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The field campaign was conducted at the Xianghe Atmospheric Observatory (39.798°N, 116.958°E; 35 m above sea level) during the summer of 2018. Xianghe is a typical suburban site, about 50 km, 75 km, and 35 km away from Beijing, Tianjin, and Langfang in Hebei province, respectively. The site is surrounded by agricultural land and residential areas. The downtown center (population of about 30 000) is about 4 km east of the site.Trace gases (including O3, NOx, and CO) were measured by commercial instruments from Thermo Fisher Scientific, USA. The instruments were located on the roof of a single-story building. O3, NOx, and CO were continuously measured using the O3 analyzer (Model 49i), the NO-NO2-NOx chemiluminescence analyzer (Model 42i), and the CO analyzer (Model 48i), respectively. The precision and accuracy, operation and maintenance, and calibration methods for these instruments have previously been described in detail (Ji et al., 2014). Ambient VOC samples were analyzed continuously using a gas chromatography (GC) instrument (7820A, Agilent Technologies, Santa Clara, CA, USA) equipped with a mass spectrometer (MS) and a flame ionization detector (FID) (5977E, Agilent Technology, Santa Clara, CA, USA) with a time resolution of 1 h. Detailed description of the GC-MS/FID analysis method can be found in Wang et al. (2014). Dual columns and detectors were applied for the simultaneous analysis of C2?C12 hydrocarbons. The VOCs measurements include C2?C12 alkanes, C2?C6 alkenes, and C6?C10 aromatics. HONO was measured using a custom-made HONO analyzer, which was described in detail by Hou et al. (2016). Briefly, the principle of a HONO analyzer is similar to a long path absorption photometer (LOPAP) (Kleffmann et al., 2002). Information about detection limit and data accuracy are presented in Table S1 in the electronic supplementary material (ESM). Further details about the instruments including their operation and calibration procedures are available in the supplemental material.
The photolysis frequencies (JO1D, JNO2, JHONO, JH2O2, JHCHO, and JNO3) were measured using a PFS-100 spectroradiometer (Focused Photonics Inc., Hangzhou, China), which was described in detail by Zhao et al. (2021). The mixing layer height was observed by ceilometer (CL31, Vaisala, Finland), described in detail by Tang et al. (2016). Other meteorological parameters, such as the ambient temperature, pressure, and relative humidity were simultaneously measured at the Xianghe Atmospheric Observatory. Measurement results from 1?23 July, the period during the experiment when the photochemical pollution was the most severe, are presented in this paper. The time series of meteorological parameters are shown in Fig. S1 in the ESM.
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2.2. Chemical box model
A box model was used to explore the radical budget and O3 photochemical formation and loss. The model is built on the NCAR Master Mechanism (Madronich and Calvert, 1990; Ma et al., 2002, 2012), which is an explicit gas phase chemical mechanism and calculates the local photochemical equilibrium with a time scale of several minutes. In addition, heterogeneous reactions of trace gases and radicals on aerosol surfaces were also incorporated in the model (see section 2.2 of Ma et al., 2012). Meanwhile, dry deposition and entrainment losses were also included in the model to account for the physical loss processes. The model was constrained by the concentrations of measured trace gases, including inorganic species (H2O, NO, NO2, O3, HONO, and CO) and VOCs. The observed individual VOC species (Table S2 in the ESM) were applied to the model simulations in the same way as used by Ma et al. (2012). Measurements of photolysis frequencies, mixing layer height, and meteorological parameters were also used to constrain the model simulations.The measured data were averaged or interpolated with a time resolution of 1 hour for the model constraints. Simulations were performed for the time period from 1?23 July starting at 0000 LST (LST = UTC + 8), with a five-day pre-run in advance to let the unconstrained compounds to reach steady state, and then the results after that were used for analyses. The model calculates radical concentrations and chemical reaction rates, which can be used to further quantify radical budget and O3 photochemical production. The uncertainty of model calculation consists of uncertainty of the measurements used to constrain the model and uncertainty of the kinetic reaction rate. OVOCs concentrations were simulated by the model. The mean observed concentration of HCHO was 1.2 ± 0.9 ppbv for the period from Nov 2017 to Jan 2018 at Xianghe (Tang et al., 2019) and 4.4 ± 1.6 ppbv in July 2018 (X. R. LI, personal communication). The mean simulated HCHO concentrations in our study was 3.7 ± 1.3 ppbv, comparable to the other observed results at the same site.
