Exploring the inconsistent variations in atmospheric primary and 1 secondary pollutants during the G 20 2016 Summit in Hangzhou , China : 2 implications from observation and model 3

Complex aerosol and photochemical pollution (ozone and peroxyacetyl nitrate (PAN)) 22 frequently occur in eastern China and mitigation strategies to effectively alleviate both kinds of pollution 23 are urgently needed. Although the effectiveness of powerful control measures implemented by the 24 Chinese State Council has been comprehensively evaluated on reducing atmospheric primary pollutants, 25 the effectiveness on mitigating photochemical pollution is less assessed and therein the underlying 26 mechanisms are still poorly understood. The stringent emission controls implemented from 24 August to 27 6 September, 2016 during the summit for Group of Twenty Finance Ministers and Central Bank 28 Governors (G20) provides us a unique opportunity to address this issue. Surface concentrations of 29 atmospheric O3, PAN, and their precursors including volatile organic compounds (VOCs) and nitrogen 30 dioxides (NOx), in addition to the other trace gases and particulate matter were measured at the National 31 Reference Climatological Station (NRCS) (30.22 o N, 120.17 o E, 41.7 m a.s.l) in urban Hangzhou. We 32 found significant decreases in atmospheric PAN, NOx, the total VOCs, PM2.5, and sulfur dioxide (SO2) 33 under the unfavorable meteorological condition during G20 (DG20) relative to the adjacent period 34

In this study, to evaluate the effectiveness of emission control measures on reducing pollutant 105 4 concentrations, we compared the variations of atmospheric O 3 , PAN, particulate matter, VOCs, NO x , 106 and other trace gases before, during, and after G20, also demonstrating the effect of meteorological 107 conditions by using WRF-Chem model. An observation-based chemical box model (OBM) was used to 108 identify the predominant precursors and key chemical processes in PAN and O 3 formation and to further 109 assess the effect of reducing their respective precursors before, during, and after G20. Positive matrix 110 factorization (PMF) was employed to appoint the corresponding sources of various VOCs and compare 111 their variations and their respective ozone formation potentials (OFPs) before, during, and after G20.  Trace gases including O 3 , SO 2 , NO x , and CO were detected by a set of commercial trace gas analyzers 121 (Thermo Environmental Instruments Inc., USA i-series 49i, 43i, 42i, and 48i), respectively (Zhang et al.,122 2018). All trace gas analyzers were weekly span and daily zero checked. Ambient VOCs were measured 123 by using an on-line gas chromatography (Syntech Spectras Instrument Co., Ltd., The Netherlands) 124 coupled with dual detectors (Photo Ionization Detector (PID) and flame ionization detector (FID) for 125 quantifying C 2 -C 5 VOCs (GC955 series 811) and PID for detecting C 6 -C 12 VOCs (GC955 series 611). for domain one. RADM2 chemical mechanism and MADE/SORGAM aerosols were used in this study.

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Here we assumed no significant change in chemical processes (specifically the other reactive gases 148 involved in the chemical reactions with these pollutants) from BG20 to AG20. Thereby, the net 149 contribution (NCC) of emission controls and meteorological conditions primarily results in the 150 difference between observed PM 2.5 before and during G20, which is represented by the ratio of 151 (observed PM 2.5 (BG20)-observed PM 2.5 (DG20 II))/observed PM 2.5 (BG20). The effect of (1) In general, the modeled results of PM 2.5 before and after G20 can reproduce the observation results

