Meteorology and Atmospheric Physics https://doi.org/10.1007/s00703-018-0598-1

ORIGINAL PAPER

Distribution and urban–suburban differences in ground‑level ozone and its precursors over Shenyang, China Ningwei Liu1,2,3 · Wanhui Ren4 · Xiaolan Li3 · Xiaogang Ma5 · Yunhai Zhang3 · Bingkun Li6 Received: 10 November 2017 / Accepted: 28 February 2018 © Springer-Verlag GmbH Austria, part of Springer Nature 2018

Abstract Hourly mixing ratio data of ground-level ozone and its main precursors at ambient air quality monitoring sites in Shenyang during 2013–2015 were used to survey spatiotemporal variations in ozone. Then, the transport of ozone and its precursors among urban, suburban, and rural sites was examined. The correlations between ozone and some key meteorological factors were also investigated. Ozone and ­Ox mixing ratios in Shenyang were higher during warm seasons and lower during cold ones, while ozone precursors followed the opposite cycle. Ozone mixing ratios reached maximum and minimum values in the afternoon and morning, respectively, reflecting the significant influence of photochemical production during daytime and depletion via titration during nighttime. Compared to those in downtown Shenyang, ozone mixing ratios were higher and the occurrence of peak values were later in suburban and rural areas downwind of the prevailing wind. The differences were most significant in summer, when the ozone mixing ratios at one suburban downwind site reached a maximum value of 35.6 ppb higher than those at the downtown site. This suggests that photochemical production processes were significant during the transport of ozone precursors, particularly in warm seasons with sufficient sunlight. Temperature, total radiation, and wind speed all displayed positive correlations with ozone concentration, reflecting their important role in accelerating ozone formation. Generally, the correlations between ozone and meteorological factors were slightly stronger at suburban sites than in urban areas, indicating that ozone levels in suburban areas were more sensitive to these meteorological factors.

1 Introduction Tropospheric ozone ­(O3) is an important trace gas that determines the lifetimes of other trace gases through its photolysis to produce the highly reactive OH radical (Levy 1971; Wofsy et al. 1972). It also acts as a key greenhouse gas, with the third most significant radiative forcing after Responsible Editor: S. Trini Castelli. * Ningwei Liu [email protected] 1



Nanjing University of Information Science & Technology, Nanjing, China

2



Chinese Academy of Meteorological Sciences, Beijing, China

3

Institute of Atmospheric Environment, China Meteorological Administration, Shenyang, China

4

Shenyang Environmental Monitoring Central Station, Shenyang, China

5

Fuxin Meteorological Bureau, Fuxin, China

6

Fushun Meteorological Bureau, Fushun, China



carbon dioxide (­ CO2) and methane (IPCC 2013). Additionally, ozone is an environmental pollutant that impairs human health and vegetation (Bates 2005; He et al. 2007; Minghong et al. 2000; WHO 2006). From a global perspective, tropospheric ozone has two major sources: transport from the stratosphere (Ding and Wang 2006; Holton et  al. 1995; Hsu and Prather 2009; Zheng et al. 2011) and in situ photochemical production from ozone precursor gases in the presence of sunlight (Chameides and Walker 1976; Crutzen 1974; Fishman et al. 1979). The spatial and temporal distribution of ozone precursor gases, i.e., ­NOx, CO, ­CH4 and volatile organic compounds ­(VOCs), are primarily driven by the distribution of their sources, both natural and anthropogenic. The anthropogenic sources of ozone precursors are vehicle emissions, industrial emissions, and biomass burning, among which vehicle emissions are the predominant precursor to N ­ Ox (Monks et al. 2015). The natural sources of ozone precursors are more complex. ­NOx is produced by wild fires, lightning, and soil emissions, and C ­ H4 is derived from livestock, rice fields, and wetland emissions, while CO is released from wild fires and volcanic eruptions (Seinfeld and Pandis 2016).