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3.1. Observed O3 and precursor analysis
Figure 1 presents the mean diurnal variations of measured NOx, CO, HONO, AVOC (anthropogenic VOC), isoprene, O3, and Ox (O3+NO2). The primary anthropogenic pollutants including NOx, CO, and AVOC have similar diurnal variations and all reach a maximum in the early morning and a minimum in the afternoon. The maximum in the morning is related to gasoline and diesel vehicle exhaust (Tang et al., 2019) during rush hour coinciding with a shallow planetary boundary layer (PBL). In the afternoon, the pollutants decrease to minimum due to strong dilution with the development of the PBL. During the nighttime, the pollutants tend to accumulate when the PBL decreases. HONO has a similar variation pattern as NO2. Heterogeneous reactions of NO2 are expected to be the most important source of HONO (Liu et al., 2021) and a good correlation between HONO and NO2 during different field studies has been reported by Elshorbany et al. (2012). In this study, the averaged daytime HONO concentration is about 0.9 ppbv, comparable to those observed in Beijing (Lu et al., 2010) and Hong Kong (Xue et al., 2016), and higher than observations reported in New York (Ren et al., 2003) and Birmingham (Emmerson et al., 2005b). Isoprene emissions include both biogenic and anthropogenic sources. Biogenic emissions have a good correlation with temperature. Different to the diurnal variation of AVOC, the diurnal maximum of isoprene occurrs in the afternoon (1500 LST), indicating that isoprene is mostly from biogenic rather than anthropogenic emissions at the Xianghe site.Figure1. Averaged diurnal variations of measured NOx, CO, HONO, AVOC, isoprene, O3, and Ox at the Xianghe site. The vertical bars show the hourly standard deviation.
O3 has a variation pattern that is typical for photochemical pollution with a maximum around 76 ppbv in the afternoon. The hourly maximum O3 is 136 ppbv, much higher than the Chinese National Air Quality Standard Grade II, indicating serious O3 pollution at the Xianghe site. During the daytime, with incoming solar radiation, the rapid chemical cycle between NO, NO2, and O3 converts some O3 to NO2. Therefore, total oxidant Ox, the sum of O3 and NO2, is used to indicate O3 pollution, especially in the urban and suburban areas where NO concentrations are high (Liu et al., 1987; Lu et al., 2010). The mean Ox diurnal profile shows a maximum value of 83 ppbv. Mean concentrations plus/minus standard deviations of O3, Ox, NO, NOx, CO, HONO, isoprene, and AVOC were 46.1 ± 28.8 ppbv, 57.2 ± 26.5 ppbv, 1.9 ± 1.8 ppbv, 13.0 ± 6.0 ppbv, 694.6 ± 478.1 ppbv, 1.0 ± 0.5 ppbv, 0.7 ± 0.9 ppbv, and 20.0 ± 11.0 ppbv, respectively.
From field campaign data, 56 VOC species including alkanes, alkenes, aromatics, and isoprene are quantitatively identified. The reactivity of individual VOC species is calculated using observed VOC concentration multiplied by its corresponding reaction rate constant with OH at 298 K (Atkinson and Arey, 2003). Figure 2 shows the percentage contributions of alkanes, alkenes, aromatics, and isoprene to measured total VOC concentration and calculated total VOC reactivity. The average mixing ratio and reactivity of total VOC at Xianghe are 20.7 ppbv and 4.3 s?1, respectively, comparable to the values observed at Yufa suburban site (39.514°N, 116.305°E) in Beijing in summer 2006 (Shao et al., 2009; Lu et al., 2010), and much lower than results (41.8 ppbv and 15.8 s?1) measured at the Shangdianzi (SDZ) regional background station (40.650°N, 117.117°E) for summertime of 2007 (Xu et al., 2011). The difference between Xianghe and SDZ could be caused by different sampling times (samples on each Tuesday at 0800?0830 LST and 1400?1430 LST were measured at SDZ, see section 2.2 of Xu et al., 2011). As shown in Fig. 2a, alkanes contribute 62.2% to the total VOC mixing ratio. The contributions of alkenes and aromatics are the same with the value of 17.3%, and isoprene only contributes 3.2%. According to Lu et al. (2010), the contributions of alkanes, alkenes, aromatics and isoprene to the total VOC mixing ratio at the Yufa site were 53%, 24%, 21%, and 2%, respectively, with higher contributions of alkenes and aromatics than results at Xianghe. With respect to the reactivity, however, isoprene accounts for 38.6% of the measured VOC reactivity, higher than that of alkenes, aromatics, and alkanes. The contributions of alkenes and aromatics groups are comparable, with a slightly different portion of 21.1% and 24.7%, respectively, and alkanes only account for 15.6%. The above results indicate the high reactivity of isoprene at this suburban site.
