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We present a new volatility basis set (VBS) representation of aromatic secondary organic aerosol (SOA) for atmospheric chemistry models by fitting a statistical oxidation model with aerosol microphysics (SOM‐TOMAS) to results from laboratory chamber experiments. The resulting SOM‐VBS scheme also including previous work on SOA formation from semi‐ and intermediate volatile organic compounds (S/IVOCs) is implemented in the GEOS‐Chem chemical transport model and applied to simulation of observations from the Korea‐United States Air Quality Study (KORUS‐AQ) field campaign over South Korea in May–June 2016. Our SOM‐VBS scheme can simulate the KORUS‐AQ organic aerosol (OA) observations from aircraft and surface sites better than the default schemes used in GEOS‐Chem including for vertical profiles, diurnal cycle, and partitioning between hydrocarbon‐like OA and oxidized OA. Our results confirm the important contributions of oxidized primary OA and aromatic SOA found in previous analyses of the KORUS‐AQ data and further show a large contribution from S/IVOCs. Model source attribution of OA in surface air over South Korea indicates one third from domestic anthropogenic emissions, with a large contribution from toluene and xylenes, one third from external anthropogenic emissions, and one third from natural emissions.

 

To quantify the volatility of organic aerosols (OA), a comprehensive campaign was conducted in the Chinese megacity. Volatility distributions of OA and particle‐phase organic nitrate (pON) were estimated based on five methods: (a) empirical method and (b) kinetic model based on the measurement of a thermodenuder (TD) coupled with an aerosol mass spectrometer; (c) Formula‐based SIMPOL model‐driven method; (d) Element‐based estimations using molecular formula measurements of OA; and (e) gas/particle partitioning. Our results demonstrate that the ambient OA volatility distribution shows good agreement between the two heating methods and the formula‐based method when assuming ambient OA was mainly composed of organic nitrate (pON), organic sulfate and acid groups using the SIMPOL model. However, the element‐based method tends to overestimate the volatility of OA compared to the above three methods, suggesting large uncertainties in the parameterizations or in the representativeness of the molecular measurements that need further refinement. The volatility of ambient OA is generally lower than that of the laboratory‐derived secondary OA, emphasizing the impact of aging. A large fraction at the higher and lower volatility ranges (approximately logC* ≤ −9 and ≥2 μg m⁻³) was found for pON, implying the importance of both extremely low volatile and semi‐volatile species. Overall, this study evaluates different methods for volatility estimation and gives new insight into the volatility of OA and pON in urban areas.

 

The dominant fraction of anthropogenic volatile organic compound (VOC) emissions shifted from transportation fuels to volatile chemical products (VCP) in Los Angeles (LA) in 2010. This shift in VOC composition raises the question about the importance of VCP emissions for ozone (O₃) formation. In this study, O₃chemistry during the CalNex 2010 was modeled using the Master Chemical Mechanism (MCM) version 3.3.1 and a detailed representation of VCP emissions based on measurements combined with inventory estimates. The model calculations indicate that VCP emissions contributed to 23% of the mean daily maximum 8‐hr average O₃(DMA8 O₃) during the O₃episodes. The simulated OH reactivity, including the contribution from VCP emissions, aligns with observations. Additionally, this framework was employed using four lumped mechanisms with simplified representations of emissions and chemistry. RACM2‐VCP showed the closest agreement with MCM, with a slight 4% increase in average DMA8 O₃(65 ± 13 ppb), whereas RACM2 (58 ± 13 ppb) and SAPRC07B (59 ± 14 ppb) exhibited slightly lower levels. CB6r2, however, recorded reduced concentrations (37 ± 10 ppb). Although emissions of O₃precursors have declined in LA since 2010, O₃levels have not decreased significantly. Model results ascribed this trend to the rapid reduction in NO_Xemissions. Moreover, given the impact of COVID‐19, an analysis of 2020 reveals a shift to a NO_X‐limited O₃formation regime in LA, thereby diminishing the influence of VCPs. This study provides new insights into the impact of VCP emissions on O₃pollution from an in‐depth photochemical perspective.

