domain: chim sde

text:
Yunfeng Li

Xuezhong Wang

Zhenhai Wu

Ling Li

Chuhan Wang

Hong Li
email: lihong@craes.org.cn

Xin Zhang

Yingnan Zhang

Junling Li

Rui Gao
email: gaorui@craes.org.cn

Likun Xue

Abdelwahid Mellouki

Yangang Ren

Qingzhu Zhang

Atmospheric nitrous acid (HONO) in an alternate process of haze 1 pollution and ozone pollution in urban Beijing in summertime: 2 Variations, sources and contribution to atmospheric photochemistry 3

Keywords: Nitrous acid (HONO), Haze pollution period, Ozone pollution period, 62 Heterogeneous conversion, unknown daytime source, Observation-Based Model, 63 1

come

Atmospheric nitrous acid (HONO) in an alternate process of haze pollution and ozone pollution in urban

Beijing in summertime: Variations, sources and contribution to atmospheric photochemistry

In the past 10 years, some studies have been carried out on the ambient levels and 112 formation mechanisms of HONO in China (Hendrick et al., 2014;Hou et al., 2016;Jia 113 et al., 2020;[START_REF] Liu | The promotion effect of nitrous acid on aerosol formation in 729 wintertime in Beijing: the possible contribution of traffic-related emissions[END_REF][START_REF] Liu | Evidence of aerosols as a media for rapid daytime HONO 732 production over China[END_REF][START_REF] Meng | High-resolution vertical distribution and sources of HONO and 738 NO2 in the nocturnal boundary layer in urban Beijing, China[END_REF]Spataro et al., 2013; 114 Wang et al., 2017;Yang et al., 2014;Zhang et al., 2019a;Zhang et al., 2019b;Zhang et 115 al., 2020). However, most studies focused on the characteristic and source of HONO 116 during the severe haze period, the HONO observations over the ozone pollution period 117 were limited in China. In this study, we performed the high time-resolved observation 118 of HONO in an urban site of Beijing in summer of 2019. In the following sections, we 119 first compared the atmospheric levels and variations of HONO and related species 120 during a haze pollution period and an ozone pollution period. Then, we explored several 121 sources of HONO in the two typical cases. Finally, the impacts of HONO on 122 atmospheric oxidative capacity (AOC), primary OH radical production, and O3 123 production rates were assessed. HONO to OH and O3 production (Jiang et al., 2020;Xue et al., 2016;196 Xue et al., 2014;Xue et al., 2013;Yang et al., 2018b;Yang et al., 2017). The MCM 197 described the detailed degradation reactions of 143 primary VOCs and the latest 198 inorganic reactions (Jenkin et al., 2003;Saunders et al., 2003). The heterogeneous 199 chemistry processes, dry deposition and dilution mixing within the boundary layer are 200 also included in the model. A more detailed description of this model configuration has 201 been provided elsewhere (Xue et al., 2016;Xue et al., 2014;Xue et al., 2013). The HONO to OH production (Jiang et al., 2020;Yang et al., 2018b).

208

Here our emphasis is placed on the computation of AOC, OH production rates, 209 and O3 budget. AOC is defined here as the sum of oxidation rates of VOCs and CO by 210 the dominant atmospheric oxidants including OH, O3, and NO3 (Xue et al., 2016). The 211 major primary sources of OH production include photolysis of O3, HONO, and OVOCs 212 as well as reactions of O3+VOCs (Jiang et al., 2020;Xue et al., 2016). The ozone 213 formation rates refer to the formation rates of the total oxidant (Ox=O3+NO2) instead 214 of O3 alone (Xue et al., 2014;Xue et al., 2013) for the Beijing summer period (Spataro et al., 2013;Yu et al., 2009a).

235

As OH concentration is not available in our study, the daytime OH concentration is within the range of those measured in Beijing [START_REF] Lu | Nighttime observation and chemistry of HOx in the Pearl River 734 Delta and Beijing in summer 2006[END_REF]Tan et al., 2018). The

258

The average hourly levels of NO, NO2, and CO were 2.7±1.9 ppb (1.0-14.2 ppb), 15.5±8.8 ppb (1.7-54.5 ppb), and 1.20±0.32 ppm (0.47-2.57 ppm), respectively. The 260 levels of PM2.5 and O3 ranged from 5.5 to 125.1 μg/m 3 and from 1.0 to 157.7 ppb, and Grade II of NAAQS (75 ppb, corresponding to 160 μg/m 3 ). In this study, a haze 273 pollution period from 17 to 21 June (Period I, the blue area in Fig. 1) and an ozone 274 pollution period from 22 to 26 June (Period II, the orange area in Fig. 1) were selected 275 as two typical case studies. The diurnal profiles of HONO, NO2, O3, and HONO/NO2 ratio were illustrated in et al., 2001). A criterion of NO/NOx > 0.7 was often adopted to select the 335 fresh air masses. However, in our study the relatively low NO/NOx ratio (from 0.09 to 336 0.53) suggested that the air mass had become aged before arriving at the sampling site.

337

The HONO/NOx ratios of 0.0065 (Spataro et al., 2013;Tong et al., 2015) and 0.008 et al., 2003;Kurtenbach et al., 2001), the ratios ranging from 0.3% to 0.8% 341 in fresh vehicle exhaust had been reported. Thus, the values of 0.003, 0.0065 and 0.008 342 were adopted to estimate the contribution from traffic emission. The directly emitted

343

HONO concentration can be calculated by Eq. ( 2) below:

NO+OH homogeneous formation 356

The reaction of NO with OH was also anticipated as a dominant homogeneous 357 production of HONO in nighttime [START_REF] Li | Exploring the atmospheric chemistry of nitrous acid (HONO) at a 717 rural site in Southern China[END_REF][START_REF] Lu | Nighttime observation and chemistry of HOx in the Pearl River 734 Delta and Beijing in summer 2006[END_REF]

P net NO+OH = kNO+OH[OH][NO] -kHONO+OH[HONO][OH]

(3)

363

where the rate constants kNO+OH and kHONO+OH are 7.2 × 10 -12 and 5.0 × 10 -12 cm 3 364 molecule -1 s -1 for reactions R1 and R2 at 298 K, respectively [START_REF] Li | Exploring the atmospheric chemistry of nitrous acid (HONO) at a 717 rural site in Southern China[END_REF]; [NO] and

365

[HONO] represents concentrations of NO and HONO, respectively. Since the rate 366 constants of R1 and R2 are similar, the P net NO+OH is determined by NO and HONO 367 concentrations. The nighttime OH concentration with 5 × 10 5 molecules cm -3 was 10 5 molecules cm -3 was assumed to the nighttime OH concentration of Beijing in this 370 study (Cui et al., 2018;Huang et al., 2017;Spataro et al., 2013;Tong et al., 2015).

Heterogeneous conversion of NO2

390 Numerous field measurements in urban sites reported that heterogeneous 391 conversion reaction of NO2 on wet surfaces could be an important HONO source at 392 night in the atmosphere (Sorgel et al., 2011;Spataro et al., 2013;Su et al., 2008a). The

397

The aerosol surface is considered as an important media for the heterogeneous 398 conversions of NO2 in several studies (Huang et al., 2017;[START_REF] Li | Exploring the atmospheric chemistry of nitrous acid (HONO) at a 717 rural site in Southern China[END_REF]Liu et al., 399 2014). As aerosol surface density is not measured, PM2.5 concentrations are used as

419

Additionally, the water uptake processes could occur on aerosol/ground surfaces. Many 420 studies have reported that the water droplets act as a role in the HONO sink when the 421 RH exceeds 96% [START_REF] Acker | Concentrations of nitrous acid, nitric acid, nitrite and nitrate in 650 the gas and aerosol phase at a site in the emission zone during ESCOMPTE 2001 651 experiment[END_REF]He et al., 2006;Yu et al., 2009b;Zhou et al., 2007).

422

Since the maximum RH is 92% in this study, the process of HONO uptake by water is 423 not considered.

424

The conversion frequency (CHONO) is widely used to estimate the conversion rate 425 from NO2. It was assumed that all measured HONO came from heterogeneous 426 conversions of NO2 (Hou et al., 2016), and the CHONO value could be calculated by Eqs.

427

(4) and ( 5) (Su et al. 2008a;Wang et al. 2017a;Zhang et al. 2019b). To eliminate the 428 influence of direct vehicle emission, the HONO concentration was corrected by Eq. ( 6)

429
and was denoted as [HONO]corr.