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Ozone is removed from the troposphere by in situ chemistry and uptake at the Earth’s surface (Fishman et al. 1979; Galbally and Roy 1980; Ripperton and Vukovich 1971). From a regional perspective, in addition to the sources at the global scale, tropospheric ozone also originates from horizontal long-range transport (Ma et al. 2002c). Since 2007, more than half of the world’s population has lived in urban areas, and many in metropolises and megacities (Zhu et al. 2012), where ground-level ozone has become a common serious air quality issue over the last decade. Major regions of elevated ozone are observed over North America, Europe, and East Asia from urban/industrial activities in the northern hemisphere, particularly in warm seasons. Some tropical regions also experience ozone enhancement due to both biomass burning and other human activities. A number of studies evaluating ozone pollution in various metropolises located in India, Brazil, America, and China, among others, have discovered markedly high ozone levels exceeding air quality standards, (Department for Environment 2016; Ghude et al. 2008; Parrish et al. 2011; Sánchez-Ccoyllo et al. 2006; Xu et al. 2011b; Zhu et al. 2012). Local/regional transport of these air masses into surrounding areas can lead to greater pollution concentrations outside cities. Modeling studies showed that, in Tokyo, sea breezes that developed during the day transported emissions from the urban center to the north, which enhanced ozone levels in downwind areas 50–100 km away (Kondo et al. 2010). A modeling study on the impacts of Istanbul (and Athens) on air quality in the eastern Mediterranean also found much lower concentrations of ozone within the metropolises owing to significant N ­ Ox emissions depressing ozone levels. Rural sites in the surrounding area had much higher ozone concentrations, 11–24 ppbv greater in summer and 9–14 ppbv greater in winter than in the urban areas, emphasizing the impact of megacity emissions on regional air quality (Im and Kanakidou 2012). Measurements of surface trace gases at Wuqing, a suburban site between the metropolitan areas of Beijing and Tianjin in the North China Plain (NCP), detected relatively high concentrations, due to regional mixing and transport of pollutants (Xu et al. 2011b). Ozone and fine particulate matter ­(PM2.5) episodes at the station for observing regional processes of the earth system (SORPES), located in the western part of the Yangtze River Delta (YRD) region of China, were generally associated with an air mass transport pathway over the mid-YRD, namely, along the Nanjing–Shanghai axis with its city clusters, suggesting that transport played an important role in air pollution, especially for ozone (Ding et al. 2013). Depending on the prevailing wind, pollution was transported from Guangzhou, Dongguan, and Hong Kong in the Pearl River Delta (PRD) region of China to the downwind rural site of Xinken, elevating local concentrations of VOCs and

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ozone (Liu et al. 2008). However, few studies have investigated multi-site trace gases and compared them within the same metropolis, with particular attention to their transport among urban, suburban, and rural sites located along different prevailing wind directions. Shenyang (123.40ºE, 41.83ºN), the largest city in Northeast China (NEC), is located in the south of the NEC plain at an altitude of 5441 m, rising in elevation from southwest to northeast. The climate is warm sub-humid continental, and the annual average temperature is 6.2–9.7 °C. The prevailing wind direction is southwesterly with an average speed of 2.2 m/s. Shenyang is the political, economic, and cultural center of Liaoning Province, and is an old industrial base dating from the founding of the People’s Republic of China in 1949. Over the last four decades, the atmospheric environmental problems of Shenyang have attracted significant attention both domestically and internationally (Li et al. 2017; Liu et al. 2011; Ma et al. 2005b). Despite strong governance over the past two decades, the urbanization trend, leading to a current population of over 8.4 million and an urban area that has rapidly grown to 3500 km2 within the total area of Shenyang of 1.3 million km2, makes air pollution a continuing significant problem in this metropolis. As a result, Shenyang was ranked number ten of cities with the worst air quality in China in 2015 (China’s Ministry of Environmental Protection 2016) based on the air quality index (AQI), which is based on the maximum values of the six most regularly observed pollutants, i.e., ­PM2.5, ­PM10, ­SO2, ­NO2, ­O3, and CO, according to China’s ambient air quality standard (GB3095–2012) (China’s Ministry of Environmental Protection 2012). In recent decades, although a number of studies have analyzed the mechanism of pollution formation in Shenyang and its ambient areas (Che et al. 2015; Chen et al. 2017; Fang et al. 2017; Li et al. 2017; Ma et al. 2011), few have focused on ground-level ozone. In fact, the 90th percentile of average maximum daily 8-hour ozone concentration over Shenyang was up to 155 μg/m3 in 2015, comparable to those of NCP (162 μg/m3), YRD (163 μg/ m3), and PRD (145 μg/m3), and was over the environmental standard (average maximum daily 8-hour value of 160 μg/ m3) for 62 days (China’s Ministry of Environmental Protection 2016). In this paper, we present analyzed ground-level ozone and its main precursors at most ambient air quality monitoring sites in Shenyang during 2013–2015 to survey the spatiotemporal variations in ozone in recent years. Then, we analyze the transport of ozone and its precursors among urban, suburban, and rural sites around Shenyang. Additionally, we investigate the correlations between ozone and some key meteorological factors.

