Secondary Organic Aerosol Yields from the Oxidation of Benzyl Alcohol

. Recent inventory-based analysis suggests that emissions of volatile chemical products in urban areas are now competitive with those from the transportation sector. Understanding the potential for secondary organic aerosol formation from these volatile chemical products is, therefore, critical to predicting levels of aerosol and for formulating policy to reduce aerosol exposure. It is clear that a plethora of oxygenated compounds are either emitted directly into the atmosphere or emitted indoors and later escape into the outdoors. Experimental and computationally simulated environmental chamber data provide an under- 5 standing of aerosol yield and chemistry under relevant urban conditions (5–200 ppb NO and 291–312 K) and give insight into the effect of volatile chemical products on the production of secondary organic aerosol. Benzyl alcohol, one of these volatile chemical products, is found to have a large secondary organic aerosol formation potential. At NO concentrations of ∼ 80 ppb and 291 K, secondary organic aerosol mass yields for benzyl alcohol can reach 1.

During the background collection period of ∼1 h for each experiment, the standard deviation of the benzyl alcohol mixing ratio, along with the uncertainty in the calibration, was used to estimate the uncertainty of the initial benzyl alcohol mixing ratio (see Table 1). This combined standard deviation was also considered as the uncertainty in the measurement of the time-resolved gas-phase mixing ratio throughout the experiment. The SOA yield is determined from the reacted benzyl alcohol, which is the difference between the measured benzyl alcohol concentration at any given time and the initial benzyl alcohol concentration.
The variance of the reacted benzyl alcohol is the sum of the variances of the initial and measured benzyl alcohol mixing ratios.

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The uncertainty reported in Table 1 is, then, the square root of the reacted benzyl alcohol mixing ratio variance.
The conversion from mixing ratio to mass concentration of reacted benzyl alcohol was performed assuming a constant pressure of 1 atm. Note that the chamber is located three floors from a weather station, which reported an average atmospheric pressure of 0.97 atm in the year 2019 (TCCON Weather Data, 2020); thus, 1 atm is a reasonable estimate of the pressure in the experiments.

