Simulation of SOA Formation from the Photooxidation of Monoalkylbenzenes in the Presence of Aqueous Aerosols Containing Electrolytes under Various NO<sub><i>x</i></sub> Levels

Abstract

<p><strong>Abstract.</strong> The formation of secondary organic aerosols (SOAs) from the photooxidation of three monoalkylbenzenes (toluene, ethylbenzene, and n-propylbenzene) in the presence of inorganic seeds (SO<sub>4</sub><sup>2−</sup>-NH<sub>4</sub><sup>+</sup>-H<sub>2</sub>O system) under varying NO<sub><i>x</i></sub> levels has been simulated using the Unified Partitioning-Aerosol Phase Reaction (UNIPAR) model. The evolution of the volatility-reactivity distribution (mass-base stoichiometric coefficient, α<sub><i>i</i></sub>) of oxygenated products, which were created by the near-explicit gas kinetic mechanism, was integrated with the model using the parameters linked to the concentrations of HO<sub>2</sub> and RO<sub>2</sub> radicals. This dynamic distribution was applied to estimate the model parameters related to the thermodynamic constants of the products in multiple phases (e.g., the gas phase, organic phase, and inorganic phase) and the reaction rate constants in the aerosol phase. The SOA mass was predicted through the partitioning and aerosol chemistry processes of the oxygenated products in both the organic phase and aqueous solution containing electrolytes, with the assumption of organic-inorganic phase separation. The prediction of the time series SOA mass (12-hr), against the aerosol data obtained from an outdoor photochemical smog chamber, was improved by the dynamic α<sub><i>i</i></sub> set compared to the prediction using the fixed α<sub><i>i</i></sub> set. Overall, the effect of an aqueous phase containing electrolytes on SOA yields was more important than that of the NO<sub><i>x</i></sub> level under our simulated conditions or the utilization of the age-driven α<sub><i>i</i></sub> set. Regardless of the NO<sub><i>x</i></sub> conditions, the SOA yields for the three aromatics were significantly higher in the presence of wet electrolytic seeds than those obtained with dry seeds or no seed. When increasing the NO<sub><i>x</i></sub> level, the fraction of organic matter (OM) produced by aqueous reactions to the total OM increased due to the increased formation of relatively volatile organic nitrates and peroxyacyl nitrate like products. The predicted partitioning mass fraction increased as the alkyl chain length increases but the organic mass produced via aerosol phase reactions decreased due to the increased activity coefficient of the organic compounds containing longer alkyl chains. Overall, the lower mass-base SOA yield was seen in the longer alkyl-substituted benzene in both the presence and absence of inorganic seeded aerosols. However, the difference of mole-base SOA yields of three monoalkylbenzenes becomes small because the highly reactive organic species (i.e., glyoxal) mainly originates from ring opening products without alkyl side chain. UNIPAR predicted the conversion of hydrophilic, acidic sulfur species to non-electrolytic dialkyl-organosulfate (diOS) in the aerosol. Thus, the model predicted the impact of diOS on both hygroscopicity and acidity, which subsequently influenced aerosol growth via aqueous reactions.</p>

Prediction of Secondary Organic Aerosol from the Multiphase Reaction of Gasoline Vapor by Using Volatility–Reactivity Base Lumping

“…These equations are mathematically derived by using explicit products predicted from MCM v3.3.1. The gas concentration ( , ) of lumping species, i, is estimated by multiplying ΔHC by dynamically predicted (Zhou et al, 2019).…”

Supplementary material to "Prediction of Secondary Organic Aerosol from the Multiphase Reaction of Gasoline Vapor by Using Volatility–Reactivity Base Lumping"

“…Experimental conditions for each chamber experiment are summarized in the Table S2. (Zhou et al, 2019). 100 c. "SA", "wAS", or "wAHS" denotes that the experiment with sulfuric-acid aerosol, wet ammonium-sulfate aerosol, or wet ammonium-hydrogen sulfate aerosol is directly injected to the chamber, respectively.…”

Modeling of Gas-Wall Partitioning of Organic Compounds Using a Quantitative Structure–Activity Relationship

“…The variation of the O:C ratios of products is large even in an individual SOA. For example, the O:C ratios of 1,3,5trimethylbenzene SOA products range from 0.11 to 3.0 (Jenkin et al, 2012;Im et al, 2014;Zhou et al, 2019). The 65 hygroscopicity of the organic-coated Teflon wall also can influence , (Krechmer et al, 2016;Huang et al, 2018).…”

“…The characteristic times (τ , τ , τ , τ , and τ ) are estimated in Fig. 6 for the eight surrogate SVOCs differentiated by two different levels of , (10 -1 and 10 1 ), , ((1 × 10 −6 and 4 × 10 −6 ), and the reactivity scale (fast and 275 no reaction) in the aerosol phase (Im et al, 2014;Beardsley and Jang, 2016;Zhou et al, 2019).…”

“…For example, the UNIPAR model predicts SOA mass by counting the volatility and aerosol phase reactions of the lumping species sourced from the SVOCs that are produced explicitly during hydrocarbons' photooxidation (Im et al, 2014;Beardsley and Jang, 2016;Zhou et al, 2019). The integration of GWP parameters with the explicit SOA model improves the 365 quantification of the bias in SOA mass attributable to GWP.…”