A lumped species approach for the simulation of secondary organic aerosol production from intermediate-volatility organic compounds (IVOCs): application to road transport in PMCAMx-iv (v1.0) (Geoscientific Model Development)

Secondary organic aerosol (SOA) is formed in the atmosphere through the oxidation and condensation of organic compounds. Intermediate volatility compounds, compounds with effective saturation concentration (C*) at 298 K between 103 and 106 μg m-3, have high SOA yields and can be important SOA precursors. The first efforts to simulate IVOCs in chemical transport models (CTMs) used the volatility basis set (VBS), a highly parametrized scheme that oversimplifies their chemistry. In this work we propose a more detailed approach for simulating IVOCs in CTMs, treating them as lumped species that retain their chemical characteristics. Specifically, we introduce four new lumped species representing large alkanes, two lumped species representing polyaromatic hydrocarbons (PAHs) and one species representing large aromatics, all in the IVOC range. We estimate IVOC emissions from road transport using existing estimates of volatile organic compound (VOC) emissions and emission factors of individual IVOCs from experimental studies. Over the European domain, for the simulated period of May 2008, estimated IVOC emissions from road transport were about 21 Mmol d-1, a factor of 8 higher than emissions used in previous VBS applications. The IVOC emissions from diesel vehicles were significantly higher than those from gasoline ones. SOA yields under low-NOx and high-NOx conditions for the lumped IVOC species were estimated based on recent smog chamber studies. Large cyclic alkane compounds have both high yields and high emissions, making them an important, yet understudied, class of IVOCs.Manavi, S. E. I. and Pandis, S. N.: A lumped species approach for the simulation of secondary organic aerosol production from intermediate-volatility organic compounds (IVOCs): application to road transport in PMCAMx-iv (v1.0), Geosci. Model Dev., 15, 7731–7749, https://doi.org/10.5194/gmd-15-7731-2022, 202