Distribution and urban–suburban differences in ground‑level ozone and its precursors over…

2 Sites and data Since 2007, most of the original heavy industry enterprises in downtown Shenyang have been relocated to a new economic development zone approximately 20 km away to the west of the urban center; thus, it is not industrial emissions but traffic emissions that directly affect the ambient air quality over the Shenyang urban area from a total of 2 million automobiles, which increase at the rate of 800 per day. There are 11 ambient air quality monitoring sites in Shenyang, which have been successively set up by Shenyang Environmental Monitoring Central Station. Six pollutants, including particulate matter (­PM10 and P ­ M2.5), sulfur dioxide (­ SO2), nitrogen dioxide (­ NO2), ozone, and CO, are monitored automatically and continuously all year round. For this study, eight representative sites with complete data during 2013–2015 were chosen: Taiyuan Street, Wenyi Road, Lingdong Street, Senlin Road, Xinxiu Street, Jingshen Street, Yunong Road, and Hunnan Road, hereafter referred to as TYS, WYR, LDS, SLR, XXS, JSS, YNR, and HNR, respectively (Fig. 1). TYS, WYR, and LDS are urban sites; HNR, XXS, YNR, and JSS are suburban sites; and SLR is a rural site due to its remote location. The land

cover at the suburban sites is a mixture of city and cropland, whereas the rural site, SLR, is primarily covered by forest and a reservoir. There are no large pollution sources near any of the eight sites. The pollutant data used in this study (i.e., ozone, CO, ­NO2, NO) came from the eight sites and were collected hourly in mass concentration units of μg/m3 as they were directly measured, which were then converted to the volume mixing ratio units of ppbv and ppmv (thereafter, ppb and ppm). The relationship between concentration and mixing ratio can be expressed by the following equation: (1) where vmr is the mixing ratio, 𝜌 is the mass concentration, R is the gas constant with a value of 8.314 J/(mol k), P is the gas pressure, and M is the molar mass in units of g/mol. In this study, meteorological data were mainly obtained from the automatic weather station installed at Shenyang national basic meteorological station (SY NBMS) located in the southeast of Shenyang (123.45ºE, 41.73ºN, 50 m height). Wind parameters are observed at a height of 10 m, whereas temperature, pressure, and humidity data are collected at a height of 1.5 m. We also used total ultraviolet radiation data. All of these meteorological data are collected hourly. The locations of the eight ambient air quality monitoring sites and SY NBMS are shown in Fig. 1.

vmr = 𝜌 ⋅ (R ⋅ T)∕(P ⋅ M)

3 Results and discussion 3.1 Meteorological overview

Fig. 1  Ambient air quality monitoring sites and Shenyang National Basic Meteorological Station (SY NBMS). The black circle indicates the Third Ring Road, which marks the boundary of the Shenyang urban region

Figure 2 presents the average wind frequency and wind speed roses over Shenyang. According to the 3-year average (a), the wind frequencies ran along SW–NE sectors with the southwest being the prevailing wind direction, suggesting that air masses are dominantly transported to the northeast over the whole year. Furthermore, the wind speeds in the SW sector were greater than 3 m/s, in excess of those in any other direction. This indicates that polluted air masses from the urban areas (e.g., TYS) of Shenyang are smoothly transported to the downwind suburban areas (e.g., YNR) under the southwestern wind. Moreover, the SW–NE wind direction persists across all seasons (b). The prevailing wind came dominantly from the SW sector during the spring and summer, while from the SW and NE sectors with approximately equal frequencies in the fall, and mainly from N–NE sectors in winter. Despite value differences, wind speeds also remained at their maximum in the SW sector during each season, while there was some wind in the N-NE sectors (c), suggesting that while pollutants are transported northeasterly during the warm seasons, they can also be transported southerly during cold seasons.

