JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42

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Observations of atmospheric pollutants at during 2014–2015: Pollution status and the influence of meteorological factors

Bu Duo1,3,⁎⁎, Lulu Cui1,⁎⁎, Zhenzhen Wang1, Rui Li1, Liwu Zhang1, Hongbo Fu1,2,⁎, Jianmin Chen1,⁎, Huifang Zhang4, A. Qiong4

1. Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China 2. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Nanjing 210044, China 3. Department of Chemistry & Environmental Science, University, Lhasa 850000, China 4. Environmental Monitoring Center Station of , Lhasa 850000, China

ARTICLE INFO ABSTRACT

Article history: Atmospheric pollutants including SO2,NO2, CO, O3 and inhalable particulate matter (PM2.5 and

Received 19 November 2016 PM10) were monitored continuously from March 2014 to February 2015 to investigate Accepted 8 March 2017 characteristics of air pollution at Lhasa, Tibetan Plateau. Species exhibited similar seasonal

Available online 4 April 2017 variations except O3, with the peaks in winter but low valleys in summer. The maximum O3 concentration was observed in spring, followed by summer, autumn, and winter. The positive

Keywords: correlation between O3 and PM10 in spring indicated similar sources of them, and was Atmospheric pollutants assumed to be turbulent transport. Temperature was the dominant meteorological factor for

Biomass burning most species in spring. High temperature accelerates O3 photochemistry, and favors air Meteorological factors disturbance which is conductive to dust resuspension in spring. Relative humidity (RH) and Lhasa atmospheric pressure were the main meteorological factors in summer. RH showed negative correlations with species, while atmospheric pressure posed opposite situation. Wind speed (WS) was the dominant meteorological factor in autumn, the negative correlations between WS and species indicated diffusion by wind. Most species showed non-significant correlations with meteorological factors in winter, indicating the dependence of pollution on source emission rather than restriction by meteorology. Pollution weather character indicated that emissions were from biomass burning and dust suspension, and meteorological factors also

played an important role. Air stream injection from the stratosphere was observed during O3 pollution period. Air parcels from Southwest Asia were observed during air pollution period in

winter. An enhancement in air pollutants such as O3 would be expected in the future, more attention should be given to countermeasures for prevention of air pollution in the future. © 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

⁎ Corresponding authors. E-mail: [email protected] (Hongbo Fu), [email protected] (Jianmin Chen). ⁎⁎ These authors contributed equally to this work.

http://dx.doi.org/10.1016/j.jes.2017.03.010 1001-0742/© 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 29

