An Aerodyne time-of-flight (ToF) CIMS (Lee et al., 2014) that uses acetate (CH3C(O)O-) as the reagent ion was deployed at the Horse Pool site during UBWOS 2014 to measure organic acids, inorganic acids and nitrated phenols. These compounds are ionized in the ion–molecule reaction region (IMR, 61.8 ± 0.3 mbar) via proton abstraction (Veres et al., 2008) or by a sequence of clustering–declustering/deprotonation reactions (Brophy and Farmer, 2015) in the reaction with acetate ions. Acetate ions were produced by introducing saturated acetic anhydride/N2 mixture (5 mL min-1) mixed with another flow of N2 (2.5 L min-1) into a polonium-210 (210Po) radioactive source. The instrument was operated under strong declustering conditions by applying voltages in the first quadrupole ion guide (i.e., SSQ, 2.50 ± 0.01 mbar) during UBWOS 2014, with the ratio of acetate cluster (CH3C(O)O-⚫ CH3C(O)OH)/acetate (CH3C(O)O-) at 0.4 ± 0.1 %. Under such declustering conditions, the conjugate anions were usually observed as the product ions, with little contribution from cluster ions. The reagent ions and product ions are analyzed using a high-resolution time-of-flight mass spectrometer (Tofwerk AG, Switzerland). The signals of acetate ion were approximately 1–2 × 106 counts per second (cps) during the campaign (ToF extraction frequency = 25 kHz). The mass resolution of the ToF analyzer during UBWOS 2014 was approximately 3200 for ions of m/z > 200.

Background signals associated with the instrument were measured every 2 h for 15 min by passing ambient air through three stages of zero air generation: a platinum catalytic converter heated to 350 ∘C, nylon wool coated with sodium bicarbonate (NaHCO3), and activated charcoal, which were used in series to remove acidic gases from the sample air and determine instrument backgrounds. During the UBWOS 2014 study, two CIMS inlets constructed from Teflon tubing heated to ∼ 40 ∘C with similar lengths (∼ 10 m) placed at heights of 1 and 18.5 m above ground were switched automatically every 30 min during the period of 24 January–1 February in order to measure the vertical concentration gradient of nitrated phenols and other acidic gases. Inlet switching between a long heated and a short unheated inlet was conducted during 1–5 February in order to explore possible inlet interferences to CIMS measurements of nitrated phenols from the long heated inlet. We did not observe differences in signals between the long and short inlets for nitrated phenols except DNP (Fig. S1 in the Supplement), indicating that potential loss in the sampling line was minimal for the reported single nitrated phenols in this study. The inlet issues for DNP will be discussed in Sect. 2.1.2.

The ToF-CIMS data were processed using the Tofware software package (www.tofwerk.com/tofware) written in Igor Pro (Wavemetrics Inc., USA). The detailed data processing procedures are presented in recent studies (Yatavelli et al., 2014; Stark et al., 2015). Post-measurement mass calibrations were performed using nine isolated ions: m/z 31.9904 (O2-), m/z 34.9694 (Cl-), m/z 44.9982 (CHO2-), m/z 59.0139 (C2H3O2-), m/z 61.9884 (NO3-), m/z 143.9840 (C3F4O2-), m/z 162.9824 (C3F5O2-), m/z 193.9808 (C4F6O2-), and m/z 243.9776 (C5F8O2-). The four fluorine-containing ions in the list were released from the Teflon inlet during UBWOS 2014 and their persistent presence was used for mass calibration. The accuracy of mass calibration was 4.7 ± 1.9 ppm for the whole campaign and the errors of mass calibration for individual ions were usually within 10 ppm (average + 3σ). The fitted raw signals for the targeted compounds were normalized using an acetate signal at the level of 1 × 106 cps, and the normalized signal has a unit of normalized counts per second (ncps).

The fitted m/z used for quantification of concentrations of nitrated phenols in the acetate CIMS are m/z 138.0197 (C6H4NO3-) for NP, m/z 152.0353 (C7H6NO3-) for MNP, m/z 166.0510 (C8H8NO3-) for dimethylnitrophenol + ethylnitrophenol (DMNP) and m/z 183.0047 (C6H3N2O5-) for DNP. Compounds with the same molecular formulas as nitrated phenols include phenyl nitrates/benzyl nitrates, methoxynitrobenzenes, nitrobenzyl alcohols, and hydroxycarboxylic acids derived from pyridine. The first three groups of compounds have lower acidities than acetic acid (Bartmess, 2015) and hence they are unlikely to be observed in acetate CIMS, while hydroxycarboxylic acids derived from pyridine are expected to be small in the atmosphere.

