Photolytically induced changes in composition and volatility of biogenic secondary organic aerosol from nitrate radical oxidation during night-to-day transition

Night-time reactions of biogenic volatile organic compounds (BVOCs) and nitrate radicals (NO₃) can lead to the formation of NO₃-initiated biogenic secondary organic aerosol (BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$). Here, we study the impacts of light exposure on the chemical composition and volatility of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ formed in the dark from three precursors (isoprene, α-pinene, and β-caryophyllene) in atmospheric simulation chamber experiments. Our study represents BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ formation conditions where reactions between peroxy radicals (RO₂ + RO₂) and between RO₂ and NO₃ are favoured. The emphasis here is on the identification of particle-phase organonitrates (ONs) formed in the dark and their changes during photolytic ageing on timescales of ∼ 1 h. The chemical composition of particle-phase compounds was measured with a chemical ionization mass spectrometer with a filter inlet for gases and aerosols (FIGAERO-CIMS) and an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF). Volatility information on BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ was derived from FIGAERO-CIMS desorption profiles (thermograms) and a volatility tandem differential mobility analyser (VTDMA). During photolytic ageing, there was a relatively small change in mass due to evaporation (< 5 % for the isoprene and α-pinene BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$, and 12 % for the β-caryophyllene BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$), but we observed significant changes in the chemical composition of the BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$. Overall, 48 %, 44 %, and 60 % of the respective total signal for the isoprene, α-pinene, and β-caryophyllene BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ was sensitive to photolytic ageing and exhibited decay. The photolabile compounds include both monomers and oligomers. Oligomers can decompose into their monomer units through photolysis of the bonds (e.g. likely O–O) between them. Fragmentation of both oligomers and monomers also happened at other positions, causing the formation of compounds with shorter carbon skeletons. The cleavage of the nitrate functional group from the carbon chain was likely not a main degradation pathway in our experiments. In addition, photolytic degradation of compounds changes their volatility and can lead to evaporation. We use different methods to assess bulk volatilities and discuss their changes during both dark ageing and photolysis in the context of the chemical changes that we observed. We also reveal large uncertainties in saturation vapour pressure estimated from parameterizations for the ON oligomers with multiple nitrate groups. Overall, our results suggest that photolysis causes photodegradation of a substantial fraction of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$, changes both the chemical composition and the bulk volatility of the particles, and might be a potentially important loss pathway of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ during the night-to-day transition.

1 Introduction

Secondary organic aerosol (SOA), formed via the oxidation of volatile organic compounds (VOCs) emitted from human activities (anthropogenic) and vegetation (biogenic), has important impacts on climate (Shrivastava et al., 2017) and human health (Daellenbach et al., 2020). Biogenic VOCs, such as isoprene (C₅H₈), monoterpenes (C₁₀H₁₆), and sesquiterpenes (C₁₅H₂₄), are key precursors for global SOA formation due to their larger emissions (Guenther et al., 2006; Guenther et al., 1995) and higher reactivity towards atmospheric oxidants compared with the VOCs from anthropogenic emissions. While oxidation initiated by ozone (O₃) and hydroxyl radicals (OH) dominates during daytime, nitrate radicals (NO₃), generated at night by the reaction of nitrogen dioxide (NO₂) with O₃, are the major nocturnal oxidant. Modelling studies estimate that 5 %–21 % of SOA is produced by NO₃ chemistry at the global scale (Hoyle et al., 2007; Pye et al., 2010).

The reaction of NO₃ with VOCs is a major pathway for the production of organonitrates (ONs, e.g. RONO₂), which represent a substantial fraction of submicron aerosol nitrate at both urban and rural sites (Kiendler-Scharr et al., 2016). ONs also play an important role in the removal and transport of nitrogen oxides (NO_x), and impact NO_x cycling and O₃ formation (Perring et al., 2013). While the lifetime of aerosols in the atmosphere typically spans over multiple day–night cycles, the lifetime of ONs within particles is much shorter (Lee et al., 2016; Zare et al., 2018). Reactions influencing particulate lifetime of ONs include oxidation, hydrolysis (Pye et al., 2015; Takeuchi and Ng, 2019), and photolysis (Müller et al., 2014; Suarez-Bertoa et al., 2012). They change both chemical and physical properties of SOA and ONs, and have different impacts on the atmospheric NO_x budget.

Compared with OH and O₃, there are few laboratory studies on NO₃-initiated biogenic SOA (BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$); thus, very little is known about the chemical composition and volatility of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$. While there are extensive studies on photolytic/photochemical (photolysis + OH) ageing of OH- and O₃-initiated SOA under low-NO_x conditions (Surratt et al., 2006; Walser et al., 2007; Mang et al., 2008; Pan et al., 2009; Henry and Donahue, 2012; Presto et al., 2005; Zawadowicz et al., 2020), studies on photolytic/photochemical ageing of NO₃-initiated SOA and ONs are limited. The few studies that have examined optical properties of SOA show that there is a significant difference in SOA produced from NO₃ oxidation compared with other oxidation pathways (Nakayama et al., 2015; Peng et al., 2018), as well as in BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ from different precursors (He et al., 2021). Nah et al. (2016) reported that SOA from β-pinene + NO₃ is generally resilient to photochemical ageing and does not exhibit significant changes in its chemical composition, whereas most of the SOA from α-pinene + NO₃ evaporates during photochemical ageing (photolysis + OH). However, little is known about SOA from other VOC precursors and SOA formed in chemical regimes with different fates of the peroxy radical (RO₂), such as RO₂ + HO₂, RO₂ + NO₃, and RO₂ + RO₂. The knowledge gaps related to the effects of photolysis on lifetime and physicochemical properties of ONs currently hinder a quantitative understanding of their impacts on the atmospheric nitrogen budget, chemical interactions between anthropogenic and biogenic compounds, and climate.

In this study, we performed chamber experiments where we formed SOA in the dark and photolytically aged the NO₃-initiated SOA and ONs from three biogenic VOCs, namely isoprene, α-pinene, and β-caryophyllene. This article is a companion paper to “Particle-phase processing of α-pinene NO₃ secondary organic aerosol in the dark”, published in the same journal (Bell et al., 2021). Bell et al. (2021) present the evolution of the composition of NO₃-initiated SOA from α-pinene during dark ageing. Here, we focus on the impacts of photolytic ageing on both the chemical composition and volatility of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$. We compare the chemical composition of particle-phase compounds before and after 1 h of ultraviolet (UV) irradiation using advanced mass spectrometric techniques, determine photolabile fractions for each BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ system, and investigate the potential chromophores that photolyze. In addition, we also examine the changes in the bulk volatility with both parameterization and experimental methods.

2 Experimental section

2.1 Chamber and experimental description

Experiments were conducted in the Paul Scherrer Institute Simulation Chamber for Atmospheric Chemistry (PSI-SCAC, Platt et al., 2013), which is an 8 m³ flexible Teflon chamber suspended in a temperature-controlled shipping container. The chamber is surrounded by a bank of black lights (40×100 W Cleo Performance solarium lamps, Philips; Krapf et al., 2016). The experiments were performed under humid conditions (RH ≈ 60 %) and at a temperature of 21 ± 3 ^∘C (with an increase of 3–4 ^∘C during photolysis). A list of the experiments is given in Table 1.

Table 1 List of experiments and summary of experimental conditions.