and the most concentrated human activities of the Tibet Introduction autonomous region. At a high altitude above 3650 m, the absolute content of oxygen in Lhasa is about 68% of that at the Tibetan Plateau (TP) is the highest (average altitude of 4000 m sea level (Ran et al., 2014). Much different from other cities in above sea level) and one of the most remote plateaus on the Middle or Eastern China, Lhasa, with a history of limited world (Shao et al., 2016; Yang et al., 2013), with an area of energy consumption and religious activities such as the approximately 2.5 × 106 km2 and size of about one quarter of burning of juniper, has special atmospheric environment the Chinese territory, which extends over the area of 27°–45°N, which is much different from other cities on the world (Li 70°–105°E (Bu et al., 2015). It is an important ecological security et al., 2008; Tao et al., 2010). Furthermore, due to being the barrier for China and even for the whole of Asia (Loewen et al., largest city of the southern TP, it was suggested that pollutant 2007), which has long been identified to be critical in regulating emissions of Lhasa is a potential pollution source of the south the Asian hydrological cycle and monsoon climate (Yanai et al., TP (Yu et al., 2001; Zhang et al., 2001). Investigations on 1992; Wu and Zhang, 1998; Xu and Chan, 2001). Due to the surface trace gases have rarely been reported for Lhasa (Yu unique landform, fragile ecosystem, and special monsoon et al., 2001; Zhou et al., 2001; Tang et al., 2001; Dechen et al., circulation (Qiu, 2008), TP has been regarded as a sensitive 2008). Although the previous researches have indicated that region to anthropogenic impact. the air quality in Lhasa was quite fine in comparison with Due to the sparse human population and almost no many other cities in China (He et al., 2002), Lhasa occasionally industry (Zhu et al., 2013), TP is often presumed to be a pristine suffered from air pollution due to incomplete fuel combustion region. It is located at the juncture of several important natural in the low oxygen-containing atmosphere (Chaffin and and anthropogenic aerosol sources. Although it is surrounded Ullman, 1994; Bishop et al., 2001; Nagpure et al., 2011), as by the earth's highest mountains, anthropogenic emissions well the increasing motor vehicles and rapid development of from strong pollution events can occasionally be transported to tourism resulted in an increase of local atmospheric pollution the central TP by prevailing southwesterly winds (Xia et al., (Huang, 2001; Zhang et al., 2003). Atmospheric pollutants 2011). The high altitudes of the Himalayas block most of black reduce the visibility, degrade the air quality, and do harm to carbon (BC) particles intruding into the TP, but the Yarlung human health. Particles, such as inhalable particulate matter “ ” Tsangpo River valley serves as a leak by which contaminants (PM2.5), are of growing concern due to their deeper penetration can reach the southeast TP (Cao et al., 2010). Taklamakan and abilities into lung areas and more adverse health outcomes Gobi deserts are two major dust sources with long-range (Guo, 2015). Previous studies about trace elements of inhalable transport occurs mainly in spring (Liu et al., 2008). Research particulate matter (PM10) in Lhasa reported that the mean (Chan et al., 2006) showed that pollution from active fire elemental concentrations were generally comparable with regions in southern and western Asia had rather strong impact other European urban areas while much lower than some on the abundance of ozone (O3), trace gases and aerosols in the Asian cities (Cong et al., 2011). The sources of carbonaceous background atmosphere of TP. Relative high contents of aerosols include emissions from motor vehicles, biomass human harmful trace metals were found in some environmen- burning and religious activities of local residents, as well as tal matrices and large rivers of the TP area (Yang et al., 2007; emissions from ground vegetation and plant residues in soil Zhang et al., 2014a, 2014b; Zhang et al., 2002; Fu et al., 2008; (Huang et al., 2010; Yu et al., 2001). Huang et al., 2008). Trace elements related to anthropogenic In this research, systematically collected data of surface activities in snow and ice cores from TP and its surrounding nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide area, such as eastern Tien Shan, Mt. Muztagh Ata in the eastern CO, ozone (O3), and PM2.5 and PM10 during one year were Pamirs (Li et al., 2006), and Mt. Qomolangma (Everest) in the presented and analyzed in the detail. The seasonal variations of Himalayas (Kang et al., 2007; Lee et al., 2008; Hong et al., 2009; the air pollutants and meteorological factors were discussed in Kaspari et al., 2009) have been elucidated in several studies. the paper as well. Typical pollution weather and possible Researches showed that pollutants such as persistent organic emission sources were analyzed; backward trajectories were pollutants and heavy metals from South and Central Asia could used to trace the influence of long-distance air flow transpor- be carried into the TP region through long-range transport by tation. The results herein will serve to understand the air the atmospheric circulation (Huang et al., 2007; Loewen et al., pollution characteristics of Lhasa city and provide some 2007; Wu et al., 2009; Wang et al., 2010a, 2010b). Dusts and BC suggestions for the mitigation of atmospheric pollutants. from smoke of nearby Southeast Asian countries and the northern part of the Indian Peninsula (Engling et al., 2011) were significantly built-up in TP. Lu et al. pointed out that the 1. Measurement description contribution of BC from South Asia may account for 67% of BC transported to the Himalayas and the TP region (HTP) on an Six monitoring sites were located in environmental protection annual basis (Lu et al., 2012). Research found that the highly agency of Tibet autonomous region (A), Lhasa railway station elevated surface air over the Plateau may act as an “elevated (B), Barkhor Street (C), East Jiangsu Road (D), radiation station of heat pump” and alter the regional climate significantly through Doilungdêqên county (E), and former site of environmental the absorption of solar radiation by dust coupled with black protection bureau which is located across the Niangre road (F). carbon (Lau et al., 2006). The measurement of O3,SO2, CO, and NO2,alongwithPM2.5 and