High-resolution (HR) peak fitting to m/z 138, m/z 152, and m/z 183 in the averaged mass spectra of ToF-CIMS on a typical day (25 January 2014) are shown as examples in Fig. 2. Isotope signals from lower masses (dark-green lines) accounted for small fractions of the m/z signals. Multiple overlapping ion peaks were identified in the m/z channels. In addition to nitrated phenols, several ions without deprotonation were also present in the even m/z (e.g., C8H10O2- at m/z 138), possibly due to electron transfer reactions and/or fragmentation in the quadrupole ion guides (Stark et al., 2015). The signals of NP and MNP were either the largest or significantly larger than their neighboring peaks at their respective m/z, whereas the signal of DNP was much smaller than its neighboring peaks on 25 January 2014. Smaller ratios of the signals between the targeted peak and its neighboring peaks have been shown to deteriorate the precision of the fitted signals for the targeted peak (Cubison and Jimenez, 2015; Müller et al., 2011; Corbin et al., 2015). Based on the provided equations in Cubison and Jimenez (2015), the imprecision arising from mass calibration (not including counting error) for the signals of NP, MNP, and DNP are 3.2, 1.8, and 47 % based on the mass spectra of 25 January, respectively. Imperfect mass calibration can also affect fitted magnitudes of ion signals. Figure S2 shows the sensitivity of the fitted signals of various masses as a function of the errors in mass calibration. The signal changes at 10 ppm (average + 3σ) error of mass calibration relative to the perfect mass calibration (error = 0 ppm) for NP, MNP, and DNP signals are as high as 14, 5, and 81 %, respectively. The results from both precision calculation and sensitivity of fitted magnitudes indicate that the peak signals of NP and MNP can be fitted well with low uncertainties. The peak fitting at m/z 166 for DMNP shows similar results as m/z 138 for NP and m/z 152 for MNP. However, large uncertainties are associated with the peak signals of DNP on 25 January 2014, which is mainly affected by the C3F6HO2- ions (m/z 182.9886) as indicated by the opposite behaviors of the DNP ion and C3F6HO2- ion in Fig. S2c.

The C3F6HO2- ion (m/z 182.9886) was released from the heated Teflon inlet along with other fluorine-containing ions that were used for mass calibration. The release of the C3F6HO2- ion was supported by much higher signals from the long heated inlet compared to the short unheated inlet when inlet-switching experiments were conducted in 2–5 February (Fig. S1). Long-heated inlets were used for most of the time during UBWOS 2014 (23 January–13 February), except during 18–22 January, when a short unheated inlet was used. The averaged mass spectra of m/z 183 measured on 18 January is shown in Fig. 2d. Compared to the mass spectra on 25 January, C3F6HO2- signals on 18 January were lower and the signals of DNP were larger than those of C3F6HO2- ions. As a result, the uncertainty from peak fitting for the DNP ion was much lower on 18 January (Fig. S2d). Thus, we will only use measured DNP data in the beginning of the campaign (18–22 January), when the long heated inlet was not connected to the acetate CIMS and no inlet switching was performed.

The response of the CIMS instrument for nitrated phenols, including 2-NP, 4-NP, 2-methyl-4-nitrophenol, and 2,5-dinitrophenol, was calibrated using a liquid calibration unit (LCU, IONICON Analytik). In the LCU, a water solution with known concentrations of the targeted compounds is nebulized and diluted by another gas stream at different flow rates to produce a gas standard at various concentrations (Kaser et al., 2013). The results of the calibrations to various nitrated phenols are shown in Table 1. The sensitivity of 4-NP in our instrument was determined to be higher than that of 2-NP by a factor of 2.1. A higher sensitivity of 4-NP in acetate CIMS was reported in Mohr et al. (2013), but in that study the difference was larger by 3 orders of magnitude (Mohr et al., 2013). The different sensitivity ratios of 4-NP/2-NP can be caused by many different instrumental conditions between our instrument and that in Mohr et al. (2013), such as the amount of acetic anhydride introduced into the instrument, IMR and SSQ pressures, and declustering settings in the quadrupole ion guides, all of which affect sensitivities of acetate CIMS significantly (Stark et al., 2012). The main reagent ions in IMR were shown to be acetic acid–acetate clusters rather than acetate (Bertram et al., 2011), and the cluster distributions in IMR may depend on operated pressure in IMR and the amount of acetic anhydride introduced into the ion source. While declustering in SSQ helps the interpretation of recorded mass spectra, declustering also obscures a precise understanding of cluster distributions in IMR and hence accurate prediction of sensitivities in acetate CIMS. This result also emphasizes the importance of instrument calibrations in deriving concentration from acetate CIMS. We note that 3-nitrophenol (3-NP) is not usually present in the atmosphere (Harrison et al., 2005a). Thus, the average of the sensitivities of 2-NP and 4-NP was used for calculating concentrations of NP. DMNP was not calibrated in this study and we assumed the same sensitivity as determined for MNP.

