Measurement report: Long-term variations in surface NOx and SO2 from 2006 to 2016 at a background site in the Yangtze River Delta region, China

China has been experiencing rapid changes in emissions of air pollutants in recent decades. Increased emissions of primary particulates and reactive gases caused severe haze in several polluted regions including the Yangtze River Delta 10 (YRD). Measures implemented in recent years for improving air quality have reduced the emissions of NOX, SO2, etc. The emission changes of these gases are reflected by tropospheric columns from satellite observations and surface measurements of surface concentrations from urban sites. However, little is known about the long-term variations in regional background NOX and SO2. In this study, we present NOX and SO2 measurements from the Lin’an station (LAN, 119°44′ E,30°18′ N,138.6 m a.s.l.), one of the Global Atmosphere Watch (GAW) stations in China. We characterize the seasonal and diurnal 15 variations and study the long-term trends of NOX and SO2 mixing ratios observed at LAN from 2006 to 2016. We also interpret the observed variations and trends in term of changes in meteorological conditions as well as emission of these gases. The overall average mixing ratios of NOX and SO2 during 2006–2016 were 13.6 ± 1.2 ppb and 7.0 ± 4.2 ppb, respectively. The averaged seasonal variations showed maximum values of NOx and SO2 in December (23.5 ± 4.4 ppb) and January (11.9 ± 6.2 ppb), respectively, and minimum values of 7.1 ± 0.8 ppb and 2.8 ± 2.3 ppb (both in July), respectively. 20 The average diurnal variation characteristics of NOX and SO2 differed considerably from each other though the daily average mixing ratios of both gases were significantly correlated (R2 = 0.29, P < 0.001). The annual average mixing ratio of NOX increased during 2006–2011 and then decreased significantly at 0.78 ppb/yr (‒5.16 %/yr, P < 0.01). The annual 95 % and 5 % percentiles of hourly NOX mixing ratios showed upward trends until 2012 and 2014, respectively, before a clear decline. The annual average mixing ratio of SO2 decreased significantly at 0.99 ppb/yr (‒8.27 %/yr, P < 0.01) from 2006–2016. The 25 annual 95 % and 5 % percentiles of hourly SO2 mixing ratios all exhibited significant (P < 0.001) downward trends at 3.18 ppb/yr and 0.19 ppb/yr, respectively. Changes in the total NOX and SO2 emissions as well as the industrial emissions in the YRD region were significantly correlated with the changes in annual NOX and SO2mixing ratios. The significant decreases in NOX from 2011 to 2016 and SO2 from 2006 to 2016 highlight the effectiveness of relevant control measures on the reduction in NOX and SO2 emissions in the YRD region. A decrease of annual S/N ratio was found, suggesting a better 30 efficacy in the emission reduction of SO2 than NOX. We found gradual changes in average diurnal patterns of NOX and SO2, https://doi.org/10.5194/acp-2021-227 Preprint. Discussion started: 7 May 2021 c © Author(s) 2021. CC BY 4.0 License.

process (Lin et al., 2019). The quality control measures mainly included the following: (1) daily zero and span checks (automatic); (2) monthly multi-point calibrations (≥5 points, including zero); (3) comparisons of reference SO2/N2 and 95 NO/N2 gas mixtures to the standards of the National Institute of Standards and Technology before and after their usage (periodically) to ensure data traceability; (4) instrument self-diagnosis, manual testing, checking, and maintenance; and (5) data correction according to the quality control results, especially the results of zero/span checks and multipoint calibrations.

Data processing methods
(1) Data statistics. The daily means of NOX and SO2 were calculated using the hourly average data, and only daily mean data 105 calculated from at least 18 hourly data were used as valid daily means. The monthly means of NOX and SO2 were calculated from the valid daily average data, and considered valid if they were based on at least 21 valid daily averages (or at least 17 valid daily averages in February). Annual means were calculated on the basis of the complete monthly mean data each year.
If a month's mean data were unavailable, we used an interpolating value from the corresponding monthly means in different years during the observation. In China, spring is from March to May, summer is from June to August, autumn is from 110 September to November, and winter is from December to February.
(2) Monthly satellite-based NO2 OMI data were provided by Lin's research group at Peking University; the data were retrieved using an optimized inversion algorithm (Lin et al., 2014;Lin et al., 2015;Boersma et al., 2019). A grid range of 115. 125°E-122.875°E and 27.125°N-35.875°N was selected to cover the entire YRD region.