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Fig. 2  Wind frequency (%) and wind speed (units: m/s) roses over Shenyang during 2013–2015. a 3-year average wind frequency and speed; b seasonal wind frequency; c seasonal wind speed

To further show the transport of the air masses from Shenyang, 36-h forward trajectories were computed using the HYSLPIT 4.8 model from the US National Oceanographic and Atmospheric Administration (NOAA) Air Resources Laboratory (http://www.arl.noaa.gov/ready​/ hyspl​it4.html) and the 6-hourly (at 00:00, 06:00, 12:00, and 18:00 UTC) archive meteorological data from the National Centers for Environmental Prediction (NCEP) global data assimilation system (GDAS) with a horizontal resolution of 1° × 1°. The trajectory starting point was 41.83°N, 123.40°E (Shenyang urban center) at a height of 10 m above ground level. Cluster analysis was applied to all trajectories in summer and winter during the 3-year study period (Fig. 3). In

summer, the trajectories were grouped into seven clusters according to the similarity of their behaviors. According to the model results, nearly 43% of the trajectories moved northeastward following paths 4, 5, and 7. The highest proportion of trajectories in this direction were in cluster 5, with relatively slow speed and low height during the first 12 h, suggesting a significant negative influence from the urban area on neighboring areas in the downwind direction. Compared to those in summer, trajectories in winter were more concentrated within four clusters. Nearly 75% of the trajectories moved southward following paths 1, 2, and 4, and they were the dominant negative influence on the air quality in the downwind direction.

Fig. 3  Seasonal variation in air mass forward trajectories in Shenyang. a summer; b winter

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Distribution and urban–suburban differences in ground‑level ozone and its precursors over…

3.2 Variations in ozone and its precursors in Shenyang 3.2.1 Seasonal variations Due to a significant increase in ozone levels during daytime in Shenyang (which we discuss in the next subsection), the hourly observations from 08:00 to 20:00 were used to calculate the seasonal mixing ratios of ozone, CO, ­NO2, NO, ­Ox, and ­NOx in Shenyang (summarized in Table 1). The annual cycle of mean ozone mixing ratios showed a single peak in June and a trough in December, differing from the cycles reported in previous studies in Shangdianzi (Lin et al. 2008), Lin’an (Xu et al. 2008), Mountain Tai (Sun et al. 2016), and Mountain Huang (Li et al. 2007) located in eastern China, which showed primary and secondary peaks. CO mixing ratios reached their maxima in January and their minima in July. ­NO2, NO, and ­NOx mixing ratios reached their maxima in December, whereas their minima occurred in August, July, and July, respectively. ­Ox, which is an indicator of total air oxidation capacity, reached its maximum mixing ratio in June and its minimum in December. As mentioned above, ozone and O ­ x mixing ratios were higher during warm seasons and lower during cold ones, while primary pollutants followed the opposite cycle. Several factors account for these variations. First, meteorological conditions, such as airflow convergence, lower wind speed, and temperature inversion, tend to favor the accumulation of pollutants during the winter, promoting the formation of haze and fog. Furthermore, annual domestic heating accompanied with enormous coal combustion occurs from November to March, leading to higher concentrations of primary pollutants. Then, owing to the dominant UV radiation and temperatures, photochemistry is most active during the summer, accelerating the transformation of primary gases to secondary pollutants. Finally, despite the distinct decline in ozone Table 1  Seasonal mixing ratios of ozone, CO, N ­ O2, NO, ­Ox, and ­NOx in Shenyang

