2.1.1 Reactor

The CFR has four inlets, three outlets and two septum seals. The two septum seals allow a UV pen-ray and coupled temperature and humidity sensor to be mounted inside the sampling bag. UV radiation is generated using a Hg pen-ray (UVP, Cambridge, UK), which emits at 254 nm (primary energy) and 185 nm, forming ozone and hydroxyl radicals (in the presence of nitrous acid or water vapour) inside the reactor. The UV pen-ray can become hot to touch after several hours of operation. Approximately 60 cm of 0.0625 in. stainless steel tubing was wrapped around the UV pen ray in a cone shape, preventing the UV lamp from touching the sampling bag without blocking the light source. The reactor temperature and humidity are measured using a TE HTM2500LF sensor (Future Electronics, Surrey, UK) operated via a U3 LabJack (LabJack, Colorado, USA) and an in-house-built program in DAQFactory Express software. The sampling bag is covered in foil to maximize light intensity inside the reactor and minimize ozone formation inside the enclosure. Mass flow controllers are used to balance the in and out flows of the reactor, ensuring the reactor volume remains constant. Humidified air, nitric oxide, and one or two VOC precursors (i.e. mixed VOC precursor experiments) can be continuously introduced into the CFR via three separate inlets (see Fig. 1). The fourth inlet is used to rapidly fill the reactor with dry purified air prior to an experiment. Humidified air is generated by flowing dry purified air through a water bubbler. VOCs are introduced into the CFR by flowing a low flow rate (< 300 mL min⁻¹) of dry purified air through a temperature-controlled glass bulb, containing the VOC precursor in a liquid state and in excess. An additional flow of dry purified air (i.e. make-up flow) is used to rapidly transport the VOC vapour into the CFR via a heated stainless steel line, minimizing condensational losses of the VOC precursor. Gaseous- and particulate-phase measurements can be obtained via any of the three reactor outlets.

2.1.2 Inlet system

The reactor is supplied with dry hydrocarbon-scrubbed air from an oil-free compressed air generator (SPRST, Spiral air, Oxfordshire, UK) using an in-built water and in-line hydrocarbon trap (GateKeeper GPU gas purifier, Entegris, Billerica, USA). Dry hydrocarbon-scrubbed air is delivered to the inlet system through 0.25 in. perfluoroalkoxy (PFA) tubing at a pressure of ∼760 kPa (output of compressed air generator). Five 0.25 in. PFA lines are connected to the main feed of dry hydrocarbon-scrubbed air. These lines are as follows: (i) VOC 1 (ii) VOC 2 (iii) make-up flow, (iv) humidity and (v) fast fill (see Fig. 1). The operation of each line is controlled by a 0.25 in. two-way tap. VOCs are introduced into the reactor through lines (i) and (ii).

A series of safety features have been installed in lines (i) and (ii) to ensure the upstream glassware is not subjected to high positive pressure. Immediately after the two-way tap, the tubing size of lines (i) and (ii) are reduced from 0.25 to 0.125 in. PFA. The pressure and flow rate in these lines are controlled to < 55 kPa and < 300 mL min⁻¹ using a 3 to 7 bar pressure regulator (product code 122-649, IMI Norgren, RS Components, Northants, UK) and a 0.005 to 1 L min⁻¹ mass flow controller (Alicat, Premier Control Technologies, Norfolk, UK), respectively; at ∼70 kPa the upstream glassware over-pressurizes and the gas-tight seals fail. VOC precursors are contained in 250 mL three-necked glass bulbs (271–1513, VWR International, Leicestershire, UK). Suba-seals (Sigma Aldrich, Dorset, UK) are used to cover each opening of the glass bulb, providing a gas-tight seal. Two pieces of 0.125 in. stainless steel tubing, filed at one end to create a sharp point, are inserted through the rubber gas-tight suba-seals on either end of the glass bulb, allowing dry hydrocarbon-scrubbed air to pass through the glassware. The suba-seal on the middle neck of the glass bulb acts as a pressure relief (in the event of over-pressuring) and is left unclamped with no attached tubing. Heated stainless steel lines (heated to ∼70 ^∘C) are used from the outlet of the VOC bulb to the inlet of the CFR to minimize condensational losses of the VOC precursor. A non-return valve is installed directly after the VOC bulb on lines (i) and (ii); see Fig. 1. The non-return valves ensure the higher pressure and flow rate of the dry hydrocarbon-scrubbed air in the make-up flow line does not enter lines (i) and (ii), which would result in the VOC glass bulbs over-pressurizing. The VOC bulbs on lines (i) and (ii) can be temperature-controlled using a water or ethylene glycol bath (temperature range of −10 to 95  ^∘C, Grant, Cambridge, UK) or an electrothermal heater (temperature range of ambient to 450 ^∘C, EM series, Cole-Parmer, Cambridge, UK), allowing greater control over the desired mixing ratio of the VOC precursors injected into the CRF (e.g. low-volatility VOCs can be heated to introduce higher mixing ratios into the reactor).