 

Abstract. Previous studies have demonstrated volatility-dependent absorption of gas-phase volatile organic compounds (VOCs) to Teflon and other polymers. Polymer–VOC interactions are relevant for atmospheric chemistry sampling, as gas–wall partitioning in polymer tubing can cause delays and biases during measurements. They are also relevant to the study of indoor chemistry, where polymer-based materials are abundant (e.g., carpets and paints). In this work, we quantify the absorptive capacities of multiple tubing materials, including four nonconductive polymers (important for gas sampling and indoor air quality), four electrically conductive polymers and two commercial steel coatings (for gas and particle sampling). We compare their performance to previously characterized materials. To quantify the absorptive capacities, we expose the tubing to a series of ketones in the volatility range 104–109 µg m−3 and monitor transmission. For slow-diffusion polymers (e.g., perfluoroalkoxy alkane (PFA) Teflon and nylon), absorption is limited to a thin surface layer, and a single-layer absorption model can fit the data well. For fast-diffusion polymers (e.g., polyethylene and conductive silicone), a larger depth of the polymer is available for diffusion, and a multilayer absorption model is needed. The multilayer model allows fitting solid-phase diffusion coefficients for different materials, which range from 4×10-9 to 4×10-7 cm2 s−1. These diffusion coefficients are ∼ 8 orders of magnitude larger than literature values for fluorinated ethylene propylene (FEP) Teflon film. This enormous difference explains the differences in VOC absorption measured here. We fit an equivalent absorptive mass (CW, µg m−3) for each absorptive material. We found PFA to be the least absorptive, with CW ∼ 105 µg m−3, and conductive silicone to be the most absorptive, with CW ∼ 1013 µg m−3. PFA transmits VOCs easily and intermediate-volatility species (IVOCs) with quantifiable delays. In contrast, conductive silicone tubing transmits only the most volatile VOCs, denuding all lower-volatility species. Semi-volatile species (SVOCs) are very difficult to sample quantitatively through any tubing material. We demonstrate a system combining several slow- and fast-diffusion tubing materials that can be used to separate a mixture of VOCs into volatility classes. New conductive silicone tubing contaminated the gas stream with siloxanes, but this effect was reduced 10 000-fold for aged tubing, while maintaining the same absorptive properties. SilcoNert (tested in this work) and Silonite (tested in previous work) steel coatings showed gas transmission that was almost as good as PFA, but since they undergo adsorption, their delay times may be humidity- and concentration-dependent.

 

Abstract. Obtaining quantitative information for molecular species present in aerosols from real-time mass spectrometers such as an extractive electrospray time-of-flight mass spectrometer (EESI) and an aerosol mass spectrometer (AMS) can be challenging. Typically, molecular species are calibrated directly through the use of pure standards. However, in some cases (e.g., secondary organic aerosol (SOA) formed from volatile organic compounds (VOCs)), direct calibrations are impossible, as many SOA species can either not be purchased as pure standards or have ambiguous molecular identities. In some cases, bulk OA sensitivities are used to estimate molecular sensitivities. This approach is not sufficient for EESI, which measures molecular components of OA, because different species can have sensitivities that vary by a factor of more than 30. Here, we introduce a method to obtain EESI calibration factors when standards are not available, and we provide a thorough analysis of the feasibility, performance, and limitations of this new technique. In this method, complex aerosol mixtures were separated with high-performance liquid chromatography (HPLC) followed by aerosol formation via atomization. The separated aerosols were then measured by an EESI and an AMS, which allowed us to obtain sensitivities for some species present in standard and SOA mixtures. Pure compounds were used to test the method and characterize its uncertainties, and obtained sensitivities were consistent within ±20 % when comparing direct calibrations vs. HPLC calibrations for a pure standard and within a factor of 2 for a standard mixture. In some cases, species were not completely resolved by chromatography, and positive matrix factorization (PMF) of AMS data enabled further separation. This method should be applicable to other real-time MS techniques. Improvements in chromatography are possible that would allow better separation in complex mixtures.

 

Abstract. The Aerodyne Aerosol Mass Spectrometer (AMS) and Aerosol Chemical Speciation Monitor (ACSM) are the most widely applied tools for in situ chemical analysis of the non-refractory bulk composition of fine atmospheric particles. The mass spectra (MS) of many AMS and ACSM observations from field and laboratory studies have been reported in peer-reviewed literature and many of these MS have been submitted to an open-access website. With the increased reporting of such datasets, the database interface requires revisions to meet new demands and applications. One major limitation of the web-based database is the inability to automatically search the database and compare previous MS with the researcher's own data. In this study, a searchable database tool for the AMS and ACSM mass spectral dataset was built to improve the efficiency of data analysis using Igor Pro, consistent with existing AMS and ACSM software. The database tool incorporates the published MS and sample information uploaded on the website. This tool allows the comparison of a target mass spectrum with the reference MS in the database, calculating cosine similarity, and provides a range of MS comparison plots, reweighting, and mass spectrum filtering options. The aim of this work is to help AMS and ACSM users efficiently analyze their own data for possible source or atmospheric processing features by comparison to previous studies, enhancing information gained from past and current global research on atmospheric aerosol.