We apply a full year of continuous atmospheric acetone measurements from the University of Minnesota tall tower Trace Gas Observatory (KCMP tall tower; 244 m a.g.l.), with a 0.5° × 0.667° GEOS-Chem nested grid simulation to develop quantitative new constraints on seasonal acetone sources over North America. Biogenic acetone emissions in the model are computed based on the MEGANv2.1 inventory. An inverse analysis of the tall tower observations implies a 37% underestimate of emissions from broadleaf trees, shrubs, and herbaceous plants, and an offsetting 40% overestimate of emissions from needleleaf trees plus secondary production from biogenic precursors. The overall result is a small (16%) model underestimate of the total primary + secondary biogenic acetone source in North America. Our analysis shows that North American primary + secondary anthropogenic acetone sources in the model (based on the EPA NEI 2005 inventory) are accurate to within approximately 20%. An optimized GEOS-Chem simulation incorporating the above findings captures 70% of the variance (R = 0.83) in the hourly measurements at the KCMP tall tower, with minimal bias. The resulting North American acetone source is 11 Tg a⁻¹, including both primary emissions (5.5 Tg a⁻¹) and secondary production (5.5 Tg a⁻¹), and with roughly equal contributions from anthropogenic and biogenic sources. The North American acetone source alone is nearly as large as the total continental volatile organic compound (VOC) source from fossil fuel combustion. Using our optimized source estimates as a baseline, we evaluate the sensitivity of atmospheric acetone and peroxyacetyl nitrate (PAN) to shifts in natural and anthropogenic acetone sources over North America. Increased biogenic acetone emissions due to surface warming are likely to provide a significant offset to any future decrease in anthropogenic acetone emissions, particularly during summer.

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30–40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.