The make-up flow line consists of 0.25 in. PFA tubing with a pressure regulator, mass flow controller and 0.25 in. four-way tee, connecting the make-up flow with lines (i) and (ii) to the inlet of CFR (see Fig. 1). The pressure in this line is controlled to ∼140 kPa, which is a sufficient pressure to achieve the full flow range on a 0.1 to 20 L min⁻¹ mass flow controller (Alicat, Premier Control Technologies, Norfolk, UK). The make-up flow has two functions: to rapidly transport the VOC precursor into the CFR and to balance the total outflows of the reactor. All other introduction lines except for the fast fill (not used during an experiment) require a set flow rate for a desired mixing ratio. The make-up flow effects overall dilution but does not require a set flow rate, allowing the flow to be increased or decreased as desired to counterbalance the outflows of the reactor. The remaining two lines connected to the main feed of dry hydrocarbon-scrubbed air are the humidity (iv) and fast-fill (v) lines. The humidity and fast-fill lines are connected to two separate reactor inlets (second and third inlet; see Fig. 1). The humidity line controls the amount of water vapour introduced into the reactor and is comprised of 0.25 in. PFA tubing with a pressure regulator, mass flow controller and a 1000 mL water bubbler (pyrex glass bottle with an in-house-built screw-top water bubbler attachment). The humidity line requires a slightly higher line pressure than the VOC lines due to the back-pressure created by flowing through the water bubbler. The pyrex glass bottle has thicker walls than the VOC glass bulbs, allowing a slightly higher line pressure to be used. The pressure in the humidity line is controlled to below ∼70 kPa; the lowest possible pressure to achieve the required flow rate. A maximum flow rate of ∼12 L min⁻¹ was used in the humidity line and was controlled using a 0.1 to 20 L min⁻¹ mass flow controller (Alicat, Premier Control Technologies, Norfolk, UK). Relative humidity in the reactor can be controlled by changing the ratio of humidity line flow rate/total reactor flow rate (linear relationship). The maximum relative humidity, which could be achieved in the reactor was ∼60 %. The fast-fill line is used to rapidly fill the reactor with dry hydrocarbon-scrubbed air. The fast-fill line pressure and flow rate are unregulated (i.e. output of compressed air generator), allowing the reactor to be rapidly filled when required. The pressure and flow rate of the fast-fill line can be loosely controlled using the 0.25 in. two-way tap. The final introduction line, which is not connected to the main feed of dry hydrocarbon-scrubbed air and subsequently not discussed above, is the nitric oxide line (see Fig. 1). A standard of nitric oxide (5 or 60 ppm in N₂, BOC, UK) can be introduced into the CFR through the fourth reactor inlet using a 0.02 to 2 L min⁻¹ mass flow controller (Alicat, Premier Control Technologies, Norfolk, UK). The nitric oxide cylinder is easily interchangeable, allowing other oxidants or scavengers to be introduced into the reactor if required.

2.1.3 Outlet system

Gaseous- and particulate-phase measurements can be obtained via any of the three reactor outlets. A variety of instruments can be coupled to the CFR and easily interchanged. The limiting factor of coupling multiple instruments to the CFR is the total reactor outflow. The higher the total reactor outflow, the more difficult it becomes to balance the reactor volume. At 30 L min⁻¹, the reactor volume is replaced every 10 min. Mass flow controllers considerably reduce the difficulty in balancing the reactor volume when installed on the in and out flows of the reactor. However, over several hours of operation, the reactor volume can increase or decrease, due to the permeability of the PVF sampling bag and the error in the accuracy of numerous mass flow controllers. Quick changes can be made to reactor volume by shutting off all the in or out flows to the reactor for ∼1 to 2 min, decreasing or increasing the reactor volume, respectively.

Several instruments have been successfully coupled to the CFR. These include a selected ion flow tube mass spectrometer (SIFT-MS, SYFT Technologies, New Zealand) for the measurement of VOC mixing ratios and gaseous oxidation products; an electrical low-pressure impactor (ELPI, model ELPI+, Dekati, Finland) for SOA collection and real-time particle mass, number, and diameter measurements; and a NO_x (model 42i) and O₃ (model 49i, Thermo Scientific, Warrington, UK) analyser for the measurement of NO_x and O₃ mixing ratios, respectively. The measurements from some of these instruments are discussed below.