Particle-phase measurements
To measure the particle size distribution, a custom-built scanning mobility particle sizer (SMPS) with a 308100 TSI Differential Mobility Analyzer (DMA) and a TSI 3010 t-butyl alcohol condensation particle counter (CPC) was used with a sheath flow rate of 2.64 Lpm, an aerosol flow rate from the chamber of 0.515 Lpm, and a dilution flow of 0.485 Lpm. A full size-scan was collected every 5.5 minutes (for experiments S1-3 and E1 scans were performed every 6 min), and the voltage was scanned 105 over 4 min from 15 to 9875 V. Data inversion was performed using the method described in Mai et al. (2018). Total number, volume, and surface area concentrations were determined assuming 431 size bins between 22 and 847 nm. When the sample flow was <0.515 Lpm, an adjustment to the total number concentration was performed to account for the sampled flow. Particles were charged with a 500 microcurie Po 210 source, except for experiments S1-3 and E1, which used an X-ray source.
When the aerosol size distribution was close to the edges of the measurable range, a logarithmic fit of the distribution tail 110 was performed on the edges of the distribution: diameters of 382 to 600 nm were used to fit particles above 600 nm, and those with diameters 35 to 200 nm were used to fit particles with diameters smaller than 35 nm. Fits of the tail distribution were performed on the upper end of the size distribution for experiment N5, which produced an average of a 3.4% decrease from the raw measurement in the volume concentration; the lower end of the size distribution for experiment S2, which led to a volume concentration adjustment of <0.1%; and on both the upper and lower ends of the size distribution for experiment S1 (the 115 nucleation experiment), which (for those points after at least 100 min of oxidation) led to a volume concentration difference of <1% from that measured in the absence of any adjustment. Particle volume was converted to particle mass with a SOA density of 1.4 g cm −3 , consistent with past work on isoprene (Dommen et al., 2006;Kroll et al., 2005Kroll et al., , 2006 and on benzyl alcohol (Li et al., 2018).
Uncertainty in the particle size was assumed not to exceed 2 nm, based on a comparison with the SMPS at the University 120 of California, Riverside. For the CPC-associated margin of error, according to approximate Poisson statistics, the uncertainty of the number in each particle size bin was taken as the square root of the number concentration in that bin and that value of uncertainty was propagated into surface area and volume measurements both by bin and, eventually, for the total number concentration. Additionally, an uncertainty in the measured volume concentration due to sample noise was added from the uncertainty of the wall-loss corrected volume concentrations in the background collection period prior to lights on (see Sect. 3.2.1).
Aerosol-phase bulk composition was determined using an in situ high-resolution time-of-flight aerosol mass spectrometer (AMS, Aerodyne Research) in the high-sensitivity V-mode. Data were analyzed with Igor Pro (version 6.37) and the Squirrel (1.57l) and Pika (1.16l) toolkits. Elemental composition was determined following the improved-ambient method from Canagaratna et al. (2015) and Aiken et al. (2008). Absolute uncertainties of O:C and H:C ratios are ±28% and ±13%, respectively 130 (Canagaratna et al., 2015).
Measurements from the AMS can be utilized to determine the mass fraction of organonitrates (RONO 2 ) in the aerosolphase following the method described by Farmer et al. (2010). Both inorganic and organic nitrates fragment to an m/z of 30 (NO + ) and an m/z of 46 (NO + 2 ), but the ratio of these two fragments for organonitrates (including those derived from aromatic hydrocarbons) and for ammonium nitrate is quite different and this difference can be utilized to determine the contribution of 135 organonitrates to the nitrate signal in the AMS (Farmer et al., 2010;Fry et al., 2013;Kiendler-Scharr et al., 2016;Sato et al., 2010). Note that fragments of the form C x H y N + z are sufficiently scarce that they are neglected (the N:C ratio was never more than 0.026 for the experiments considered here).
The measured mass ratio of NO/NO 2 (called the NO + x ratio) is calibrated for ammonium nitrate for experiments R4 and U7-8 (3.20±0.04) and is assumed for organonitrates (7.2±1.1). The organonitrates ratio was calculated using the ammonium nitrate ratio and the correlation derived by Fry et al. (2013). From this NO + x ratio, the time-resolved ratio of the fraction of the nitrate signal that comes from organonitrates for each experiment (x ON ) can be obtained using Eq. 1 in Farmer et al. (2010). With the mass concentration of nitrates (m N O3 ) and the mass concentration determined to be organics (m Org ), the time-resolved organonitrate mass fraction of the aerosol is This is plotted in Sect. 4 and in Fig. A1. For experiments N1-3 and U1-6, the chemical composition of particle-phase compounds was further analyzed using offline ultra-high performance liquid chromatography electrospray ionization quadruple time of flight mass spectrometry (UPLC/ESI-Q-ToFMS) (Zhang et al., 2016). Post-oxidation samples were taken using 47 mm Pall Teflon filters, which were collected for ≥2 hours at 6.5 Lpm using an upstream activated carbon denuder. Additional Teflon filters were collected during photooxidation at 2 Lpm. This experimental set up is described by Nguyen et al. (2014).
The SOA collected was extracted by placing each filter sample into 6 mL of milliQ water and agitating the samples on an 150 orbital shaker for 1 h. In an effort to prevent on-filter chemistry from occurring, samples were stored at -14 ○ C after initial collection and before extraction. Analysis using UPLC-MS was carried out in negative mode (where the parent molecule is observed at M-H) which is sensitive to the nitroaromatics formed in the aerosol-phase. The 12 min eluent program for UPLC-MS and MS/MS fragmentation analysis required 4 µL of sample with gradient eluents between a 0.1% formic acid/99.9% water solution and a 100% acetonitrile solution. The total flow rate was 0.3 mLpm, and masses were scanned from m/z = 7 to 4000.

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MassLynx software was used to analyze the resulting spectra, which calculates possible chemical formulas based on masses quantified during analysis. Mass assignments were limited to carbon-, oxygen-, and nitrogen-containing formulas as these were the only chemically viable formulas for benzyl alcohol oxidation chemistry. The structures assigned to chemical formulas from MassLynx analysis were based on structures that corresponded to expected oxidation products and were confirmed based on MS/MS fragmentation analysis. Isomeric analysis was not conducted for these compounds, thus structures in Table A1 160 represent just one possible isomer. Several experiments with similar reaction conditions (U1-4; see Table 1) were analyzed to probe reproducibility of this technique; these experiments showed consistent results.
Other organic compounds may be present in the SOA collected that is insoluble in the extractant solvent, not able to elute from the chromatographic column, or not detectable in negative ion mode (Surratt et al., 2008). Additionally, the UPLC-MS exhibits different sensitivities to compounds depending on the polarizability of the compound as well as its ability to ionize. It 165 is likely that the UPLC-MS is quite sensitive to the nitroaromatics reported in this work as compared to other compounds.
3 Calculations of SOA yield

Method
The secondary organic aerosol yield (SOA Y) is given by where ∆SOA meas is the difference between the measured and wall-deposition-corrected aerosol mass concentration at a given time and the aerosol concentration prior to the beginning of oxidation. ∆BnOH meas is the reacted mass of benzyl alcohol; that is, the difference between the initial concentration and the measured concentration at a given time.
This SOA yield calculation uses ∆SOA meas , which is the wall-deposition-corrected SOA mass. The wall-deposition correction assumes that once a particle deposits on the wall, suspended gas-phase molecules no longer condense onto it; its growth ceases. This corresponds to the technical assumption that ω = 0, where ω is a proportionality factor that describes the degree to which vapor condenses onto particles already deposited on the chamber walls compared to those suspended in the bulk of the chamber: if ω = 0, once a particle deposits on the chamber wall it is lost to the system and no longer acts as a condensation sink; if ω = 1, a particle deposited on the chamber wall acts as a condensation sink identically to that of a suspended particle (Trump et al., 2016;Weitkamp et al., 2007). The SOA yield is bounded by the assumptions that ω = 0 and ω = 1. The extent of 180 difference between these cases is dependent on characteristics of the chamber (e.g., the rate of particle-wall-deposition) and of the chemical system (e.g., the amount of kinetic vs. equilibrium particle growth that occurs) (Trump et al., 2016).
To estimate the upper bound (ω = 1) of the yield, we assumed that only particles that deposited after the onset of oxidation would take up vapor. That is, inorganic seed deposited during the background collection period of each experiment is not considered.