Figure2. Percentage contributions of alkane, alkene, aromatic, and isoprene to measured VOC concentration (a) and reactivity (b) at the Xianghe site.
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3.2. Modeled OH reactivity
The total OH reactivity (KOH), equivalent to the inverse of the OH lifetime, is defined as the pseudo-first-order rate coefficient of OH radical in ambient atmosphere. The KOH is calculated by the following equation (Lou et al., 2010; Mao et al., 2010):where [Xi] is the ambient concentration of individual reactive species (NOx, CO, VOCs, and OVOC, etc.),
Figure3. Averaged diurnal variations of the contributions from all measured species and model generated species (denoted as Others) (a). Percent contributions of all measured species and model generated species to the total OH reactivity (b).
Over the past two decades, direct measurements of KOH have been performed in different regions, such as New York (Ren et al., 2003), Mexico (Shirley et al., 2006), Paris (Dolgorouky et al., 2012), Guangzhou (Lou et al., 2010; Yang et al., 2017), and Beijing (Lu et al., 2013; Williams et al., 2016). According to the observed results from Guangzhou (Lou et al., 2010; Yang et al., 2017), the KOH values at a rural site, Backgarden (23.49°N, 113.03°E), in summer 2006 and a suburban site, Heshan (22.73°N, 112.93°E), in autumn 2014 were in the range of 20 to 50 s?1. The KOH was also measured at the Yufa site in summer 2006, with the average values falling in the range of 10?30 s?1 (Lu et al., 2013). At the rural Wangdu site (39.514°N, 116.305°E) in the NCP, the measured KOH ranged between 10?20 s?1 in summer 2014 (Fuchs et al., 2017). The calculated OH reactivity at the Xianghe site is comparable to that measured at Wangdu in the NCP and lower than those observed in Guangzhou.
Figure 3b shows the percentage contributions of different species to the total OH reactivity. The sum of CO and NOx accounts for 49.1% of total OH reactivity, with CO contributing 27.5% (4.1 s?1) and NOx contributing 21.6% (3.2 s?1), respectively. The AVOCs, including alkanes, alkenes, and aromatics, contribute 17.6% to the total OH reactivity. The isoprene reactivity accounts for 11.1%. Model calculated other secondary species (HCHO, acetaldehyde, acetone, etc.) account for the remaining 22.2%. Our results show that the sum of VOCs and secondary species contributes to 50% of the total OH reactivity.