SOA was formed in the chamber by the reaction of the precursors with NO₃ radicals. Each experiment followed a similar protocol. First, the chamber was cooled from 30 to ∼20 ^∘C, and the humidity was then increased by boiling Milli-Q water (18 Mohm) until the desired relative humidity (RH) was reached. After the chamber conditions were stabilized, the desired VOC was injected into the chamber volumetrically, and its concentration was monitored with a proton transfer reaction mass spectrometer (quadrupole-PTR-MS, IONICON). β-Caryophyllene could not be monitored with the PTR-MS because its mass-to-charge ($m/z$) ratio of 204 Th is outside of the mass transmission range for quantitative measurements, although trace amounts of the molecule were detected in the experiment. After the VOC concentration had been stable for 5–15 min, N₂O₅ was injected into the chamber, which acted as the source of NO₃ radicals via decomposition. N₂O₅ was synthesized by reacting O₃ (∼1 %–2 %, generated with an Innovatec ozone generator using PSI-provided O₂) with a pure source of NO₂ (99 %). N₂O₅ crystals were collected by passing the gaseous components into a cooled flask (−70 ^∘C). Each day, the sample was brought to the chamber in a dry-ice ethanol bath and warmed for 1–2 min prior to injection (5 L min⁻¹ for ∼10 s). A 0-D box model (F0AM) (Wolfe et al., 2016) utilizing the Master Chemical Mechanism (MCM) (Jenkin et al., 1997) was used to model the VOC precursor decay to determine a range of initial N₂O₅ concentrations. This was performed when the VOC was measurable, which was not the case for the β-caryophyllene experiment (Exp. 4), where the estimate of >200 ppb (Table 1) comes from the average N₂O₅ concentrations in the other experiments performed. After the injection was complete, the chamber was stirred by injecting zero air into the chamber (100 L min⁻¹ for ∼10 min). Following chamber stirring, the volume of the chamber started to decrease due to all of the instruments sampling air from the chamber. Experiments started under dark conditions to probe NO₃-initiated SOA formation and to follow its chemical transformation with no external stimulus. After ∼3–5 h of dark ageing, the chamber was irradiated with UV lights (λ_max= 350 nm; see Platt et al., 2013) for about 1 h to test the impacts of photolytic ageing. After each experiment, ∼1000 ppb O₃ was added, the chamber was continuously flushed with zero air (∼100 L min⁻¹), and the temperature of the enclosure was increased to 30 ^∘C overnight to promote the evaporation of HNO₃ from the walls of the chamber.

O₃ was measured with an O₃ analyser (Thermo 49C), and NO_x and NO₂ were measured with a chemiluminescence NO_x monitor (Thermo 42C). Aerosol number size distributions were measured using a scanning mobility particle sizer (SMPS, TSI Model 3938). Both a chemical ionization mass spectrometer with a filter inlet for gases and aerosols (FIGAERO-CIMS, Aerodyne Research, Inc.) with iodide as the reagent ion and an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF, TOFWERK) were used to measure the molecular composition of organic compounds. The FIGAERO-CIMS performed semi-continuous online measurements and shifted analysis between the particle phase and the gas phase, and the EESI-TOF continuously measured the particle phase with rapid response. In a subset of the experiments (Exp. 1, Exp. 2, and Exp. 4), the evaporation of particles was measured with a custom-built volatility tandem differential mobility analyser (VTDMA) (Tritscher et al., 2011).

2.2 Chemical ionization mass spectrometer with a filter inlet for gases and aerosols

The design and operation of the FIGAERO-CIMS were similar to those described in previous studies (Lopez-Hilfiker et al., 2014; Lee et al., 2014; Huang et al., 2018). In this study, the FIGAERO inlet was coupled to a high-resolution time-of-flight chemical-ionization mass spectrometer (HR-TOF-CIMS) ($M/\mathrm{\Delta }M\sim$ 5000–6000), and I⁻ was used as the reagent ion. An X-ray generator was used to ionize methyl iodide and produce the reagent ion in a nitrogen flow. Particles were collected on a 25 mm Zefluor^® polytetrafluoroethylene (PTFE) filter (Pall Corp.) inside the FIGAERO via a sampling port (stainless-steel tube of ca. 1.5 m length, flow rate 5 L min⁻¹). The duration of particle-phase sampling depended on the mass concentrations in the chamber and was 10–20 min for most of the experiments. For each experiment, three to four filters were sampled during dark ageing, and one filter was collected after about 1 h of photolytic ageing. In addition, one particle blank was performed for each experiment during dark ageing (for details on the background subtraction, see Fig. S1 and the supporting information in the Supplement). During particle-phase collection, gases were measured via a 6 mm Teflon tube of ∼1 m length at 5 L min⁻¹. When the particle-phase sampling was completed, the gas-phase measurement was switched off and particles on the filter were desorbed by a flow of ultra-high-purity (99.999 %) nitrogen. A FIGAERO desorption round lasted about 55 min: 20 min of ramping the temperature of the nitrogen flow from ambient temperature up to 200 ^∘C was followed by a 20 min “soak period” at a constant temperature of 200 ^∘C and 15 min of cooling down to room temperature. The mass spectral signal evolutions as a function of desorption temperature are termed thermograms (Lopez-Hilfiker et al., 2014). The integration of thermograms of individual compounds (cooling period excluded) yields their total signal in counts per deposition. Here, we did not convert the counts per deposition into chamber concentrations, as we only show normalized signal (either signal normalized to the dominating compound or to the sum signal of all compounds). We observed modest or negligible fragmentation due to thermal desorption in the FIGAERO inlet (5 %–27 %, 1 %–4 %, and 10 %–23 % of the total organic signal of the isoprene, α-pinene, and β-caryophyllene SOA respectively). As shown in Fig. S3, most of the thermograms of individual compounds for all systems exhibited unimodal and sharp peaks. Thermal fragmentation products were detected either through thermograms of individual compounds with multiple peaks (normally double peaks) or one peak with T_max (desorption temperature at which a compound's signal exhibits a maximum) much higher than the estimated T_max (e.g. for α-pinene SOA, a C₁₀ monomer had a T_max≈ 140 ^∘C which is in the range of T_max for C₂₀ dimers; Faxon et al., 2018). Artefacts resulting from thermal fragmentation products were corrected for (see Sect. S1.2 and Fig. S2 in the Supplement). In addition, only a small fraction (< 1 % of the total mass) of the compounds were deprotonated. In this study, we only report the molecules clustered with I⁻. Further information concerning the correction of thermal decomposition and the data analysis is provided in the supporting information in the Supplement.

2.3 Extractive electrospray ionization time-of-flight mass spectrometer

A detailed description of the EESI-TOF can be found in previous work (Lopez-Hilfiker et al., 2019; Pospisilova et al., 2020) and in the companion paper to this publication (Bell et al., 2021). In brief, the EESI-TOF samples the aerosol formed in the chamber via a sampling line (∼3.5 m long stainless-steel tube) and removes the gaseous components by passing the sampled volume through a multichannel charcoal denuder. The aerosol sample then intersects a spray of droplets emanating from a fused silica electrospray capillary (50 : 50 H₂O : acetonitrile doped with 100 ppm NaI). The droplets envelope the aerosol sample and extract the water-soluble fraction of the aerosol. During droplet evaporation, a majority of the extracted molecules bind to Na⁺, creating positively charged adducts. The ions are guided to the time-of-flight mass spectrometer ($M/\mathrm{\Delta }M\sim$ 5500–7000) where their $m/z$ ratio is determined. Background measurements were conducted every 4 min for 1 min by passing the sample air through a particle filter. The reported signal throughout the work is the difference spectrum of consecutive 4 min average signal and 1 min average background signal. The EESI-TOF signal (Hz) is scaled by the molecular weight of each ion in order to represent the EESI-TOF signal as a mass-based measurement (ag s⁻¹). Artefacts associated with these measurements are discussed in Bell et al. (2021). The EESI-TOF data for most experiments had similar bulk sensitivities, except for the α-pinene experiment (Exp. 3), which was about a factor of 10 lower because the EESI-TOF was still being optimized and the capillary position and TOF settings were being altered.

2.4 Volatility tandem differential mobility analyser

The custom-built VTDMA (see e.g. Tritscher et al., 2011) sampled aerosols through the same inlet as the EESI-TOF, the SMPS, and a silica gel diffusion drier downstream of the chamber. The VTDMA combines two differential mobility particle sizer (DMPS) systems, coupled in series with a heating unit in between. Both DMPS systems consist of a custom-made DMA (Stockholm University, operated with closed-loop sheath air) and a condensation particle counter (CPC, TSI Model 3010). Before entering each DMPS system, the particles were brought into charge equilibrium using a Ni-63 source. The first DMA selected a nearly monodisperse aerosol with the diameter set to the geometric mean diameter measured in situ by the SMPS upstream (127, 87, and 219 nm) during both dark ageing and photolysis for Exp. 1, Exp. 2, and Exp. 4 respectively). The sample flow was then split into two, with one half going to the CPC measuring the selected particle concentration and the other half entering a 35 cm long custom-built thermodenuder (TD) with a residence time of 1.9 s, which heated the aerosol to 150 ^∘C in Exp. 1 and Exp. 2 and to 175 ^∘C in Exp. 4. The size distribution (over 15 bins) of the heated aerosol was measured in the second DMPS system with a time resolution of approximately 5 min, and the change in size was converted to an estimate of the volume fraction remaining (VFR):

$$\begin{array}{}\text{(1)}& \mathrm{VFR}={\displaystyle \frac{D{\left(T\right)}^{\mathrm{3}}}{D_{\mathrm{init}.}^{\mathrm{3}}}},\end{array}$$

where D_init. is the initial diameter, and D(T) denotes the heated (temperature, T) diameters, represented by the geometric mean mode diameter estimated using a Gaussian fit of the whole heated size distribution.