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While different-sized particles both deposit to the wall at different rates and grow due to condensation at different rates, to simplify the calculation of the SOA yield upper bound, the volume-weighted mean diameter of the suspended size distribution was determined for each time point such that D p,av,t = where N total,t is the total number concentration at time point t, nbins is the number of diameter size bins measured by the SMPS, D p,i is the mean diameter of of SOA mass formed during the experiment is given by where ρ is the particle density, N lost,t is the number concentration of particles lost to the chamber wall between t i and t i+1 , and t end is the time in the experiment considered. This calculation was performed for 1 min time steps. Table 1 shows the SOA yields calculated with uncertainties for the ω = 0 and the ω = 1 assumption. The SOA yield calculation 195 with both ω = 0 and ω = 1 is shown for experiment R1 in Fig. 1. Since the difference between the SOA yield calculated with ω = 1 and with ω = 0 is dependent on the amount of organic aerosol that deposits onto the chamber walls, experiments with a higher initial aerosol concentration or that simply last for a longer period tend to have a greater disparity between SOA yields calculated with the ω = 0 assumption and those calculated with the ω = 1 assumption. Even so, for all the experiments considered here, the ω = 1 calculated SOA yield is within the uncertainty of the SOA yield found assuming that ω = 0.  one. The shaded regions is the associated uncertainty for the ω = 0 case. Panel (b) shows the wall-deposition-corrected mass concentration of SOA formed assuming ω = 0 (blue solid curve fitted to the circles and error bars) and ω = 1 (dashed blue curve). The measured mass concentration of benzyl alcohol is the yellow circles with associated error bars, to which the yellow curve is fit.

Corrections
The chamber walls have, primarily, two effects on the SOA yield results: particles with organic mass on them may deposit on the chamber walls and not be detected (called particle wall deposition) or low-volatility compounds that, in the atmosphere, would condense onto suspended particles and form secondary organic aerosol mass instead deposit directly onto the chamber walls (called vapor wall deposition).

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Since vapor wall deposition involves the loss to the wall of not just the precursor compound, in this case benzyl alcohol, but also of all the oxidation products, which, as is the case here, are often not all fully measured and characterized, it is difficult to directly correct for the effect of vapor wall deposition on the observed SOA yield. Instead, one can minimize its effect by increasing the presence of the suspended aerosol surface area concentration so that the suspended aerosol outcompetes the chamber wall as a condensation sink. To do so, however, increases the effect of particle wall deposition because as there are

Particle-wall deposition
To determine the particle-wall-deposition correction parameters for the 17.9 m 3 chamber, two-parameter fits to the eddydiffusivity coefficient (k e ) and the mean electric field experienced within the chamber (Ē), as outlined in Charan et al. (2018), were performed on dry, ammonium sulfate experiments with an assumed density of 1770 kg m −3 . Two experiments were carried out for 8 h in the dark with only ammonium sulfate seed present, one was a 6 h experiment under irradiation, and an 220 additional four were 4 h dark experiments with the precursors of a VOC oxidation experiment. All dark experiments were carried out at 25.6 ○ C and that in the presence of light was performed at 28.6 ○ C. Analysis began 30 min after initial mixing and used 15 size bins to improve the counting statistics. All bins were included in analysis.
When a two-parameter minimization on k e andĒ for each experiment was performed following the protocol described in experiments. Uncertainty in wall-loss was determined by taking the smallest k e value found from each of these experiments (0.0004 s −1 ) as a lower bound and the largest k e value (0.5 s −1 ) as an upper bound. The total mass concentration of SOA formed, which was used to calculate the SOA yield, was found from a smoothing spline fit of the particle-wall-depositioncorrected volume concentration (R 2 ≥ 0.994). Wang et al. (2018a) have shown, for a similarly configured chamber to those used here, that neither UV lights turning on and off, nor flushing of the chamber, nor gas-phase injections had an effect on 235 particle wall deposition.
As additional verification, for three experiments performed under the standard replication conditions, the contents of the chamber were allowed to sit undisturbed for 4 h prior to the lights being turned on. During these 4 h, the wall loss correction was performed using the parameters k e = 0.0769 s −1 andĒ = 0, for which it was verified that these values gave constant volume concentrations.