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We used the concentration weighted trajectory (CWT) method to identify potential source areas (PSAs) of NOX and SO2 because this method can effectively distinguish the relative strength of potential sources (Xin et al., 2016). In the CWT method, the study area is divided into × small grids with equal size, and each grid (i, j) is assigned a weighted concentration according to the following equation: more distant grids, an empirical weighting factor Wij is introduced (Wang et al., 2006;Deng et al., 2020), with the following equation: Here, Where D denotes the number of days included, t denotes the number of trajectories per day, n denotes the trajectory endpoints of each trajectory, and i×j denotes the total number of grids.
We used a hybrid single-particle Lagrangian integrated trajectory model (Hysplit4.9) from National Oceanic and Atmospheric Administration, USA, to calculate the 24-h backward trajectories at 10 m above ground level over LAN during 130 2006-2016; the NCEP-NCAR reanalysis meteorological data set (https://ready.arl.noaa.gov/archives.php) and was used to calculate the trajectories and atmospheric mixed layer heights. The computed backward trajectories were subsequently processed using the TrajSat plug-in for CWT in Meteoinfo software (Wang, 2014), covering the region located within 20-40°N and 110-130°E and with a grid size resolution of 0.5°× 0.5°.

Observational levels and comparison with other sites
The hourly average NOX mixing ratios at LAN ranged from 0.4 ppb to 165.6 ppb, with NO2 mixing ratios ranging from 0.2 ppb to 106.8 ppb. Only 3 hours' data exceeded the secondary standard limit value for NO2 (106 ppb) as stated in the national ambient air quality standard (GB3095 -2012). The hourly average SO2 mixing ratios ranged from 0.1 ppb to 128.6 ppb, which were all below the GB3095-2012 secondary standard limit for SO2 (190 ppb). in GB3095-2012. However, the annual average SO2 mixing ratios (10.6-14.6 ppb) from 2006 to 2008 was much higher than the limit of the primary standard though lower than the limit of the secondary standard (22.8 ppb).  Figure 3 illustrates the average seasonal variations in NOX and SO2 mixing ratios at LAN. The maximum monthly average mixing ratios of NOX and SO2 were observed in December and January, at 23.5 ± 4.4 ppb and 11.9 ± 6.2 ppb, respectively.

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The minimum values both occurred in July, at 7.1 ± 0.8 ppb and 2.8 ± 2.3 ppb, respectively. The average monthly variations in NOX exhibited significant correlations with the monthly NO2 satellite data (R 2 = 0.82, P < 0.001). Seasonal variation patterns of NOX and SO2 look alike, showing a concave shape with its minimum in summer. The highest mixing ratios occurred in winter (NOX: 19.5 ppb; SO2: 10.1 ppb), followed by spring (NOX: 13.4 ppb; SO2: 7.8 ppb), autumn (NOX: 13.6 ppb; SO2: 6.7 ppb), and summer (NOX: 8.1 ppb; SO2: 3.3 ppb). The monthly average mixing ratios of both NOX and SO2 170 showed a dip in February-a phenomenon also observed in NOX and SO2 (Wang et al., 2016;Xue et al., 2020) and NO3 − and SO4 2− in PM2.5 in Shanghai (Duan et al., 2020). The source emission inventory data indicated that NOX and SO2 emissions from industry, transportation, and coal-fired power plants were all lower in February than in January and March throughout China (Li et al., 2017), which may be related to decreased emissions due to lower economic activity during Chinese Spring Festival. In addition, the higher RH in February (Fig. 2) might have led to higher NOX and SO2 removal rates. SO2 at LAN showed relatively small average diurnal variation ( Fig. 4b), with higher mixing ratios from midnight to 190 noontime and lower ones during later afternoon and evening. The average diurnal amplitude of SO2 at LAN was much smaller than those found in Nanjing and Jiaxing. The seasonal average diurnal profiles of SO2 at LAN were similar to the annual average one except for that in winter, which had a peak around noon (Fig. 4d).
The diurnal variation of pollutants emitted at ground level are closely related to the intensity of emissions, atmospheric transport, diurnal development in boundary layer height, and atmospheric photochemical reactions (Resmi et al., 2020). The 195 mixing layer depth (MLD) was much lower at night than during the daytime, as shown in Fig. 4b. Low MLDs at night are not conducive to pollutant dispersion, whereas high MLDs during the daytime are conducive to pollutant dispersion. This day-night difference in the MLD is one of the factors causing lower levels of SO2 and NOX during afternoon hours.
Photochemistry during the daytime also contributes to rapid chemical transformation of SO2 and NOX, which results in low NOX and SO2 mixing ratios in the afternoon. Overall, the morning peak of NOX was lower than the evening peak, the 200 morning peak of SO2 was higher than the evening subpeak, and the morning peak of SO2 was not as protruding as and occurred slightly later than that of NOX, reflecting the differences in their sources. The morning peak of NOX may be influenced by vehicle emissions during the morning rush hour, and the early peak of SO2 may be more influenced by vertical changes during the developing mixed layer depth height (Qi et al., 2012). The evening peaks of NOX and SO2 were relatively similar because both were closely related to the MLD decrease and for NOX likely also vehicle emissions during the evening 205 rush hour.