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Here we used OBM model to simulate in situ PAN and O 3 production and their sensitivity to changes in In order to comprehensively evaluate air quality during the G20 period, we compared the concentrations 217 of pollutants during G20 with the adjacent time period in 2016, respectively. According to the control 218 measures schemes, we classified the whole period into three episodes: one week before G20 (BG20) 219 (16-23 August, 2016), during G20 (DG20) (24 August-6 September) including Phase Ι (24-27 August) 220 and Phase II (28 August-6 September), and one week after G20 (AG20) (7-15 September).  (Fig. S2). Thus, meteorological conditions before G20 were favorable for the dispersal of 234 8 atmospheric pollutants. On 26 and 27 August, the weather pattern changed to a cold continental high 235 with showery and windy days. The total precipitation and mean wind speed both reached their 236 respective maximums of 14.6 mm and 3.7 m s -1 on 26 August. Accordingly, all species except CO 237 significantly decreased by 12.3% for SO 2 , 29.7% for NO x , 6.7% for PM 2.5 , 11.9% for daily maximum 238 average-8 h (DMA8) O 3 , and 56.1% for PAN relative to BG20. With respect to the last half of DG20 I 239 and the beginning of DG20 II (28-31 August), the prevailing wind experienced a shift from northwest to 240 west and to southwest. On 28 August, the prevailed wind was from the north with the average daily 241 maximum wind speed of 3.9 m s -1 during G20, and the relative humidity rapidly decreased by 26.2%  Table S1). On 1 September, the prevailing wind was from  Statistically, observed daytime concentrations of PM 2.5 , NO x , and SO 2 in DG20 II both exhibited 272 significant decreases relative to those in BG20 with the reduction ratios of 11.3%, 17.0%, and 18.0%, 273 respectively (Fig. 2). Furthermore, by using WRF-Chem model we quantified the contributions of the 274 emission control measures (ECC) with 63.5%, 44.1%, and 31.2% to the reductions of PM 2.5 , SO 2 , and 275 NO 2 in DG20 II relative to BG20, respectively, but for the meteorological conditions it made negative DMA8 O 3 increased by 12.4% in DG20 I relative to BG20, which was attributed to regional transport 286 from the northern provinces and the enhanced solar radiation intensity. Afterwards, DMA8 O 3 decreased 287 by 33.4% from DG20 II to AG20 (Fig. 2), as did the peak values of mean daily O 3 in DG20 II compared 288 to BG20 and DG20 I (Fig. S3). This evidence suggests that additional vehicles controls implemented   With respect to VOCs, the mixing ratios of total VOCs also showed significant reduction of 20.0% in 302 DG20 compared with BG20, but increased by 104.1% in AG20 after control (Table S2). Alkanes were 303 the most abundant VOCs group (55.4%) in all periods, and were reduced by 19.8% from BG20 to DG20.

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On the contrary, alkenes increased by 20.0% in DG20 compared to BG20, among which ethylene 305 10 accounted for 63.9%-78.0% during the three periods, although other alkenes decreased to a minor extent.

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As expected, aromatics were reduced by 49.7% in DG20 compared with BG20. Ambient mixing ratios 307 of specific VOCs at NRCS station are summarized in Table S3. Ethane, ethylene, benzene, and toluene 308 are the four most abundant species during all the periods. Compared with BG20, except ethane, 309 isopentane, and ethylene, the mixing ratios of all species decreased in DG20. Ethylene, as a 310 representative tracer of fuel combustion, showed continuous increase from BG20 to AG20, possibly 311 indicating the ineffectiveness of control measures in this source.

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To identify the key precursors and chemical processes for PAN, we employed the observation-based 314 model to investigate the daytime average contributions to PA radical production rates directly from 315 individual pathways for these four episodes (Fig. 3). Acetaldehyde (e.g., oxidation of OH and NO 3 ) and incremental reactivity (RIR), which is widely used in the OBM study of ozone formation (Chameides et 328 al., 1999). Here RIR is defined as the ratio of decrease in PAN production rates to decrease in precursor 329 concentrations (e.g., 20% reduction is used in this study). A number of sensitivity model runs were 330 performed to calculate the RIRs for NO x , alkanes, alkenes, and aromatics classes as well as the 331 individual C 2 -C 10 hydrocarbon species. As shown in Fig. 4a, production of PAN was sensitive to VOCs 332 from BG20 to AG20. Meanwhile, the negative RIR values for NO x also indicated a VOCs regime of 333 PAN production around the G20 period in urban Hangzhou. In terms of BVOCs, the positive RIRs 334 values for isoprene (0.18-0.38) from BG20 to AG20 implied that in-situ formation of PAN at NRCS was 335 highly sensitive to isoprene. As to AVOCs, alkenes and aromatics were the most important  Furthermore, we identified the other specific VOCs controlling PAN production, which were xylenes, 338 trans/cis-2-butenes, trimethylbenzenes, toluene, and propene evidenced by their positive RIRs.

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Compared with their individual RIRs between control and non-control period, the in-situ production of 340 11 PAN was dominated by aromatics in BG20 and DG20 I, but controlled by alkenes in AG20. Besides  Fig. 4b. 346 Overall, the in-situ ozone formation was also controlled by VOCs from BG20 to AG20. AVOCs were 347 dominated by alkenes and aromatics, along with their increasing and decreasing RIRs, respectively.