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Prior to the commencement of oxidation, all experiments were mixed and then allowed to sit undisturbed for ≥1 h. During this background-collection period, during which we assume no aerosol growth took place, the wall-deposition-corrected volume concentration was calculated using the k e andĒ parameters given above. To quantify the degree to which this volume concentration was properly wall-deposition corrected, the slope of a linear fit of the volume concentration as a function of the time (with a 95% confidence interval) during this background period is reported in Table 1. Since experiment S1 was 245 performed in the absence of initial seed, the aerosol volume concentration during the background collection time was 0 and no slope is reported. For all 20 experiments in which a SOA yield is reported (excluding S1), the wall-deposition-corrected volume concentration during the background collection time was relatively constant: the absolute value of the slopes for all experiments was < 0.1 µm 3 cm 3 s −1 and the mean was 0.03 µm 3 cm −3 s −1 .
The initial particle surface area concentration was taken to be the average of the wall-loss corrected values of the seed volume 250 during the background-collection period.

Vapor-wall deposition
Based on three periods of vapor wall loss prior to experiment S3, each >100 min, the timescale of the loss of benzyl alcohol to the Teflon chamber walls is on the order of days (∼2 to 5 days). While benzyl alcohol itself may be lost slowly, the significant SOA yield dependence on initial seed surface area seen for the similar toluene-oxidation system  suggests 255 that other benzyl alcohol oxidation products might partition to the wall. A low derived accommodation coefficient of vapor to suspended particles (α p ), as discussed in Sect. 6.2, also implies the presence of a seed surface area effect. For, the slower the gas-particle equilibration, the more likely that the chamber wall is an attractive condensation sink.
To understand the extent to which the chamber wall is competitive with the suspended aerosol as a condensation sink, the initial seed surface area concentration was varied for otherwise identical experimental conditions. Figure 2 shows this observed 260 SOA yield, where no vapor-wall-deposition corrections are performed, for a range of initial seed surface area concentrations.
Above ∼1800 µm 2 cm −3 , there appears to be little change in the observed SOA yield; thus, we assume that the effect of vapor wall deposition is minimal. Figure 2. Variation in observed benzyl alcohol SOA yield with an initial NO mixing ratio of 80 ppb at 291 K as a function of the amount of benzyl alcohol reacted and the initial aerosol seed surface area. The lack of a difference in the yield over differing seed surface areas above ∼1800 µm 2 cm −3 indicates that the experiments lie within a regime where the seed surface area does not affect the measured SOA yield.
For each chamber and each chemical system, the initial seed surface area concentration at which the effect of vapor wall deposition is no longer significant is different: this is a function of, among other factors, the particle-vapor equilibration time, 265 the accommodation coefficient of the gas-phase product to the chamber walls, the chamber dimensions, and the initial precursor concentration (Charan et al., 2019;Zhang et al., 2015).
In theory, the fact that we can neglect the effects of vapor wall deposition on SOA yield at a temperature of 291 K and an initial NO mixing ratio of ∼80 ppb (as is the case for experiments R1-5 and S1-4, which are shown in Fig. 2), does not mean that we can neglect the effects for all temperatures and all NO mixing ratios, since different experimental conditions may 270 change the chemistry of the system. However, while the identities and relative ratios of gas-phase products may differ for the different experiments explored in this paper, and hence the propensity to partition into the wall may vary, it is assumed that the products are sufficiently similar that the range at which vapor-wall deposition is considered insignificant remains the same.
And, so, we apply the assumption that vapor wall deposition minimally affects the observed SOA yield at initial seed surface area concentrations above ∼ 1800 µm 2 cm −3 to all experiments in this paper.