2.5 Wall loss correction

The particle mass concentrations (in µg m⁻³) were derived from integrated number size distributions and their conversions to mass using an assumed organic aerosol density (1.19 g cm⁻³; Vaden et al., 2011). They were corrected for wall losses using a uniform dynamic wall loss rate k_wall for the whole size range. k_wall was determined from the observed exponential decay of the particle number concentration (taking coagulation into account) using Eq. (2), where N corresponds to the particle number concentration, and k_coag corresponds to the coagulation coefficient ($\mathrm{5}\times {\mathrm{10}}^{-\mathrm{10}}$ s⁻¹; Pospisilova et al., 2020):

$$\begin{array}{}\text{(2)}& {\displaystyle \frac{\mathrm{d}N}{\mathrm{d}t}}=-k_{\mathrm{coag}}\cdot N^{\mathrm{2}}-k_{\mathrm{wall}}\cdot N.\end{array}$$

The wall-loss-corrected particle mass concentration was divided by the uncorrected mass concentration to obtain the wall loss correction factor applied to the EESI-TOF and FIGAERO-CIMS signal. In the experiments performed here, the total number concentration (in cm⁻³) varied between 10⁶ and 10⁴ at the beginning of the experiment to 10⁴ and 10³ at the end of the experiment. In experiments with large number concentrations (e.g. > 5×10⁴ cm⁻³ in Exp. 4), coagulation was the dominant particle sink, which resulted in a mobility diameter that increased during the experiment, even though the mass was decreasing due to evaporation. The particle number concentration was constrained to be constant throughout the lifetime in the chamber, based upon k_wall and k_coag. Evaporation of semi-volatile compounds will not affect the particle wall loss correction because this does not change the particle number concentration, only the particle volume (or mass).

2.6 Estimating bulk saturation mass concentration C^* based on FIGAERO-CIMS and VTDMA

The saturation mass concentration (C^*) of individual compounds was calculated based on their molecular composition using three different, previously published parameterizations:

1. an updated version of the parameterization by Donahue et al. (2011), modified based on the saturation concentrations of highly oxygenated molecules (HOMs) detected by Tröstl et al. (2016) and published by Mohr et al. (2019):

   $$\begin{array}{}\text{(3)}& \begin{array}{rl}{\log }_{\mathrm{10}}{C}^{*}& =\left(n_{\mathrm{0}}-n_{\mathrm{C}}\right)b_{\mathrm{C}}-(n_{\mathrm{O}}-\mathrm{3}{n}_{\mathrm{N}})b_{\mathrm{O}}\\ & -\mathrm{2}{\displaystyle \frac{n_{\mathrm{C}}(n_{\mathrm{O}}-\mathrm{3}{n}_{\mathrm{N}})}{n_{\mathrm{C}}+n_{\mathrm{O}}-\mathrm{3}{n}_{\mathrm{N}}}}{b}_{\mathrm{CO}}-n_{\mathrm{N}}{b}_{\mathrm{N}},\end{array}\end{array}$$

   where n₀= 25, b_C= 0.475, b_O= 0.2, b_CO= 0.9, and b_N= 2.5. n_C, n_O, and n_N are the number of carbon, oxygen, and nitrogen atoms in the compound respectively. For ONs, it is assumed that a nitrate group reduces a compound's vapour pressure by about 2.5 orders of magnitude (Donahue et al., 2011; Pankow and Asher, 2008).

2. an updated version of Li et al. (2016) with a modified nitrogen coefficient for organic nitrates (Isaacman-VanWertz and Aumont, 2021):

   $$\begin{array}{}\text{(4)}& {\log }_{\mathrm{10}}{C}^{*}=\left(n_{\mathrm{0}}-n_{\mathrm{C}}\right)b_{\mathrm{C}}-n_{\mathrm{O}}{b}_{\mathrm{O}}-\mathrm{2}{\displaystyle \frac{n_{\mathrm{C}}{n}_{\mathrm{O}}}{n_{\mathrm{C}}+n_{\mathrm{O}}}}{b}_{\mathrm{CO}}-n_{\mathrm{N}}{b}_{\mathrm{N}},\end{array}$$

   where n₀= 22.66, b_C= 0.4481, b_O= 1.656, and b_CO= −0.7790 for CHO compounds, and n₀= 24.13, b_C= 0.3667, b_O= 0.7732, b_CO= −0.07790, and b_N= −1.5464 for CHON compounds. n_C, n_O, and n_N are the number of carbon, oxygen, and nitrogen atoms in the compound respectively. The modification of the parameterization is based on the observation that a nitrate group has a similar impact on vapour pressure as a hydroxyl; thus, one nitrate group (one nitrogen atom and three oxygen atoms) reduces a compound's vapour pressure by 0.7732 orders of magnitude (Isaacman-VanWertz and Aumont, 2021).

3. a parameterization based on highly oxygenated organic molecules (HOMs) from α-pinene ozonolysis (Peräkylä et al., 2020):

   $$\begin{array}{}\text{(5)}& \begin{array}{rl}{\log }_{\mathrm{10}}{C}^{*}& =\mathrm{0.18}\times n_{\mathrm{C}}-\mathrm{0.14}\times n_{\mathrm{H}}-\mathrm{0.38}\times n_{\mathrm{O}}\\ & +\mathrm{0.80}\times n_{\mathrm{N}}+\mathrm{3.1},\end{array}\end{array}$$

   where n_C, n_H, n_O, and n_N are the number of carbon, hydrogen, oxygen, and nitrogen atoms in the compound respectively. With this parameterization, a nitrate group reduces a compound's vapour pressure by 0.34 orders of magnitude.

We note here that more such parameterizations exist in literature (Donahue et al., 2011; Daumit et al., 2013). We choose these three parameterizations as they have explicit formulations for nitrate groups/nitrogen. The parameterizations calculate C^* at a temperature of 300 K. The temperature dependence of C^* is considered as follows:

$$\begin{array}{}\text{(6)}& C^{*}\left(T\right)=C^{*}\left(\mathrm{300}\mathrm{K}\right)\exp \left({\displaystyle \frac{\mathrm{\Delta }{H}^{\mathrm{VAP}}}{R}}\left({\displaystyle \frac{\mathrm{1}}{\mathrm{300}\mathrm{K}}}-{\displaystyle \frac{\mathrm{1}}{T}}\right)\right),\end{array}$$

where T is the temperature in kelvin, C^*(300 K) is the saturation concentration at 300 K, R is the gas constant, and ΔH^VAP is the vaporization enthalpy. The latter is calculated as follows (Epstein et al., 2010):

$$\begin{array}{}\text{(7)}& \begin{array}{rl}\mathrm{\Delta }{H}^{\mathrm{VAP}}& =-\mathrm{11}{\log }_{\mathrm{10}}{C}^{*}\left(\mathrm{300}\mathrm{K}\right)+\mathrm{129};\mathrm{\Delta }{H}^{\mathrm{VAP}}\\ & <\mathrm{200}\mathrm{kJ}{\mathrm{mol}}^{-\mathrm{1}}.\end{array}\end{array}$$

For each filter sample from the FIGAERO-CIMS, the mass-weighted average log₁₀C^* for the entire particle population deposited on the filter (bulk) was calculated and adjusted to the same T (298.3 K) as that used by the kinetic model (see the description below) for further comparison.

The T_max, the desorption temperature at which a compound's signal exhibits a maximum in the FIGAERO-CIMS, has previously been shown to be qualitatively connected to the compound's volatility (log₁₀C^* or enthalpy of vaporization) (Lopez-Hilfiker et al., 2014; Thornton et al., 2020; Bannan et al., 2019). For each filter sample from the FIGAERO-CIMS, we calculated the mass-weighted average T_max of the entire particle population deposited on the filter (bulk).

As an additional method to constrain the bulk volatility, VTDMA measurements of the VFR were used to determine the bulk log₁₀C^* with a kinetic model that simulates the evaporation of a monodisperse aerosol in the heated part of the VTDMA (Riipinen et al., 2010). The bulk log₁₀C^* (at 298.3 K) was determined manually so that the calculated VFR matches the measurements. Additional model input parameters include the settings of the VTDMA (i.e. initial particle diameter and concentration), the residence time and temperature in the heated section, and the ambient temperature at the time of the measurement.