430

𝐶 𝐻𝑂𝑁𝑂 𝑋 = 2( [𝐻𝑂𝑁𝑂𝑐𝑜𝑟𝑟] 𝑡2 [𝑋] 𝑡2 ×[𝑋 ̅] - [𝐻𝑂𝑁𝑂𝑐𝑜𝑟𝑟] 𝑡1 [𝑋] 𝑡1 ×[𝑋 ̅] ) (𝑡 2 -𝑡 1 )( [𝑁𝑂 2 ] 𝑡2 [𝑋] 𝑡2 ×[𝑋 ̅] + [𝑁𝑂 2 ] 𝑡1 [𝑋] 𝑡1 ×[𝑋 ̅] ) 431 = 2( [𝐻𝑂𝑁𝑂𝑐𝑜𝑟𝑟] 𝑡2 [𝑋] 𝑡2 - [𝐻𝑂𝑁𝑂𝑐𝑜𝑟𝑟] 𝑡1 [𝑋] 𝑡1 ) (𝑡 2 -𝑡 1 )( [𝑁𝑂 2 ] 𝑡2 [𝑋] 𝑡2 + [𝑁𝑂 2 ] 𝑡1 [𝑋] 𝑡1 ) (4) 432 𝐶 𝐻𝑂𝑁𝑂 = 1 3 (𝐶 𝐻𝑂𝑁𝑂 0 + 𝐶 𝐻𝑂𝑁𝑂 𝐶𝑂 + 𝐶 𝐻𝑂𝑁𝑂 𝑁𝑂2 )
(5) Several studies reported that the gas phase reaction of OH and NO was not 462 sufficient to explain the HONO concentration in the daytime. An unknown daytime

463

HONO source needs to be identified. Based on the source and sink pathways of HONO,

464

the net daytime HONO formation rate can be calculated by a detailed budget Eq. ( 7)-

465

(9) (Jia et al., 2020;Sorgel et al., 2011). 3.69 × 10 -4 to 5.13 × 10 -4 s -1 during the daytime (10:00 LT-15:00 LT). According to 476 previous studies (Hou et al., 2016;[START_REF] Li | Impacts of HONO sources on the air quality in Beijing, Tianjin and 719 Hebei Province of China[END_REF], the deposition velocity Vd and the 477 daytime mixing height H in Beijing were assumed as 1.6 cm s -1 and 500 m, respectively.

478

Table 2 summarized the daytime HONO production rate from unknown source at [START_REF] Li | Oxidizing capacity of the rural atmosphere in Hong Kong, 721 Southern China[END_REF]Jia et al., 2020;Li et al., 2018b;Wang et al., 2017). the previous study (Li et al., 2018a). When HONO concentration was not constrained, 558 the contribution from HONO photolysis was much underestimated reaching up to 89% 559 (0.10 ppb h -1 ).

560

To accurately evaluate the impacts of HONO on in-situ photochemical O3

  was conducted from 13 June to 4 July 2019. The 127 observation site is on the roof (about 8 m above ground) of the Laboratory of 128 Atmospheric Photochemical Simulation of Chinese Research Academy of 129 Environmental Sciences (CRAES, 40.04° N, 116.42° E), in the north of Chaoyang 130 District of Beijing (Fig. S1). Chaoyang District is one of the six main urban districts 131 (Haidian, Chaoyang, Dongcheng, Xicheng, Shijingshan and Fengtai) of Beijing and is 132 located at the eastern area of Beijing. The CRAES site is to the north (about 2 km) of 133 the North Fifth Ring Road with high level of heavy traffic. It is located in a residential 134 and commercial area, without obvious industrial pollution sources nearby (Cheng et al., 135 2018; Zhang et al., 2017). Thus, CRAES site could be considered as an urban site that 136 can represent the urban environment of Beijing.

  photo-metrically. The LOPAP is designed as a two-channel system to minimize

  Based Model (OBM) incorporating the nearly explicit chemical 193 mechanism, Master Chemical Mechanisms (MCM, v3.3.1), has been widely employed 194 in previous studies to dissect the atmospheric oxidative capacity (AOC) and the 195 contributions of

202

  model was constrained by the measured concentrations of O3, SO2, CO, NO, NO2, 203 HONO, VOCs, carbonyls, JNO2, T, P and RH at a time resolution of 5 min. For VOCs 204 and carbonyl compounds, which were not measured in real-time, the time-dependent 205 data were linearly interpolated into 5 min. Such approximation may lead to some 206 uncertainties but should not significantly affect the estimation of the contribution of 207

236

  can be estimated by using the empirical power-law Eq. (1) (Rohrer and Berresheim, 4.2 × 10 6 cm -3 , b = 1.0, c = 0.6 × 10 6 cm -3 ) 240Where [OH] represents the OH concentration, JO1D is the photolysis frequencies 241 of O 1 D modelled by the TUV model. The daytime OH concentration ranged from 6.5 242 × 10 5 to 9.2 × 10 6 molecule cm -3 with the mean value of 4.4 × 10 6 molecule cm -3 , which 243

244

  correlations between the daytime calculated OH concentrations and the modelled 245 concentrations by the OBM from 22 to 26 June were displayed in Fig. S2. The good 246 correlations (R 2 =0.88) showed the reliability of the OH concentrations calculated by 247 the empirical power-law equation. of HONO, O3, CO, NO, NO2, PM2.5 and meteorological parameters 252 from 13 June to 4 July are displayed in Fig. 1. During the observation period, the 253 temperature ranged from 18 to 38℃, with average values of 28±4℃; the RH ranged 254 from 16% to 92%, with average values of 52±18%. The wind direction during the 255 observation period was dominated by the south wind and the average WS was 256 2.73±1.65 m/s. Occasionally on 29 and 30 June, the dominant wind direction was north, 257 and the hourly WS exceeded 7 m/s.

  295

Fig. 1

 1 Fig. 1 Time series of HONO, O3, CO, NO, NO2, PM2.5, and meteorological parameters from 13 June to 4 July 2019. Blue and orange areas are

  303

Fig. 2 .Fig. 2

 22 Fig. 2. The obvious diurnal variation of HONO resembled those at other urban sites in

338(

  Jia et al., 2020;[START_REF] Meng | High-resolution vertical distribution and sources of HONO and 738 NO2 in the nocturnal boundary layer in urban Beijing, China[END_REF] Zhang et al., 2020) have been chosen as the emission 339 urban area of Beijing in previous studies. Based on the tunnel studies 340 (Kleffmann

  HONO]emis represents the HONO levels from the traffic emission, [NOx] 346 represents the NOx concentration, and F represents the emission factor. To avoid the 347 influence of HONO photolysis, only the nocturnal data from 20:00 LT to the next 06:00 348 LT were considered. The statistical results of the ratios of [HONO]emis/[HONO] were 349 shown in Fig. S3. The average calculated [HONO]emis levels contributed 15%, 31%, 350 and 40% to the whole measured nocturnal HONO levels at the emission factor of 0.003, 351 0.0065 and 0.008, respectively. In previous studies, the contributions from vehicle 352 emission ranged between 20.59% and 52% in urban areas of Beijing (Spataro et al., 353 2013; Tong et al., 2015; Zhang et al., 2019b). Therefore, direct emissions from vehicles 354 could be an important HONO source in Beijing.

  355

Fig. 3

 3 Fig. 3 Average nocturnal variations of P netNO+OH during the whole observation period,

  389

393

  NO2 conversion efficiency mainly depends on the surface properties. The positive 394 correlation between HONO and NO2 (R 2 =0.31, shown in Fig.S4) was also found in 395 this study, implying that NO2 might be a precursor ofHONO production (Huang et al., 396 2017; Qin et al., 2009).

400

  surrogates to identify the influences of aerosols on HONO formation. Fig.4(a)showed 401 the correlation of HONO/NO2 with PM2.5 concentrations at night, and the positive 402 correlation revealed the heterogeneous conversions of NO2 on aerosol surfaces.403Additionally, it can be seen that the mean HONO/NO2 value increased gradually with 404 the increasing PM2.5 concentrations. The correlations between HONO/NO2 and PM2.5 405 concentrations at night during Period I and Period II were displayed in Fig.S5. A higher 406 correlation was found in Period I, indicating the possibility of a higher conversion 407 frequency on aerosol surfaces in the haze pollution period than in the clean period.408The effects of RH on the heterogeneous formation of HONO are further investigated.Stutz et al. (2004) asserted that the absorbed water on the surface 410 participated in the heterogeneous conversion of NO2 to HONO. The influence of RH 411 on heterogeneous HONO formation at night was illustrated in Fig.4(b). An increase of 412 HONO/NO2 along with the increasing RH was found when the RH was less than 60%.413Further increase (>60%) of RH led to a decrease of the HONO/NO2 value. This 414 phenomenon can be associated with the number of water layers formed on aerosol 415 surfaces. The excess water on the surface is a limiting factor for the NO2 conversion.416When the RH is larger than 60% in this study, the heterogeneous conversion efficiency 417 seems to be depended negatively on RH. The similar phenomenon was also observed 418 byYu et al. (2009b) in Nepal,[START_REF] Li | Exploring the atmospheric chemistry of nitrous acid (HONO) at a 717 rural site in Southern China[END_REF] andWang et al. (2013) in China.