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

concentrations over the lower-latitude area of China impacted by the East Asian summer monsoon, the southerly transport advects ozone and its precursors from the polluted regions of eastern China northwards to NEC, elevating ozone concentrations across Shenyang (Liu and Ma 2017; Xu et al. 1998, 2009). We compared the ozone levels in Shenyang with those in other parts of China, the USA, and Europe using the monthly 5th, 50th, 95th, and midday ozone percentiles during 2013–2015 at YNR, a suburban site 15 km northeast of the Shenyang urban center in the downwind direction of the urban pollution plume (Fig. 4). Ozone values were all significantly less than 30 ppb at the 5th percentile, similar to levels at Miyun, Hohenpeissenberg, and Beltsville, three rural sites in China, Germany, and the USA, respectively (Cooper et al. 2014). However, they were significantly lower than those at Joshua Tree in California, where the higher ozone values are due to the high elevation and deep daytime boundary layer, which drops to 4 km a.s.l. during spring and summer, allowing lower levels of free tropospheric ozone to be mixed down to the surface (Cooper et al. 2011). At the 50th percentile, ozone values at YNR were higher than those in Hohenpeissenberg and Beltsville, and similar to those in Miyun. The pattern of ozone levels at YNR differed from that in Miyun, with a lower peak (81.6 ppb in July) and a longer high-level period above 70 ppb during summer at YNR. As for the 95th percentile, levels at YNR displayed a significantly lower peak (141.9 ppb in August) at YNR compared to Miyun (162 ppb) (Cooper et al. 2014), and a longer elevated value period during April–October, showing marked high ozone concentrations in the warm seasons. These comparisons indicate that YNR and Miyun, which are both downwind sites from major metropolitan areas in China, have similar ozone levels, which are generally higher than those in Europe and the USA.

O3 (ppb)

CO (ppm)

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NOx (ppb)

19.7 27.4 34.7 44.5 60.4 61.9 60.5 59.3 48.8 39.5 23.8 17.7

1.7 1.2 1.0 0.9 0.8 0.7 0.7 0.8 0.8 1.0 1.2 1.3

29.9 23.9 22.9 20.7 20.1 20.8 18.6 17.7 23.5 27.4 30.5 30.6

23.9 11.5 8.1 6.3 5.4 5.1 4.4 5.9 12.8 16.4 23.4 30.4

49.6 51.3 57.6 65.2 80.5 82.7 79.1 77 72.3 66.9 54.3 48.3

53.8 35.4 31.0 27.0 25.6 25.9 23.0 23.5 36.4 43.9 53.9 61.0

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Fig. 4  Monthly ozone mixing ratios at YNR

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3.2.2 Diurnal cycles Figure 5 shows the diurnal ozone cycles at the key sites (TYS, LDS and YNR) along the major transport route in Shenyang. The ozone mixing ratios reached their maxima and minima in the afternoon and morning, respectively, owing to the significant influence of photochemical production during daytime and the depletion by titration during nighttime (Ma et al. 2002a, 2016; Wang et al. 2017; Xu Fig. 5  Diurnal cycles in ozone levels at key sites along the major transport route in Shenyang

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et al. 2008). Diurnal variations in surface ozone are primarily influenced by solar radiation strength, variations in the levels of precursors, and horizontal/vertical transport (Lin et al. 2008). In fact, photochemistry plays a dominant role in surface ozone variability due to the high anthropogenic emissions in eastern China, including Shenyang (Ma et al. 2002c; Wang et al. 2006). ­NOx levels generally displayed a pattern opposite those of ozone, with maxima and minima in the nighttime and afternoon, respectively (figure not

