentrations aresimulated for the continental United States using CMAQv.4.7.1; results arecompared for a base case (with default CMAQ parameters) and two bestavailable parameter cases to illustrate the high- and low-NOx limits ofbiogenic SOA formation from monoterpenes. Results are discussed in terms ofimplications for current chemical transport model simulations andrecommendations are provided for future modeling and measurement efforts.The comparisons of SOA yield predictions with data from 22 published chamberstudies illustrate that: (1) SOA yields for naphthalene, and cyclic and> C5 straight-chain/branched alkanes are not well representedusing either the newly developed or existing parameters for low-yieldaromatics and lumped alkanes, respectively; and (2) for four of sevenvolatile organic compound+oxidant systems, the 2p-VBS parameters betterrepresent chamber data than do the default CMAQ v.4.7.1 parameters. Usingthe "best available" parameters (combination of published 2p and newlyderived 2p-VBS), predicted SOA mass and PM2.5 concentrations increaseby up to 15% and 7%, respectively, for the high-NOx case and up to215% (~3 μg m−3) and 55%, respectively, forthe low-NOx case. Percent bias between model-based and observationally-basedsecondary organic carbon (SOC) improved from −63% for the base case to−15% for the low-NOx case. The ability to robustly assign "bestavailable" parameters in all volatile organic compound+oxidant systems,however, is critically limited due to insufficient data; particularly forphoto-oxidation of diverse monoterpenes, sesquiterpenes, and alkanes under arange of atmospherically relevant conditions

Analyzing experimental data and model parameters: implications for predictions of SOA using chemical transport models