Influence of meteorological factors
Changes in meteorological factors have considerable effects on the levels of air pollutants. In this section, we investigate the influences of meteorological factors on the variations in NOX and SO2 mixing ratios through statistical plots showing relationships between pollutant concentrations and meteorological factors as well as correlation analysis. The variation characteristics of hourly average mixing ratios of NOX and SO2 along with meteorological parameters are presented in Fig. 5.
The variation characteristics of NOX and SO2 with WS ( Fig. 5a,b)  of T on the two pollutants varied considerably, with the SO2 mixing ratios decreasing nearly monotonically with increasing T (Fig. 5d), whereas NOX increased with increasing T in the low temperature range and decreased with increasing T in the high temperature range (Fig. 5c). Fig. 5c indicates a positive correlation between NOX and T in winter and negative correlations in other seasons, but the positive correlation in winter is weak and insignificant (Table 3). Pandey et al. ( 2008) reported that low T might facilitate the increase of NOX emissions from motor vehicle exhaust. The variations in NOX and SO2 with RH 220 (Fig. 5e,f) and P (Fig. 5g,h) exhibit a convex pattern and the former patterns in 3 different periods show well consistent but the latter ones are not.The correlation between SO2 and RH was stronger than that of NOX and RH. The variation characteristics of NOX and SO2 mixing ratios with the MLD exhibited diverse patterns (Fig. 5g,h). The mixing ratio of NOX  in the dependence of NOX and SO2 on wind direction. In summer, the high mixing ratios of NOX and SO2 were mainly from 230 the NW -NNE and SSW-NW sectors, respectively (Fig. 6b). In other seasons, relatively high NOX and SO2 values were mainly from the N-ENE and S-WSW directions, respectively, under the influences of the dominant and subdominant WDs ( Fig. 2b, d). Overall, NOX and SO2 observed at LAN originated mainly from the NW-ENE and SSW-NW sectors, respectively. However, this result provides only little information about the actual geographic distributions of major NOX and SO2 sources influencing LAN. Therefore, we used the CWT method to identify the PSAs for NOX and SO2. Fig. 7 235 presents the areas, from which NOX and SO2 observed at LAN originated. Although the PSAs covered the entire YRD, the PSAs for the highest NOX and SO2 levels appeared mainly in the eastern coastal region, which is closely related to the booming local economy. More obvious provincial differences were observed in a higher PSA for NOX than that for SO2.
Temporally, the high PSA (>10 ppb) of NOX and SO2 was most extensive in winter, followed by spring and autumn, with the least extensive PSA in summer. The NOX PSAs over coastal areas were more extensive than those for SO2 in each season.

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The YRD is one of the five major port clusters in China; thus, this region's ship emissions might be a major cause of this difference (Fan et al., 2016;Wan et al., 2020). The CWT analysis indicated that SO2 was mainly influenced by industrial emissions from inland areas, whereas NOX was mainly influenced by both inland and marine traffic.  al., 2019). Different from NOX, the annual average of SO2 at LAN decreased more rapidly than in most of the aforementioned regions (Table 4), which demonstrates the effectiveness of the policies in controlling SO2 emission during the observation period in the YRD.