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3.3. Simulated ROx radical concentrations
Measurements of ROx radicals in China are relatively rare. In this study, ROx radical concentrations are calculated using the NCAR-MM chemical box model, constrained by the observed hourly gas concentrations and physical parameters. Figure 4 presents the mean diurnal variations of OH, HO2, and RO2 radicals at the Xianghe site. Radical concentrations show typical diurnal variations with a maximum occurring at noon. The maximum concentrations of OH, HO2, and RO2 in the averaged diurnal cycle at Xianghe are 10.6 × 106, 5.5 × 108, and 3.7 × 108 molecules cm?3, respectively, comparable to those simulated at the Peking University campus (PKU) site in August 2007, with corresponding values of 9 × 106, 6.8 × 108, and 4.5 × 108 molecules cm?3 (Liu et al., 2012). According to the simulated hourly radical concentrations (Fig. S2 in the ESM), the daily maximums of OH, HO2, and RO2 at Xianghe have ranges of (4?17) × 106, (1?13) × 108, and (1?11) × 108 molecules cm?3, respectively. Observed daily maximum concentrations of OH and HO2 had ranges of (4?17) × 106 and (2?24) × 108 molecules cm?3 at the Yufa suburban site in August 2006 (Lu et al., 2013). Daily maximum OH, HO2, and RO2 concentrations were also observed with ranges of (5?15) × 106, (3?14) × 108 and (3?15) × 108 molecules cm?3, respectively, at the Wangdu rural site in the NCP in summer 2014 (Tan et al., 2017). In contrast, higher daily maximum values of (15?26) × 106 molecules cm?3 for OH and (3?25) × 108 molecules cm?3 for HO2 were observed at the Backgarden rural site in Guangzhou during July 2006 (Lu et al., 2012). The simulated ROx concentrations in this study are comparable to observed values at Wangdu (Tan et al., 2017) and much lower than those at Backgarden (Lu et al., 2012).Figure4. Averaged diurnal variations of OH, HO2, and RO2 radical concentration modeled for the Xianghe site. Black lines represent the calculated concentrations with all measured gases as model constraint, and the vertical bars show the hourly standard deviation; Blue lines represent the sensitivity results without the HONO constraint; Red lines represent the sensitivity results considering heterogeneous reactions of gases and radicals on aerosols.
Using the NCAR-MM chemical box model, HONO concentrations are calculated with the daytime average value being 0.08 ppbv, only about 10% of the measured result (0.9 ppbv). The large underestimation proportion of HONO in this study is consistent with previously reported results (Su et al., 2011; Tong et al., 2016; Liu et al., 2021), due to only considering homogeneous reactions of NO + OH and a lack of large sources such as heterogeneous reactions of NO2 in the current chemical models. In order to estimate the impact of the missing HONO source on the radical chemistry at Xianghe, we calculate the ROx concentrations without the HONO constraint. The sensitivity simulation results show that the maximum concentrations of OH, HO2, and RO2 decrease to 7.2 × 106, 3.8 × 108, and 2.6 × 108 molecules cm?3, respectively, as presented in Fig. 4. For daytime average (0600 to 1800 LST), the OH decreases by 41%. Decreasing OH leads to less active photochemistry and thus 38% and 37% decrease of HO2 and RO2 concentrations, respectively, in agreement with previous results (Su et al., 2011; Liu et al., 2012; Li et al., 2014; Tong et al., 2016). Therefore, the measured HONO data should be included to properly simulate the ROx chemistry.
The aerosol size distributions, a key parameter for the calculation of heterogeneous reaction rates, are not measured at Xianghe. Regardless of the uptake coefficients and aerosol particle size distributions, the heterogeneous reaction rates are ultimately determined by the calculated pseudo first-order rate coefficients. So, we adopt the pseudo first-order rate coefficients from our previous study, which were calculated with the particle size distributions observed at the Xin’an rural site, about 60 km east of Xianghe (Ma et al., 2012). According to Ma et al. (2012), the calculated pseudo first-order rate coefficient of HO2 was 0.025 s?1, which could represent an upper limit since the observed PM2.5 concentrations in that field campaign were more than twice those at Xianghe. Therefore, we use the scaling factor of 0.5 with the corresponding value 0.012 s?1 to represent the pseudo first-order rate coefficients of HO2 at Xianghe. The sensitivity simulations considering heterogeneous reactions of trace gases and radicals on aerosols show that the daytime average HO2 concentration drops by 17%, OH drops by 11%, and RO2 drops by 14%, which indicates that aerosol uptake of trace gases and radicals are not negligible and the measured aerosol size distributions are needed to accurately calculate heterogeneous reaction rates.