2.3.1 Generating SOA standards

Individual compounds in the SOA were isolated and collected using semi-preparative high-performance liquid chromatography ion-trap mass spectrometer (HPLC-ITMS) coupled to an automated fraction collector (FC 203B, Gilson, Dunstable, UK); an extension of the work performed by Finessi et al. (2014). An Agilent 1100 series HPLC (Berkshire, UK) and Bruker Daltonics HTC Plus ITMS (Bremen, Germany) were used. The semi-preparative column was a reverse-phase Ascentis 150 cm ×10 mm, with a 5 µm particle size (Sigma Aldrich, Dorset, UK). The HPLC solvents consisted of water (LC-MS grade, optima, Fisher Scientific, UK) with 0.1 % (v∕v) formic acid (Sigma Aldrich, UK) (A) and methanol (B) (LC-MS grade, optima, Fisher Scientific, UK). Gradient elution was used, starting at 87 % (A), decreasing to 27 % (A) at 92 min and re-equilibrating to 87 % (A) at 97 min. A 5 min pre-run consisting of the starting mobile-phase conditions was performed prior to each injection. The flow rate was set to 3.5 mL min⁻¹ with an injection volume of 100 µL. The eluent post-column was split via a tee piece and two lengths of PEEK tubing to the ITMS and the automated fraction collector. The use of a narrower internal diameter PEEK tubing to the ITMS resulted in a split ratio of 1:8 ITMS:fraction collector. Electrospray ionization (ESI) was used with a nebulizer pressure of 483 kPa, dry gas flow rate of 12 L min⁻¹ and a dry gas temperature of 365 ^∘C. The ITMS was operated in negative and positive ionization mode with a scan range of m∕z 50–600. Collision-induced dissociation (CID) was used with a fragmentation amplitude of 2 V. The data were analysed using ESI Compass 1.3 for HTC esquire version 4. The fraction collector was preprogrammed with the retention times of the target compounds and collected into 10 mL glass vials. The collected fractions were evaporated to dryness using a solvent evaporator (model V10, Biotage, Hertford, UK) and resuspended in 500 µL deuterium oxide with 0.05 % (w∕w) of 3-(trimethylsilyl)propionic-2,2,3,3-d₄ acid (TSP) (Sigma Aldrich, UK). Finally, the collected fractions were transferred into 5 mm tubes (Wilmad, Sigma Aldrich, UK) for NMR analysis.

2.3.2 NMR spectroscopy

The collected fractions and SOA samples were analysed using one-dimensional ¹H and two-dimensional ¹H-¹³C heteronuclear single quantum correlation (HSQC) NMR spectroscopy. A 700 MHz Bruker Daltonics Avance Neo NMR spectrometer equipped with a prodigy triple resonance cryoprobe was used. The operating temperature was set to 21 ^∘C. The ¹H-NMR spectra were acquired at 700 MHz, with a pulse sequence of 45^∘ and a relaxation delay of 4 s. The number of scans was set to 640, resulting in a total runtime of 1 h and 8 min. The ¹H-¹³C-NMR HSQC Bruker Daltonics pulse program used was hsqcetgpsi2 with a time domain data size of 256 and 1024 for channels F1 and F2, respectively. The number of scans was set to 20, resulting in a total runtime of 1 h and 40 min. The ¹H NMR spectra were analysed using TopSpin version 3.5 (Bruker Daltonics, Bremen, Germany). All spectra were baseline corrected and a spectral line broadening of 0.3 Hz was used. The concentration of the collected fractions was determined using the peak integrals of the internal standard (i.e. TSP) and the methyl group observed in the collected fractions from ¹H-NMR spectroscopy (see Finessi et al., 2014, and Bharti and Roy, 2012, for further information). The compound structure of the collected fractions was determined using a combination of techniques, including ¹H and ¹H-¹³C-HSQC NMR spectroscopy and the fragmentation patterns obtained from CID using the HPLC-ITMS and higher-energy collisional dissociation (HCD) using the UPLC-UHRMS. The ¹H-¹³C HSQC spectra were analysed using Spectrus Processor (ACD labs, Bracknell, UK), which contains an in-built carbon–hydrogen coupling prediction tool. This prediction tool provides estimated chemical shifts of carbon–hydrogen bonds in drawn chemical structures. Chemical structures of known and structurally similar photo-oxidation products of toluene and β-caryophyllene were drawn in the Spectrus Processor software to aid in the interpretation of the spectra discussed in Sect. 3.2.2.

2.3.3 Ultra-high-resolution mass spectrometry

A proportion of the ELPI SOA mass collected from each experiment was transferred into a clean vial and dissolved in 50:50 methanol : water (optima, LC-MS grade, Fisher Scientific, UK). The α-pinene standards and SOA samples were analysed using ultra-performance liquid chromatography with a UV/Vis detector (Dionex 3000, Thermo Scientific, Warrington, UK) coupled to an ultra-high-resolution mass spectrometer (QExactive Orbitrap, Thermo Scientific, Warrington, UK). An Accucore reverse-phase C₁₈ column 100 mm ×2.1 mm with a 2.6 µm particle size was used for compound separation (Thermo Scientific, Warrington, UK). The mobile phase consisted of water with 0.1 % (v∕v) formic acid (A) and methanol (B) (optima LC-MS grade, Fisher Scientific, UK). Gradient elution was used, holding at 10 % (A) for 1 min after injection, decreasing to 90 % (A) at 26 min, followed by re-equilibration to 10 % (A) at 28 min. A 2 min pre-run of the starting mobile-phase conditions was performed prior to each injection. The flow rate was set to 0.3 mL min⁻¹, with a 2 µL injection volume. The column temperature was controlled at 40 ^∘C and the samples were kept at 4 ^∘C in the autosampler tray during analysis. The UV/Vis wavelength ranged from 190 to 800 nm with a data collection rate of 5 Hz s⁻¹. Heated electrospray ionization (HESI) was used, with the following parameters: sheath gas flow rate of 70 (a.u.), aux gas flow rate of 3 (a.u.), capillary temperature of 320 ^∘C and an aux gas heater temperature of 320 ^∘C. Spectra were acquired in negative and positive ionization mode with a scan range of m∕z 85 to 750. Higher-energy collisional dissociation (HCD) was used with a stepped fragmentation amplitude of 65 and 115 (normalized collision energy, NCE). The number of most abundant precursors selected for fragmentation per scan was set to 10, with a 3 s dynamic exclusion and an apex trigger of 2 to 4 s. Two authentic standards, cis-pinonic acid (purity 98 %, Sigma Aldrich, UK) and pinic acid (Santa Cruz Biotechnology, Netherlands), were used for α-pinene SOA quantification. Chromatographic integration was performed using the software package Freestyle version 1.1 (Thermo Scientific, Warrington, UK). SOA samples were also analysed using the software package Compound Discoverer version 2.1 (Thermo Scientific, Warrington, UK), which was used to extract all chromatographic peaks with a signal-to-noise ratio greater than 3 from the spectra, identify the molecular formulae and perform a mass spectral library search using m∕z Cloud (https://www.mzcloud.org/, last access: 17 April 2018). Molecular formulae were calculated using the following restrictions: unlimited C, H and O atoms were allowed with a maximum of five N atoms. In positive ionization mode, up to three Na and two K atoms were also allowed. Compounds with assigned molecular formulae outside of the following tolerances were excluded from the data set: oxygen-to-carbon ratio (O∕C) 0.05 to 2, hydrogen-to-carbon (H∕C) ratio 0.7 to 2 (following the lower limits provided in Bateman et al., 2009), double bond equivalent (DBE) < 20, molecular formulae accuracy < 3 ppm. Chromatographic peaks identified in the solvent or procedural blanks and the SOA samples were removed from the data set.