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Distribution and urban–suburban differences in ground‑level ozone and its precursors over…

shown). The higher ­NOx corresponded to lower ozone during nighttime. Theoretically, under stable conditions, ozone is depleted by NO titration at night or during cold seasons via the following reaction: (2) leading to lower ozone mixing ratios in urban areas (Monks et al. 2015). Furthermore, the shallow boundary layers and localized deposition at nighttime may also contribute to decreasing ozone levels. The nighttime ozone levels are generally lower in eastern than in western China (Lin et al. 2008; Ma et al. 2005a, 2014; Wang et al. 2006; Xu et al. 2008, 2016; Xue et al. 2013), particularly on the Tibetan Plateau, where ozone levels are mainly affected by stratospheric intrusion and long-range transport (Ma et al. 2002b, 2014; Wang et al. 2006; Xu et al. 2016), and ozone background levels are lower in populated regions. The patterns of ozone variability were similar at all three sites. However, the ozone mixing ratios decreased in the order TYS > LDS > YNR, with increasing distance from downtown Shenyang. Furthermore, the peak values occurred following the same sequence (separated by approximately 1 h), reflecting the photochemical production and transport processes from urban to suburban areas along the prevailing wind direction. Additionally, the diurnal ozone variations (differences between peak and trough values) also increased in the order TYS > LDS > YNR, suggesting that photochemistry played a more significant role in ozone levels in the suburban areas.

O3 + NO → NO2 + O2 ,

3.2.3 Transport between urban and surrounding areas Figure 6 shows the seasonal variations in the levels of ozone and its precursors at each site based on hourly observations during daytime. Each pollutant at each site generally followed the temporal variations observed for the Shenyang area as a whole. However, there were large differences among the sites based on their locations within the metropolitan area, closely related to the wind directions determining air mass transport. Ozone and O ­ x mixing ratios were higher at YNR than at any other site, confirming that enhanced ozone usually appears downwind of urban centers (Farmer et al. 2011; Ge et al. 2012; Lin et al. 2008; Xu et al. 2008, 2011a, b). Even at SLR, a rural site 30 km northeast of the urban center in the downwind direction, enhanced ozone mixing ratios similar to those at YNR were observed. However, TYS and LDS, the two urban sites outside of the prevailing wind transport path, had much lower ozone mixing ratios, indicating that downtown Shenyang is typically VOC limited, as high N ­ Ox mixing ratios suppress ozone mixing ratios (Im and Kanakidou 2012; Tie et al. 2013). The year-round ozone mixing ratio differences, up to 22.4 ppb

between YNR and TYS, emphasized the influence of urban emissions on surrounding air quality. Theoretically, owing to the large quantities of anthropogenic emissions, particularly traffic emissions, in highly urbanized areas, ozone mixing ratios should be significantly enhanced in the presence of sufficient sunlight and the reactions of ozone precursors. However, it is during the transport processes that ozone precursors largely transform to ozone, leading to much higher ozone mixing ratios in the downwind suburban and rural areas than in the urban centers. Mixing ratio differences between urban centers and their surrounding areas varied seasonally. Summer was the most significant season, during which ozone mixing ratios at YNR were as high as 88.3 ppb, higher than those at TYS by 35.6 ppb, and at LDS by 27.9 ppb. Similarly, ozone mixing ratios at SLR were 26.8 and 18.7 ppb higher than those at TYR and LDS, respectively, significantly greater than the urban–suburban differences of 11–24 ppb observed in Istanbul and Athens (Im and Kanakidou 2012). The differences can be explained by photochemical production effects during the transport processes of ozone precursors in warm seasons with sufficient sunlight (Monks et al. 2015). In contrast, ozone mixing ratio differences were much smaller in winter, with a 12.1 ppb difference between YNR and TYS, and 8.6 ppb between SLR and TYS, which can be explained by the prevailing northern wind transporting pollutants to the southern areas over Shenyang, and the relatively inactive photochemistry in winter. Observations of primary pollutants differed greatly from what was observed with ozone. In winter, significant CO enhancement appeared at every site except the remote ones, YNR and SLR, with relatively low mixing ratios, leading to larger urban–suburban differences. In summer, decreased CO levels did not differ much by site. Similarly, N ­ O2 and NO were distinctly enhanced at urban sites during cold seasons, while they remained at lower levels year-round at SLR than at any other site, suggesting the intensity of traffic emissions in urban areas. In contrast to ozone, the urban–suburban differences for ­NO2 and NO were larger in winter than in summer. In winter, the low-level primary pollutants at suburban and rural sites were due not only to lower emissions, but also to southerly transport, which induced the large urban–suburban differences. 3.2.4 Correlations between ozone and key meteorological factors Daytime observations were used to examine the correlations between ozone levels and other meteorological factors during 2013–2015 over Shenyang. Considering the strong influence of precipitation on pollutant levels and other meteorological factors, we ignored all rainy hours, leaving a total of 3016 samples for the 3-year correlation study.