The accuracies of nitrated phenols measurements by the CIMS are conservatively estimated to be around 40 % for NP and 50 % for other nitrated phenols, mainly arising from uncertainties in the concentration output of the LCU (∼ 10 %), uncertainties associated with calibration procedures (∼ 5 %), errors in high-resolution (HR) peak fittings to mass spectra (see above and Fig. S2), and the representativeness of the calibrated species to other isomers (0–30 % for NP and 0–40 % for other nitrated phenols). Assuming random errors in the observed ion counts follow a Poisson distribution, detection limits of nitrated phenols, i.e., concentrations with a signal to noise ratio (S/N) of 3, are calculated to be 0.1–0.3 ppt for 1 min average data (Table 1). Following the discussions in Bertram et al. (2011), the measured background ion counts in ToF-CIMS drift over time and thus detection limits are more appropriately calculated as the concentrations at 3 times the standard deviation of the measurement background counts. The determined detection limits of nitrated phenols increase to the range of 0.3–0.5 ppt based on this approach (Bertram et al., 2011) (Table 1).

We will focus on NP to understand the budget of nitrated phenols, because NP had higher concentrations than the substituted nitrated phenols (MNP and DMNP) and there is more information on sources and sinks of NP in the literature. A series of zero-dimensional box model simulations on the formation of phenol and NP were conducted using the online AtChem tool (https://atchem.leeds.ac.uk). The MCM v3.2 (Jenkin et al., 2012) was used as the chemical mechanism in the box model. We note that ambient temperature (-5 ± 5 ∘C) during UBWOS 2014 was much lower than the temperature (around 25 ∘C) at which rate constants of many reactions are usually measured. Rate constants as a function of temperature are only available for the reactions of OH radical with benzene and phenol among those shown in Fig. 1, and they were already included in the MCM v3.2. The model ran in a time-dependent mode and a 48 h spin-up time was applied in the box model. Measured concentrations of various hydrocarbons, NOx, O3, NO3, and photolysis frequencies (Table S2) were used as constraints in the box model. The simulation period of the model was chosen to be 18–27 January, a period associated with several buildup episodes of ozone and other secondary products, with high measured concentrations of NP and without precipitation. Following previous box model studies (Yuan et al., 2015; Edwards et al., 2014), dilution and deposition processes were represented together using a diurnally varying first-order physical loss parameter in the box model. The physical loss rate at night (5.8 × 10-6 s-1) was calculated from the decrease rate of NP concentration between 00:00 and 06:00, when the chemical loss was expected to be low (see Sect. 3.3.4). A higher physical loss rate (2.0 × 10-5 s-1) during daytime was used to account for larger turbulent mixing during daytime (Edwards et al., 2014), which results in the decrease in concentrations of inert tracers in the afternoon, e.g., benzene (Fig. 3) and methane. Based on sensitivity tests of the box model, increase and decrease in the physical loss rate terms by a factor of 2 resulted in -48 and +39 % of changes in the modeled NP concentrations.

As shown in the introduction section, photolysis has been recognized as an important sink for nitrated phenols. However, the photolysis of NP (and other nitrated phenols) is not included in the MCM v3.2. We added the photolysis frequency of NP from Bardini (2006) (1.4 % of photolysis frequency of NO2) into the MCM v3.2 and this model run is referred to as the base simulation. Here, we assume that photolysis of NP produces 2-phenoxy biradicals and HONO, as proposed in Bejan et al. (2006) (Fig. 1, Route1). There are other possible chemical routes for photolysis of NP: producing phenoxy radicals (C6H5O) by losing NO2 (Route2 in Fig. 1) and producing nitrophenoxy radical by hydrogen abstraction (Route3 in Fig. 1). The simulation test in Fig. S4 indicates that the pathway forming C6H5O radicals and NO2 is an ineffective sink for NP, since C6H5O radical will re-form NP by reacting with NO2. However, we cannot exclude that this pathway occurs along with that producing 2-phenoxy biradicals and HONO. The photolysis frequency determined in Bardini (2006) based on concentration changes of 2-nitrophenol in a chamber may not include this pathway as well. As a result, attributing the photolysis rates determined in Bardini (2006) to other pathways other than Route2 is reasonable. The route producing nitrophenoxy radical will be discussed in Sect. 3.3.