  ]t, [NO2]t and [X]t represents the concentrations of the HONOcorr, NO2 435 and reference gases at the time t, respectively. [X ̅ ] is the averaged reference gases concentration during the time interval of t1 and t2. 𝐶 𝐻𝑂𝑁𝑂 𝑋 is the conversion frequency 437 scaled with reference gases X (CO and NO2) and 𝐶 𝐻𝑂𝑁𝑂 0 is the conversion frequency 438 which is not scaled. The emission factor is 0.0065. The heterogeneous conversion rates 439 of NO2 were 0.0036 h -1 , 0.0075 h -1 , and 0.0028 h -1 on average during the whole 440 observation period, Period I and Period II, respectively. The rates were comparable to 441 the values of 0.0039 h -1 in winter of Beijing in 2014 (Hou et al., 2016), 0.0058 h -1 in 442 winter of 2016 (Zhang et al., 2019b), and 0.0078 h -1 in autumn of 2018 (Jia et al., 2020), 443 but lower than the values obtained in other studies of Beijing, such as 0.010 h -1 in 444 summer of 2016 (Wang et al., 2017) and 0.016 h -1 in spring of 2018 (Zhang et al., 2020). 445 Based on the study of Su et al. (2008a), the conversion rates could be affected by several 446 factors including surface features, aerosol concentrations, and the environments. The 447 discrepancies may be related to the different types of surface and aerosol concentrations 448 in different environments. A heterogeneous production rate of HONO at night (CHONO 449 × [NO2]) of 0.06 ppb h -1 was derived during the whole observation period, which is 450 higher than the rate from homogeneous reaction of NO with OH. This showed that the 451 heterogeneous conversion from NO2 was more important for HONO formation at night 452 during the observation period.

Fig. 4

 4 Fig. 4 The correlations between HONOcorr/NO2 and PM2.5 concentration (a) and RH

  photolysis frequency of HONO obtained by the TUV model simulation, varying from

479

  different sites. The calculated average Punknown was 0.59 ppb h -1 (ranging from 0.02 to 480 1.83 ppb h -1 ) in our study, which was lower than those values in most urban sites, but 481 comparable to the values (0.40 and 0.50 ppb h -1 ) in sites of Paris and Germany.482Interestingly, a larger Punknown (0.80 ppb h -1 ) was found during Period II than the value 483 (0.73 ppb h -1 ) calculated during Period I. The diurnal contributions of production and 484 loss pathways to the HONO budget during the whole observation period, Period I, and 485 Period II were illustrated in Fig. 5, Fig. S6(a), and Fig. S6(b), respectively. The Punknown 486 values are still about 5-6 times greater than the POH+NO values, suggesting that Punknown 487 is the dominant daytime HONO source during the observation period. As the largest production process, the unknown source could account for up to 87% of the HONO 489 production. The proportion could even reach up to 92% during Period II. 490 491

Fig. 5

 5 Fig. 5 Diurnal production and loss rates for the daytime HONO budget

  photo-enhanced NO2 conversion on unknown HONO sources, the relationships

Fig. 6

 6 Fig. 6 The correlations between Punknown and PM2.5 (a), PM2.5×NO2 (b), JNO2×NO2 (c)

  Impact of HONO on AOC, OH and O3 budget 530It is known that photolysis of HONO plays a crucial role for OH radical production 531 in the atmosphere. The elevated levels of daytime HONO indicated that a strong 532 atmospheric oxidizing capacity exists in the atmosphere in Beijing. Additionally, OH 533 radical acts as an important role in ozone photochemistry. Since the ozone pollution 534 was severe during the observation period, the production and loss rates of O3 were also 535 quantified. Fig.7showed the simulated average diurnal profiles of AOC, primary 536 production rates of OH radical, O3 production, and loss budget with and without HONO 537 data constraints. The meaning of "without HONO data constraints" is that the measured 538 HONO concentrations are not entered into the OBM model. The calculated AOC with 539 and without HONO constrained were up to 8.58 × 10 7 and 6.63 × 10 7 molecules cm -3 s - 540 1 at noon, with average daytime (7:00-19:00 LT) values of 4.33 × 10 7 and 3.27 × 10 7 541 molecules cm -3 s -1 , respectively. The AOC levels were relatively lower than those 542 determined at the same site in 2008(Yang et al. 2018), but comparable to the values at 543 a background site in Hong Kong(Li et al., 2018b). This implied the decreased oxidation 544 capacity due to the implementation of strict emission reduction measures taken in 545 Beijing in recent years. OH was the predominant oxidant, as expected, accounting for 546 88% and 85% of the AOC with and without HONO constrained, respectively. During 547 the nighttime, the contributions from O3 and NO3 to AOC began to increase due to low 548 OH levels.549Here we calculated the production rate of OH radicals from HONO photolysis and 550 compared it with those from other sources, including O3 photolysis, OVOCs photolysis 551 as well as ozonolysis of alkenes (Fig.7 (c) and (d)). In terms of the daytime average,552HONO photolysis was the largest contributor to OH production with an average value 553 of 0.93 ppb h -1 , followed by O3 photolysis (0.36 ppb h -1 ), and ozonolysis of alkenes 554 (0.16 ppb h -1 ). The contribution of OVOCs photolysis could be neglected with an 555 average of 0.03 ppb h -1 . Even at noontime, HONO photolysis still presented the 556 dominant contributor of OH production, which was consistent with the conclusion in

  557

Fig. 7

 7 Fig. 7 Simulated average diurnal variations of AOC (a, b), major primary OH sources

  resolution field observation of HONO, together with other air pollutants 590 and meteorological parameters were conducted at an urban site in Beijing from June to 591 July 2019. A haze pollution period (Period I) and an ozone pollution period (Period II) 592 were selected for a comparative study of two typical cases. Higher HONO 593 concentrations and HONO/NO2 ratios were found during Period I than those during 594 Period II, implying that the heterogeneous conversion from NO2 on aerosol surfaces 595 may contribute to HONO formation. Direct vehicle emission exhibited significant 596 contribution from 15% to 40% on ambient HONO at night. The calculated 597 homogeneous formation rate and heterogeneous conversion frequency of NO2 to 598 HONO formation during Period I were higher than those during Period II. Compared

the availability of carbonyls data, the model was only performed from 22 219 to 26 June (an ozone pollution period) with 00:00 local time (LT) as the initial time. 220 Two model cases with and without HONO constraints were run to assess the role of

  . The situ O3 photochemical formation

	215
	216	mechanism can be clarified into three pathways, HO2+NO, CH3O2+NO, and other
	217	RO2+NO reactions. The O3 loss pathways include NO2+OH, RO2+NO2, O3+OH/HO2,
		O3 photolysis, and other reactions (VOCs+O3, VOCs+NO3, Heter.lossN2O5).
	221
	222	HONO to AOC, OH production rate, and ozone budget. A six-day pre-run was made to
	223	stabilize the unconstrained compounds and the final outputs were extracted to further
	224	analyses.
		2.3

218

Considering

.2 Photolysis rates and OH concentration 225

	231	and angstrom exponent values (α) were input into the TUV model. The AOD, α, O3
	232	column concentration, and cloud optical thickness were determined by Moderate
		Resolution	Imaging	Spectroradiometer	(MODIS)	satellite
	226	The photolysis rates of HONO and O( 1 D) were not measured directly in this work.
	227	The JHONO and JO1D values can be calculated by the Tropospheric Ultraviolet and Visible
	228	(TUV) radiation model developed by the Nation Center for Atmospheric Research
	229	(NCAR) (http://www.acd.ucar.edu/TUV). To reflect the influence of aerosols on JHONO
		and JO1D values, aerosol vertical optical depth (AOD), single scattering albedo (SSA),

233

(https://neo.sci.gsfc.nasa.gov/blog/). In our work, the value of 0.91 was used as SSA 234

  Tong et al., 2015), but comparable to measurements at Shanghai(Bernard et al.,

	292
	293	2016), Hong Kong (Xu et al., 2015), Roma (Acker et al., 2006a), and Paris (Michoud
	294	et al., 2014). The lower HONO/NO2 ratios may suggest a less conversion from NO2 to
		HONO formation in this study.
	283
	284	Period I. The HONO/NO2 ratio was often applied to assess the contribution of NO2 to
	285	HONO from the heterogeneous conversion (Li et al., 2012). It implied that the
		heterogeneous conversion from NO2 might contribute to HONO formation.

Table 1 documented the average hourly HONO, NO2, NO,

276 PM2.5, O3 concentrations, and HONO/NO2 ratio during the two periods. Given that the 277 NOx analyzer probably overestimated the NO2 concentrations, the HONO/NO2 ratios 278 discussed in Section 3 are lower limits for the values. The average hourly HONO level 279 during Period I (p<0.05) was higher than that during Period II. The result of higher 280 HONO level during Period I was consistent with the previous studies (Cui et al., 2018; 281 Zhang et al., 2019b). The average hourly ozone levels were similar in two periods.