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3.4. ROx budget analysis based on model results
Figure 5 shows the average diurnal variation of primary sources and termination sinks of ROx. The maximum ROx primary production rate, P(ROx), is 6.9 ppbv h?1. HONO photolysis is the predominant source of ROx in the early morning and also a major source throughout the daytime. O3 photolysis followed by reaction with water vapor, together called the effective photolysis of O3, and photolysis of HCHO and other carbonyls are the other important ROx sources at midday. In contrast, alkene ozonolysis dominates the ROx source during nighttime. In the following, the daytime average (0600 to 1800 LST) will be the focus for the radical budget analysis. The photolysis of HONO and the effective photolysis of O3 contribute 41% and 20% to P(ROx), with average production rates of 1.6 ppbv h?1 and 0.8 ppbv h?1, respectively, which are also the predominant sources of OH radical, while other OH sources from photolysis of H2O2 and HNO3 are negligible in this study. The photolysis of HCHO and other OVOCs contributes 26% to P(ROx), with an average production rate of 1.0 ppbv h?1, among which HCHO photolysis produces HO2 (0.4 ppbv h?1) and other OVOCs photolysis produces HO2 (0.3 ppbv h?1) and RO2 (0.3 ppbv h?1). Alkene ozonolysis contributes 13%, with an average contribution of 0.5 ppbv h?1 (0.2 ppbv h?1 for OH, 0.2 ppbv h?1 for HO2, and 0.1 ppbv h?1 for RO2). Overall, the average daytime P(ROx) is 3.9 ppbv h?1, and photolysis reactions dominate 87% of the ROx sources.Figure5. Averaged diurnal variations of primary sources (a) and termination sinks (b) of ROx radicals derived from model calculations. The colored lines show the speciated ROx primary sources and termination sinks. o-OVOCs represent the other OVOC species excluding HCHO. OH + others denotes loss rates by OH with other species (e.g. HNO3, HNO2, and HNO4).
Primary ROx production depends on the intensity of solar radiation as well as NOx and VOCs levels. Therefore, partitioning of primary ROx sources is unique in different areas (Xue et al., 2016 and references therein). At Yufa, HCHO photolysis dominates the P(ROx) due to high concentration of HCHO (on average 10?15 ppbv at daytime, Lu et al., 2013). In Beijing, Hong Kong, and Mexico City, OVOC photolysis (excluding HCHO) is the dominant source because of high OVOC levels (Volkamer et al., 2010; Liu et al., 2012; Xue et al., 2016). In this study, HONO photolysis dominates the P(ROx) due to high HONO concentration, similar to New York city (Ren et al., 2003) and Wangdu (Tan et al., 2017). Sensitivity results without the HONO constraint show that the daytime average P(ROx) decreases by 55% from 3.9 to 1.7 ppbv h?1 (Fig. S3 in the ESM), highlighting the importance of measuring HONO for ROx budget analysis. In addition to HONO, other radical precursors including HCHO and OVOCs should be measured in future studies since the contributions of their photolysis to the ROx production are also important in some areas. Sensitivity results considering heterogeneous reactions of trace gases and radicals on aerosols show that there is close to no change in the strength and partition of P(ROx) (Fig. S4 in the ESM).
Due to the short lifetime of ROx radicals, the total ROx loss rate, L(ROx), is equal to the total ROx primary production rate, P(ROx), as shown in Fig. 5b. At the Xianghe site, the radical losses are dominanted by their reactions with NOx forming nitrogen containing compounds (LN), including HNO3, HONO, and PAN-type and RONO2 species, a typical feature of chemistry under high NOx concentrations. During daytime, the reaction of NO2 + OH producing HNO3 is the largest contributor to radical termination (1.6 ppbv h?1, 41%), followed by reactions of RO2 + NO2 and RO2 + NO, producing net PAN-type species (1.0 ppbv h?1, 26%) and RONO2 species (0.5 ppbv h?1, 13%), respectively. In comparison, the radical losses via HO2 + HO2/RO2 reactions forming peroxides (LH) are much lower (0.3 ppbv h?1, 8%). Contribution of PAN-type species to radical loss is important in urban and suburban areas (Whalley et al., 2018; Tan et al., 2019). According to results found by Whalley et al. (2018), the formation of PAN-type species contributed 30% to the total radical loss in downtown London, similar to the result in this study. Taking into account heterogeneous reactions, aerosol uptake of HO2 contributes 11% to L(ROx) for the daytime average (Fig. S4).
The ratio of LN to L(ROx) can be used to evaluate the O3 production sensitivity, as suggested by Kleinman et al. (1997). The threshold of the LN/L(ROx) ratio is 0.5. When LN/L(ROx) is greater than 0.5, LN dominates the radical loss, indicating the O3 production is limited by the VOC abundance. On the other hand, when LN/L(ROx) is less than 0.5, the radical loss is dominated by LH and the O3 production is controlled by NOx. The radical budget analysis shows that LN contributes about 90% to L(ROx) at Xianghe, which indicates that the O3 production is in the VOC-sensitive regime.