2.3.4 ATR-FTIR spectroscopy

SOA filter samples were analysed using Fourier transform infrared spectroscopy with a diamond-attenuated total reflectance attachment (ATR-FTIR, ALPHA, Bruker Daltonics, Bremen, Germany). The scan range was set to 500–4000 cm⁻¹, with a spectral resolution of 4 cm⁻¹. Spectra were acquired in absorbance with 40 scans per sample. A preconditioned blank filter was used as the background measurement correcting for any instrument drift during analysis (cf. Coury and Dillner, 2009). The background measurement was subtracted from the sample spectra. The crystal was cleaned with isopropanol prior to the analysis of each sample or background measurement. Three replicate measurements were obtained for each sample. Spectral analysis was performed using essential FTIR software (eFTIR, Madison, USA). Spectra were ATR-corrected using the automated function in eFTIR software package. The use of quartz fibre filters will result in two silicon dioxide absorption peaks at wavenumbers ∼1060 and 804 cm⁻¹. This region of spectra provided no additional compositional information when comparing the SOA obtained from the ELPI with the quartz fibre filter.

2.3.5 CHNS elemental analysis

The elemental composition of the SOA was determined using a carbon, hydrogen, nitrogen and sulfur (CHNS) elemental analyser (model CE-440, Exeter Analytical, Coventry, UK). SOA samples were weighed using a Sartorius SE2 analytical balance (Surrey, UK). The reported elemental composition consists of an average of two replicate measurements. The remaining proportion of the SOA mass that did not contain elements C, H, N or S has been attributed to O.

3.2.1 Elemental composition

The elemental composition of the SOA samples was determined using a CHNS elemental analyser. CHNS analysis offers high accuracy and precision but is rarely used within aerosol science due to the large amount of organic aerosol mass required per analysis (1–5 mg). Elemental composition is usually determined using aerosol mass spectrometry (AMS) or electrospray ionization ultra-high-resolution mass spectrometry (Liu et al., 2018; Tasoglou and Pandis, 2015; Tuet et al., 2017; Zhao et al., 2015; Kroll et al., 2011, and references therein). Whilst both mass-spectrometric techniques are invaluable within aerosol science, both methods suffer from inaccuracies, either through the use of a selective ionization source (i.e. ESI) or assumptive corrections in AMS data processing (Canagaratna et al., 2015). The H∕C and O∕C ratios and the average carbon oxidation state (${\stackrel{\mathrm{‾}}{\mathrm{OS}}}_c=\mathrm{2}\times \mathrm{O}/\mathrm{C}-\mathrm{H}/\mathrm{C}$; see Kroll et al., 2011, for further information) were calculated from the CHNS data for each SOA sample. The O∕C and H∕C ratios ranged from 0.41 to 0.45 and 1.57 to 1.67 for α-pinene SOA, 0.45 to 0.49 and 1.59 to 1.71 for limonene SOA, 0.22 to 0.36 and 1.60 to 1.67 for β-caryophyllene SOA and 0.78 to 0.84 and 1.35 to 1.45 for toluene SOA, respectively. The elemental composition of two SOA samples formed under replicate conditions (exps. 22 and 23; see Table 1) displayed excellent agreement, with the O∕C and H∕C ratios observed to be within error of the analytical instrumentation (instrument accuracy ±0.15 % for a reference standard, as quoted by the manufacturer EAI, 2018).