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With the proceeding of emission control, the RIR for AVOCs showed gradual decrease from BG20 to 349 DG20, but increased after G20. In contrast, BVOCs (mainly as isoprene) exhibited gradual increases for 350 all periods, especially during the phase II in DG20 and AG20 when their RIRs were both higher than   The fifth source was characterized by abundant 2-methylpentane (61.7%) and BTEX, which is a typical 376 tracer for vehicle exhaust (Liu et al., 2008;Li et al., 2015). In addition, 2, 2, 4-trimethylpentane is a fuel vehicle exhaust (66.1%) and gasoline evaporation (61.8%) relative to DG20 I, while significant increase 410 was also found in fuel combustion with the increment of 0.7 ppbv (152.6%). After G20, the 411 13 contributions of vehicle-related emission and industry-related emission both showed bounces due to 412 lifting a ban on industry, power plant, and transport in and around Zhejiang Province. It should be 413 mentioned that biogenic emission also played an indispensable importance in contributing to the VOCs 414 mixing ratios, from 0.81 ppbv to 1.29 ppbv. About 20.9% of the total VOCs mixing ratios could be 415 ascribed to the biogenic emission, acting as the second major source, during the G20 II period. It 416 indicated that biogenic VOCs might make more contribution to the VOCs mixing ratios especially when 417 anthropogenic VOCs were substantially reduced following the process of control measures. 418 Moreover, we quantified their respective ozone formation potential (OFP) before, during, and after G20 419 by using the latest maximum incremental reactivity (MIR) and the appointed concentration profiles 420 above (See Fig. 7). Overall, the total OFP in DG20 was significantly reduced by the implement of 421 stringent control measures compared with BG20 and AG20. Specifically, the OFPs of solvent utilization, 422 industrial manufacturing, and vehicle exhaust both showed significant decreases (17.3%-77.2%) 423 compared with BG20, while fuel combustion significantly increased by 52.2% with the OFP of 6.9 ppbv, 424 accounting for 25.6% of the total during G20. Thus, it is clear that the high OFP of fuel combustion 425 contributed by ethylene was also responsible for the enhanced concentration of O 3 during G20. Such 426 high OFP from fuel combustion was also elucidated in APEC in Beijing (Li et al., 2015). To classify the 427 specific fuel type, we first examined the fire spots derived from the Fire Inventory NCAR Version-1.5 428 (FINNV1.5) in eastern China before, during, and after the period of 2016 G20 (See Fig. S4 in SI). Straw 429 combustion was excluded according to the decrease in the number of fire spots in the same time period 430 from BG20 to AG20. As mentioned above, industrial process with coal combustion was strictly limited  In this study, ground-based concentrations of atmospheric trace gases and particulate matter, together 442 with meteorological parameters, were measured at a NRCS site in urban Hangzhou before, during, and 443 after G20. We found significant decreases in atmospheric VOCs, PM 2.5 , NO x , and SO 2 in DG20 relative 444 to BG20 and AG20, respectively, under the unfavorable meteorological conditions (e.g., stable weather 445 pattern and regional transport). This evidence well indicated that the powerful control measures have 446 14 taken effect in their emissions in Hangzhou. On the contrary, observed DMA8 O 3 increased from BG20 447 to DG20 I, which was attributed to the regional transport from the northern provinces and the enhanced 448 solar radiation intensity, and then decreased from DG20 II to AG20. The decreases in the peak 449 concentration of daily O 3 and the OFP estimated from various VOCs sources both suggested the 450 effectiveness of stringent control measures on reducing atmospheric O 3 concentrations. Unlike O 3 , PAN 451 exhibited gradual decrease from BG20 to DG20. With the OBM model, we found acetaldehyde and 452 methyl glyoxal (MGLY) to be the most important second-generation precursors of PAN, accounting for 453 37.3-51.6% and 22.8%-29.5% of the total production rates. Furthermore, we confirmed that the 454 production of PAN was sensitive to anthropogenic and biogenic VOCs (isoprene) throughout the whole 455 period, specifically aromatics in BG20 and DG20 I but alkenes in AG20. Similarly, the sensitivity of 456 ozone formation was also under VOC-limited regime throughout G20 period. These findings suggest 457 that reducing emissions of alkanes, alkenes, and aromatics would mitigate photochemical smog 458 including PAN and O 3 formation. Furthermore, traffic (vehicle exhaust and gasoline evaporation) and 459 industrial sources (solvent utilization, industrial manufacturing, and chemical feedstock) were found to 460 be the major VOCs sources before G20, accounting for ca. 50.0% and 31.7% of the total, respectively,