Lhasa is the metropolis of the Tibet autonomous region of PM10 was conducted from 1st March 2014 to 28th February 2015

China, which is located in the middle of TP. It is a famous city in Lhasa. O3 was measured by a UV photometric analyzer for tourism, and an area with the highest population density (Thermo 49i, Thermo Fisher, USA), which uses a system on the 30 JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 principle of the Beer–Lambert law for measuring the ambient lowest RH was observed in winter (25% on average) and the

O3. The lowest detection limit of the analyzer is 0.5 ppb. SO2 was highest in summer (54.1% on average), and annually varied detected by a pulsed fluorescence analyzer (Thermo 43i, between 11% and 75%. The near-surface layer of Lhasa is Thermo Fisher, USA), the lowest detection limit is 0.05 ppb. A under the thermal low pressure control, the southwest gas filter correlation analyzer was used to measure CO monsoon invades into the Lhasa region each year since June concentrations and the lowest detection limit of the analyzer (Huang, 2001), and southwest wind brought the fresh air of is below 1 ppm. In addition, NO2 were continuously measured India ocean with high RH (Dechen et al., 2008), resulting that using an ambient nitrogen oxides analyzer (Thermo 42i, the temperature rises and rainfall increases during summer in Thermo Fisher, USA) with the lowest detection limit of Lhasa. Atmospheric pressure showed seasonal patterns

0.4 ppb. Particulate matters (PM2.5 and PM10)weremeasured opposite to RH and temperature, which was lower in with the continuous ambient particulate monitors, which summertime while higher in wintertime. TP was more sampled ambient air at flow rates of 10 L/min through particle influenced by solar radiation in summer and generated size separators and then through 47 mm filters. Particles were upward motion, and the low level convergence caused low sampled on the filters, and were weighed pre- and post- air pressure in summer. exposure with a microbalance. The inbuilt flow meter of the The frequencies of seasonally WD are displayed in Fig. 3. instrument is calibrated with an accuracy of ±2% (Singh et al., WD was mostly in WNW (West-North-West)–WSW (West- 2016), and the lowest detection limit is 0.06 μg/m3.Themean South-West) and ENE (East-North-East)–ESE (East South East) concentrations of the six stations were calculated and reported sectors as a result of the orientation of the Lhasa River valley in μg/m3 to represent the overall air condition in Lhasa. (Ran et al., 2014). The dominant WD was east in spring, but Meteorological parameters, including wind speed (WS), wind northwest in the other three seasons. WS was highest in direction (WD), temperature, relative humidity (RH), and spring but lowest in autumn. The plateau strong westerlies in atmospheric pressure, were provided by Lhasa meteorological wintertime contribute to the windy weather, while north bureau (Fig. 1). branch of the westerly jet northward in summertime leads to the weak wind. The annual average occurrence of calm conditions (lower than 1 m/sec) was about 2.5% and the 2. Results and discussion frequency of WS larger than 2 m/sec was around 25%.

2.1. Meteorological interpretation 2.2. Overview of observed concentrations

The day-to-day values of meteorological parameters such as Air quality index (AQI) is an indicator of air quality, and the RH, WS, WD, atmospheric pressure and temperature are mean annual AQI of Lhasa during 2014–2015 was 65, which was plotted in Fig. 2. Lhasa is located in the central part of the close to Beihai (Guangxi province), Qujing (Yunnan province) plateau with temperate arid and semi-arid plateau monsoon and Quanzhou (Fujian province). The air quality in Lhasa was climate. During the observation period, the annual mean much better than prosperous cities such as Beijing, Shanghai temperature was 5.1°C varying from −0.9 to 18.3°C. The and Nanjing, yet was worse than clean coastal cities such highest temperature was observed in summer (16.7°C on as Sanya and Haikou (Hainan province). Air quality was average) and the lowest in winter (0.5°C on average). RH considered as a major environmental risk to health where showed a similar seasonal pattern with temperature: the because individuals have little control for the exposure (Hanna