282

Compared with that during Period II, a higher HONO/NO2 ratio was found during

286

The averaged daytime and nighttime HONO, NO2 and HONO/NO2 of our 287 observation and other urban sites were summarized in Table

S1

. The higher HONO, 288 NO2, and HONO/NO2 levels occurred at nighttime in all sites except Nanjing

(Liu et

obtained by this study were lower than those in previous results of Beijing

(Jia et al., 291

2020;

Table 1

 1 Average hourly HONO, NO2, NO, PM2.5, O3 concentrations, and HONO/NO2 299 ratios during the haze pollution period and the ozone pollution period

	300
	Pollutant	Unit	Period I Haze pollution period	Period II Ozone pollution period
	HONO	ppb	0.58±0.26 (0.25-1.39)	0.54±0.19 (0.24-1.04)
	NO2	ppb	16.4±6.5 (7.4-38.7)	18.5±8.0 (6.1-44.0)
	NO	ppb	3.6±2.5 (1.3-14.2)	2.6±1.5 (1.2-11.4)
	PM2.5	μg/m 3	69.5±29.7 (13.6-123.3)	43.5±13.4 (15.0-72.9)
	O3	ppb	62.9±39.4 (1.0-157.7)	73.2±43.4 (1.0-145.0)
	HONO/NO2	%	3.8±1.6 (1.4-9.2)	3.1±0.9 (1.4-5.8)
	301
	3.2

Diurnal variations of HONO 302

  03±0.03, 0.05±0.03 and 0.03±0.01 ppb h -1 ,

	382
	383	respectively. Note that the P net	NO+OH value averaged at 0.04±0.02 ppb h -1 during Period
	384	I were slightly higher than those during the whole observation period (0.03±0.02 ppb
	385	h -1 ) and Period II (0.03±0.01 ppb h -1 ). The calculated average P net	NO+OH ranged from
	386	0.002 to 0.17 ppb h -1 , which was comparable to those obtained at an urban site of
	387	Western China in summer (0.04-0.15 ppb h -1 ) (Huang et al., 2017), but lower than the
		results in severe haze periods in urban Beijing (0.98-2.18 ppb h -1 ) (Tong et al., 2015;

388

Zhang et al., 2019b).

Table 2

 2 Comparison of the HONO concentrations and the derived Punknown at different sites 492

	Site	Date	HONO/ppb Punknown/ppb h -1	Reference
	Beijing (suburban, China)	2006.8	0.45	1.00	(Yang et al., 2014)
	Beijing (urban, China)	2014.2-3	1.95	1.26-1.85	(Hou et al., 2016)
	Beijing (urban, China)	2015.9-2016.7	5.97	3.05	(Wang et al., 2017)
	Beijing (urban, China)	2016.12	3.5	0.98-1.25	(Zhang et al., 2019b)
	Beijing (urban, China)	2018.8-9	1.23	2.33	(Jia et al., 2020)
	Beijing (urban, China)	2019.6-7	0.44	0.59	This study
	Jinan (urban, China)	2015.9-2016.8	1.15	2.95	(Li et al., 2018a)
	Xi'an (urban, China)	2015.7-8	1.04	0.75	(Huang et al., 2017)
	Shanghai (urban, China)	2016.5	2.31	1.78-2.98	(Cui et al., 2018)
	Guangzhou (rural, China)	2004.10	1.25	4.90	(Su et al., 2008b)
	Paris (suburban, France)	2009.7	0.10	0.40	(Michoud et al., 2014)
	Jülich (rural, Germany)	2003.7-8	0.14	0.50	(Kleffmann et al., 2005)
	493

  Though the researches of HONO could also be the main HONO sources. Additionally, the photolysis of total 516 nitrate (HNO3 and particle nitrate) have been considered as potential formation 517 pathways of ambient HONO in several other studies(Ye et al., 2016; Zhang et al., 2020;

	518
	519	Zhou et al., 2011). However, it was a pity that HNO3 and particulate nitrate were not
		observed during the sampling period. The effect of total nitrate on HONO formation

512

Ziemba et al

(2010)

,

Rutter et al (2014)

,

Leong et al (2016)

and

Gall et al (2016)

, it can 513 be learned that the heterogeneous conversion of HNO3 on primary organic aerosol 514 emitted by motor vehicles and the homogeneous VOCs-mediated conversion of HNO3 to 520 could not be evaluated in this study. Considering the significant role of total nitrate, the 521 conversion of total nitrate to HONO in ozone pollution period will be studied in the 522 future.

Acknowledgements

production, the diurnal variations of O3 production and loss rates with and without 562 HONO were depicted in Fig. 7 (e) and (f). The average O3 production is dominated by 563 the HO2+NO and other RO2+NO reactions. For the average O3 loss, the predominate 564 two pathways are NO2+OH and NO2+RO2 reactions. Other reactions including 565 VOCs+O3, VOCs+NO3, NO2+RO2, and Heter.lossN2O5 dominated the O3 loss during 566 the nighttime. All pathways except O3 photolysis and other reactions were 567 underestimated when HONO data were not constrained in the model. The net O3 568 production rate can be obtained as the difference between the production and 569 destruction rate. In this study, the daytime average net production rate was 10.19 ppb h -1 570 with HONO constrained, which was 1.2 times higher than the value (8.18 ppb h -1 ) 571 without HONO constrained.

572

Note that the homogeneous reaction of OH+NO was the only source of HONO in 573 the model now, the differences of the simulated results between the two cases could


Junling Li

Hong Li
email: lihong@craes.org.cn

Xuezhong Wang

Weigang Wang

Maofa Ge

Hao Zhang

Xin Zhang

Kun Li

Yan Chen

Zhenhai Wu

Fahe Chai

Fan Meng

Yujing Mu

Abdelwahid Mellouki

Yujie Zhang

Lingyan Wu

Yongchun Liu

A Large-Scale Outdoor Atmospheric Simulation Smog Chamber for Studying Atmospheric Photochemical Processes: Characterization and Preliminary Application

Keywords:

Understanding the formation mechanisms of secondary air pollution is very important for the formulation of air pollution control countermeasures in China. Thus,

Introduction

Air pollution has been one of the most important global environmental issues in the past few decades, which is related to human health, ecological environment, and climate change [START_REF] Guo | Elucidating severe urban haze formation in China[END_REF][START_REF] Huang | High secondary aerosol contribution to particulate pollution during haze events in China[END_REF][START_REF] Menon | Climate effects of black carbon aerosols in China and India[END_REF][START_REF] Zhang | Air pollution and control action in Beijing[END_REF].

To study the chemical processes of atmospheric pollution, many smog chambers had been developed worldwide. Smog chambers were initially constructed for developing and evaluating atmospheric gas-phase chemical mechanisms, generating and validating computer models of the chemistry occurring in polluted atmosphere (Akimoto et al., 1979a;CARTER et al., 1982a). Now the smog chambers could be used to study the formation and evolution of specific pollutants in the atmosphere by controlling or restricting certain meteorological conditions and reactant compositions, and could also be applied to obtain kinetic parameters of specific reactants [START_REF] Knox | A New Mechanism for the Low Temperature Oxidation of Hydrocarbons in the Gas Phase[END_REF]Li et al., 2017a;Li et al., 2017b;[START_REF] Mcfiggans | Secondary organic aerosol reduced by mixture of atmospheric vapours[END_REF][START_REF] Yu | Atmospheric photooxidation of alkylbenzenes-Ⅰ. carbonyl product analyses[END_REF][START_REF] Zhou | Simulation of SOA formation from the photooxidation of monoalkylbenzenes in the presence of aqueous aerosols containing electrolytes under various NOx levels[END_REF].

According to the light sources adopted, the smog chambers were usually divided to be indoor chamber and outdoor chamber; indoor chambers were equipped with artificial light sources while outdoor chambers benefitted from natural solar radiation [START_REF] Seakins | A brief review of the use of environmental chambers for gas phase studies of kinetics, chemical mechanisms and characterisation of field instruments[END_REF]. For indoor chambers, ultraviolet lamps were used to simulate natural solar radiation, thus the spectral distribution was not exactly the same as the tropospheric sunlight spectrum, which made the simulation results might deviate from that in nature. However, it is relatively easier to control the experimental conditions for the indoor chambers, various experimental conditions (e.g. temperature, relative humidity, pressure) could be precisely designed for different experimental purposes, which means that the repeatability of experimental results could be ensured under precise control of the reaction conditions. In comparison, since outdoor chambers usually had larger size, there are relative smaller surface to volume ratio for outdoor chamber, which could minimize the wall effects and wall loss of gaseous species and particles. The experiments inside the outdoor chambers were performed at ambient temperature and pressure, and also with natural solar radiation. Hence, the outdoor chamber was an ideal reactor to simulate the atmospheric photochemical processes.

However, the drawbacks of the outdoor smog chamber were that the temperature, humidity, and solar flux varied gradually during the experimental period, and it was almost impossible to guarantee reproducible irradiation from day to day. [START_REF] Johnson | Simulating the formation of secondary organic aerosol from the photooxidation of toluene[END_REF][START_REF] Karl | Kinetic Study of the OH-isoprene and O3-isoprene reaction in the atmosphere simulation chamber[END_REF][START_REF] Seakins | A brief review of the use of environmental chambers for gas phase studies of kinetics, chemical mechanisms and characterisation of field instruments[END_REF].