3 Results and discussion

3.1 Mass yields of isoprene, α-pinene, and β-caryophyllene BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$

As shown in Table 1, the wall-loss-corrected SOA yields and maximal mass concentrations formed from isoprene, α-pinene, and β-caryophyllene are 4 %–9 % at 11–24 µg m⁻³, 3 % at 18 µg m⁻³, and 110 % at 464 µg m⁻³ respectively. The SOA yields observed here are comparable to previously reported values: for isoprene + NO₃, yields between 2 % and 24 % have been presented (Rollins et al., 2009; Ng et al., 2008); for α-pinene + NO₃, yields between 0 % and 16 % have been presented (Hallquist et al., 2009; Nah et al., 2016; Fry et al., 2014); and for β-caryophyllene + NO₃, yields between 86 % and 146 % have been presented (Fry et al., 2014; Jaoui et al., 2013). The yields at the lower end of the range of reported values of the isoprene and α-pinene SOA in our study can likely be explained by the lack of seed aerosol in those experiments. For β-caryophyllene, most of the products are of sufficiently low volatility (see Sect. 3.5), and the SOA yields are similar to those from the seeded experiments. The variation in SOA yields can also be caused by different chemical regimes, resulting, for example, in different branching ratios for the peroxy radicals (RO₂) + hydroperoxyl radical (HO₂), RO₂ + NO₃, and RO₂ + RO₂ pathways after the initial RO₂ formation via NO₃ + VOCs. The RO₂ + RO₂ pathway is a more effective channel for forming SOA than the RO₂ + HO₂ and RO₂ + NO₃ pathways (Ng et al., 2008). In Ng et al. (2008), the SOA yield from the isoprene + NO₃ experiments (seeded), where the RO₂ + RO₂ pathway dominated, was much higher (23.8 %) than that from experiments where the RO₂ + NO₃ pathway dominated (4.3 %), as RO₂ + RO₂ chemistry led to the formation of oligomers. In the study of Nah et al. (2016), the branching ratios for the RO₂ + HO₂, RO₂ + NO₃, and RO₂ + RO₂ pathways were 5 : 4 : 1, and an SOA yield of 1.7 % at 1.2 µg m⁻³ (no seed) was observed for α-pinene + NO₃ SOA. In our experiments, we achieved higher SOA yields from α-pinene + NO₃, due to N₂O₅ : VOC ratios between 1 and 5 and the radical balance being dominated by either RO₂ + RO₂ (at low N₂O₅ : VOC) or RO₂ + NO₃ (at high N₂O₅ : VOC) chemistry and no significant source of HO₂ radicals. As discussed in Bell et al. (2021), even in experiments where the N₂O₅ : VOC ratio is high (∼3) and the MCM model predicts the RO₂ + NO₃ pathway to be dominant, the initial composition of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ formed here in the dark is still dominated by RO₂ + RO₂ reactions, resulting in substantial fractions of oligomers and indicating that the rate of the RO₂ + RO₂ pathway is likely underestimated by the MCM model.

The evolution of the SOA mass concentrations and particle size during both dark ageing (2 h before photolysis) and photolysis are shown in Fig. 1 for all systems. Before photolysis, for the α-pinene system (Exp. 3), steady evaporation was observed from the particles, which is consistent with a shrinking mean diameter (from 240 to 233 nm) resulting in a 15 % loss of particle mass (corrected for wall loss) or volume. For the two isoprene experiments (Exp. 1 and Exp. 2), ∼6 % of the mass was lost during dark ageing. The wall-loss-corrected mass concentrations of the β-caryophyllene SOA are stable throughout the dark ageing period, while the geometric mean diameter of the particles increases from 229 nm (at time −2 h in Fig. 1) to 266 nm (at time 0 h), as a result of particle coagulation following the large number concentrations (∼10⁶ cm⁻³). The differences in evaporation can likely be attributed to the lower volatility of β-caryophyllene monomers (C₁₅) compared with isoprene dimers (C₁₀) and α-pinene monomers (C₁₀) (for details, see Sect. 3.5). Overall, the BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ formed during dark ageing exhibits slight to moderate shrinkage of its mass and size (following correction for wall loss) after the initial production.

Figure 1 Time series of the normalized mass concentration (a) and geometric mean diameter (b) of the SOA measured by the SMPS. SOA mass loadings were corrected for particle wall losses based on the decay of the particle number concentration. The mass concentration is normalized to the mass concentration value when the lights were turned on (time = 0 in the figure). The area shaded in yellow corresponds to the period of UV irradiation. The expected curvature of the mass concentration and geometric mean diameter without UV irradiation is represented by the dashed lines.

3.2 Chemical composition of isoprene, α-pinene, and β-caryophyllene BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$

In total, 478, 425, and 366 organic molecular compositions (including 436, 332, and 348 ONs) were identified with the FIGAERO-CIMS, and 359, 158, and 441 organic molecular compositions (including 273, 134, and 268 ONs) were identified with the EESI-TOF, for the isoprene, α-pinene, and β-caryophyllene SOA respectively. In the α-pinene + NO₃ experiment (Exp. 3), due to the lower sensitivity of the EESI-TOF compared with other experiments (described in Sect. 2.3), the compounds detected by the EESI-TOF were fewer than those detected in other experiments. Due to the dominating RO₂ + RO₂ pathway, oligomers make a substantial contribution to the total mass formed in the dark. The mass fractions of oligomers are ∼100 %, 86–88 %, and 60–63 % with the FIGAERO-CIMS and 97 %–98 %, 85 %–99 %, and 13 %–22 % with the EESI-TOF, for the isoprene, α-pinene, and β-caryophyllene SOA respectively. The dimer-to-monomer ratio varies across the three systems, and it increases with decreasing carbon number of the precursors.

The mass spectra of the particle-phase species of the three systems obtained from the FIGAERO-CIMS and the EESI-TOF shortly before switching on the lights are shown in Fig. 2. For the isoprene system, Exp. 1 and Exp. 2 are similar; thus, only Exp. 1 is presented here, and Exp. 2 is presented in the Supplement (Fig. S6). For the isoprene SOA, monomers are negligible (C_1–5 compounds are less likely to partition into the particle phase due to their relatively high volatility), and dimers with three to four nitrate groups (e.g. C₁₀H₁₇N₃O₁₃ and C₁₀H₁₈N₄O₁₆, each contributing 15 % to the total mass) dominate the mass measured by the FIGAERO-CIMS. Dimers with one, two, and five nitrate groups (44 %), and trimers (21 %) also contribute a substantial fraction to the total mass. The major compounds observed in our study are similar to those observed by Ng et al. (2008), who used a Waters ACQUITY ultra-performance liquid chromatography system coupled to a Waters LCT Premier XT time-of-flight mass spectrometer equipped with an ESI source that is operated in the negative (–) ionization mode (UPLC/(–)ESI-TOFMS) and investigated N₂O₅ : isoprene ratios from 0.6 to 5. For the EESI-TOF, the major compounds are similar, with the same highest peak (C₁₀H₁₇N₃O₁₃) as measured by the FIGAERO-CIMS. However, the relative intensities are different. Compared with the FIGAERO-CIMS, the EESI-TOF measures higher signals of C₁₀H₁₆N₂O₁₀, C₁₅H₂₄N₄O₁₈, and C₂₀H₂₅N₃O₁₉, but lower signals of C₁₀H₁₇N₃O₁₂, C₁₀H₁₈N₄O₁₆, and C₁₀H₁₇N₅O₁₈. There is a high signal from C₄H₆O₂, which comes from the degradation of oligomeric species C₁₀H₁₆N₂O_9,10 and C₁₀H₁₇N₃O₁₃.

Figure 2 FIGAERO-CIMS (positive axis) and EESI-TOF (negative axis) mass spectra of particle-phase C_xH_yO_zN_0–4 formed during (a) Exp. 1 (isoprene + NO₃), (b) Exp. 3 (α-pinene + NO₃), and (c) Exp. 4 (β-caryophyllene + NO₃) shortly before photolysis. For FIGAERO-CIMS, the last filter before photolysis is chosen (Pre 2 in Fig. 3). The EESI-TOF mass spectra are averaged mass spectra during the same sampling time as that of FIGAERO-CIMS. All mass spectra are normalized to the corresponding maximal signal.