Figure 6 shows the conversion rates between OH, HO2, and RO2 radicals. As shown in Fig. 6a, the conversion of OH to HO2 is mainly caused by reactions of CO and HCHO with OH. The reactions of speciated VOCs and OVOCs with OH lead to the RO2 peroxy radicals (Fig. 6b). The conversion of HO2 from RO2 is dominated by reactions of isoprene-derived radical (ISOP) and methyl peroxy radical with NO (Fig. 6c). The recycling of OH from HO2 is mainly generated by the reaction of HO2 with NO (Fig. 6d). Evidently, the recycling processes between OH, HO2, and RO2 are fast at the Xianghe site. For the daytime average, oxidation production rates of HO2 and RO2 by OH are 5.6 and 7.2 ppbv h?1, respectively. The reactions of RO2 + NO and HO2 + NO further recycle HO2 and OH, with the corresponding production rates of 6.5 ppbv h?1 and 12.5 ppbv h?1, respectively. In polluted areas under the coexistence of abundant VOCs and NOx, efficient radical recycling can amplify the effect of the initially produced radicals (Ma et al., 2012; Xue et al., 2016).
Figure6. Averaged diurnal variations of radical conversion rates of OH→HO2 (a), OH→RO2 (b), RO2→HO2 (c), and HO2→OH (d). (a): OH + others denotes conversion rates by the reaction of OH with other species (e.g. H2, O3, and C6H6).
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3.5. O3 photochemical production and loss
The photolysis of NO2 produces O3 and NO. NO titrates O3 to regenerate NO2. These reactions represent a null cycle for O3 production in sunlight because there is no change in O3 abundance at steady state. The removal of NO without consuming O3 leads to net O3 production. In the photochemical system, HO2 and RO2 radicals are the major NO consumers and O3 is produced via the reactions of NO with HO2 and RO2 radicals. On the other hand, O3 chemical loss occurs via O3 photolysis (production of O1D, followed by reaction with water vapor) and reactions with OH, HO2, and alkenes. The reaction of NO2 with OH should also be considered as O3 chemical loss because the conversion of NO2 to HNO3 terminates the catalytic cycle between NO and NO2. As in previous studies (Liu et al., 1987; Lu et al., 2010; Xue et al., 2013), the total oxidant (Ox = O3 + NO2) is used to calculate instantaneous O3 photochemical formation rate F(O3) and loss rate L(O3), as denoted in Eqs. (2) and (3),where [OH], [HO2], [RO2], [O1D], [NO], [O3], and [Alkene] are concentrations, and
Figure7. Averaged diurnal variations of O3 production (a) and loss rate (b) derived from model calculations. The left panel represents the speciated O3 formation rate from different RO2 species. The right panel represents the speciated O3 destruction rate.
Using an observation-based model, Lu et al (2010) calculated the hourly F(O3), varying from zero to 120 and 50 ppbv h?1 at PKU and Yufa sites, respectively, during summer 2006 in Beijing. Liu et al (2012) simulated the average diurnal maximum F(O3) of 60 ppbv h?1 at PKU during summer 2007. Tan et al (2018) reported the average diurnal maximum F(O3) was 17 ppbv h?1 at Wangdu during summer 2014. The maximum F(O3) at Xianghe lies between the simulated results at rural site Wangdu and urban site PKU. The ROx radical concentrations at Xianghe are comparable to Wangdu and PKU as mentioned in section 3.3, while the corresponding noontime NO concentrations are 2.3 ppbv, 0.16 ppbv, and 5.0 ppbv at Xianghe, Wangdu, and PKU, respectively, resulting in the difference in the F(O3) which depends on both ROx and NO as shown in Eq. 2.
The average diurnal maximum L(O3) is 4.3 ppbv h?1, appearing at 1100 LST. The reaction of NO2 + OH is the main process leading to O3 chemical loss, with a contribution of 63% toward the daytime average. The effective photolysis of O3 and alkene ozonolysis contribute to 15% and 12%, respectively. By integrating the difference between the photochemical formation and loss rates over the whole day, the P(O3) approaches 237 ppbv d?1, indicating that the photochemical production of O3 is active at the suburban site in the NCP region.
