Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS.

Community Multiscale Air Quality (CMAQ) model simulations utilizing the volatility basis set (VBS) treatment for organic aerosols (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of organic aerosol (OA) in southern California. CMAQ-VBS (OA lumped by volatility, semivolatile POA) underpredicted total organic carbon (OC) at CSN (-25.5% Normalized Median Bias (NMdnB)) and IMPROVE (-63.9% NMdnB) locations and total OC was underpredicted to a greater degree compared to the CMAQ-AE6 (9.9 and -55.7% NMdnB, respectively; semi-explicit OA treatment, SOA lumped by parent hydrocarbon, nonvolatile POA). However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA indicated that CMAQ-VBS better represented the diurnal profile and the primary/secondary split of OA. CMAQ-VBS secondary organic aerosol (SOA) underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate of SOA) concentration by a factor of 5.2 (4.7 μgm^-3 measured vs. 0.9 μgm^-3 modeled), a considerable improvement to CMAQ-AE6 SOA predictions, which were approximately 24× lower than the average AMS OOA concentration. We use two new methods, based on species ratios and on a simplified SOA parameterization from the observations, to apportion the SOA underprediction for CMAQ-VBS to too slow photochemical oxidation (estimated as 1.5× lower than observed at Pasadena using -log(NO_x : NO_y )), low intrinsic SOA formation efficiency (low by 1.6 to 2× for Pasadena), and too low emissions or too high 25 dispersion for the Pasadena site (estimated to be 1.6 to 2.3× too low/high). The first and third factors will be similar for CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7×. For CMAQ-VBS, 90% of the anthropogenic SOA mass formed was attributed to aged secondary semivolatile vapors (70% originating from volatile organic compounds (VOCs) and 20% from intermediate volatility compounds (IVOCs)). From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48%, and consistent with a substantial fraction of cooking OA in the observations), compared to 18% from gasoline vehicle emissions, 13% from biomass burning (in the form of residential wood combustion), and 8% from diesel vehicle emissions. All "other" inventoried emission sources (e.g. industrial/point sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA)+cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 (1.16 μgm^-3 modeled vs. 2.05 μgm^-3 observed) compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but did well to capture the AMS diurnal profile of HOA and CIOA, with the exception of the midday peak. We estimated that using the National Emission Inventory (NEI) POA emissions without scaling to represent SVOCs underestimates SVOCs by ~ 1.7×. [ABSTRACT FROM AUTHOR]