Long-term variations in NOx and SO2 mixing ratios
The change in the annual SO2 mixing ratio was closely correlated with changes in industrial SO2 emission (R 2 = 0.95, P < 280 0.001) and total SO2 emission (R 2 = 0.94, P < 0.001) in the YRD (Fig. 8b). In 2011, the SO2 mixing ratio rebounded slightly, with an increase of 9 % compared with the value in 2010. This seemed to be consistent with the variation of industrial SO2 emission. The weakening impact of the global financial crisis and the recovery of industry in the YRD region may explain this slight rebound in SO2 emissions (Xie, 2017b). Seasonally, the SO2 mixing ratio exhibited the strongest decreasing trend (−1.69 ppb/yr, R 2 = 0.90, P < 0.001) in winter, followed by spring (−1.05 ppb/yr, R 2 = 0.97, P < 0.001) and autumn (−0.99 285 ppb/yr, R 2 = 0.93, P < 0.001), with the smallest decreasing trend observed in summer (−0.35 ppb/yr, R 2 = 0.61, P < 0.001).
In the annual statistics, the 95th and 5th percentile of the pollutants' concentrations can be regarded as influenced by polluted and clean air masses, respectively. The annual trends of the 95th percentile of NOX and SO2 (Fig. 9a) exhibited similar patterns to the corresponding trends in annual average mixing ratios (Fig. 8a, b), but the peak of the 95th percentile of NOX   (Yang, 2018;Xu et al., 2019). These results indicate that NOX has been gaining a more important role in the processes of precipitation acidification and secondary inorganic aerosol formation in the YRD region. Therefore, NOX emission reduction should be further strengthened in subsequent air pollution control measures and legislation in the YRD region. Figure 11 reveals the average diurnal variations in NOX and SO2 during the periods of 2006-2009, 2010-2013, and 2014-315 2016. During these three periods, the average diurnal curves in NOX exhibited a valley around 13:00, with minimum values of 7.5 ppb, 11.2ppb, and 9.2 ppb, respectively. The morning and evening NOX peaks, which occurred respectively at 09:00 and 19:00, became increasingly distinct over time (Fig. 11a, c, e). and Control, the state introduced a series of policies to promote automobile and motorbike ownership in response to the international financial crisis and to ensure economic growth; these policies effectively stimulated the automobile market (Mi and Qin, 2011;Hao and Song, 2018) and led to an increase in vehicle emissions and atmospheric oxidation in the YRD region (Yu et al., 2019). Thus, the NOX mixing ratios around the morning and evening peaks were much higher than those at 325 night during 2014-2016 (Fig. 11e), which differs much from the pattern during 2006-2009 (Fig. 11a). The disappearance of the small peak around 01:00 at night during 2012-2016 may be related to the introduction of stricter air pollution control policies for factories that emit at night.
The average diurnal variation curve of SO2 at LAN from 2006 to 2009 (Fig. 11b) is of the single-valley type, with an average valley mixing ratio of 6.5 ppb. After 2010, the peak shape has changed from single-valley type to the double-peak and 330 double-valley type (Fig. 11d, f). The valleys of SO2 during 2010-2013 occurred at 06:00 and 15:00, with average mixing ratios of 5.2 ppb and 4.7 ppb, and the peaks occurred at 10:00 and 19:00, with average mixing ratios of 5.9 ppb and 5.3 ppb, respectively. The NOX and SO2 evening peaks occurred at the same time (19:00), but the SO2 morning peak time was 1 hour later than the NOX morning peak (09:00), indicating that the NOX and SO2 morning peaks were influenced by different sources, whereas the evening peaks were from similar sources. The formation of the SO2 morning peak may be mainly 335 related to the vertical exchange during the development of the atmospheric boundary layer and the air in the upper layer with a higher SO2 mixing ratio than that at the surface draining down. The formation of the peaks of NOX and SO2 may be mainly

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We found gradual changes in diurnal patterns of both gases. After 2010, both NOX and SO2 showed diurnal patterns with two peaks and two valleys. The morning peak of NOX occurred at approximately 09:00, earlier than that of SO2 (10:00), and the evening peak occurred at the same time as SO2 (19:00). The morning and evening peaks of both gases protruded gradually.
This phenomenon can hardly be attributed to changes in meteorological conditions (such as the MLD