The sensitivity results without the HONO constraint show that average diurnal maximum F(O3) decreases from 32.9 to 22.6 ppbv h?1 (Fig. S5 in the ESM). The daytime average F(O3) decreases by 42%, consistent with the results reported by Liu et al (2012). Therefore, it is necessary to constrain the photochemical models with the measured HONO data. The sensitivity results considering heterogeneous reactions show that average diurnal maximum F(O3) decreases to 28.4 ppbv h?1 (Fig. S5 in the ESM). The daytime average F(O3) decreases by 14%, about one third of the results without the HONO constraint, indicating that aerosol size distributions should be measured to accurately calculate heterogeneous reaction rates and O3 photochemical formation.
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3.6. Chemical regimes of O3 production
The O3-NOx-VOCs sensitivity is investigated using the Empirical Kinetic Modelling Approach (EKMA). The base case refers to the averaged conditions over the whole campaign during the daytime. The averaged chemical and physical parameters are summarized in Table S2 in the ESM. By increasing or decreasing the concentrations of NOx and AVOCs up to a factor of 3 with 30 equal-distance steps and fixing all other parameters as in the base case, the corresponding O3 production rates are calculated and used to generate an isopleth plot illustrating the P(O3) on the concentration of NOx and AVOCs. The change of VOCs concentrations only applies to AVOCs to investigate the impact of anthropogenic emission changes on P(O3).Figure 8 shows the response of P(O3) to precursors of NOx and VOCs at the Xianghe site. The O3 chemical regimes between VOC-sensitive and NOx-sensitive are separated by the black line, also called the ridge line. The ridge line connects the turning points of the P(O3) isopleths and represents the optimum initial NOx and VOC concentrations for O3 production. Above the ridge line, a reduction in initial NOx results in an increase in the P(O3), whereas a reduction in initial VOC results in a decrease in the P(O3), and this condition is considered VOC-sensitive. Below the ridge line, a reduction in initial VOC has only a very small effect on the P(O3), whereas P(O3) is reduced by reduction in the initial NOx, and this condition is considered NOx-sensitive. The black filled square in the isopleth diagrams represents the daytime averaged NOx and AVOCs concentrations for the time period of 1?23 July, and blue circles stand for the daytime averaged NOx and AVOCs concentrations for each day. The filled square and most of the circles are above the ridge line, indicating that the O3 production is mainly controlled by VOCs. This conclusion is consistent with the result from radical loss analysis in section 3.4. Compared to Xianghe, O3 formation at Wangdu was NOx-sensitive due to lower NOx levels during daytime (Tan et al., 2018). This radical loss process was further verified by the fact that the radical loss was dominated by HO2 + HO2/RO2 reactions at Wangdu, representing a NOx-sensitive regime (Tan et al., 2017). When the NOx concentration is larger than 10 ppbv, the calculated P(O3) decreases with increasing NOx, demonstrating that O3 production enters the NOx titration regime.
Figure8. Isopleth diagrams of the net O3 production rate [P(O3), units: ppb h?1] as functions of the NOx and AVOCs derived from an empirical kinetic modeling approach. The black filled squares represent the daytime averaged NOx and AVOCs concentrations measured for the time period of 1?23 July. The blue circles represent daytime averaged AVOCs and NOx concentrations measured for each day. The left panel represents the EKMA diagram with all measured gases as model constraints; the middle panel represents the EKMA diagram without the HONO constraint; the right panel represents the EKMA diagram considering heterogeneous reactions of gases and radicals on aerosols.
The impact of HONO and aerosol uptake of trace gases and radicals on P(O3) chemical regimes is also investigated as part of this study. As shown in Fig. 8, without the HONO constraint, the ridge moves down and all circles are above the ridge line, which means that the O3 formation is more VOC-sensitive. The aerosol uptake of trace gases and radicals makes the ridge move up as shown in Fig. 8, whereas the filled square and most of the circles are still above the ridge line, which means that the O3 production is unchanged but has a tendency shifting toward NOx-sensitive. Therefore, VOCs control should be the optimal way to mitigate the O3 pollution at Xianghe.