A Van Krevelen diagram showing the H∕C vs. O∕C ratios of the SOA samples generated in this study, with a comparison to literature values, is shown in Fig. 5. The high VOC mixing ratios used in this study will result in higher-volatility oxidation products partitioning into the particulate phase than observed at lower (ambient) mixing ratios, likely affecting the observed chemical composition (Donahue et al., 2006; Pankow, 1994a, b). However, from Fig. 5 it can be observed that the H∕C and O∕C ratios of the SOA samples display good agreement with the literature values, suggesting that for the experimental conditions investigated, the bulk elemental composition is largely unaffected by the use of high VOC mixing ratios. It is worth noting that a further study, not included in Fig. 5 due to the large number of data points, reported H∕C ratios ranging between ∼1.4 to 1.7 for α-pinene SOA, which is consistent with the results shown in this work (Zhao et al., 2015). Laboratory and ambient OA has been found to follow a general trajectory in the Van Krevelen diagram (Chen et al., 2015; Heald et al., 2010; Ng et al., 2011a). An approximate −1 slope was first proposed by Heald et al. (2010) and was later re-evaluated to an approximate slope of −0.5 (Chen et al., 2015; Ng et al., 2011b). The SOA samples generated in this study were consistent with the characteristic Van Krevelen diagram trajectory, with a slope of −0.41 observed for all SOA precursors investigated.

The ability to use a highly accurate CHNS elemental analyser to determine the elemental composition of the SOA samples, allowed us to evaluate the accuracy of SOA elemental compositions obtained using UHRMS. The O∕C and H∕C ratios were calculated from the UHRMS using the assigned molecular formulae in each SOA sample. The total number of compounds (sum of positive and negative ionization mode) identified in each SOA sample ranged from 100 to 910; see Table S1 in the Supplement. Peak area weighted O∕C and H∕C ratios were calculated using the equation shown in Bateman et al. (2009), substituting peak intensity for peak area. In all of the experiments performed, the O∕C ratios obtained for each SOA sample using UHRMS were lower than the O∕C ratios obtained from the CHNS analyser (the non-selective and more accurate technique); see Fig. S2. The SOA ΔO∕C ratios varied for each SOA precursor, with an average ΔO∕C of 0.08±0.01, 0.13±0.01, 0.06±0.03 and 0.36±0.08 for α-pinene, limonene, β-caryophyllene and toluene SOA, respectively. For toluene SOA, this means that the average O∕C ratio would have been under reported by 45 % if obtained from UHRMS (using the data processing methods described; see Sect. 2.3.3) rather than the CHNS elemental analyser. A linear relationship (R²=0.9222) was observed for the O∕C ratios obtained from UHRMS vs. a CHNS elemental analyser for the β-caryophyllene SOA samples, suggesting that with further work a possible correction factor could be applied to UHRMS generated SOA O∕C ratios to correct for the inaccuracy in the use of a selective ionization source. Further work is required to investigate the accuracy of SOA O∕C ratios obtained from UHRMS, including the effect of different SOA precursors, introduction techniques (i.e. liquid chromatography or direct infusion) and data processing methods. This investigation demonstrates the capabilities and use of the CFR, allowing sufficient quantities of SOA mass to be generated in order to evaluate the accuracy of existing techniques.

Figure 5Comparison of the elemental hydrogen-to-carbon ratio (H∕C, y axis), oxygen-to-carbon ratio (O∕C, x axis) and average carbon oxidation state (${\stackrel{\mathrm{‾}}{OS}}_c$, colour scale) of the SOA formed from the photo-oxidation of β-caryophyllene, limonene, α-pinene and toluene in this study (unfilled shapes) vs. literature values (colour-filled shapes). Letters correspond to the references where the literature values were obtained: b, Bateman et al. (2009); n, Nakao et al. (2013); r, Reinhardt et al. (2007); tu, Tuet et al. (2017); t, Tasoglou and Pandis (2015); h, Huffman et al. (2009); s, Shilling et al. (2009); k, Kim et al. (2014); z, Zhao et al. (2015); c, Chhabra et al. (2011); l, Liu et al. (2018).

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3.2.2 NMR spectroscopy

NMR spectroscopy can provide detailed structural information on the carbon, hydrogen and nitrogen nuclei bonds present in complex mixtures. This technique is complementary to detailed chemical speciation, providing molecular-level insight into the bulk chemical composition of OA (Chalbot and Kavouras, 2014; Duarte and Duarte, 2011, 2015; Simpson et al., 2012). Proton NMR spectroscopy (¹H NMR) is the most commonly used NMR technique for the analysis of OA, although numerous alternative nuclei and two-dimensional spin–spin coupling methods exist (see Duarte and Duarte, 2015, for further information). The complexity of OA can reduce the amount of chemical information that can be obtained from ¹H NMR analysis. Ambient OA contains thousands of compounds of differing chemical functionalities, which combined with the relatively small dispersion of proton chemical shifts (0 to ∼10 ppm), often results in a complex unresolved spectrum with few abundant peaks (Duarte and Duarte, 2011). The binning of spectral regions that correspond to certain functionalities (e.g. aliphatic protons, aromatic protons, etc.) via offline data processing, can aid in the compositional interpretation of bulk OA using ¹H NMR analysis (Decesari et al., 2000, 2001) and has been successfully used in several studies (see Chalbot and Kavouras, 2014, and references therein). Two-dimensional NMR spectroscopy, however, can provide increased resolution and additional compositional information in comparison to ¹H NMR spectroscopy, although is rarely used within aerosol science due to the large amount of mass required for analysis (> 1 mg) (Duarte and Duarte, 2015; Simpson et al., 2012). Here we show, as an example, how the large quantity of SOA mass collected from the CFR can be used to gain greater compositional insights into SOA using two-dimensional NMR spectroscopy.