Effect of corrections on measured SOA yield
The SOA yield is defined as the ratio of the mass of aerosol formed to the mass of precursor reacted (see Eq. 1). One may overestimate the yield by underestimating the amount of benzyl alcohol reacted or by overestimating the amount of aerosol formed. If the particle-wall-deposition adjustment overcorrects the aerosol formed, it would seem as if a higher yield exists than that in actuality. Table 2 shows the SOA yield that would be calculated assuming that no particles were lost to the chamber 280 walls during the experiment. Except for experiment R3 and L1, which ran for 12 h and 17 h, respectively, the raw particle volumes at the end of the experiments were > 80% of the wall-deposition-corrected volumes. So, even if there are errors in the particle-wall-deposition correction, the SOA yields will still be quite large. Throughout all the experiments, the O:C ratio also first decreases and then increases. Figures 3 and 4 show the aerosol chemical composition analyzed at different temperatures and NO mixing ratios, respectively. If particle growth is mass-transfer limited (supported by a modeled α p ∼ 10 −2 , see Sect. 6.2), this might simply be a result of the greater abundance of higher volatility 290 oxidation products at the beginning of the experiment. Only the lowest volatility (which are, presumably, compounds with the highest O:C ratios) condense initially, but as higher volatility compounds build up they may eventually partition into the aerosol phase, decreasing the O:C ratio. As lower volatility second-and third-generation compounds are formed, these might then increase the O:C ratio observed. There may also be particle-phase chemical reactions occurring that leads to the change in O:C ratio throughout the experiment or the observed change could result from a change in the nitrogen-containing compounds 295 in the aerosol-phase. Note that, when there is a large contribution of organonitrates to the aerosol, the O:C ratio will be an underestimate (Aiken et al., 2008). . Variation in (a) the hydrogen to carbon atomic ratio, (b) the NO + x ratio, and (c) the oxygen to carbon atomic ratio indicate that the difference in SOA yield observed at different temperatures might be a result of chemical differences in the aerosol formed. Absolute uncertainties are 13% and 28% for the H:C and O:C ratios, respectively. Since the ratios are relevant only when there is a sufficient amount of aerosol present, the first 15 min after oxidation are not shown. A SOA yield is not calculated for experiment U2 due to uncertainties in the rate of particle-wall deposition, but that should not affect the chemical composition of the aerosol.  . Variation in the (a) hydrogen to carbon atomic ratio, the (b) NO to NO 2 signal mass ratio, and the (c) oxygen to carbon atomic ratio indicate that the difference in SOA yield observed at different NO mixing ratios is a result of chemical differences in the aerosol formed.
Absolute uncertainties are 13% and 28% for the H:C and O:C ratios, respectively. Since the ratios are relevant only when there is a sufficient amount of aerosol present, the first 15 min after oxidation are not shown. Data were collected only after ∼2 h of oxidation for experiment N4. A SOA yield is not calculated for experiment U6 due to uncertainties in the rate of particle-wall deposition, but that should not affect the chemical composition of the aerosol.
It appears that at the beginning of each experiment, the first secondary organic aerosol formed comprised a significant portion of organonitrates (as much >20% by mass), as shown in Fig. A1. While the mass fraction of organonitrates is not reported for the experiments shown in Figs. 3 and 4 (due to calibration issues), the NO + x ratio trend is the same as that for the experiments 300 shown in Fig. A1, where the mass fraction can be reported. Note that one pathway to form organonitrates is by reaction with the nitrate radical; since all our analysis from the AMS is of experiments with the ultraviolet lights on, one does not expect a significant concentration of nitrate radicals (Seinfeld and Pandis, 2016). Instead, we expect the organonitrates to have been formed by a RO 2 ⋅+NO reaction; this reaction has a high gas-phase yield for organonitrates for large compounds (Arey et al., 2001;Rollins et al., 2010). As oxidation continued, more non-nitrogenated organic compounds condensed into the particle 305 phase decreasing the mass concentration of organonitrates. Simultaneously, the NO + x ratio decreased, which could have been caused by nitric acid, formed from OH + NO 2 , partitioning into the aerosol phase and forming nitrate ions. Partitioning of HNO 3 into secondary organic aerosol has been observed by Ranney and Ziemann (2016). Another possibility is that other compounds, such as organonitrites, might produce NO + 2 fragments that lower the NO + x ratio throughout the experiment. Indeed, UPLC analysis found a high prevalence of compounds of the form RNO 2 (see Table A1), which likely will not 310 lead to the same NO + x ratios as organonitrates and might contribute NO + 2 fragments that could lower the NO + x ratio. For all experiments with filters collected (N1-3 and U1-6), nearly all compounds detected with UPLC analysis were nitroaromatics.
This indicates that the low-volatility products that condense into the aerosol phase retain their aromatic rings. It is possible, however, that there are non-ring retaining compounds which condense onto SOA that are simply not detectable by the UPLC.
Some of the ring-retaining compounds have C 7 structures, as does benzyl alcohol. However, several of the compounds detected 315 are C 6 structures, indicating the possible loss of the methanol group. In particular, UPLC analysis showed a particularly high concentration of nitrocatechol in the aerosol. The atomic ratios of oxygen to carbon atoms (O:C) are quite large: between 0.6 and 1.0, which matches that of very oxygenated rings, but could also match nitrocatechol (O:C of 0.67).
The prevalence of nitroaromatics may be because the UPLC analysis method is particularly sensitive to nitroaromatics: the detection of aerosol phase compounds via the UPLC/MS method is limited to detecting compounds that are water soluble and 320 lie within the detection limits of the instrument. Though filter samples were stored at low temperatures, on-filter chemistry may be possible. Certain compounds may also be prone to hydrolysis when in the aqueous phase, which may alter the molecular weight of the original compounds collected in the particle phase (Zhang et al., 2016).
Nevertheless, it is clear that there are many nitrogen containing compounds in the particle phase. Differences in aerosol chemical composition as a function of temperature and NO concentration is discussed in Sects. 5.2 and 5.3. 325 5 SOA yields