Many outdoor and indoor chambers had been established and applied to simulate the atmospheric photochemical processes worldwide (Table S1). The construction of large-size smog chamber abroad began in the 1970s, when the starting point was to study near-ground ozone pollution (Akimoto et al., 1979b;Carter et al., 1982b). In the following thirty years, indoor and outdoor chambers were widely used to study the generation mechanism of secondary pollutants, such as ground-level-ozone [START_REF] Dodge | Chemical oxidant mechanisms for air quality modeling: critical review[END_REF][START_REF] Hess | The evaluation of some photochemical smog reaction mechanisms-ⅠTemperature and initial composition effects[END_REF][START_REF] Simonaitis | Evaluation of the condensed carbon bond (CB-IV) mechanism against smog chamber data at low VOC and NOx concentrations[END_REF] and SOA [START_REF] Griffin | Organic aerosol formation from the oxidation of biogenic hydrocarbons[END_REF][START_REF] Leone | An outdoor smog chamber and modeling study of Toluene-NO Photooxidation[END_REF][START_REF] Martian-Reviejo | Is Benzene a Precursor for Secondary Organic Aerosol?[END_REF][START_REF] Mcmurry | Gas and aerosol wall losses in Teflon film smog chambers[END_REF][START_REF] Odum | Gas/particle partitioning and secondary organic aerosol yields[END_REF]Paulsen et al., 2005a;[START_REF] Saathoff | Temperature dependence of yields of secondary organic aerosols from the ozonolysis of α-pinene and limonene[END_REF]. After the 1980s, many large smog chambers have been transformed, rebuilt, and upgraded, to deal with the emerging scientific issues of atmospheric environment and atmospheric chemistry, such as PM2.5 pollution [START_REF] Hallquist | The formation, properties and impact of secondary organic aerosol: current and emerging issues[END_REF][START_REF] Hurley | Organic aerosol formation during the atmospheric degradation of toluene[END_REF][START_REF] Johnson | Simulating the formation of secondary organic aerosol from the photooxidation of toluene[END_REF], intermediate products of VOCs reaction [START_REF] Bloss | Development of a detailed chemical mechanism (MCMv3.1) for the atmospheric oxidation of aromatic hydrocarbons[END_REF][START_REF] Bohn | Actinometric measurements of NO2 photolysis frequencies in the atmosphere simulation chamber SAPHIR[END_REF][START_REF] Brauers | The atmosphere simulation chamber SAPHIRHE: A tool for the investigation of photochemistry[END_REF][START_REF] Ren | Investigation of the reaction of ozone with isoprene, methacrolein and methyl vinyl ketone using the HELIOS chamber[END_REF], multiphase reactions [START_REF] Poschl | Multiphase Chemistry at the Atmosphere-Biosphere Interface Influencing Climate and Public Health in the Anthropocene[END_REF][START_REF] Warneke | Comparison of daytime and nighttime oxidation of biogenic and anthropogenic VOCs along the New England coast in summer during New England Air Quality Study[END_REF], reaction kinetic parameters [START_REF] Karl | Kinetic Study of the OH-isoprene and O3-isoprene reaction in the atmosphere simulation chamber[END_REF][START_REF] Ren | Atmospheric fate and impact of perfluorinated butanone and pentanone[END_REF][START_REF] Rohrer | Characterisation of the photolytic HONO-source in the atmosphere simulation chamber SAPHIR[END_REF], etc.

The domestic experimental research with the smog chamber started in the early 1980s, later than abroad. Peking University built the earliest indoor photochemical smog chamber in 1982, in response to the photochemical smog phenomenon that occurred in Lanzhou [START_REF] Tang | Trial production and performance experiment of photochemical smog chamber[END_REF]. A series of photochemical simulation experiments of hydrocarbons and NOx were designed and conducted according to the atmospheric conditions in Lanzhou and Beijing [START_REF] Zhang | Research on photochemical smog pollution in Chinese cities[END_REF]. Then a serious environmental issues were studied based on the smog chambers constructed with various size in the past decades, including the mechanism of photochemical reaction (Liu et al., 2017;[START_REF] Wang | Design and characterization of a smog chamber for studying gas-phase chemical mechanisms and aerosol formation[END_REF][START_REF] Wu | Construction and characterization of an atmospheric simulation smog chamber[END_REF], ozone and SOA formation (Li et al., 2018a;[START_REF] Ma | The influences of ammonia on aerosol formation in the ozonolysis of styrene: roles of Criegee intermediate reactions[END_REF][START_REF] Wang | Evaluation and Application of Dual-Reactor Chamber for Studying Atmospheric Oxidation Processes and Mechanisms[END_REF], biomass burning reactions [START_REF] Zhang | Particle Size Distribution and Polycyclic Aromatic Hydrocarbons Emissions from Agricultural Crop Residue Burning[END_REF], the photochemical process of the gasoline and diesel (Chen et al., 2019a;Chen et al., 2019b;[START_REF] Kamens | Secondary organic aerosol formation from toluene in an atmospheric hydrocarbon mixture: Water and particle seed effects[END_REF], physicochemical properties of SOA formed under various conditions (Li et al., 2017a;[START_REF] Li | Temperature effects on optical properties and chemical composition of secondary organic aerosol derived from n-dodecane[END_REF]Li et al., 2018b;[START_REF] Peng | The optical properties of limonene secondary organic aerosols: the role of NO3, OH and O3 in the oxidation processes[END_REF][START_REF] Zhang | Effects of SO2 on optical properties of secondary organic aerosol generated from photooxidation of toluene under different relative humidity[END_REF], et al. However, most of the chambers constructed in China were indoor smog chambers, establishment large-scale outdoor smog chambers in China was limited. In order to study the atmospheric pollution process close to China's actual atmospheric environment, it was necessary to build a large outdoor smog chamber in China.

This work described a new outdoor photochemical smog chamber constructed at the Chinese Research Academy of Environmental Sciences (the CRAES chamber). As the large-scale outdoor smog chamber in China at present, it was designed to simulate the atmospheric photochemical processes at ambient temperature and radiation. A series of characterization experiments were performed, including the light-transmission rate of the Teflon reactor, the mixing ability, the wall loss of gaseous pollutants and particles, and the blank photochemical background. We had also performed preliminary applications of the smog chamber, including the classic gas-phase photochemical reaction of propene, the yield of SOA derived from α-pinene ozonolysis and 1,3,5trimethylbenzene photochemical reaction. The temperature and seed effects on vapor wall loss and SOA yield were investigated in this work.

Facility

The CRAES chamber was located on the rooftop of atmospheric photochemical smog chamber simulation laboratory building (40 °02'27.73'N, 116 °24'41.56'E), aligning in north-south direction. The chamber was mainly composed of a Teflon reactor, an enclosure, an auxiliary system and a detection system. Its schematic was illustrated in The frame of the reactor was made of aluminum alloy, of which the bottom was made of aluminum supported by steel structure. As shown in Fig. S1, injection and sampling ports, air purification system import and export, and port for personnel in and out (staged manual cleaning the walls inside the chamber) were located on the bottom of the frame by using the flanges. All the connection parts on the bottom of the reactor were made of Teflon or stainless steel (covered with Teflon film) without O-rings to avoid the evaporation of the organic impurities into the reactor. The reactor walls were made of 0.1 mm fluorinated ethylene propylene (FEP) Teflon film (FEP 100,DuPont USA), and it was suspended on the frame. The volume of the reactor was 56 m 3 (3.2 m × 6.2 m × 2.5 m), with a surface to volume ratio approximately 1.55 m -1 .

The enclosure consisted of a shield and an electrical control system. The main body of the shield was made of stainless steel supported by a full steel frame and had a rectangular parallelepiped shape. This shield could protect the reactor against adverse weather conditions. The opening and closing of the shield was achieved by an electrical control system. The entire system was equipped with an emergency stop device to deal with sudden failures and ensured that the enclosure and Teflon reactor was not damaged.

The cooling system consisted of a condensing compressor (Industrial Chiller, ANGES, China) and a condensing tube. The tube connected with the condensing compressor being evenly distributed below the steel plate at the bottom of the reactor.

The water-cooling method ensured that the temperature of the reactor was within a controllable range, especially under high temperature condition in summer.

The zero air generation system consisted of two air compressors, two air tank and two AADCO pure air generators (Model 737, AADCO Instruments Inc., USA). The NO, NO2, ozone, NH3, non-methane hydrocarbons (NMHC) (< 1 ppb, volume fraction), and particles in the purified air were below detection limit, and the relative humidity (RH) was less than 1%. The maximum flow rate of the purified air was 245±5 L/min.

The purified air was used as the matrix air and carrier gas. All gas lines of the system were made of stainless steel or Teflon. Gaseous species were injected into the reactor through Teflon lines by cylinders connected with pressure reducing values and mass flow controllers. Most gaseous species were commercial cylinder gases, and there were also gaseous species that were configured according to the experimental requirements.