Figure 6¹H and ¹H-¹³C HSQC NMR spectra of β-caryophyllene (a and b, respectively) and toluene (c and d, respectively) SOA formed at 55 % relative humidity with a VOC∕NO_x ratio of 13 (exps. 31 and 36, respectively; see Table 1). The proton spectral regions, as defined in Decesari et al. (2000, 2001), are shown in the ¹H NMR spectra as dashed black lines. The spectral regions shown in the ¹H-¹³C HSQC NMR spectra have been adapted from Chen et al. (2016); see the text for further information.

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The SOA samples were analysed using ¹H and two-dimensional ¹H-¹³C heteronuclear single-quantum correlation (HSQC) NMR spectroscopy. HSQC detects the carbon–hydrogen couplings of each bond in a molecular substructure, providing the proton and carbon shifts for both atoms. The ¹H and ¹H-¹³C HSQC NMR spectra of β-caryophyllene and toluene SOA formed at 55 % relative humidity and VOC∕NO_x ratio of 3 (exps. 31 and 36 Table 1, respectively) are shown in Fig. 6. The ¹H NMR spectral regions, as defined in Decesari et al. (2000, 2001), are shown in Fig. 6a and c. The ¹H NMR spectra of β-caryophyllene and toluene SOA are vastly different. β-caryophyllene SOA displays an abundance of aliphatic proton groups (δ¹H 0.7 to 3.2 ppm) with hardly any peaks observed for protons bonded to oxygenated saturated aliphatic carbon atoms (δ¹H 3.4 to 4.1 ppm and δ¹H 5.0 to 5.6), confirming the SOA sample is not very oxidized (CHNS data, O∕C ratio =0.31). The ¹H NMR spectra of toluene SOA displays an abundance of protons bonded to an adjacent aliphatic carbon–carbon double bond (δ¹H 1.9 to 3.2 ppm) and (dissimilar to β-caryophyllene SOA) oxygenated saturated aliphatic carbon atoms (δ¹H 3.4 to 4.1 ppm), suggesting the sample contains ring-opened species and is highly oxidized (CHNS data, O∕C ratio =0.84). In contrast to the ¹H NMR spectrum of β-caryophyllene SOA, toluene SOA displays protons bonded to an aromatic carbon atom (ring-retaining species) and an unresolved low-intensity peak for protons bonded to aliphatic methyl, methylene and/or methyne groups (δ¹H 0.7 to 1.9 ppm).

The ¹H-¹³C HSQC NMR spectra displays considerably more compositional information than observed in the ¹H NMR spectra (see Fig. 6). The spectral regions shown in the ¹H-¹³C HSQC spectra have been adapted from Chen et al. (2016) using a structural carbon–hydrogen coupling predictive tool for known and structurally similar β-caryophyllene and toluene oxidation products (see Sect. 2.3.2 for further information). The abundant aliphatic protons (δ¹H 0.7 to 3.2 ppm), observed in the ¹H NMR spectra of β-caryophyllene SOA (Fig. 6a), display over 40 carbon–hydrogen coupling signals in the HSQC spectra (Fig. 6b). The compositional benefits of ¹H-¹³C HSQC analysis can be observed in region I of Fig. 6a and b. The most abundant peak in the ¹H NMR spectrum of β-caryophyllene SOA is from protons bonded to a methyl group (δ¹H 1.1 ppm). In the ¹H-¹³C HSQC spectrum, it can be observed that the methyl group at δ¹H 1.1 ppm consists of two carbon–hydrogen coupling signals (i.e. the same proton chemical shift but different carbon chemical shifts). The two carbon–hydrogen coupling signals correspond to a methyl group bonded to an adjacent tertiary carbon atom at δ¹³C 21.2 ppm and an adjacent cyclic carbon atom at δ¹³ 29.9 ppm, both which are bonded to a neighbouring methyl group (resembling the carbon-backbone structure of β-caryophyllene). This compositional information cannot be observed in the ¹H NMR spectra. Similarly, additional compositional information can be observed in the ¹H-¹³C HSQC spectrum of toluene SOA. Region II in the ¹H NMR spectra displays an abundant aliphatic proton peak at δ¹H 2.0 ppm. In the HSQC spectrum, two defined carbon–hydrogen coupling signals can be observed. Based on predicted carbon–hydrogen couplings, these two signals likely represent the carbon–hydrogen bonds in the methyl group attached to an aromatic ring with (δ¹³C 19.1) and without (δ¹³C 12.5 ppm) an electronegative aromatic substituent, such as a hydroxyl group, in the meta-position to the methyl group. In addition, region III likely displays aromatic carbon–hydrogen bonds that are in the meta-position to a nitro aromatic substitution; the only aromatic substituent which would result in an adjacent carbon–hydrogen chemical shift of δ¹³C ∼125 ppm and δ¹H ∼8 ppm, respectively. It is imperative to note that predictive carbon–hydrogen coupling tools should only be used as a guide and authentic standards (where possible) should be used to confirm predicted carbon–hydrogen coupling shifts. Nevertheless, the above discussion demonstrates the additional compositional information which can be obtained using two-dimensional NMR spectroscopy. Few studies have used two-dimensional NMR spectroscopy for the compositional analysis of bulk OA. This technique, in combination with the use of a spectral library, has the capability to aid in the interpretation of detailed chemical speciation and provide new insights into the bulk chemical composition of SOA.