Time dependence
While, usually, the SOA yield is reported as a single number at the end of an experiment, it can also be understood as a function of time since multiple generations of oxidation products usually exist (Cappa et al., 2013). For example, in the α-pinene system, the SOA yield has been shown to depend on the total hydroxyl radical exposure (Donahue et al., 2012;Wang et al., 2018b). 330 Figure 5 shows, for each experiment, the terminal SOA yield and the bands indicating at which times each of the experiments lie within 10%, 5%, and 1% of the final reported yield. The most atmospherically representative SOA yield is that to which the experiments converge. For almost all the experiments, the yields appear to have converged sufficiently to justify the reporting of the final yield, though the benzyl alcohol concentration may not yet have all reacted (see Fig. 6); as more reacts, more aerosol is formed but the SOA yield levels out. Experiments R3 and R5, which were run for considerably longer than other experiments, 335 show that the final SOA yield changed little from earlier in oxidation, when the other experiments were terminated. Instead of looking at this in terms of reaction time, one can see instead the SOA yield as a function of the amount of the initial benzyl alcohol reacted ( Fig. 7) and see that the yield also converges in terms of the fraction of benzyl alcohol reacted.   Note that for experiment L1, also run for considerably longer than the other experiments, the light strength was < 10% of that in all the other experiments. At this lower oxidation rate, the SOA yield takes much longer to converge but does appear to 340 be somewhat a function of the fraction of benzyl alcohol that has reacted at any given time. This shows that the convergence time depends on the rate of oxidation. Figure 6 shows the decay of benzyl alcohol throughout the experiment: for all except experiment L1, the curves show a very similar decay. The first-order exponential decay constant (k BnOH+OH [OH]) for each experiment is given in Table 1.

Temperature dependence
345 Figure 8 shows the SOA yield of benzyl alcohol over a range of temperatures, all corresponding to approximately the same initial surface area range (1500-2800 µm 2 cm −3 ) and the same initial NO mixing ratio of ∼ 80 ppb (see R1-5 and T1-4 in Table   1). In general, a lower yield of benzyl alcohol exists at higher temperatures; this is expected due to the decreased volatility of oxidation products at lower temperatures and to the increased rapidity of second-generation reactions, which may potentially form high volatility fragments before the lower volatility first-generation products have time to partition into the particle phase.   Table 1).
At the lowest temperature measured, where one would expect the greatest seed surface area effect (that is, the most competition between the wall and suspended aerosol condensation sinks), we have already determined that we are outside the range of the seed surface area effect (Fig. 2). So, one would not expect that the difference in SOA yield is related to competition with the chamber wall.
A higher SOA yield at lower temperatures is also supported by Fig. 3, which shows how the chemical makeup of the aerosol 355 is different for aerosol formed at different temperatures: the O:C ratio is higher and the H:C ratio is lower on aerosol formed at higher temperatures, meaning that more volatile compounds that might condense at lower temperatures (and have a smaller O:C ratio and a lower H:C ratio) do not condense at the higher temperature (panels a and c). Though the difference is slight, there is a trend for a larger NOx + ratio (panel b) and, correspondingly, a larger mass fraction of organonitrates at higher temperatures.
The former indicates that the organonitrates may be less volatile than other nitrogen-containing compounds that may condense 360 into the aerosol phase (including, potentially, inorganic ammonium nitrate). The latter suggests that the gas-phase branching may be different. It may be that fewer organonitrates are formed at lower temperatures.

Nitric oxide mixing ratio dependence
To probe the different chemical pathways that form, the SOA yield dependence on variable NO concentrations was investigated ( Fig. 9). NO mixing ratios were maintained throughout experiments N1-6 and U6, leading to an increase in the total NO x in 365 the system. NO x increased by ∼60 ppb for experiment N1 and ∼100-200 ppb for experiments N2-6 and U6. Generally, the SOA yield seems to decrease with increased NO concentration. As shown in Fig. 4c, there are also larger O:C ratios after ∼2 h of oxidation for the lower NO mixing ratios (N1, N2, and N4). Note that experiment N4 appears to behave more similarly to N1-2 than to N5-6 and U6; the control on the NO mixing ratio for N4 was much less successful than for the other constant NO experiments (see the error bars in Fig. 9). While the [NO] 370 throughout experiment N4 was, on average, 74 ppb, it was only 62 ppb on average during the first 3 h of oxidation (experiment N3 had an average [NO] of 62 ppb during the first 3 h of oxidation).
We suspect that there are a large number of nitroaromatics in the organic aerosol (see Sect. 4). Perhaps at higher NO concentrations there are more nitroaromatics, and these compounds are more volatile than the nitrogen-free oxidation products (such as the very oxygenated rings). Though the differences in H:C and O:C ratios are slight, the larger O:C ratios-corresponding 375 to the very oxygenated rings-that are seen at lower NO concentrations support the theory that the compounds formed differ (see Fig. 4).