Instrumentations of the CRAES chamber were summarized in Table 1. The intensity of the UVA and UVB was monitored by meteorological ecological environment monitoring system (Jinzhou Sunshine Technology Co. Ltd. China). Airmo VOC online analyzer (GC-866, Chromato-sud, France) was used to detect the parent VOCs concentrations in the chamber. Its detection limit was less than 1.0 ppb. The VOCs concentrations were also monitored by a gas chromatography mass spectrometer (GC-MS, 7890A/5975C, Agilent) coupled with a model 7100 preconcentrator (Entech Instruments Inc., USA). The formed aldehyde and ketone were collected by a custommade Aldehyde Ketone Sampler, and then the samples were analyzed by a high performance liquid chromatography-UV detector-mass spectrometry (HPLC-UV-MS; SHIMADZU, Japan, LC20AD/SPD-20A; ABSCIEX, USA, API 3200). The aerosols formed in the chamber were collected by a low flow sampler (LV 40BW, Sibata Scientific Technology Ltd., Soka, Japan) with a sample speed of 5 L/min. High performance liquid chromatography mass spectrometry (HPLC-MS, SHIMADZU, LC20A; ABsciex API3200) and high resolution electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS, micrOTOFⅡ, Bruker) were used to detect the chemical composition of the formed aerosols. The aerosol particle size distribution was detected by a scanning mobility particle sizer (SMPS), which composed of an electrostatic classifier (EC, Model 3080, TSI Inc., USA), a differential mobility analyzer (DMA, Model 3081, TSI Inc., USA) and a condensation particle counter (CPC, Model 3772, TSI Inc., USA). The flow rates of sheath and aerosol flow were set to 3.0 and 0.3 L/min, respectively, allowing for a size distribution scan ranging from 15.1 to 661.2 nm within 120 s. The aerosol particles were also monitored by a nano-scanning mobility particle sizer (nano-SMPS, TSI3938E57), which was composed of an electrostatic classifier (EC, Model 3082, TSI Inc., USA), a differential mobility analyzer (DMA, Model 3086, TSI Inc., USA), a Nano Enhancer (Model 3757), and a condensation particle counter (CPC, Model 3750, TSI Inc., USA). The flow rates of sheath and aerosol flow were set to 25 and 2.5 L/min, respectively, allowing for a size distribution scan ranging from 1 to 30.5 nm within 60 s. The temperature and relative humidity inside the chamber were monitored by industrial temperature and humidity transmitter (CWS16, CCY11, Beijing Star Sensor Technology Co., LTD. China).

Characterization Experiments

In order to verify the smog chamber's utility, a series of characterization experiments were performed, including the light transmission of the Teflon film, the mixing ability, the background experiments (zero air, zero air +NOx), and wall losses of gaseous pollutants and particles.

Light Transmission

The light densities of the solar radiation before and after the Teflon film were detected by an irradiation spectrometer (Jaz spectral sensing suite, Ocean Optics Inc., USA), and then the light transmission of the new Teflon film was calculated.

Fig. 2 showed the transmission rate of the full solar spectrum for the Teflon film.

The transmission rate was above 90% at the wavelength range of 350-900 nm. The solar radiation spectra were almost identical before and after the film, which showed that this film was suitable for the Teflon reactor of the smog chamber. The light transmission of this chamber were also detected by comparing the NO2 photolysis rate inside and outside the chamber. The NO2 photolysis rate inside the chamber was estimated by steady-state actinometry [START_REF] Wang | Evaluation and Application of Dual-Reactor Chamber for Studying Atmospheric Oxidation Processes and Mechanisms[END_REF]. NO2 was injected into the chamber and irradiated, and the resulting ozone, NO2, and NO mixing ratios were measured. The photolysis rate constant, J(NO2), was then estimated as the following equation:

𝐽 = 𝑘 1 [𝑂 3 ][𝑁𝑂]/[𝑁𝑂 2 ] (1)
where k1 (cm 3 /molecule/sec) was the rate constant of NO and ozone reaction. The measured J(NO2) inside the chamber was compared to the NO2 photolysis rate outside the chamber, and the results were shown in Fig. 3. Results showed that the NO2 photolysis rate inside the chamber was close to that of natural sunlight.

Mixing Ability

The mixing ability of the chamber was characterized by the length of time when the gas concentration got stable. Generally, the shorter mixing time referred to the better mixing ability of the chamber. Carbon monoxide (CO) was used as the tracer to detect the mixing ability of gaseous species inside the chamber. A known volume of CO gas was injected into the chamber by cylinder. The injection line was located in the middle of the chamber. Three high-speed fans were placed at the opposite corner of the chamber: one bracket was equipped with a vertical blown fan, and one bracket was equipped with two horizontal blown fans. The brackets supporting the fans were all covered with Teflon films. The CO concentration was measured by an EC 9810 CO analyzer (ECOTECH, Australia) with a detection limit of 50 ppb.

As revealed by Fig. 4, the CO gas entering the chamber could be mixed evenly within four min for the four injections. The mixing time was very short compared to the entire experimental process (usually several hours). This showed the good mixing ability of the chamber for experiments.

Preliminary Application Experiments

Background Experiments

In order to minimize the existence of organic impurities desorbing from Teflon films [START_REF] Kelly | Characterization of Fluorocarbon-Film Bags as Smog Chambers[END_REF], the newly-made reactor was exposed to sunlight for 10 hours with zero air containing 1.5-2 ppm of ozone. Then the chamber was flushed for 24 hours with zero air. After the above protocols, the chamber filled with zero air was kept in the dark for more than 12 hours, and no measurable organic impurities was detected by the Airmo VOC online analyzer. Then the chamber filled with zero air or zero air + NOX was exposed to sunlight for 8 hours. The concentrations of ozone, NO, and NO2 were measured by EC 9830 ozone analyzer and EC 9841 NOx analyzer (Ecotech, Australia).

The detection limit of ozone and NOx were both 0.5 ppb. The aerosol particle size distribution was detected by a SMPS.

The gas analyzers above were calibrated weekly by gas dilution calibration system (4010 Gas Dilution Calibrator and Model 1001 Zero Air Source, Sabio) with certified cylinders of gases. The NO, NO2 and CO gases (≥ 99%) were commercially available, and they were used without further purification. Ozone was generated by a commercial ozone generator (VMUS-4, Azco Industries Ltd, Canada), which connected the oxygen cylinder through the Teflon tube. The concentration of generated ozone could be estimated based on the oxygen flow rate and time through the ozone generator.

Fig. 5a andb showed the concentration of NO, NO2, ozone and mass of formed particles for background experiments with only zero air. NO concentration was in the range of 0-1 ppb with no detectable increase, while NO2 was in the range of 0-2 ppb with a slightly increasing trend, which was probably due to the release from the Teflon films. Concentration of ozone increased slowly with the sunlight irradiation, up to 21 ppb. This was likely due to the irradiation of the purified matrix air, and was consistent with the previous reported data [START_REF] Grosjean | Wall Loss of Gaseous Pollutants in Outdoor Teflon Chambers[END_REF]. As shown in Fig 4b, the formation of particles was negligible (less than 0.01μg m -3 ).

The chamber filled with zero air and 71 ppb NOx was exposed to sunlight irradiation for 8 hours. As shown in Fig. 5c andd, concentration of NOx slightly decreased as the illumination time increases, while ozone concentration increased and reached 32 ppb when the chamber was closed. After 4 h of sunlight irradiation, a small amount of particles was formed, which might be from the reaction of OH radicals (from NOx cycles) with organic impurities desorbed from the Teflon films. However, the particle mass concentration here (< 0.1μg m -3 ) was much less than the particles produced by reactions of volatile organic compounds discussed below.

Wall Loss of Gaseous Pollutants

In the CRAES chamber, the wall loss of propene, NO, NO2, and ozone were evaluated by injecting the gases into the chamber and monitoring their decay with duration of more than 8 hours in the dark. The wall loss rates of the gaseous pollutants were obtained by treating the gas wall losses as first order process. The temperature and relative humidity conditions during the measurement processes were 20-29 ℃ and less than 7%, respectively. All wall loss experiments were performed with initial concentration ranging from 80 ppb to 400 ppb.

As shown in Table 2, the wall loss rates of NO, NO2, ozone and propene were 0.65×10 -4 min -1 , 1.01×10 -4 min -1 , 2.65×10 -4 min -1 , and 0.09×10 -4 min -1 , respectively.

The wall loss rates of interested gaseous species were all within the value ranges of previous data for chambers facilities constructed from Teflon films [START_REF] Bloss | Development of a detailed chemical mechanism (MCMv3.1) for the atmospheric oxidation of aromatic hydrocarbons[END_REF][START_REF] Grosjean | Wall Loss of Gaseous Pollutants in Outdoor Teflon Chambers[END_REF][START_REF] Metzger | Evaluation of 1,3,5 trimethylbenzene degradation in the detailed tropospheric chemistry mechanism, MCMv3.1, using environmental chamber data[END_REF][START_REF] Wang | Evaluation and Application of Dual-Reactor Chamber for Studying Atmospheric Oxidation Processes and Mechanisms[END_REF][START_REF] Wang | Design and characterization of a smog chamber for studying gas-phase chemical mechanisms and aerosol formation[END_REF]. For the relative high wall loss rate of ozone, it might indicate the permeability of the film, and ozone might react with the reactive compounds for its high reactivity. While for propene, its wall loss rate was nearly negligible, which was consistent with the reported values:

for GIG-CAS [START_REF] Wang | Design and characterization of a smog chamber for studying gas-phase chemical mechanisms and aerosol formation[END_REF] smog chamber, no wall loss was detected; Wu et al.

(2007) calculated the wall loss rate as 0.066×10 -4 min -1 in a 2 m 3 Teflon smog chamber;

and for ICCAS [START_REF] Wang | Evaluation and Application of Dual-Reactor Chamber for Studying Atmospheric Oxidation Processes and Mechanisms[END_REF] smog chamber, the wall loss rates were (0.30-0.31) × 10 -4 min -1 , respectively.