Fig. 1 – Sampling locations at Lhasa on Google map. JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 31

Fig. 2 – Time series of meteorological elements including relatively humidity, temperature, air pressure.

et al., 2016). As shown in Fig. 4, AQI that in the range of 0–50 heating and a small fraction of incense burning and vehicular – (excellent air quality) and 50 100 (good air quality) accounted exhaust (Ran et al., 2014), and the relatively low SO2 level was for 94.8% of the monitoring days, only 5.2% of monitoring days likely due to deindustrialization. The major sources of NOx in our study exceeded the Grade (II) of National Ambient Air emissions were industry sector, power plants, and on-road

Quality Standards (NAAQS) (GB3095-2012) for a 24 hr period. transportation (Yu et al., 2001). Compared to SO2, the higher

Slight pollution weather appeared in April, May, June, December concentration of NO2 indicates definite effect of on-road of 2014 and January of 2015, and moderate pollution weather transport in Lhasa. The most serious pollution period was appeared in December of 2014, January and February of between December and March of the next year with respect to

2015. Only one day of severe pollution weather occurred on the levels of SO2,NO2,CO,PM2.5 and PM10, possibly as a result of 25 December of 2014. increased emissions and accumulation within the boundary

As shown in Fig. 5, the concentrations of atmospheric layer. The highest daily mean mixing ratios of NO2,COand μ 3 pollutants stayed at low levels except for several parallel abrupt PM2.5 were 176, 3220 and 83 g/m , respectively, occurring on peaks in wintertime. The annual concentrations of SO2,NO2, 25th December, 2014.

CO, O3,PM2.5,andPM10 were 10.89, 21.94, 943.95, 100.27, 25.74, Fig. 6 shows the monthly mean variations of SO2,NO2, CO, μ 3 and 61.18 g/m , respectively, all of which were lower than the O3,PM2.5 and PM10 concentrations during the observation Grade (II) of NAAQS (GB3095-2012). With respect to daily mean period, the seasonal pollutants and AQI varied significantly by values, only two days of NO2 concentrations exceeded the k-independent samples nonparametric tests (p < 0.05). The

Grade (II) of NAAQS (GB3095-2012) throughout the year, while mean concentrations of CO, PM2.5 and PM10 were highest 3 μ 3 five days for O3, four days for PM2.5, and nine days for PM10. The in December (CO 1.58 mg/m ,PM2.5 48.62 g/m ,PM10 results indicated that the primary atmospheric pollutant in 89.39 μg/m3, respectively) and lowest in July (CO 0.64 mg/m3, μ 3 μ 3 Lhasa was PM10, followed by O3,PM2.5,andNO2. The level of SO2 PM2.5 14.12 g/m ,PM10 33.57 g/m , respectively). The highest μ 3 was the lowest among all the species, and had never exceeded SO2 concentration was observed in December (16.43 g/m ) μ 3 the Grade (I) of NAAQS (GB3095-2012) throughout the year. Lu and lowest in August (8.1 g/m ). The mean NO2 concentration μ 3 et al. (2011) reported that the contribution of SO2 from various was highest in January (39.2 g/m ) and lowest in March μ 3 anthropogenic sources was 60%, 32%, 6%, and 2% from power, (13.47 g/m ). Seasonally, the mean concentrations of SO2, industry, residential, and transport, respectively. In China, CO, PM2.5 and PM10 were highest in winter, followed by spring, power plants, industry, and domestic sources were the three autumn, and summer. The mean PM2.5/PM10 ratio was 55% in main contributors to SO2 emissions, responsible for about 59%, winter but was below 50% in the other three seasons, which 31%, and 10%, respectively by 2006 (Qu et al., 2016). In Lhasa, indicated that fine particles were dominant in winter. The emission sources of SO2 mainly include residential coal-fired variability of seasonal concentrations was likely due to 32 JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42

