Volatility of aerosol particles from NO₃ oxidation of various biogenic organic precursors

Abstract

Abstract. Secondary organic aerosol (SOA) is formed through the oxidation of volatile organic compounds (VOC), which can be of both natural and anthropogenic origin. While the hydroxyl radical (OH) and ozone (O3) are the main atmospheric oxidants during the day, the nitrate radical (NO3) becomes more important during the night time. Yet, atmospheric nitrate chemistry has received less attention compared to OH and O3. The Nitrate Aerosol and Volatility Experiment (NArVE) aimed to study the NO3-induced SOA formation and evolution from three biogenic VOCs (BVOC), namely isoprene, α-pinene and β-caryophyllene. The volatility of aerosol particles was studied using isothermal evaporation chambers, temperature-dependent evaporation in a volatility tandem differential mobility analyzer (VTDMA), and thermal desorption in a filter inlet for gases and aerosols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). Data from these three setups present a cohesive picture of the volatility of the SOA formed in the dark from the three biogenic precursors. Under our experimental conditions, the SOA formed from NO3 + α-pinene was generally more volatile than SOA from α-pinene ozonolysis, while the NO3 oxidation of isoprene produced similar, although slightly less volatile SOA than α-pinene under our experimental conditions. β-caryophyllene reactions with NO3 resulted in the least volatile species. Three different parametrizations for estimating the saturation vapor pressure of the oxidation products were tested for reproducing the observed evaporation in a kinetic modelling framework. Our results show that the SOA from nitrate oxidation of α-pinene or isoprene is dominated by low volatility organic compounds (LVOC) and semivolatile organic compounds (SVOC), while the corresponding SOA from β-caryophyllene consists primarily of extremely low volatility organic compounds (ELVOC) and LVOC. The parameterizations yielded variable results in terms of reproducing the observed evaporation, and generally the comparisons pointed to a need for re-evaluating the treatment of the nitrate group in such parameterizations. Strategies for improving the predictive power of the volatility parameterizations, particularly in relation to the contribution from the nitrate group, are discussed.

Quantitative Characterization of the Volatility Distribution of Organic Aerosols in a Polluted Urban Area: Intercomparison Between Thermodenuder and Molecular Measurements

“…The volatility distribution of pON from the SIMPOL‐acid group method shows similar patterns as that from the TD method (UC = 0.67–0.83), which exhibits more OA masses at two ends (log C* = −9 and log C* ≥ 2) (Figures 6c and 6d). This pattern suggests that both large fractions of oligomers with low volatilities and semi‐volatile species exist in pON, which is consistent with the volatility of pON generated from the laboratory studies (Graham et al., 2022), signifying the complexity of pON species. The volatility of pON was contributed by 74% CHON and 26% CHONS groups (Figure 6d), respectively.…”

“…Only limited laboratory studies have compared OA volatility among different technique categories. The comparability of OA volatility (a) between the dilution method and heating technique from TD‐AMS (Sato et al., 2019); (b) between dilution and FIGAERO‐CIMS (Graham et al., 2022; Tikkanen et al., 2020); (c) between FIGAERO‐CIMS versus TD‐AMS measurements (Voliotis et al., 2022; Voliotis et al., 2021); (d) between element‐versus functional groups‐based method (Isaacman‐VanWertz & Aumont, 2021; Wu et al., 2021), have varied under different circumstances, highlighting the necessity for further exploration on the factors causes this discrepancy. The intercomparison of volatility distributions for ambient OA among different methods is even scarce.…”

Cloud response to co-condensation of water and organic vapors over the boreal forest

“…Alternatively, these concentrations can also result from thermal decomposition of lower volatility products during the FIGAERO-I-CIMS heating process (Lopez-Hilfiker et al, 2015) or from the tendency of the Eq. ( 18) parameterization to underestimate (despite treating the -NO3 groups at -OH groups) the volatility of organic nitrates (Graham et al, 2022), shown to be abundant in the BAECC FIGAERO-I-CIMS data set (Fig. 2e).…”

Variation in chemical composition and volatility of oxygenated organic aerosol in different rural, urban, and mountain environments

“…Chemical composition and volatility of atmospheric organic aerosol (OA) particles are interconnected. Functionalization of organic molecules can modify their vapor pressure by several orders of magnitude (Pankow and Asher, 2008;Donahue et al, 2011;Graham et al, 2023;Isaacman-VanWertz and Aumont, 2021;Kroll and Seinfeld, 2008). Volatility determines whether a compound partitions into or evaporates from the particle phase and thus influences particulate mass and lifetime in the atmosphere.…”

“…1. The molecular information of OOA can be used to parametrize volatility via calculations of the effective saturation mass concentrations (C sat ) of different organic compounds (Donahue et al, 2011;Li et al, 2016;Mohr et al, 2019;Isaacman-VanWertz and Aumont, 2021;Graham et al, 2023). There are various parametrization methods to calculate C sat , based on different assumptions, training datasets, or structurebased estimation methods (Isaacman-VanWertz and Aumont, 2021).…”