The α-pinene system according to the FIGAERO-CIMS measurements is dominated by C₂₀ dimers with two nitrate groups, i.e. C₂₀H₃₂N₂O_8–13 make up 39 % of the total mass, while the monomers and trimers contribute 12 %–14 % and 3.7 %–4.4 % respectively. Our mass spectra are similar to those reported in Takeuchi and Ng (2019) (measured with a FIGAERO-CIMS), where the α-pinene + NO₃ SOA was dominated by C₂₀ dimers with two dominating compounds, C₂₀H₃₂N₂O₉ and C₂₀H₃₂N₂O₁₀. The dominating monomer in their study was C₁₀H₁₅NO₆, also identical to our study. Their ratio of C₂₀H₃₂N₂O₉ to C₁₀H₁₅NO₆ was about 5, which was ∼2 times higher (about 10) in our study. In Takeuchi and Ng (2019), reactions between peroxy radicals (RO₂ + RO₂) and RO₂ + NO₃ are also favoured. The presence of large concentrations of RO₂ in both studies likely leads to the large fraction of oligomers. The EESI-TOF detected similar dimers and monomers as those measured by the FIGAERO-CIMS. However, the highest peak measured is C₂₀H₃₂N₂O₉ for the FIGAERO-CIMS and C₂₀H₃₂N₂O₈ for the EESI-TOF. It is also worth noting that the EESI-TOF measured a few CHO compounds without nitrate groups, such as C₁₀H₁₆O₃ and C₁₀H₁₆O₄.

The β-caryophyllene SOA mass spectrum from the FIGAERO-CIMS is dominated by C₁₅ monomers with one to two nitrate groups (C₁₅H_23,25NO_7,8 and C₁₅H_24,26N₂O₈₋₁₀) and C₃₀ dimers with two to three nitrate groups (C₃₀H₄₈N₂O_10–12 and C₃₀H₄₉N₃O₁₂₋₁₄). The mass spectrum from the EESI-TOF is dominated by C₁₅ monomers with zero and one nitrate group. The contribution from the dimers is substantially smaller compared with FIGAERO-CIMS, which may result from a decreased sensitivity of larger $m/z$ components, as observed previously (Lopez-Hilfiker et al., 2019), and/or from decomposition of ON dimers. The higher contribution from the monomers, compared with the isoprene and α-pinene systems, is likely due to the larger number of carbon atoms of β-caryophyllene, and the two double bonds (one more than α-pinene), which both lead to the low volatility of the monomers (for details, see Sect. 3.5).

Overall, both instruments are able to cover the major compounds from both monomer and dimer regions, although the sensitivity towards different compounds varies. The I⁻ CIMS is not sensitive towards non-oxygenated compounds, monoalcohols, monoketones, or monoaldehydes (Lee et al., 2014), whereas the EESI-TOF is sensitive to nearly all compounds present in SOA but is not sensitive to non-oxygenated compounds (Lopez-Hilfiker et al., 2019). Differences are also caused by the fragmentation of oligomers into smaller compounds (C_xH_yO_z) inside the EESI-TOF, such as C₄H₆O₂ in the isoprene + NO₃ system, and a few CHO compounds in the α-pinene and β-caryophyllene systems. These compounds are likely related to artefacts from the electrospray ionization (Goracci et al., 2017; James et al., 2006; Keith-Roach, 2010; Maire and Lange, 2010; Kourtchev et al., 2020; Rovelli et al., 2020). They may occur due to the proximity of –ONO₂ functional groups next to peroxy linkages, which results in fragmentation of molecules when particles are exposed to water in the electrospray (Bell et al., 2021) as well as the loss of a HNO₃ fragment during ionization (Liu et al., 2019).

3.3 Photolytic ageing of isoprene, α-pinene, and β-caryophyllene BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$

As can be observed in Fig. 1, switching on the lights affects particle mass and size for all BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ systems, although to a different extent. For the isoprene SOA, the particle size and mass show a slightly steeper decrease compared with the situation expected without UV irradiation (dashed lines). For the α-pinene SOA, both the particle size and mass decrease compared with the dark, from 229 nm and a normalized mass concentration of 0.9 to 219 nm and 0.87 after 1 h photolysis respectively. The β-caryophyllene SOA, although the least volatile, shows a decrease of 12 % (normalized mass concentration of 0.83 vs. 0.95 expected without UV irradiation) and a reduction of the mean particle size from 273 to 230 nm. These results indicate that there are slight to moderate losses of particle-phase compounds due to UV irradiation. The possible reasons for the differences in the three systems will be discussed in this section and in Sect. 3.5.

In Fig. 3, the relative changes in the chemical composition of the SOA before (pre) and after (post) photolytic ageing measured by the FIGAERO-CIMS are illustrated. During irradiation, processes/reactions occurring in the dark may also continue with the lights on – for example, consumption/decomposition of reactive oxygen species (Pospisilova et al., 2020), evaporation of semi-volatile compounds, and hydrolysis of nitrate functional groups can alter the chemical composition of SOA particles. To account for this, Fig. 3 compares the chemical composition of two particle filter samples collected during dark ageing (Pre 1 and Pre 2) and one filter sample collected after 1 h of photolytic ageing (Post). The time interval of the sampling was about 1.5–2 h or about 3 h if a particle blank was performed between two filters. The difference between the two filters during dark ageing (Pre 2 – Pre 1) shows the changes in the chemical composition caused by all processes other than photolysis, whereas the difference between the last filter during dark ageing and the one after 1 h photolysis (Post – Pre 2) shows the impacts of the above-mentioned processes plus the impact of UV irradiation.

Figure 3 Relative changes in the fraction of the total signal between two filters during dark ageing (Pre 2 – Pre 1) and between the last filter during dark ageing and the filter after 1 h of photolysis (Post – Pre 2) for (a) Exp. 1 (isoprene + NO₃), (b) Exp. 3 (α-pinene + NO₃), and (c) Exp. 4 (β-caryophyllene +  NO₃).

The comparison between the two filters during dark ageing (Pre 2 – Pre 1 in Fig. 3) shows relatively small changes in the chemical composition that are similar for all three systems: the signal fractions of high-molecular-weight compounds increase and the signal fractions of low-molecular-weight compounds decrease. The signal fraction changes in individual compounds are less than 2 %. Such change is mainly due to the evaporation of semi-volatile compounds, as gas-phase wall losses act as a sink for semi-volatile compounds, resulting in the repartitioning of the particle phase (Bertrand et al., 2018). Bell et al. (2021) show that most of the changes in chemical composition in the α-pinene SOA system occur over the first 2 h of dark ageing, meaning that the chemical composition has mostly stabilized at the time directly prior to photolysis. Figure S7 in the Supplement shows the changes in absolute signal fraction for the filter samples pre- and post-photolysis for Exp. 3.

During photolysis, the changes observed in the mass spectral patterns (Post – Pre 2 in Fig. 3) differ from those during dark ageing and also have a larger magnitude. For the isoprene system, the compounds exhibiting the largest decays in signal fraction are C₁₀H₁₇N₃O_12–13 and C₁₀H₁₆N₄O_14–15 (8 % and 2 % of the total signal respectively). At the same time, there are a few compounds (e.g. C₉H₁₄N₂O₇ and C₁₀H₁₄N₂O₉) whose signal fractions increase (< 1 %). For the α-pinene system, the signal fraction of the main dimer compounds (C₂₀H₃₂N₂O₈₋₁₀) decreases by 13.6 % during photolysis, whereas the signal fractions of a few monomers (e.g. C₉H₁₅NO₆₋₈ and C₁₀H₁₅NO₈₋₉) increase by up to 2 %. The β-caryophyllene SOA system shows decreases in the signal fractions of both monomers and dimers, mainly C₁₅H₂₅NO₈, C₁₅H₂₃NO₉, C₁₅H₂₆N₂O₉, and C₃₀H₄₈N₂O_11–13, whereas the signal fractions of quite a few compounds, including C_12–14 compounds (e.g. C₁₄H₂₃NO_6,7), C₁₅ compounds (e.g. C₁₅H₂₃NO₆, C₁₅H₂₅N₂O₈), C_16–29 compounds (e.g. C₂₉H₄₆N₂O_9–11), and C₃₀ compounds (e.g. C₃₀H₄₆N₂O₁₂), increase. Overall, our results show that the major compounds decomposing during photolysis are both monomers and oligomers and that there are also compounds formed that contain lower carbon numbers and/or fewer nitrate groups.