The simulated results for phenol and NP from the base case of the box model are shown in Fig. 5. The modeled diurnal variations agreed reasonably well with the observation for both NP and phenol in the base simulation, except for the phenol nighttime levels that will be discussed below. Although modeled NP concentrations are higher than the measurements for both daytime and nighttime, the agreement between measurements and model results is still within their combined uncertainties.

The average measured concentrations of phenol at night are higher than 10 ppt, but the modeled phenol concentrations are usually less than 2 ppt. At night, the production of phenol from benzene oxidation halts, and the fast reaction with NO3 (2.8 × 10-11 cm3 molecule-1 s-1 at 298 K) removes phenol quickly (Fig. 7 and discussion in Sect. 3.2.3). Measured nighttime NO3 radicals were quite low during UBWOS 2014 (1.4 ± 2.4 ppt). As a check on the possible uncertainties in measurements of NO3 at these low levels, simulations by varying NO3 concentrations by a factor of 2 result in little improvement for the modeled concentrations of phenol (Fig. S5). Another simulation using calculated NO3 concentrations from the equilibrium between NO3 and N2O5 (Fig. S5) also indicates that uncertainties in NO3 measurements cannot account for the discrepancies between measured and modeled phenol at night. The high phenol concentrations measured at night might be a result of primary emissions. Indeed, the measured phenol concentration was slightly enhanced in the plume with high methane concentrations (see Fig. 4a). However, a simulation using the measured phenol concentrations as a constraint in the box model predicted much higher NP concentrations than measurements (Fig. S4). Perhaps a more likely explanation for the enhanced phenol concentrations at night is that the measurements of phenol by PTR-TOF suffer from chemical interferences at night. Vinylfuran might be a candidate (Karl et al., 2007; Stockwell et al., 2015). Thus, the modeled concentrations of phenol shown in Fig. 5 will be used in the following discussions.

As shown in Fig. 1, NP is generated from the reaction of NO2 with phenoxy radicals (C6H5O⚫) (Berndt and Boge, 2003), which is an intermediate from the reactions of OH and NO3 radicals with phenol and the reaction of phenylperoxy radicals (C6H5O2) with NO. In addition to NO2, C6H5O⚫ radicals also react with NO and O3 (Platz et al., 1998) (see Fig. 1). Thus, the yield of NP has been reported to depend on NO2 concentrations in the atmosphere (Berndt and Boge, 2003).

In the MCM v3.2, only the reactions of C6H5O radical with O3 and NO2 are included and here we added the reaction of C6H5O with NO (k= 1.88 × 10-12 cm3 molecule-1 s-1) for a new simulation. Compared to the base simulation, the modeled concentrations of NP are lower, especially for the period of 11:00–17:00, as the effective yield of NP is reduced (Fig. 5). The small enhancement during the period of 11:00–17:00 in NP concentrations from the base simulation is absent in the simulation with the reaction of C6H5O with NO. The variations in modeled NP concentrations in the daytime from the new simulation are in better agreement with the measurements (Fig. 5). This indicates that the reaction of NO and C6H5O radical should be considered to account for the NO2 dependence of NP formation.

Another simulation using fixed NP yields from phenol oxidation reported in Atkinson et al. (1992) (6.7 % for OH oxidation and 25.1 % for NO3 oxidation) is also performed. This simulation neglects any dependence of NP yield from phenol oxidation on concentrations of NO2, O3 and NO. We observed lower concentrations during both the day and night compared to the base simulation (Fig. 5). However, the enhancement of modeled NP in the period of 11:00–17:00 is distinctly observed with the simulation using the fixed yields in Atkinson et al. (1992), which is in contrast to the lowest concentration in the afternoon from our observations. This, again, indicates there must be a dependence of NP yield from phenol oxidation on NO2 concentrations in the atmosphere.

