Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate volatility organic compounds and NO<sub>X</sub>

Abstract

15Semi-volatile and intermediate-volatility organic compounds (SVOCs and IVOCs) from anthropogenic sources are 16 likely to be important precursors of secondary organic aerosol (SOA) in urban airsheds yet their treatment in most 17 models is based on limited and obsolete data, or completely missing. Additionally, gas-phase oxidation of organic 18 precursors to form SOA is influenced by the presence of nitric oxide (NO), but this influence is poorly constrained in 19 chemical transport models. In this work, we updated the organic aerosol model in the UCD/CIT chemical transport 20 model to include (i) a semi-volatile and reactive treatment of primary organic aerosol (POA), (ii) emissions and SOA 21 formation from IVOCs, (iii) the NO X influence on SOA formation, and (iv) SOA parameterizations for SVOCs and 22 IVOCs that are corrected for vapor wall loss artifacts during chamber experiments. All updates were implemented in 23 the statistical oxidation model (SOM) that simulates the oxidation chemistry, thermodynamics, and gas/particle 24 partitioning of organic aerosol (OA). Model treatment of POA, SVOCs, and IVOCs was based on an interpretation of 25 a comprehensive set of source measurements and resolved broadly by source type. The NO X influence on SOA 26 formation was calculated offline based on measured and modeled VOC:NO X ratios. And finally, the SOA formation 27 from all organic precursors (including SVOCs and IVOCs) was modeled based on recently derived parameterizations 28 that accounted for vapor wall loss artifacts in chamber experiments. The updated model was used to simulate a two 29 week summer episode over southern California at a model resolution of 8 km. (except that from marine sources) to be semi-volatile resulted in a larger reduction in POA mass concentrations and 35 allowed for a better model-measurement comparison at Riverside. Model predictions suggested that both SVOCs 36 (evaporated POA vapors) and IVOCs did not contribute significantly to SOA mass concentrations in the urban areas 37 (<5% and <15% of the total SOA respectively) as the timescales for SOA production appeared to be shorter than the 38 timescales for transport out of the urban airshed. Comparisons of modeled IVOC concentrations with measurements 39 of anthropogenic SOA precursors in southern California seemed to imply that IVOC emissions were underpredicted in 40 our updated model by a factor of 2. We suspect that these missing IVOCs might arise from the use of volatile 41 chemical products such as pesticides, coatings, cleaning agents, and personal care products. Correcting for the vapor 42 wall loss artifact in chamber experiments enhanced SOA mass concentrations although the enhancement was 43 precursor-as well as NO X -dependent. Accounting for the influence of NO X using the VOC:NO X ratios resulted in 44Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-616 Manuscript under review for journal Atmos. Chem. Phys.

Urban Oxidation Flow Reactor Measurements Reveal Significant Secondary Organic Aerosol Contributions from Volatile Emissions of Emerging Importance

“…This finding is consistent with previous studies. 7,8,10 Our data further suggest that VCPs and other upstream sources (oil and gas extraction, coke ovens, etc.) can explain this additional SOA potential.…”

Oxygenated Aromatic Compounds are Important Precursors of Secondary Organic Aerosol in Biomass-Burning Emissions

“…This is because oxygenated aromatics and their oxidation products, on account of their relatively higher OH reactivity, are likely to proceed quickly through the cascade of oxidation reactions to form SOA, 50 which should make the precursors and oxidation products less susceptible to vapor wall losses. 43 When considered together, i.e., on turning transfer duct and chamber losses off, the model predicted a combined increase of 105% in SOA mass concentrations. These results imply that in the absence of dilution and similarity in chemistry, photochemical oxidation within biomass burning plumes should have twice the potential to form SOA as in the chamber.…”

“…The SOM has been previously used to model SOA formation from individual VOCs, 26,37 VOC mixtures, 28 engine emissions, 44 and precursors in an urban airshed. 29,43,76 The SOM and TOMAS models are coupled in that the particle-phase species in SOM are tracked in the TOMAS size sections. TOMAS in our setup has 36 size sections spanning dry diameters of approximately 3 nm to 10,000 nm.…”

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate-volatility organic compounds and NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;

“…Data availability. All measurements and select model predictions in this work are archived at https://doi.org/10.25675/10217/194377 (Akherati et al, 2019).…”