The FIGAERO-CIMS offers insight into the pre- vs. post-photolysis SOA composition, and the EESI-TOF allows one to monitor the evolution of individual compounds at high time resolution. Using a linear fit to the 2 h pre-photolysis time series of the individual compounds measured by the EESI-TOF and then comparing a predicted value based on this fit at 1 h post-photolysis (with 95 % confidence interval) with the actual measured signal (see Fig. S8 in the Supplement), we find that 54 (the average value from Exp. 1 and Exp. 2) out of 359, 24 out of 158, and 104 out of 441 compounds decreased significantly during photolysis, i.e. by 44 % ± 20 %, 64 % ± 24 %, and 24 % ± 18 % for the isoprene, α-pinene, and β-caryophyllene SOA respectively. These compounds contributed 48 %, 44 %, and 60 % to the total pre-photolysis signal for these three respective systems. Meanwhile, there were 116, 53, and 164 compounds that increased during photolysis for the isoprene, α-pinene, and β-caryophyllene SOA respectively. We note, however, that the fraction appearing to be resistant to photolysis or even showing increase may undergo functional group changes during photodegradation. For example, the decay of molecules C_xH_yO_zN may be compensated for by the photodegradation of other molecules which produces products with the same molecule formula C_xH_yO_zN but different structures. Here, we cannot fully exclude particle-phase compound volatilization resulting from an increase in chamber temperature (3–4 ^∘C, caused by heating from the chamber lights). However, because most of the compounds showing decay are oligomers with very low predicted volatilities, such an increase in temperature is unlikely to play a major role in the change of composition.

Figure 4 shows the time series of the main compounds that degrade during photolysis for each system, measured by both the EESI-TOF and the FIGAERO-CIMS. Within the error tolerances, the time series of the compounds measured by the two instruments have a good agreement. The decay rates of these compounds are compound dependent. Even though 1 h of photolytic ageing might be too short to observe full decay trajectories (Zawadowicz et al., 2020; O'Brien and Kroll, 2019), it is long enough to distinguish the non-photolabile compounds and the photolabile compounds and to compare the decay rates of the photolabile compounds (Henry and Donahue, 2012; Wong et al., 2015). As also shown by Nah et al. (2016), most of the changes in α-pinene + NO₃ SOA due to photochemical ageing happened in the first 1 h of light exposure.

Figure 4 Time series of the isoprene tracers C₁₀H₁₇N₃O_12,13 (Exp. 1 and Exp. 2), the α-pinene tracers C₂₀H₃₂N₂O₈₋₁₀ (Exp. 3), and the β-caryophyllene tracers C₃₀H₄₈N₂O_8–10 (Exp. 4) from the EESI-TOF and the FIGAERO-CIMS.

Figure 5 Mass-weighted number of nitrate groups per monomer (number of carbon atoms/number of the carbon atoms in precursors – 5, 10, and 15 for the isoprene, α-pinene, and β-caryophyllene SOA, respectively) and mass-weighted number of non-nitrate oxygen atoms per monomer for three filters (Pre 1, Pre 2, and Post) for all experiments.

Photolysis requires chromophores, which absorb particular wavelengths of visible light. Earlier studies on the photodegradation of OH- and O₃-initiated SOA under low-NO_x conditions have demonstrated that photolysis fragments molecules with functional groups like carbonyls (C=O) and peroxides (R–O–O–R) (Surratt et al., 2006; Walser et al., 2007; Mang et al., 2008; Pan et al., 2009; Krapf et al., 2016). In contrast to these studies, the BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ in our study is rich in nitrate groups and oligomers. In Fig. 5a, we plot the average number of nitrate groups per monomer (monomer unit) for the three FIGAERO-CIMS filter samples (the same as in Fig. 3) selected before and after photolysis for all three SOA systems. Overall, the particle-phase compounds of all three SOA types contain a similar number of nitrate groups per monomer on average (1–1.5). During the last 2–3 h of dark ageing, the nitrate group fraction is stable, but photolysis causes a slight decrease in the nitrate-to-monomer ratio for all systems, consistent with the decrease of 1 %–3 % of the mass fraction of ONs of total organic compounds for all systems. It is clear from this that UV light fragmentation of nitrate groups only plays a minor role in changing the chemical composition of SOA when transitioning from dark to light conditions. It is known that organic nitrates can undergo photolysis and release NO₂ via RONO₂ + hv−>
RO• + NO₂ (Barnes et al., 1993). Measurements of the absorption cross-sections of a number of alkyl nitrates, such as methyl nitrate, and some bifunctional organic nitrates have shown lifetimes of up to between 14 h and 6 d (Barnes et al., 1993). The absorption cross-sections of organic nitrates normally have an absorption maximum at λ < 290 nm and start to decrease when λ > 310 nm (Barnes et al., 1993; He et al., 2021). The black lights in the chamber reproduce the solar spectrum well in the range of 320–400 nm, but the intensity at lower wavelengths (< 320 nm) falls off faster than the solar spectrum. Thus, the photolysis of nitrate groups observed in our study represents a lower limit of what would be expected in the atmosphere. More recent studies have shown that the presence of a nitrate group can enhance the absorption cross-sections and make the photolysis of carbonyl nitrates faster than their reaction with OH (Müller et al., 2014; Suarez-Bertoa et al., 2012). However, based on the stability of the nitrate group fraction during photolytic ageing as described above (compare also Fig. 5), the cleavage of the nitrate functional group from the carbon chain is not the main loss pathway in our study and on the timescales of our experiments.

In terms of oligomers, for the α-pinene and β-caryophyllene systems, the major degrading compounds are C₂₀ and C₃₀ dimers, while the major compounds formed are their corresponding C₁₀ and C₁₅ monomers (the isoprene system is a mix of C₁₀ dimers, C₁₅ trimers, and C₂₀ tetramers, which makes it challenging to identify the potential parent compounds of newly formed compounds). This indicates that for some fraction of the oligomers, the linkage between two monomer blocks is photolabile. Oligomers may be formed through both gas- and particle-phase processes. As RO₂ + R'O₂−> ROOR' + O₂ is the main reaction channel for RO₂ self- and cross-reactions in the gas phase, a large fraction of peroxides can be expected, and such mechanisms of dimer formation were proposed for isoprene + NO₃ SOA (Ng et al., 2008; Zhao et al., 2021; Wu et al., 2021). Recent studies also showed multiple pathways of dimerization in the particle phase or the gas–particle interface (Zhao et al., 2019; Claflin and Ziemann, 2018). All the studies mentioned above show that the formation of dimers, in both the gas- and particle-phases, changes the functional groups of the resulting molecules compared with their building blocks (monomers). It is likely that peroxide functional groups are formed during RO₂ self-/cross-reactions, which could make some dimers photolabile, whereas the formation of potentially photolabile carbonyl functional groups is less certain from NO₃ oxidation.

Some of the compounds being formed during photolytic ageing are molecules with one to three fewer carbon atoms than their potential parent compounds (e.g. C₁₃, C₁₄, and C₂₉ compounds in the β-caryophyllene system), indicating fragmentation of the carbon skeleton. On average, each monomer (or monomer unit) of the isoprene, α-pinene, and β-caryophyllene SOA contains ca. 2, 2.5, and 3 oxygen atoms pre-photolysis (disregarding the oxygen atoms in the nitrate groups) respectively (Fig. 5b), suggesting that, in addition to nitrate groups, these compounds also possess other oxygenated functional groups and other possible chromophores. The β-caryophyllene SOA exhibited higher losses of the particle mass and reduction in size (Fig. 1), followed by the α-pinene SOA, which could partly be explained by its higher number of functional groups per monomer (or monomer unit), i.e. larger photolabile fraction, compared with the other two systems.