NP formed in the gas phase can partition into particles (Harrison et al., 2005a). Measurements in several studies demonstrated that 2-NP and MNP were mainly found in the gas phase (Herterich and Herrmann, 1990; Cecinato et al., 2005; Morville et al., 2006). However, the reported particle fractions of 4-NP and DNP exhibit a broad range in values: the particle fractions of 4-NP and DNP reported in Herterich and Herrmann (1990) were both lower than 15 %, whereas most of the concentrations of 4-NP (> 75 %) (Cecinato et al., 2005) and DNP (> 95 %) (Morville et al., 2006) were detected in particles in these two studies.

The concentrations of NP and other nitrated phenols in particles were not measured in this study. We acknowledge that some fractions of nitrated phenols in particles may evaporate into gas phase in the heated inlets. If it holds true, the measured concentrations of nitrated phenols in this study would fall somewhere between concentrations in the gas phase and the total gas + particle concentrations. Here, the gas–particle partitioning of NP as a function of time was estimated using the equilibrium absorption partitioning theory (Pankow, 1994; Donahue et al., 2006) (see details in the SI), based upon pure-compound liquid vapor pressures of 2-NP and 4-NP (Schwarzenbach et al., 1988) (Table 2) and organic aerosol (OA) concentrations measured with an aerosol mass spectrometer (AMS). The dependence with temperature was accounted for using the Clausius–Clapeyron relationship with reported enthalpies of evaporation (Hvap) (Schwarzenbach et al., 1988). Although vapor pressures from Schwarzenbach et al. (1988) might have significant uncertainties, Schwarzenbach et al. (1988) provided the only comprehensive measurements of sub-cooled liquid vapor pressures of nitrated phenols in the literature.

The calculated fractions in the particle phase (Fp) for 2-NP were generally very low (campaign average: 1.1 ± 0.9 × 10-4; max: 7.3 × 10-4), whereas Fp for 4-NP were higher (average: 0.053 ± 0.048; max: 0.38). The variability of the determined Fp values is the result of variations in both OA concentrations (12.5 ± 8.7 µg m-3; min: <1 µg m-3; max: 42.6 µg m-3) and ambient temperature (-5 ± 5 ∘C; min: -17 ∘C; max: 10 ∘C) during the campaign. The higher Fp for 4-NP is expected, as 4-NP (1.4 × 10-3 Torr at 298 K) has much lower vapor pressure than 2-NP (0.20 Torr at 298 K) (Table 2). In addition to absorption, partitioning of NP into the aqueous phase of particles is another possible pathway affecting Fp. This mechanism is estimated using Henry's law constants (Sander, 2015) and the liquid water content (LWC) (8.4 ± 7.5 µg m-3) in aerosol determined using the ISORROPIA model (Fountoukis and Nenes, 2007). The estimated Fp values based on aqueous-phase partitioning for 2-NP (1.3 × 10-7) and 4-NP (3.0 × 10-5) are both much lower than Fp estimated from the equilibrium absorption partitioning theory, indicating partitioning of NP into the particle aqueous phase was not important during UBWOS 2014.

The gas–particle partitioning of 2-NP and 4-NP determined above was incorporated into the box model by constraining the estimated Fp in the determination of gas–particle mass transport rates. The mass transport rates (Rin and Rout) of a species into and out of particles with radius r are approximated by Jacob (2000): Rin=rDg+4υα-1A×cg=1τ×cg,Rout=rDg+4υα-1A×cpKep=1τ×cpKep, where cg and cp are concentrations of the species in the gas and particle phase. Dg is the gas-phase molecular diffusion coefficient (m2 s-1), υ is the mean molecular speed (m s-1), and α is the mass accommodation coefficient. A is the aerosol surface area per unit volume of air (m2 m-3). Kep is the equilibrium constant, i.e., cp/cg, or Fp/(1-Fp). The characteristic timescale of mass transfer (τ) is estimated to be on the order of minutes for particles in the troposphere (Bowman et al., 1997; Jacob, 2000). Thus, rather than determining the characteristic timescale explicitly, we assume that the equilibrium is maintained at each model step (τ= 5 min). After entering into particles, no further reaction of NP was prescribed in the model. The modeled diurnal profiles of NP associated with the inclusion of gas–particle partitioning are shown in Fig. 6. Compared to the base simulation, the modeled NP concentrations in the gas phase using the estimated Fp from 4-NP are lower (4–8 %) for most of the day and slightly higher (2–3 %) in the morning, when NP concentrations decreased quickly. Since the predicted Fp from 2-NP is very small, the modeled NP concentrations in the gas phase using the estimates from 2-NP were almost identical to the base simulation. In contrast with the modeled concentrations of NP in the gas phase, the modeled total concentrations of NP in gas and particle phase are consistently higher than the base simulation that does not consider gas–particle partitioning. In summary, we observe relatively small changes of the modeled gaseous NP concentrations after the inclusion of gas–particle partitioning in the box model. Further measurements of the gas–particle partitioning of nitrated phenols are needed to explain the variety of Fp values observed in different studies and/or the potential differences between measurements and prediction from the equilibrium absorption partitioning model.

