Simulation of Monoterpene SOA Formation by Multiphase Reactions Using Explicit Mechanisms

Abstract

The formation of terpene secondary organic aerosol (SOA) was simulated using the unified partitioning aerosol phase reaction model that predicted multiphase reactions of hydrocarbons in the presence of electrolytic inorganic aerosols. To predict oxygenated products from the atmospheric oxidation of terpenes, the master chemistry mechanism, an explicit gas kinetic mechanism, was implemented. The resulting products were then classified into 51 lumping groups using mass-based stoichiometric coefficients according to their volatility and aerosol phase reactivity. In the presence of wet inorganic aerosol, the SOA model was approached by liquid−liquid phase separation between the organic and inorganic phases due to the hydrophobicity of terpene products (oxygen to carbon ratios <0.6). The model streamlined three SOA formation pathways including partitioning of gaseous oxidized products onto both the organic aerosol and aqueous aerosol phases, oligomerization in the organic phase, and aqueous phase reactions (acid-catalyzed oligomerization and organosulfate formation). In the model, the peroxy radical autoxidation mechanism, which is a recently derived explicit mechanism to form highly oxygenated molecules, was also included to form less volatile products. The model simulation was demonstrated for SOA data that were produced through the photo-oxidation of three different monoterpenes (α-pinene, β-pinene, and D-limonene) under various experimental conditions in a large outdoor photochemical smog chamber. Terpene SOA growth was considerably accelerated in the aqueous phase anchored in acidic seeds but much weaker with neutral seeds. This tendency is quite different from that of isoprene SOA, which noticeably grows even in the neutral aqueous phase. Unlike hydrophilic isoprene products, terpene products are hydrophobic and weakly soluble in the aqueous phase, and thus, the neutral aqueous phase is insufficient to increase SOA mass. The model underestimated the production of polar functional groups, such as −OH, −COOH, and −ONO 2 , compared to the compositions measured using Fourier-transform infrared spectral data. In particular, the model underestimated carboxylic acids due to the knowledge gaps in the mechanisms to form carboxylic acid in both gas-phase oxidation and in-particle chemistry. Under the current emission trends in which SO 2 and NO x have been decreasing, the model simulation suggested that the reduction of sulfate is more efficient to reduce SOA mass than the reduction of NO x .

Prediction of Phase State of Secondary Organic Aerosol Internally Mixed with Aqueous Inorganic Salts

“…In this study, the SRH values of the chamber-generated SOA (oxidized from β-pinene, toluene, and 1,3,5-trimethylbenzene), which were internally mixed with the ammonium sulfate system ( f anion = 0.5–0.8), were simulated against observations based on microscopic data. The SOA model parameters comprising MW, O/C ratios, and H bond were estimated using the aerosol composition predicted using the UNIPAR SOA model. ,,, The detailed description of organic parameters is shown in Section S3 and Table S4 in the Supporting Information. For all SOA data, LLPS was observed when RH was less than 90%.…”

“…The prediction of ERH can significantly improve the accuracy of the SOA model due to the pathway of SOA formation via the aqueous reactions of organic species. For example, chamber studies showed that SOA formation considerably decreases at ERH when RH decreases during daytime. ,, Owing to the mitigation of SO 2 emissions in recent years (reduced more than 74% from 2010 to 2020; ), sulfate in ambient aerosols has been gradually reduced. However, a high fraction of ammonium nitrate can appear in an ambient aerosol under the low sulfate .…”

“…The SOA model parameters comprising MW, O/C ratios, and H bond were estimated using the aerosol composition predicted using the UNIPAR SOA model. 34,38,48,49 The detailed description of organic parameters is shown in Section S3 and Table S4 in the Supporting Information. For all SOA data, LLPS was observed when RH was less than 90%.…”

Secondary Organic Aerosol Formation via Multiphase Reaction of Hydrocarbons in Urban Atmospheres Using the CAMx Model Integrated with the UNIPAR model

“…The configuration of the UNIPAR model for SOA formation from each precursor has been described in prior studies (Beardsley and Jang, 2016;Im et al, 2014;Cao and Jang, 2010;Zhou et al, 2019;Yu et al, 2021b;Han and Jang, 2021). The predetermined mathematical equations and the model parameters employed in the UNIPAR model have been evaluated in the UF-APHOR chamber for various aromatic volatile organic compounds (VOCs) and biogenic VOCs (terpenes and isoprene) under varying aqueous salted seeds, NOx, SO2, humidity levels, and temperatures.…”

“…The conventional SOA module in regional models has no feature for SOA formation via aqueous phase reactions of different oxygenated products formed from various HCs. Our laboratory's recent research efforts (Beardsley and Jang, 2016;Im et al, 2014;Cao and Jang, 2010;Zhou et al, 2019;Yu et al, 2021b;Han and Jang, 2021) have improved the state of the art science by developing the UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model, which utilizes explicit gas chemistry to predict SOA mass based on multiphase reactions. In the UNIPAR model, the products predicted using explicit gas mechanisms are lumped based on volatility and emerging chemistry in the aerosol phase.…”