3.2.3 Generating SOA standards

ESI-UHRMS is capable of providing molecular and structural speciation of individual compounds in complex mixtures and is therefore widely used within aerosol science to determine the detailed chemical speciation of OA (Laskin et al., 2012; Nizkorodov et al., 2011; Pratt and Prather, 2012). The lack of commercially available standards, however, often results in the use of surrogate standards (i.e. structurally and compositionally similar species) for quantification. The use of surrogate standards can have a considerable effect on the reported concentrations when using a selective ionization source, such as ESI. The molecular size, volatility, basicity and polarity of a compound can all affect the ionization response (Kiontke et al., 2016; Oss et al., 2010). Here, we show how the large quantity of SOA mass collected from the CFR can be used to generate SOA standards, reducing the need for additional commercially available standards or chemical synthesis.

Several experiments, in addition to those shown in Table 1, were performed to generate additional SOA mass from the photo-oxidation of α-pinene. This additional SOA mass was used to generate standards to quantify components in the SOA mass formed in the α-pinene experiments. A similar methodology has previously been used in our group, generating standards from SOA mass formed in a micro-reactor (see Finessi et al., 2014). In total, 17 compounds were targeted in the generated SOA mass. HPLC-ITMS coupled to an automated fraction collector was used to isolate and collect the targeted compounds based on their retention times. The molecular identification of each standard was determined using a combination of the molecular information and fragmentation patterns provided by the UPLC-UHRMS² and the proton chemical shifts obtained from ¹H NMR spectroscopy. ¹H NMR spectroscopy was used to determine the amount of mass collected for each targeted compound via the integration of the peak integrals of a known proton peak (e.g. a methyl group) and the internal standard (i.e. TSP). Once the concentration of each fraction had been determined, the standard was used for quantification. Major α-pinene oxidation products often contain two characteristic methyl groups attached to a cyclic ring (e.g. pinonic acid, pinonaldhyde, pinic acid, 10-hydroxypinonic acid, among others). The characteristic cyclic methyl groups can easily be identified in the ¹H NMR spectrum (Finessi et al., 2014). Several of the targeted compounds contained the two characteristic cyclic methyl groups, allowing the concentration of the standard to be determined (via the integration of the methyl protons), even if the entire chemical structure was unclear. Of the 17 targeted compounds, 10 were deemed suitable for use as standards. The other 7 compounds were excluded from further analysis due to an insufficient amount of collected mass and/or their complex spectrum, where the cyclic methyl groups could not be identified preventing the concentration of the standard from being determined. The molecular formulae, retention times and collection times of the 10 standards are shown in Table S2.

A comparison of the chromatographic peaks obtained for both the generated and authentic standard of pinic acid at a concentration of 1 ppm is shown in Fig. S3. From Fig. S3, it can be observed that both chromatographic peaks display relatively good agreement, with similar peak shapes and ion intensities observed (10 % difference in peak area). In addition to the 10 targeted compounds, 4 α-pinene standards which were generated in Finessi et al. (2014) and 2 commercially available compounds (i.e. pinic acid and cis-pinonic acid) were used to identify and quantify components in the α-pinene SOA samples using UPLC-UHRMS. An identification was confirmed if a compound in the SOA sample displayed the same molecular formula (< 2 ppm error), retention time (±30 s) and fragmentation patterns as the standard. Calibrations were performed for all of the compounds shown in Table S2, with the exception of compound 5, where the authentic pinic acid standard was used instead. Calibrations ranged from 0.001 to 15 ppm with a minimum of four concentrations and three replicate measurements per concentration. The total amount of SOA mass quantified in each experiment is shown in Fig. 7. The standards represented up to 35.8±1.6 % of the total α-pinene SOA mass. The error represents the propagated uncertainty in the slope of each calibration graph used for quantification. The quantified α-pinene SOA mass varied considerably depending on the experimental conditions. The average amount of α-pinene SOA mass quantified in the no NO_x and NO_x experiments was 6.9 % and 33.2 %, respectively. The targeted standards were selected in α-pinene SOA formed under NO_x conditions, likely accounting for the larger amount of SOA mass quantified in the NO_x experiments. Molecular speciation techniques typically quantify < 25 % of OA mass (Hallquist et al., 2009; Nozière et al., 2015). Using the techniques described, considerable improvements can be made in the total amount of SOA mass quantified.

Figure 7Total amount of SOA mass quantified using the generated standards in the α-pinene experiments shown in Table 1. Error bars represent the propagated uncertainty in the slope of the calibrations used to quantify each SOA component.