Diurnal profiles of formation and loss rates derived from the base simulation of the box model for both phenol and NP are shown in Fig. 7. Production of phenol only occurs in the daytime from OH oxidation of benzene. The magnitudes of losses of phenol due to OH oxidation (21 ppt day-1) and NO3 oxidation (19 ppt day-1) are comparable on a daily basis. From morning to afternoon (08:00–15:00), production of phenol is larger than the losses, resulting in continuous growth of phenol concentrations in this period. After 15:00, the losses start to surpass the production and phenol concentrations decrease quickly. With fast reduction of phenol concentrations in the evening, phenol loss from the reaction with NO3 mainly occurred before midnight.

As shown in Fig. 7, NP is produced during both daytime and night, with more production in the daytime. As mentioned earlier, the only formation pathway of NP is from the reaction of phenoxy radicals (C6H5O) with NO2, so the contribution from different pathways to NP formation can be derived from source analysis of C6H5O radicals (Fig. 7c). The production of C6H5O radicals is dominated by the reaction of C6H5O2 radicals with NO during daytime (71 % for 24 h average) and the reaction of phenol with NO3 radicals at night (27 % for 24 h average). There are several sources contributing to the formation of C6H5O2 radicals in the MCM, including photolysis of benzaldehyde and peroxybenzoic acid, OH oxidation of benzoic acid and phenyl hydroperoxide, and degradations of other radicals (e.g., phenylperoxyacyl radical C6H5CO3), suggesting a wide range of aromatic compounds as the precursors of NP in the daytime. The reaction of phenol with OH radicals only accounts for a small fraction of the production of C6H5O radicals (2 % for 24 h average), due to the small yield of NP (6 %) from the reaction of OH with phenol in the MCM. This indicates that phenol is not an important precursor for NP during daytime. The destruction of NP is mainly due to photolysis (17 ppt day-1), with some contributions from NO3 reaction (1.7 ppt day-1). The reaction with OH radicals is not important for the losses of NP in UBWOS 2014. Dilution/deposition processes account for 20 % of the total loss of NP in the box model. Our results are consistent with a previous proposal on photolysis as the dominant chemical loss pathway for nitrated phenols (Bejan et al., 2007). Based on the conditions at the Horse Pool site, the lifetime of NP due to photolysis at noontime is calculated to be ∼ 80 min. As the result of the short lifetime of NP during daytime, the production (23.6 ppt day-1) and loss rates (23.1 ppt day-1) of NP maintain a balanced budget of NP on a daily basis. The inclusion of the reaction of phenoxy radicals (C6H5O) with NO discussed in Sect. 3.2.2 would mainly affect the NP budget at midday, with smaller production and loss in this period.

The different diurnal variations in production and loss rates of NP explain the measured diurnal profile of NP concentrations shown in Fig. 3. The increase in loss rates from photolysis result in the quick decline of NP concentrations in the morning. The formation of NP from NO3 oxidation of phenol in the evening exceeds the destruction of NP, which accounts for the enhancement of NP in this period. The formation and loss rates of NP are comparable in the afternoon and relatively constant concentrations of NP were observed.

A previous study showed that photolysis of nitrated phenols contributes to HONO formation (Bejan et al., 2006). If we assume photolysis of nitrated phenols at rates of 1.4 % × J(NO2) yields HONO at a 100 % yield (upper limit), photolysis of NP, MNP, and DMNP together accounted for a formation rate of HONO of 1.5 ± 1.9 ppt h-1 around noontime (09:00–15:00) during UBWOS 2014. This photolysis source would increase the steady state concentrations of HONO by 0.5 ppt in early morning (07:00–08:30) and 0.2 ppt during the noontime period (09:00–15:00), which are only small fractions of measured HONO concentrations (50–100 ppt) during UBWOS 2014 (Edwards et al., 2014).