Despite critical importance for air quality and cli-mate predictions, accurate representation of secondary or-ganic aerosol (SOA) formation remains elusive. An essen-tial 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 avail-able " set of SOA modeling parameters is selected by com-paring predicted SOA yields and mass concentrations with observed yields and mass concentrations from a comprehen-sive list of published smog chamber studies. Evaluated SOA model parameters include existing parameters for two prod-uct (2p) and volatility basis set (VBS) modeling frameworks, and new 2p-VBS parameters; 2p-VBS parameters are devel-oped to exploit advantages of the VBS approach within the computationally-economical and widely-used 2p framework. Fine particulate matter (PM 2.5) and SOA mass concentra-tions 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 parame-ter cases to illustrate the high-and low-NO x limits of bio-genic SOA formation from monoterpenes. Results are dis-cussed in terms of implications for current chemical trans-port model simulations and recommendations are provided for future modeling and measurement efforts. The compar-isons of SOA yield predictions with data from 22 published chamber studies illustrate that: (1) SOA yields for naphtha-lene, 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 or-ganic 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 PM 2.5 concentrations increase by up to 15 % and 7 %, respectively, for the high-NO x case and up to 215 % (∼ 3 µg m −3) and 55 %, respectively, for the low-NO x case. Percent bias between model-based and observationally-based secondary organic carbon (SOC) im-proved from −63 % for the base case to −15 % for the low-NO x case. The ability to robustly assign " best available " pa-rameters in all volatile organic compound+oxidant systems, however, is critically limited due to insufficient data; particu-larly for photo-oxidation of diverse monoterpenes, sesquiter-penes, and alkanes under a range of atmospherically relevant conditions.
Mendeley saves you time finding and organizing research
Choose a citation style from the tabs below