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3.2.4 Chemical and physical properties of SOA single particles

SOA can exist in highly viscous semi-solid and solid states, depending on chemical composition and the conditions of the surrounding gas phase (T and RH); the phase state of SOA particles affects the diffusion rates of molecules within the aerosol phase, affecting physicochemical processes such as the partitioning of organic species between the condensed and gas phases, heterogeneous chemical reactions, and ice nucleation (Reid et al., 2018). As indicated by Shrivastava et al. (2017), there is the need for a systematic investigation of the viscosity of SOA and its effects on the physicochemical properties of SOA particles as a function of T and RH and for SOA formed from different precursors at variable NO_x and RH conditions. The CFR experiments presented in this work, coupled with the thorough information on the SOA chemical composition (Sect. 3.2.1–3.2.3) and the single-particle experiments described below, represent a unique opportunity for such a systematic investigation.

As an example of the capabilities of the single-particle EDB approach to elucidate the physiochemical properties of the SOA samples, we report in Fig. 8 a comparison of the volatility of β-caryophyllene (exps. 28; see Table 1) and toluene SOA (exp. 35) formed in the CFR at 55 % RH with no NO_x. Once a diluted SOA droplet is initially trapped (typical initial SOA extract mass fraction of ∼0.02), a steep decrease in size is observed, with both water and ethanol evaporating to reach equilibrium with the gas-phase composition (timescale of less than 10 s at 293 K). No ethanol is present in the gas phase, and therefore it evaporates completely from the droplet; by contrast, the water content in the condensed phase equilibrates such that the water activity in solution is equal to that of the gas phase. After this rapid evaporation phase, the radius of SOA-trapped single droplets is generally observed to decrease slowly over time, with the semi-volatile organic components within the droplets partitioning to the gas phase together with the solvating water. In Fig. 8, the loss of these organic components (and solvating water) is represented as a volume fraction remaining (VFR) compared to the “initial” droplet volume once the initial loss and equilibration of water content has occurred, identified as the point where the rapid water and ethanol evaporation is concluded (typical initial reference radius of ∼5–8 µm). To report the VFR values in Fig. 8, the measured radii were separated into bins, each corresponding to a log₁₀ (time) =0.1 interval and then averaged.

Figure 8Volume fraction remaining (VFR) for single β-caryophyllene SOA (a) and toluene SOA (b) droplets confined in an electrodynamic balance (EDB) over ∼1 d. VFR is compared for evaporation into high RH (solid symbols) and dry conditions (open symbols). Sample numbers correspond to the experiments shown in Table 1. The secondary x axis displays the calculated effective saturation concentration (C^∗, µg m⁻³); see text for further information.

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Figure 8a compares VFR data for two β-caryophyllene SOA particles evaporating into high RH and dry conditions. In both cases, the VFR decreases with time, indicating a mass loss from the particle, due to the volatilisation of organic species, and the two curves present a similar trend. The activity of the organic species at 0 % RH is expected to be higher than at 85 % RH, a consequence of the absence of condensed-phase water and a higher concentration of the organic components, although a faster evaporation rate would be expected under dry conditions compared to wet conditions. As a result, the two time dependencies in the VFR data sets in Fig. 8a show a very similar trend. This can likely be explained by a kinetic limitation on the diffusion of the organic components within the β-caryophyllene SOA particle at 0 % RH, due to high viscosity. Indeed, Li et al. (2015) measured a transition of β-caryophyllene SOA particles from liquid to non-liquid at a RH above 90 % from particle bounce experiments, supporting the hypothesis that a high viscosity is restricting the rate of volatilisation from the β-caryophyllene SOA particle at low RH. The secondary x axis in Fig. 8 represents an estimate of the evolving effective saturation concentration (C^∗) for a 7 µm droplet, calculated according to Donahue et al. (2006) and assuming a diffusion coefficient of 10⁻⁶ m² s⁻¹, a molecular mass of 200 g mol⁻¹ and a density of 1.4 g m⁻³. This calculation provides an estimate of the lifetime of each of the indicated C^∗ bins in the case of no kinetic limitations to the evaporation of the organic molecules. For example, organic molecules in the 10² µg m⁻³ bin are expected to have a lifetime in the condensed phase < 1000 s and at the end of the experimental timescale (∼10⁵ s), only molecules with C^∗ lower than 10⁻¹ µg m⁻³ are still present in the evaporating droplet.

When compared to β-caryophyllene SOA, toluene SOA particles present a very different VFR profile (Fig. 8b): significant evaporation of the trapped particle is observed at high RH, but the evaporative loss of semi-volatiles appears completely inhibited at 0 % RH after ∼10² s, with the particle size achieving a constant value. Similarly, but more markedly when compared to the β-caryophyllene SOA case, this complete inhibition of the volatilisation of organic components from the condensed phase is caused by the high viscosity of the toluene SOA particle at 0 % RH. Song et al. (2016) inferred a lower limit of viscosity for toluene SOA below 17 % RH of $\sim \mathrm{5}\times {\mathrm{10}}^{\mathrm{8}}$ Pa s; the observation of strong kinetic limitation to evaporation shown in Fig. 8b is consistent with such high viscosity. The difference in VFR after 10⁵ s between particles held at wet and dry conditions is significant (∼0.35) and it is a clear indication that the size of toluene SOA particles strongly depends on their phase state (liquid vs. semi-solid). In a future paper, we will provide a comprehensive analysis of all volatilisation measurements, reporting the volatility and viscosity distribution that characterize the various SOA samples in this work by using the KM-GAP model (Yli-Juuti et al., 2017) to analyse the experimental data.