Overall, the particle mass loss of nitrate-initiated SOA after 1 h photolysis in our study is less than that reported for the OH- and O₃-initiated SOA under low-NO_x conditions (Zawadowicz et al., 2020; Wong et al., 2015; Henry and Donahue, 2012; Epstein et al., 2014), despite observing larger changes in the chemical composition. One possible reason could be that our systems have a large fraction of oligomers, and photolysis-derived products may not directly evaporate, meaning that a substantial fraction of these products retain low enough volatility to remain in the particle phase. Moreover, in terms of different functional groups, the addition of a nitrate group in a given molecule is estimated to reduce its vapour pressure by about 2.5 orders of magnitude, which is comparable to other oxygenated functional groups often observed in the OH- and O₃-initiated BSOA, for example, the hydroxyl group (−OH) and hydroperoxy group (−OOH) (2.4–2.5 orders of magnitude), or the carbonyl group (=O) (1 order of magnitude) (Pankow and Asher, 2008; Donahue et al., 2011). Thus, the gas-phase compounds formed in our systems could contain fewer functional groups (disregarding nitrate groups) than those in OH- and O₃-initiated BSOA but could still be of low enough volatility to condense into the particle phase. The elemental oxygen-to-carbon (O : C) ratio (disregarding the oxygen atoms in the nitrate groups) of the α-pinene SOA was calculated to be 0.26 ± 0.01 before photolysis in Exp. 3, which is lower than the reported O : C ratios of 0.34–0.36 for BSOA from ozonolysis of α-pinene measured by the FIGAERO-CIMS in laboratory experiments (Huang et al., 2018). As shown above, nitrate groups might be less photolabile than carbonyls and peroxides; thus, different sensitivities towards photolysis can be expected for the systems initiated by different oxidants.

3.4 Changes in the gas phase during photolysis

The primary focus of this study is on the changes in condensed-phase chemical composition of BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ due to photolytic ageing. However, we cannot decouple processes happening in both the particle and gas phases. For example, photodegradation of semi-volatile compounds in the gas phase could lead to a decrease in compounds in the particle phase, as they will evaporate to re-establish equilibrium. If gas-phase photodegradation was the dominant cause of mass loss in all systems, the largest decays in the particle phase would be expected from the most volatile species. Further, large non-volatile molecules (e.g. dimers in the β-caryophyllene SOA) should be non-responsive to such a pathway. Because there is a systematic degradation of dimers in all systems, it is unlikely that repartitioning derived from gas-phase photodegradation is driving the change in SOA composition during UV ageing.

For the experiments shown here, the FIGAERO-CIMS using I⁻ as the reagent ion (and an X-ray generator as the ion source) also measured the gas phase. However, in systems with a high abundance of NO₃ radicals, charge transfer can cause losses of I⁻ and formation of NO${}_{\mathrm{3}}^{-}$ (Lee et al., 2014). Additionally, the reaction of N₂O₅ and I⁻ may partly result in NO${}_{\mathrm{3}}^{-}$ + INO₂, and H transfer reactions can occur between I⁻ and HNO₃ (HNO₃ can come from the hydrolysis of N₂O₅ in our injection inlet or on chamber walls), both providing other routes to the formation of NO${}_{\mathrm{3}}^{-}$. As the amount of NO${}_{\mathrm{3}}^{-}$ introduced in our systems was very high, the signal of NO${}_{\mathrm{3}}^{-}$ was comparable to and sometimes even higher than the signal of I⁻. Thus, gas-phase compounds were detected clustered with both NO${}_{\mathrm{3}}^{-}$ and I⁻, with changing ratios of I⁻ $/$ NO${}_{\mathrm{3}}^{-}$ during the experiments (higher during dark ageing and lower during photolysis). This was not an issue for the particle phase, as particles are desorbed from the filter with pure nitrogen. We probed the uncertainties of detected signals due to the changing I⁻ $/$ NO${}_{\mathrm{3}}^{-}$ ratio (from ∼0.1 to 1.6) after Exp. 2 (for details, see the description in the supporting information and Fig. S4 in the Supplement). In our system, for those compounds clustered with I⁻, the normalized signal did not change significantly with decreasing I⁻ $/$ NO${}_{\mathrm{3}}^{-}$ as long as I⁻ $/$ NO${}_{\mathrm{3}}^{-}$ was higher than ∼0.3, but it decreased by about 20 %–40 % when I⁻ $/$ NO${}_{\mathrm{3}}^{-}$ decreased further to 0.1, as more molecules were clustered with NO${}_{\mathrm{3}}^{-}$.

Taking these uncertainties into account, we found that the signal of the major gas-phase compounds either stayed stable (e.g. C₁₅H₂₅NO${}_{\mathrm{5},\mathrm{6},\mathrm{7}}$) or increased significantly (e.g. C₁₄H₂₃NO₄, C₁₅H₂₃NO₆, and C₁₅H₂₆N₂O₈, with increases in the normalized signals of more than 5 times) during photolytic ageing for the β-caryophyllene SOA. For the isoprene and α-pinene SOA, although the low I⁻ $/$ NO${}_{\mathrm{3}}^{-}$ ratio (< 0.1) hindered a quantitative comparison, we still observed increases of several major compounds (e.g. C₅H₁₀N₂O₈ for the isoprene SOA, and C₁₀H₁₅NO₈, C₁₀H₁₇NO₇ for the α-pinene SOA). These are likely fragmentation products from oligomers and/or monomers. As the volatility of these small compounds is much higher than their parent oligomer compounds, they would tend to entirely or partly (depending on their volatility) evaporate to the gas phase. Different from the photolytic ageing of O₃- or OH- initiated SOA, we did not, however, observe a significant increase in the signals of small acids in the gas phase, such as formic acid and acetic acid (Pan et al., 2009), despite observations of fragmentation reactions in the particle phase. Their minor importance seems not to significantly impact the measured formic or acetic acid in the gas phase.

In addition to photolytic ageing of gas-phase compounds, there are other gas-phase reactions initiated by UV irradiation, which may impact the chemical composition, e.g. OH oxidation and the reactions with O₃ or NO₃ radicals. Under our experimental conditions (>100 ppb NO₂ from decomposition of N₂O₅), if there are any OH radicals formed, they will nearly exclusively react with NO₂ given the high concentrations. However, we did not observe a significant increase in the gas-phase HNO₃ signal. For the reactions with O₃ or NO₃, if there were such appreciable reactions in the experiments with isoprene and β-caryophyllene, where double bonds are still present, we would expect to observe the significant formation of more highly oxygenated molecules, which are absent in Fig. 3. Additionally, Fig. 3 shows that there is a consistent degradation of dimers in all systems, including α-pinene, where double bonds are not retained, thereby suggesting that the dominant photolytic degradation pathways are independent of gas-phase chemistry.

3.5 Impacts of photolysis on particle volatility

Considering photolytic ageing results in the degradation of molecules, there is a shift in the volatility distribution towards higher volatility species, which can cause evaporation of particulate mass. Here, we discuss how the apparent volatility of remaining particles changes during photolytic ageing as well as the potential influence that the previously discussed chemical processes have on these changes.

Figure 6 Comparison of changes in the bulk volatility measured with three methods before and after photolysis (Pre 1, Pre 2, and Post) for all experiments: Method 1 was Δlog₁₀C^* based on the parameterizations of Mohr et al. (2019), Li et al. (2016) (updated by Isaacman-VanWertz and Aumont, 2021), and Peräkylä et al. (2020); Method 2 was mass-weighted average T_max (note the right axes are swapped, and the range in panel d is different from that in the other panels); and Method 3 was Δlog₁₀C^* from the kinetic model (data available only for Pre 2 and Post in Exp. 4).

Figure 6 shows the changes in the bulk volatility derived from different methods (bulk log₁₀C^* derived from molecular composition using different parameterizations, bulk log₁₀C^* derived from the kinetic model using the VTDMA measurements, and mass-weighted average T_max from the FIGAERO-CIMS thermograms) during dark ageing and photolysis for all BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ systems. Note that we show the Δlog₁₀C^* (calculated by subtracting the bulk log₁₀C^* of the filter Pre 1 from the bulk log₁₀C^* of each filter), as the variabilities in the absolute bulk log₁₀C^* calculated by different parameterizations span several orders of magnitude: the bulk log₁₀C^* for all three systems is in the range of −11.9 to −7.6 based on the parameterization by Mohr et al. (2019), −3.7 to −0.3 by Li et al. (2016) and Isaacman-VanWertz and Aumont (2021), and −0.5 to 0 by Peräkylä et al. (2020) (see Fig. S9 in the Supplement). As Fig. S10 in the Supplement shows, the discrepancy in log₁₀C^* from the three parameterizations becomes larger with increasing nitrogen number. While a detailed discussion on these discrepancies is beyond the scope of this paper, they clearly reflect the uncertainties related to volatility estimates of complex organic particles (O'Meara et al., 2014; Wu et al., 2021). T_max is a qualitative measure of volatility and is influenced by filter mass loadings, temperature ramp rate, and FIGAERO geometry (Huang et al., 2018; Schobesberger et al., 2018; Thornton et al., 2020). However, T_max variation due to these factors is generally smaller than the difference in monomers and dimers. We compared the shape of thermograms and T_max of several monomers and dimers observed in our study to those of the same compounds from a few field campaigns (see Fig. S11 in the Supplement). Overall, the thermal desorption behaviour observed in our chamber experiments is similar to that from field measurements. By further comparing the log₁₀C^* of individual compounds, based on studies such as Mohr et al. (2019), with their corresponding T_max (Fig. S12), we found good qualitative agreement with a clear trend of increasing T_max with decreasing log₁₀C^*, and higher T_max for dimers than corresponding monomers for all systems. We also noticed large uncertainties in the calculated log₁₀C^*, especially for ON oligomers with multiple nitrate groups. For example, the dominating dimer C₂₀H₃₂N₂O₉ has a T_max of about 70 ^∘C, which is in the range of T_max of C₁₀ monomers such as C₁₀H₁₅NO₉. However, based on the parameterization of Mohr et al. (2019), the log₁₀C^* of the dimer C₂₀H₃₂N₂O₉(−7.9) is much lower than the log₁₀C^* of the C₁₀ monomers (log${}_{\mathrm{10}}{C}^{*}\mathit{>}-\mathrm{5}$).