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Fig. 6  Seasonal variations in the mixing ratios of ozone and its precursors at sites in Shenyang: a ozone, b CO, c ­NO2, d NO, e ­Ox, and f ­NOx

Table 2 shows the correlation coefficients between ozone mixing ratios and meteorological factors. Ozone mixing ratios showed a positive relationship with temperature and total radiation at urban and suburban sites during all seasons, and the correlations were greater in warm seasons than cold ones, particularly in summer, suggesting the importance of ultraviolet radiation and temperature in accelerating ozone formation. Ozone mixing ratios were also positively correlated with wind speed, but the coefficients were higher in winter than in summer. This can be explained by the fact that horizontal and vertical mixing were more homogeneous in summer, resulting in a weaker influence on ozone levels by wind speed, while local airflow perturbations were more important in winter due to the lower ozone levels. Generally,

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the correlations between ozone and meteorological factors were slightly higher in suburban than in urban areas, indicating that suburban ozone levels were more sensitive to meteorological factors that accelerated ozone production.

4 Conclusions We assessed ground-level ozone and its main precursors at ambient air quality monitoring sites in Shenyang during 2013–2015 to survey spatiotemporal variations in ozone, and then evaluated the transport of ozone and its precursors among urban, suburban, and rural sites. Correlations

Distribution and urban–suburban differences in ground‑level ozone and its precursors over… Table 2  Correlation coefficients of ozone with meteorological factors over Shenyang

Urban  Spring  Summer  Autumn  Winter  Whole year Suburban  Spring  Summer  Autumn  Winter  Whole year

Temperature

Total radiation

Wind speed

0.73 0.82 0.58 0.50 0.77

0.81 0.90 0.69 0.53 0.82

0.53 0.49 0.44 0.60 0.48

0.85 0.88 0.65 0.52 0.73

0.82 0.96 0.45 0.62 0.87

0.71 0.55 0.50 0.76 0.63

All relationships reached 0.01 significance levels

between ozone and some key meteorological factors were also investigated. Due to regional meteorological conditions, domestic heating, ultraviolet radiation, temperature, and the East Asian summer monsoon, ozone and O ­ x mixing ratios in Shenyang were higher during warm seasons and lower during cold ones, while primary pollutants, such as CO, ­NO2, NO, and ­NOx, exhibited the opposite cycle. YNR in Shenyang had similar ozone levels to Miyun in Beijing, another site in China that is downwind of a metropolitan area, and they both generally had higher levels than sites in Europe and the USA. Ozone mixing ratios reached their maxima and minima in the afternoon and morning, respectively, reflecting the significant influence of photochemical production during daytime and depletion by titration during nighttime. Ozone mixing ratios decreased in the order TYS > LDS > YNR, with increasing distance from downtown Shenyang, and the peak values occurred in the same sequence, TYS followed by LDS followed by YNR, separated by 1 h. The differences among sites were largest in summer, when the ozone mixing ratios at YNR were higher than those at TYS by 35.6 ppb. These findings suggest that photochemistry production contributes significantly to ozone levels during the transport of ozone precursors, especially in warm seasons with sufficient sunlight. The relationships between ozone mixing ratios and meteorological factors were examined based on hourly data. Temperature, total radiation, and wind speed all displayed positive correlations with ozone, reflecting their important role in accelerating ozone formation. Generally, the correlations between ozone and meteorological factors were slightly higher in suburban than in urban areas, indicating that ozone levels in suburban areas were more sensitive to meteorological factors that accelerated ozone production.

Acknowledgements  We greatly appreciated Wanyun Xu from Chinese Academy of Meteorological Sciences for her helpful suggestions. This work is supported by LAC/CMA under Grant 2017B02 and the National Natural Science Foundation of China under grant 41605081 and 41375146.

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