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https://doi.org/10.5194/acp-2020-492 Preprint. Discussion started: 16 June 2020 c Author(s) 2020. CC BY 4.0 License. Experiment E1, which is similar to experiments R1-5 except that, prior to the beginning of oxidation, it begins with 71.0±0.8 ppb of NO 2 and no NO, shows a much lower SOA yield than that from experiments R1-5. This suggests that it is the NO that is the relevant reactant that causes initially high SOA formation. This is supported by the significant mass fraction of 380 organonitrates at the beginning of the experiments; organonitrates are formed by RO 2 ⋅ reaction with NO.
6 Benzyl alcohol oxidation chemistry

Theory
Oxidation of benzyl alcohol in the present system occurs predominantly via reaction with the hydroxyl radical (OH). The reaction with OH proceeds via H-abstraction from the CH 2 group or OH addition to the aromatic ring; its products are hypothesized 385 to include benzaldehyde, 3-hydroxy-2-oxopropanal, butenedial, and glyoxal (Wang, 2015). Measured rate constants (Harrison and Wells, 2009;Bernard et al., 2013) for reaction with the OH radical found using a relative-rate method are (2.8±0.4)×10 −11 cm 3 molecule −1 s −1 at 297 ± 3 K.
A chemical understanding of the gas-phase oxidation of benzyl alcohol is useful for modeling the system, which can aid in understanding the gas-and particle-phase dynamics. Note that while gas-phase dynamics affect the SOA formed, the assump-390 tions made in this section do not affect the measured SOA yields and are only used for understanding the system.
The measured gas-phase yield of benzaldehyde from the reaction of benzyl alcohol with OH is 24±5% at 298 K (Harrison and Wells, 2009;Bernard et al., 2013), which also matches well with a theoretical value of 29.6% (Wang, 2015). For gas-phase modeling and related optimization (Sect. 6.2 and 6.3), we use branching ratios following the results of Wang (2015), which combine theoretical and experimental branching results: 0.25 to form benzaldehyde, 0.11 to form o-hydroxy-benzyl alcohol 395 (note that this differs somewhat from the measured yield of 0.22 Bernard et al. (2013)), 0.23 to high volatility fragments (including glyoxal and butanedial), and the remaining 0.41 to low volatility and ring-containing products. Since the intermediate reactions are theoretically much faster than the initial reaction of OH with benzyl alcohol (except for the reactions of benzaldehyde), we employ the mechanism given in Fig. 10, in which compounds of similar volatilities are grouped into the precursor (BnOH), benzaldehyde (BnAl), fragments (Frags), very oxygenated rings (VORings), and hydroxy-benzyl alcohol (HOBnOH).  Table 3. For each compound class, the estimated vapor pressure is the component-weighted value found using the EVAP-ORATION method (Topping and Jones, 2016) (note that using EVAPORATION gives results similar to the Nannoonal and Myrdal methods) at the mean temperature of the experiment under consideration; for reference, the saturation mass concen-405 tration C * is given in Table 3 at 291 K. The Oxygen-to-Carbon ratio is also given for each compound class. Note that none of these predicted products are organonitrates or other nitrogen-containing organic compounds, as observed in the aerosol (see Sect. 4). The lack of nitrogen-containing products, especially at the very beginning of oxidation, could be responsible for some of the discrepancy between the observed and simulated results.

Chamber simulation
All optimization procedures and modeling are based on a fixed-bin model, as described in Charan et al. (2019). A density of 1.4 g cm −3 , consistent with past work on similar compounds (Dommen et al., 2006;Kroll et al., 2005Kroll et al., , 2006Brégonzio-Rozier et al., 2015), and a surface tension of 28.21 dyn cm −1 , that of benzene particles (Seinfeld and Pandis, 2016), are assumed for the particles with SOA. Wall accommodation coefficients are calculated using the saturation mass concentrations of each compound class (see Table 3) and the empirical fit described in Huang et al. (2018).

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Modeling is carried out by fixing the decay of benzyl alcohol to the second-order exponential fit of the concentration. these particles to grow very quickly and, therefore, requires a much smaller time step. Hence, for the surface area experiments we do not model experiment S1.
Because several of the simulation parameters are not precisely constrained (the equivalent saturation concentration of the wall, C w , the accommodation coefficient of vapor to suspended particles, α p , the accommodation coefficient of vapor to deposited particles, α pw , the accommodation coefficient of each product to the wall, α w,i ), modeling of the system is associated 425 with considerable uncertainty. If one is confident in the branching ratios under each condition, then one could determine α w for each product and optimize α p and C w with the surface area and reproduction experiments (S2-4 and R1-4). Differences in products could then be determined at different temperatures (using experiments T1-4) and at different constant NO concentrations (using experiments N1-6).
With the base assumption that α p = 1, α pw = 0, and C w = 1×10 4 µg m 3 , the model reproduces experiments R1-4 fairly well, 430 and most of the other experiments less successfully (see Fig. 11). Even for experiment R1, where the simulation captures the total organic mass well (Fig. 11A), the size distribution evolution is less successfully captured (Fig. 12). Table 4. Optimization of parameters. The equivalent saturation mass concentration of the Teflon wall, Cw, has units of µg m −3 . The accommodation coefficient of vapor to suspended particles (αp) and of vapor to deposited particles (αpw) are unitless. For all optimizations, starting conditions were αp = 1, αpw = 0, and Cw = 10 4 . When not optimized, αpw = 0, Cw = 10 4 , and αp is given in parentheses.