Overall, for the two isoprene experiments (Exp. 1 and Exp. 2), almost all methods show a decrease in volatility as the experiment progresses, with no change in trend during the transition from dark to light conditions. This agrees well with the changes in the chemical composition as shown in Fig. 3: during dark ageing, the chemical composition shifts to higher-mass (lower-volatility) compounds and causes a decrease in the bulk volatility; during photolysis, there is additional decay of some oligomers such as C₁₀H₁₇N₃O₁₃, whose volatility is in the intermediate range of all compounds (Fig. S12). As a consequence, despite clear changes in the chemical composition, the bulk volatility does not change substantially due to photolysis. In Exp. 2, the Δlog₁₀C^* by both Peräkylä et al. (2020) and Mohr et al. (2019) decreased during the dark ageing but increased slightly during photolysis, which is different from other methods. The difference between Exp. 1 and Exp. 2 is probably due to the differences in the chemical composition (Fig. 2 vs. Fig. S6), as Exp. 1 had a higher NO₃ $/$ isoprene ratio and SOA with more nitrate groups (Fig. 5), and also due to different mechanisms to treat nitrate groups in the different parameterizations. It again reflects uncertainties related to volatility estimates by different parameterizations.

In Exp. 3 (α-pinene + NO₃), no clear trend in volatility can be discerned. T_max does not exhibit significant changes during both dark ageing and photolysis. However, the Δlog₁₀C^* by the parameterizations shows a slight decrease during the dark ageing and an increase during photolysis. As shown in Fig. 3, we observed decreases in a few dimers and increases in a few monomers, which, based on the parameterizations, causes a shift from low-volatility compounds to high-volatility compounds. However, as mentioned above, the T_max of these dimers is not necessarily higher than those monomers (i.e. the volatility of these dimers is not necessarily lower than that of those monomers). Thus, the mass-weighted average T_max does not decrease. Unfortunately, no VTDMA data are available for this experiment.

In Exp. 4 (β-caryophyllene + NO₃), the different methods yield different information on the relative changes in volatility from dark to photolytic ageing. Both T_max and Δlog₁₀C^* from the parameterizations show a bulk volatility decrease during dark ageing and an increase during photolysis, which would agree with changes in chemical composition. The shift from small (high-volatility) compounds to large (low-volatility) compounds during dark ageing causes the decrease in the bulk volatility, whereas the major compounds that decay during photolysis cover both monomers and oligomers with a wide range of volatility, and there are a few newly formed C_< 15 compounds that remain in the particle phase (Fig. 3); thus, the bulk volatility increases. However, the Δlog₁₀C^* from the VTDMA data does not agree with the trend during photolysis. We note that the particle size distribution and mean particle size in Exp. 1, 2, and 3, as shown in Fig. 1, did not change substantially, whereas the particles size in Exp. 4 (β-caryophyllene + NO₃) became significantly smaller during photolysis (Fig. 1). In Fig. 7, the evolution of the volume distribution of the β-caryophyllene SOA in Exp. 4 shows that the size distribution slowly shifts to larger sizes during dark ageing, but during photolysis, the decrease in particles with diameters larger than 300 nm is much greater than the decrease in small particles, indicating that the photodegradation is dependent upon particle size. The size dependence can be explained by calculating the mass absorption efficiency as a function of particle size (see Fig. S5 in the Supplement), which shows that particles with a diameter of 300 nm are 1.5–1.7 times more efficient at absorbing the chamber lights (λ= 350 nm) than 100 nm particles. Other processes, such as coagulation and evaporation, tend to lead to larger decreases in smaller particles, which is the opposite of what we found here, while the wall loss rate (which is tested in another experiment during the same campaign) was nearly constant for the particle size range up to 400 nm; thus, the latter was unlikely the reason for the size dependence of light absorption. In comparison, the isoprene and α-pinene systems have a smaller and narrower size distribution and, consequently, do not have an equally important size dependence in their response to UV light. This could also partly explain why the β-caryophyllene SOA had the largest decay in particle mass and size among the three systems. As the particles with different sizes will not have a uniform change in their chemical composition, the volatility measured for one selected size by the VTDMA may not be able to represent the change in the bulk volatility for experiments with a wide distribution of particle sizes; similarly, caution should be applied when interpreting the representativeness of measurements based on the bulk mass for the whole particle size distribution.

Figure 7 Evolution of the particle size distribution of the β-caryophyllene SOA during dark ageing and photolysis. The solid lines are log-normal fits.

4 Conclusion and atmospheric implications

Our experimental observations on three BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ systems show that the dark-to-light transition (1 h photolytic ageing) causes slight to moderate evaporation in BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ (∼0, 3.5, and 12 % of the total mass for the isoprene, α-pinene, and β-caryophyllene SOA respectively). Evaporation is due to the fragmentation of photolabile compounds and the formation of volatile fragmentation products. Despite finding 0 %–12 % of the mass evaporating during photolysis, 48 %, 44 %, and 60 % of the total signal of the respective isoprene, α-pinene, and β-caryophyllene SOA is sensitive to photolytic ageing, representing a majority of the pre-photolysis composition.

Fragmentation of nitrate groups is not the main loss pathway on the timescale of our experiments. For all BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ studied here, UV light fragments oligomers at the linkage between the monomer units (likely peroxides), as well as functional groups at other positions, causing the formation of monomers and compounds with a shorter carbon skeleton (e.g. C₁₀→ C₉). The newly formed compounds are more volatile than their parent compounds and are, thus, entirely/partly released back into the gas phase.

The changes in bulk volatility vary with individual experiments and depend on (1) whether the volatility of the photolabile fractions is higher/lower than that of non-photolabile fractions and (2) how the fragment products remain in the particle phase. The comparisons of different methods to assess the bulk volatility reveal the complexity of volatility assessments. There is generally a good agreement with the trends between the VTDMA and thermal desorption behaviour from the FIGAERO-CIMS (both desorption-based methods). However, the uncertainties related to molecular-formula-derived parameterization, especially for the compounds with multiple nitrate groups, likely cause disagreement when assessing the changes in the absolute bulk volatility. It is also worth noting that the particle size dependence of light absorption should be considered when studying the changes in the bulk volatility for systems with broad size distributions.

Our systems represent conditions in which RO₂–RO₂ and RO₂–NO₃ reactions are favoured and ON oligomers contribute to the high SOA yields we observed. Different changes in particle mass/size due to photolysis could be expected for the BSOA${}_{{\mathrm{NO}}_{\mathrm{3}}}$ formed under different conditions, as they have different chemical composition and, thus, different amounts and/or types of chromophores. In addition, the differences among the three BVOC systems also indicate that results obtained for specific BVOCs cannot be directly generalized to SOA present in the atmosphere, and it is necessary to study different BVOC SOA systems.

To our knowledge, the photolysis of SOA has mainly been studied under low-NO_x conditions to date. The sensitivity of ONs to UV light is poorly understood. As ONs are important in high-NO_x environments and make substantial contributions to the total organic aerosols (Farmer et al., 2010; Lee et al., 2016), future studies that probe the photolytic ageing of ONs under different ambient conditions and for different SOA precursors are needed to improve our understanding of the life cycle of ONs.