Wall Loss of Particles

The particles inside the chamber could deposit on the chamber walls with the result of turbulent, Brownian diffusion, gravitational sedimentation as a function of the particle size. The wall loss rates of particles were obtained by treating the wall loss as a first-order process, and the particle loss coefficient Kdep could be expressed as following equation:

𝑑 𝑁(𝑑 𝑝 ) 𝑑 𝑡 = -𝐾 𝑑𝑒𝑝 (𝑑 𝑝 )𝑁(𝑑 𝑝 ) (2)
where N(dp) was the number concentration of the particles, and Kdep (dp) was the loss coefficient of particles in the diameter dp.

Ammonium sulfate particles were used as a reference aerosol to measure the particle wall losses. Ammonium sulfate solution was atomized with an atomizer (TSI, Model 3079A, TSI Inc., USA), then the formed particles were passed through a diffusion dryer and a neutralizer (Model 3088, TSI Inc., USA) before introducing into the reactor.

The wall loss rate of ammonium sulfate was shown in Table 3 and Fig. 6. As shown in Table 3, the overall number wall loss rate Kdep was 0.23 h -1 , which leaded to a lifetime of 4.4 h for particles. While for particles in the diameter range from 100 to 600 nm, as shown in Fig. 6b, Kdep were determined to be in the range of 0.186-0.30 h -1 . The relationship between Kdep and dp was determined by optimization of four parameters (a, b, c, d) in the following equation:

𝐾 𝑑𝑒𝑝 (𝑑 𝑝 ) = 𝑎𝑑 𝑝 𝑏 + 𝑐 𝑑 𝑝 𝑑 (3)
where parameters a, b, c and d were optimized to be 6.34718×10 -6 , 1.55745, 6.38387, and 0.66596, respectively.

As shown in Table 3, the wall loss rate for the particles in different chambers were various, this might due to the different environmental conditions insider the chamber facilities. In addition, the relationship between Kdep and dp of an aerosol in a cubic vessel were theoretically expressed by [START_REF] Corner | The coagulation and deposition of a stirred aerosol[END_REF], gravitational settling and diffusion are considered:

𝐾 𝑑𝑒𝑝 = 1 100 [ 6√𝐾 𝑒 𝐷 𝜋 + 𝑉 𝑐𝑜𝑡ℎ 𝑉𝜋 4√𝐾 𝑒 𝐷 ] (4)
where D, Ke, and V were the Brownian diffusivity, a constant for eddy diffusion, and the terminal settling velocity, respectively.

As mentioned above, two high-speed fans were located insider the chamber, which would affect the eddy diffusion and vibrate the wall of the chamber. The eddy diffusion and vibration of the chamber wall were likely to affect the deposition of the aerosol inside the chamber. For the experiments performed in this smog chamber in future, in order to reduce the loss of particles, the fans will be turned off after the precursors are evenly mixed.

Preliminary Application Experiments

On the basis of characterization experiments, we carried out a series of preliminary applications experiments with the CRAES chamber, including photochemical reactions of propene-NOx, SOA yields derived from α-pinene ozonolysis and 1,3,5trimethylbenzene (1,3,5-TMB)-NOx photo-oxidation.

Propene-NOx Experiments

The propene-NOx experiments were widely used to evaluate the ability of the smog chamber to test the chemical mechanisms [START_REF] Wang | Evaluation and Application of Dual-Reactor Chamber for Studying Atmospheric Oxidation Processes and Mechanisms[END_REF][START_REF] Wang | Design and characterization of a smog chamber for studying gas-phase chemical mechanisms and aerosol formation[END_REF]. The propene-NOx experiment was performed in the chamber close to real atmosphere. The initial concentration of propene, NO, NO2, and ozone were 83, 9, 120, and 2 ppb, respectively. And the HONO concentration was 8 ppb. The photolysis rate of NO2 was measured with J(NO2) filter radiometer (METCON, Germany). The chemical mechanism of propene from the Master Chemical Mechanism (MCM) version 3.3.1 was applied to simulate the propene oxidation, which was operated with Facsimile. The experiments were compared with the simulation results.

SOA Yields

A series of α-pinene ozonolysis and 1,3,5-trimethylbenzene (1,3,5-TMB)-NOx photochemical experiments were carried in the CRAES chamber to verify its performance in studying the formation of SOA. Temperature and seed effect on the SOA yields were also investigated. All these experiments were carried out under dry conditions.

The aerosol yield Y was defined as the fraction of a reactive organic gas (ROG) that was converted to aerosol, which was calculated by the following equation [START_REF] Odum | Gas/particle partitioning and secondary organic aerosol yields[END_REF]:

𝑌 = ∆𝑀 𝑜 ∆𝑅𝑂𝐺 (5)
where ∆Mo was the aerosol mass concentration (μg/m 3 ) produced from a given amount of ROG, and ∆ROG was the mass concentration (μg/m 3 ) of reacted precursor.

The two-product model was applied to simulate the SOA yield formed in the chamber, and it was calculated based on the following equation [START_REF] Odum | Gas/particle partitioning and secondary organic aerosol yields[END_REF]) [START_REF] Odum | Gas/particle partitioning and secondary organic aerosol yields[END_REF]:

𝑌 = ∑
where Yi was the yield of one individual product, αi was the proportionality constant basing on the total concentration of product i, Kom,i was the partitioning coefficient basing on the organic mass concentration of species i, Mo was the overall aerosol mass concentration.

The SOA yield was the result after particle and vapor wall loss correction. The correction coefficient of the particle wall loss was calculated based on the loss after the SOA mass reaches the maximum value. The details of the vapor wall loss of this chamber were introduced in the Supporting Information. Briefly, as shown in Table S2, both the temperature and seed could affect the vapor wall loss, the presence of seed in the reaction system could decrease the vapor wall loss, and the increase of temperature of the reaction system could decrease the vapor wall loss. Meanwhile, the vapor wall loss of different reaction systems was also different.

α-pinene ozonolysis experiments

Four α-pinene ozonolysis experiments were performed under dry conditions. The aerosol density was assumed to be 1 g/cm 3 , which was referred to the literature values [START_REF] Wang | Design and characterization of a smog chamber for studying gas-phase chemical mechanisms and aerosol formation[END_REF][START_REF] Wirtz | Density of secondary organic aerosols[END_REF]. The details of the experimental conditions were shown in Table 4.

The SOA yields of α-pinene ozonolysis was underestimated by a factor of 0.32-0.78 fold when considering vapor wall loss. After considering the vapor and particle wall loss, the optimal parameters α1, α2, Kom,1, and Kom,2 of this work were 0.3643, 0.4590, 0.0674, and 0.0006, respectively. The yield curve fitted well with the experiments data. SOA yields of α-pinene ozonolysis experiments of this work and data from other chamber facilities were shown in Fig. 8. The experiments in this work were performed under low temperature (4.4-11.7℃), and the yields were comparable with the yield data obtained under similar temperature condition (9.9-10.9 ℃) [START_REF] Saathoff | Temperature dependence of yields of secondary organic aerosols from the ozonolysis of α-pinene and limonene[END_REF]. Meanwhile, according to the yield values reported in other previous studies (the temperature conditions were higher than this work) [START_REF] Cocker | State-of-the-art chamber facility for studying atmospheric aerosol chemistry[END_REF][START_REF] Griffin | Organic aerosol formation from the oxidation of biogenic hydrocarbons[END_REF][START_REF] Hoffmann | Formation of organic aerosols from the oxidation of biogenic hydrocarbons[END_REF][START_REF] Saathoff | Temperature dependence of yields of secondary organic aerosols from the ozonolysis of α-pinene and limonene[END_REF][START_REF] Wang | Evaluation and Application of Dual-Reactor Chamber for Studying Atmospheric Oxidation Processes and Mechanisms[END_REF], it could be seen that temperature had important influence on the SOA yield, that a decrease in temperature could enhance the SOA yield

1,3,5-TMB-NOx photochemical experiments

For 1,3,5-TMB-NOx photochemical experiments, the density of the formed aerosols was assumed to be 1.4 g/cm 3 [START_REF] Nakao | Density and elemental ratios of secondary organic aerosol: Application of a density prediction method[END_REF], and the details were shown in Table 5. In order to obtain the SOA yield more accurately, the vapor wall loss was taken into account. Temperature and seed effect on SOA yield were all considered. As shown in Table S2, under same temperature conditions, the presence of seed could reduce timescale associated with reaching gas-particle equilibrium (𝜏 𝑔-𝑝 ̅̅̅̅̅̅), vapor could be more easily partition to the particle phase, and the vapor wall loss could be reduced during the photochemical processes. Under the same seed conditions, temperature increase could reduce the 𝜏 𝑔-𝑝 ̅̅̅̅̅̅, and the vapor wall loss would decrease.

