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 .

Abstract. The prediction of secondary organic aerosol (SOA) on regional scales is traditionally performed by using gas–particle partitioning models. In the presence of inorganic salted wet aerosols, aqueous reactions of semivolatile organic compounds can also significantly contribute to SOA formation. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model utilizes the explicit gas mechanism to better predict SOA formation from multiphase reactions of hydrocarbons. In this work, the UNIPAR model was incorporated with the Comprehensive Air Quality Model with Extensions (CAMx) to predict the ambient concentration of organic matter (OM) in urban atmospheres during the Korean-United States Air Quality (2016 KORUS-AQ) campaign. The SOA mass predicted with CAMx–UNIPAR changed with varying levels of humidity and emissions and in turn has the potential to improve the accuracy of OM simulations. CAMx–UNIPAR significantly improved the simulation of SOA formation under the wet condition, which often occurred during the KORUS-AQ campaign, through the consideration of aqueous reactions of reactive organic species and gas–aqueous partitioning. The contribution of aromatic SOA to total OM was significant during the low-level transport/haze period (24–31 May 2016) because aromatic oxygenated products are hydrophilic and reactive in aqueous aerosols. The OM mass predicted with CAMx–UNIPAR was compared with that predicted with CAMx integrated with the conventional two-product model (SOAP). Based on estimated statistical parameters to predict OM mass, the performance of CAMx–UNIPAR was noticeably better than that of the conventional CAMx model, although both SOA models underestimated OM compared to observed values, possibly due to missing precursor hydrocarbons such as sesquiterpenes, alkanes, and intermediate volatile organic compounds (VOCs). The CAMx–UNIPAR simulation suggested that in the urban areas of South Korea, terpene and anthropogenic emissions significantly contribute to SOA formation while isoprene SOA minimally impacts SOA formation.

Abstract. Secondary organic aerosol (SOA) from diesel fuel is known to be significantly sourced from the atmospheric oxidation of aliphatic hydrocarbons. In this study, the formation of linear alkane SOA was predicted using the Unified Partitioning Aerosol Phase Reaction (UNIPAR) model that simulated multiphase reactions of hydrocarbons. In the model, the formation of oxygenated products from the photooxidation of linear alkanes was simulated using a nearly explicit gas kinetic mechanism. Autoxidation paths integrated with alkyl peroxy radicals were added to the Master Chemical Mechanism v3.3.1 to improve the prediction of low-volatility products in the gas phase and SOA mass. The resulting gas products were then lumped into volatility- and reactivity-based groups that are linked to mass-based stoichiometric coefficients. The SOA mass in the UNIPAR model is produced via three major pathways: partitioning of gaseous oxidized products onto both the organic and wet inorganic phases, oligomerization in the organic phase, and reactions in the wet inorganic phase (acid-catalyzed oligomerization and organosulfate formation). The model performance was demonstrated for SOA data that were produced through the photooxidation of a homologous series of linear alkanes ranging from C9–C15 under varying environments (NOx levels and inorganic seed conditions) in a large outdoor photochemical smog chamber. The product distributions of linear alkanes were mathematically predicted as a function of carbon number using an incremental volatility coefficient (IVC) to cover a wide range of alkane lengths. The prediction of alkane SOA using the incremental volatility-based product distributions, which were obtained with C9–C12 alkanes, was evaluated for C13 and C15 chamber data and further extrapolated to predict the SOA from longer-chain alkanes (≥ C15) that can be found in diesel. The model simulation of linear alkanes in diesel fuel suggests that SOA mass is mainly produced by alkanes C15 and higher. Alkane SOA is insignificantly impacted by the reactions of organic species in the wet inorganic phase due to the hydrophobicity of products but significantly influenced by gas–particle partitioning.

Abstract. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model was established on the Comprehensive Air quality Model with extensions (CAMx) to process Secondary Organic Aerosol (SOA) formation by capturing multiphase reactions of hydrocarbons (HCs) in regional scales. SOA growth was simulated using a wide range of anthropogenic HCs including ten aromatics and linear alkanes with different carbon-lengths. The atmospheric processes of biogenic HCs (isoprene, terpenes, and sesquiterpene) were simulated for the major oxidation paths (ozone, OH radicals, and nitrate radicals) to predict day and night SOA formation. The UNIPAR model streamlined the multiphase partitioning of the lumping species originating from semi-explicitly predicted gas products and their heterogeneous chemistry to form non-volatile oligomeric species in both organic aerosol and inorganic aqueous phase. The CAMx-UNIPAR model predicted SOA formation at four ground urban sites (San Jose, Sacramento, Fresno, and Bakersfield) in California, United States during wintertime 2018. Overall, the simulated mass concentrations of the total organic matter, consisting of primary OA (POA) and SOA, showed a good agreement with the observations. The simulated SOA mass in the urban areas of California was predominated by alkane and terpene. During the daytime, low-volatile products originating from the autoxidation of long-chain alkanes considerably contributed to the SOA mass. In contrast, a significant amount of nighttime SOA was produced by the reaction of terpene with ozone or nitrate radicals. The spatial distributions of anthropogenic SOA associated with aromatic and alkane HCs were noticeably affected by the southward wind direction owing to the relatively long lifetime of their atmospheric oxidation, whereas those of biogenic SOA were nearly insensitive to wind direction. During wintertime 2018, the impact of inorganic aerosol hygroscopicity on the total SOA budget was not evident because of the small contribution of aromatic and isoprene products that are hydrophilic and reactive in the inorganic aqueous phase. However, an increased isoprene SOA mass was predicted during the wet periods, although its contribution to the total SOA was little.

In the presence of inorganic salts, secondary organic aerosol (SOA) undergoes liquid–liquid phase separation (LLPS), liquid–solid phase separation, or a homogeneous phase in ambient air. In this study, a regression model was derived to predict aerosol phase separation relative humidity (SRH) for various organic and inorganic mixes. The model implemented organic physicochemical parameters (i.e., oxygen to carbon ratio, molecular weight, and hydrogen-bonding ability) and the parameters related to inorganic compositions (i.e., ammonium, sulfate, nitrate, and water). The aerosol phase data were observed using an optical microscope and also collected from the literature. The crystallization of aerosols at the effloresce RH (ERH) was semiempirically predicted with a neural network model. Overall, the greater SRH appeared for the organic compounds with the lower oxygen to carbon ratios or the greater molecular weight and the higher aerosol acidity or the larger fraction of inorganic nitrate led to the lower SRH. The resulting model has been demonstrated for three different chamber-generated SOA (originated from β-pinene, toluene, and 1,3,5-trimethylbenzene), which were internally mixed with the inorganic aqueous system of ammonium–sulfate–water. For all three SOA systems, both observations and model predictions showed LLPS at RH <80%. In the urban atmosphere, LLPS is likely a frequent occurrence for the typical anthropogenic SOA, which originates from aromatic and alkane hydrocarbon.