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An accommodation coefficient close to 1 means that equilibrium between the gas-and particle-phase is quickly reached because there are few mass-transfer limitations. The smaller α p found here indicates that the particles are highly viscous, i.e., that it takes some time for the particle-phase to equilibrate with the gas-phase. For systems with lower values of α p , one expects to see more of a seed surface area effect, which is discussed in Sect. 3.2.2.
Since any optimizations involving α pw indicated very small values, for this chamber it appears that ω = 0 is closer to reality 445 than ω = 1. This is because if α pw ≈ 0, then effectively no gas-phase compounds are condensing onto particles that have already deposited on the chamber wall, which is the same as the assumption that ω ≈ 0.

Gas-phase insights
Benzaldehyde, which is a first-generation product of benzyl alcohol, photolyzes in addition to reacting with the OH radical (Bernard et al., 2013;Zhu and Cronin, 2000). Using absorption cross sections from the lamp-diode array from Thiault et al.

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(2004), assuming a quantum efficiency of 1, and normalizing the measured wavelengths in the chamber with the j N O2 value for the chamber gives j BnAl = 4.58 × 10 −4 s −1 .
Just as we employed chamber simulation to derive unknown chamber parameters, we can also determine which of the compound classes (Table 3) are most similar to benzaldehyde oxidation products. To do so, one must make assumptions about the other chamber parameters: here we take α p = 1, ω = 0, C w = 10 4 µg m −3 , the first-generation branching ratios given in 455 Fig. 10, the assumption that photolysis products of benzaldehyde are volatile and act similarly to the Frags compound class, and the assumption that oxidation products of benzaldehyde condense into the particle phase (and so are most similar to the VORings compound class). This leaves only a single parameter to determine: k OH+BnAl [OH], which governs the amount of the oxidation product versus the photolysis product of benzaldehyde.
Performing a minimization on the difference between the predicted and measured secondary organic aerosol products while 460 varying this parameter k OH+BnAl [OH] gives, for most of the experiments, a k OH+BnAl [OH] ≈ 0. Since we did not measure the benzaldehyde gas-phase concentration throughout the experiment, this result says nothing about the benzaldehyde that is Since we are looking at the particle-phase results, and we assume that Frags do not condense onto particles, this is equivalent to assuming that k OH+BnAl [OH]=0 without the constraint that no benzaldehyde reacts with OH. Experiments by Carter et al. (2005) also indicate that benzaldehyde oxidation products do not contribute significantly to the SOA formed from benzyl alcohol.
Depending on the temperature and the other experimental conditions (such as the NO mixing ratio), one would expect the 470 chemistry to vary between experiments. The gas-phase concentration of hydroxy-benzyl alcohol (HOBnOH) has a molar mass of 124 g mol −1 and is detected at M+19, corresponding to the addition of F - (Schwantes et al., 2017b). This signal normalized to the reactant ion signal by the initial benzyl alcohol concentration (expressed in signal normalized to reactant ion signal) for each of the experiments described here is given in Fig. 13. Note that this is, essentially, the HOBnOH concentration divided by the initial benzyl alcohol concentration. The temporal evolution of HOBnOH for nearly identical experiments is fairly 475 reproducible, as shown in panel a. The formation of HOBnOH or the rate at which it reacts away seem to increase slightly at higher temperatures (Fig. 13d) and possibly at higher constant NO concentrations (Fig. 13e but not 13f), but considering that the uncertainty in initial BnOH mixing ratio is on the order of 10% (see Table 1), it is difficult to make any concrete statements about the shift in gas-phase chemistry due to changing conditions except to say that changes are not hugely significant. (2018), who found that volatile chemical products might contribute very significantly to SOA formation in cities like Los Angeles, estimated a SOA yield of 0.090 ± 0.023 for benzyl alcohol. Even in its upper limit, this is less than a third of the SOA yields found in this study. While benzyl alcohol is one of a number of compounds considered, the fact that the experimental results disagree significantly with the estimates made in accounting studies indicates that we could still be vastly underestimating 485 or poorly predicting SOA yields from oxygenated species.
The benzyl alcohol mixing ratios used in this study (>130 ppb) exceed substantially those in the atmosphere. Especially since we have suggested that, at least initially, SOA growth may proceed in a mass-transfer-limited regime, this could be a problem for extrapolating these results to the behavior of benzyl alcohol in the atmosphere. However, the long reaction time and the flattening out of the SOA yields (Fig. 5) suggests that the SOA yield has reached equilibrium and would be the same regardless