As shown in Table 5, the SOA yields of 1,3,5-TMB-NOx was in the range of 4.02-5.43% for high temperature unseeded conditions; when the ammonium sulfate seeds were introduced, the yield was increased (7.08%). Under low temperature unseeded condition, the yield was 8.11%, which was higher than that under high temperature condition; when the ammonium sulfate seeds were introduced, the yield was increased to 11.78%. Fig. 9 showed the photolysis rate of NO2 (J(NO2)) of the 1,3,5-TMB-NOx photochemical experiments. The J(NO2) at high temperature (in summer) was similar, and it was also at low temperature (in winter), but the J(NO2) in winter was smaller than that in summer. The photolysis rate was positively correlated with the intensity of the photochemical reaction, indicating that the photochemical reaction in winter was weak. However, the SOA yield in winter was higher than that in summer, indicating that temperature was one of the main factors affecting the SOA yield. The results obtained showed that both the temperature and seed could affect the SOA yield, the increase of temperature could lower the SOA yield, while the presence of seed could enhance the SOA yield. [START_REF] Im | Simulation of aromatic SOA formation using the lumping model integrated with explicit gas-phase kinetic mechanisms and aerosol-phase reactions[END_REF] reported 1,3,5-TMB SOA yield with the outdoor smog chamber at high temperature unseeded condition, and the yields (4.9±0.4 %, 3.4±0.3 %) were comparable with the data we obtain under similar condition.

According to the vapor wall loss and final SOA yields under various conditions, the seed was suggested to be used in the chamber experiments, as this could minimize the interaction between the gas phase and the chamber walls.

Conclusions

We have constructed and characterized the CRAES chamber in this study. To our knowledge, it is the only large-scale outdoor chamber in China at present. A series of characterization experiments were performed, including the light transmission of the FEP Teflon film, the mixing ability of the chamber, the background experiments (zero air, zero air +NOx), and wall loss of gaseous pollutants and particles. The transmission rate was above 90% for the wavelength range 350-900 nm; the mixing time was very short (within 4 min) compared to the entire experimental process (usually several hours); under both zero air and zero air + NOx background experiments, negligible gases and particles were released from the film or formed; the wall loss rates of propene, ozone, NO, and NO2 were 0.09 × 10 -4 , 2.65 × 10 -4 , 0.65 × 10 -4 , and 1.01 × 10 -4 min -1 , respectively; for inorganic ammonium sulfate particles, the wall loss rate was 0.23 h -1 , resulting a lifetime of 4.4 h.

The propene-NOx photo-oxidation reaction was performed and the results were compared with the MCM modelling results, which showed good agreement and meant that it could provide valid data in studying gas-phase photochemistry reactions. For dark reactions, α-pinene-O3 experiments were performed and two product model was used, the SOA yields fitted well with the model curve. For photochemical reactions, 1,3,5-trimethylbenzene-NOx experiments were performed, the SOA yields were compared with the data obtained from other chamber facilities. The dark and photochemical reactions showed that temperature and seed could have important effect on the vapor wall loss and SOA yields. Higher temperature and the presence of seed could reduce the vapor wall loss, the seed were suggested to be used in the chamber to reduce the interaction between the gas phase and chamber walls; SOA yield was found to depend inversely on temperature, and the presence of seed could increase SOA yield.

Overall, the results of characterization and preliminary experiments demonstrated that the chamber was in good condition and could be used to provide simulation data with high quality for gas-phase chemistry and secondary air pollutants formation under conditions close to the real atmosphere.

Fig. 1 ,

 1 Fig. 1, and the pictures of the reactor and enclosure were shown in Fig. S1.

Fig. 1 .

 1 Fig. 1. Schematic diagram of the CRAES chamber.

Fig. 2 .

 2 Fig. 2. Ultraviolet-visible transmission spectra of the Teflon film.

Fig. 3 .

 3 Fig. 3. The NO2 photolysis rate inside and outside the chamber.

Fig. 4 .

 4 Fig. 4. Measured carbon monoxide concentration as a function of time in four injections.

Fig. 5 .

 5 Fig. 5. NO, NO2, NOx, and ozone concentration as a function of sunlight irradiation time with zero air (a) and with zero air + NOx (c); Mass concentration of formed particles as a function of sunlight irradiation time with zero air (b) and with zero air + NOX (d).

Fig. 6 .

 6 Fig. 6. (a) Number concentration of ammonium sulfate particles as a function of time after its introduction into the chamber, the color map refers to the number concentration of the particles (#/cm 3 ). (b) Particle wall loss rate constants for different particle diameter sizes.

Fig. 7 Fig. 7 .

 77 Fig.7showed the concentration-time profiles of monitored and simulated propene, NO, NO2, and ozone in propene-NOx experiment. The wall loss rates of propene, NO,

Fig. 8 .

 8 Fig. 8. SOA yield of α-pinene ozonolysis experiments and comparison with other chamber facilities, the unit density (1 g/cm 3 ) was used for all the experiments when comparing our results with those from previous studies.

Fig. 9

 9 Fig. 9 Photolysis rate of NO2 (J(NO2)) of the 1,3,5-TMB-NOx photochemical experiments.

Table 1 .

 1 Overview of Instruments of the CRAES Chamber.

	Instrument	Manufacturer	Measured Parameters	Accuracy
	SO2 analyzer	EC 9850, ECOTECH, Australia SO2 concentration	0.5 ppb
	O3 analyzer	EC 9830, ECOTECH, Australia O3 concentration	0.5 ppb

Table 2 .

 2 Summary of wall loss rates of gaseous pollutants in CRAES smog chamber and comparison with other chamber facilities.

						Wall Loss Rate (×10	-4 min	-1 )
	Species	CRAES GIG-CAS 56 m 3 30 m 3	a	ERT 80 m b 3	EUPHORE 200 m 3	c	ICCAS 3 d 5×2 m right	left	e PSI 3 27 m
	C 3 H 6	0.09	ND	f		NA	g	NA		0.31	0.3	NA
	O 3	2.65	1.310.24	1.30.9	1.8		3.1	2.5	1.2-4.8
	NO	0.65	1.410.40	0-2.0	NA		3.1	3.0	NA
	NO 2	1.01	1.390.68	0-8.2	NA		4.5	3.8	0.13-2.52

a: Wang et al. (2014); b: Grosjean (1985); c: Bloss et al. (2005); d: Wang et al. (2015); e: Metzger et al. (2008); f: Not detectable; g: Not applicable

Table 3 .

 3 Summary of wall loss rates of particles in CRAES smog chamber and comparison with other chamber facilities.

	Chamber	Volume (m 3 )	Chamber Materials	Wall Loss Rate (h -1 )	Particle (h) Life Time	References
	CRAES	56	FEP	0.23	4.4	This work
	GIG-CAS	30	FEP	0.17	5.9	Wang et al. (2014)
	PSI	27	FEP	0.21	4.8	Paulsen et al. (2005b)
	EUPHORE	200	FEP	0.18	5.6	Martian-Reviejo and Wirtz (2005)
	ICCAS	5×2	FEP	0.12-0.26	3.8-8.3	Wang et al. (2015)
	SAPHIR	270	FEP	0.27	3.7	Rollins et al. (2009)
	CMU	12	FEP	0.40	2.5	Donahue et al. (2012)

Table 4 .

 4 Experimental conditions and resulting SOA data of the α-pinene ozonolysis experiments.

	Date	Initial VOC (ppb)	Initial O3 (ppb)	Mo (μg/m 3 )	Temp. (℃)	SOA yield (%)
	2019.12.11	394	500	841	4.4-8.8	51.83
	2019.12.13	250	390	414	6.6-11.7	44.72
	2019.12.16	175	307	210	6.2-6.8	39.46
	2019.12.18	95	370	73	4.7-8.6	32.31

Table 5 .

 5 Experimental conditions and resulting SOA data of the 1,3,5-TMB photooxidation experiments.

	Experiments	Seed	Initial VOC (ppb)	Initial NOx (ppb)	VOC/NOX (ppbC/ppb)	Temp. (℃)	SOA yield (%)
	2019.0903	--	105	211	4.26	24-43	4.02
	2019.0925	--	180	197	8.22	24-43	5.43
	2019.1014	--	170	250	6.19	12-30	5.21
	2019.1025	AS	175	285	4.32	12-28	7.08
	2019.1223	--	165	795	1.87	2-17	8.11
	2019.1226	AS	167	820	1.83	4-19	11.78
	Im et al. (2014)	--	160	243	5.14	17-44	4.9±0.4
	Im et al. (2014)	--	165	113	11.12	17-44	3.4±0.3

Acknowledgments

This work was supported by China Postdoctoral Science Foundation (2019M660752), Beijing Municipal Science & Technology Commission (No. Z181100005418015), LAC/CMA (2019B08), the Fundamental Research Funds for Central Public Welfare Scientific Research Institutes of China, Chinese Research Academy of Environmental Sciences (No. GYG5051201; No. 2009GGQD18; No. 2019YSKY-018; No. 2019YSKY-012), and Chinese Academy of Sciences Strategic Leading Science and Technology Project (Class B) (XDB05010200). We are very grateful for Prof. Shiro Hatakeyama, Dr.Akinori Takami and Dr. Kei Sato from National Institute of Environment Studies, Japan, and Prof. Xinming Wang from Guangzhou Institute

Geochemistry/CAS for their support and assistance during the construction of the smog chamber; we also would like to thank all our colleagues from Chinese Research Academy of Environmental Sciences, especially Dr. Weiqi Zhang, Dr. Rui Gao, and Dr.

Yanjun Ren for their contributions to the construction of the smog chamber. Lastly, we want to show our deep thanks to Mr. Chunshan Liu and his colleagues from Beijing Conway Environmental Technology Co., Ltd. for their helps in building the smog chamber.

Appendix A. Supplementary data

Supplementary data associated with this article can be found in the online version at xxxxxx