Fig. 3 – Distribution of wind speed (WS) and wind direction (WD) in the four seasons. N, S, W and E represents the wind directions of north, south, west and east, respectively.

meteorological factors such as RH, WS, as well as changing mainly emitted by industry, power plants, and on-road emission rates. Domestic heating was a notable reason for transportation (Yu et al., 2001). It is well known that Lhasa is sharp increase of pollutant concentrations in Lhasa. In located in a relatively pristine region with few industrial addition, aerostatic weather in winter led to poor dispersion sources, traffic emission contributed the most to NO2 concen- and accumulation of atmospheric pollutants while rainy tration. As was mentioned in the previous study by Huang weather in summertime was prone to scavenging and et al. (2010), the traffic volume increased drastically in summer cleaning the atmosphere. The NO2 concentration was highest and autumn, whereas the variation of traffic volume was in winter, followed by autumn, summer, and spring. As steady in spring. Thus it was assumed that the higher NO2 discussed above, the nitrogen oxides including NO2 were levels in summer and autumn than in spring was related to

Fig. 4 – Monthly air quality index (AQI) of Lhasa from 31st March, 2014 to 28th February, 2015. JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 33

– Fig. 5 Time series of atmospheric pollutants including SO2,NO2, CO, O3,PM2.5 and PM10 between March 2014 and February 2015. The yellow shadow shows pollutant levels during pollution episode I (24th April 2014 to 17th June 2014), episode II (18th December 2014 to 25th December 2014, and 14th January 2015), episode III (31st December 2014 to 3rd January 2015, 15th January 2015, and 19th February 2015) and episode IV (4th April 2014).

higher vehicular emissions during the summertime. Although the main reason for the increase of ozone concentration. The photochemical reaction should be higher in summer than in higher surface O3 concentration at Waliguan was positively spring, higher O3 concentration was observed in spring than in correlated with drier air mass (Ma et al., 2002), which was summer. The result suggested large-scale background of O3 in consistent with the situation in the stratosphere, indicating spring (Monks, 2000). Consistent results were observed in high close relation of high surface ozone concentration with the altitude global background sites such as Mauna Loa and stratosphere input. Surface ozone concentration increased with

Jungfraujoch station with altitude of 3397 and 3580 m, elevated vertical WS, it is suggested that higher O3 concentra- respectively (Jin et al., 2008). In addition, the annual O3 tion in spring than in summer was partly attributed to vertical concentration was higher than regional background station turbulent transport from the stratosphere in spring. such as Shangdianzi (Liu et al., 2006), but was close to the A further exploration of the relationships of SO2 and CO, NO2 region in high altitude regions such as Guangming Peak of and CO, SO2 and NO2 were conducted respectively to cast more Mountain Huang (Jin et al., 2008), indicating the altitude was light on emission sources of the primary gases. It was found one of the reasons that influence the ozone concentration in that the correlation coefficients of SO2 and CO, and SO2 and NO2 Lhasa. were 0.700 and 0.745 in winter, respectively, while 0.659 and

For a given region, the concentration of tropospheric O3 is 0.553, respectively in spring in a significant level (p <0.01).The usually determined by photochemical reactions of natural and good correlations among these primary gases in the cold season anthropogenic precursors, and transportion from other regions suggested common emission sources of SO2,NO2 and CO. In

(Donald J. Wuebbles et al., 2007). Correlation analysis showed Lhasa, SO2 is mainly from coal combustion for heating, whereas that O3 was positively correlated with PM10 and PM2.5 in less from incense burning and vehicular exhaust (Ran et al., significant levels (p < 0.01) in spring, indicating similar sources 2014), thus it was assumed that the emission from coal burning of O3 with dust which was assumed to be turbulent transport. for heating was the major common source of these three Researches folded up at Waliguan (Ding and Wang, 2006; Wang species in the cold season. In contrast, the poor correlation et al., 2006) demonstrated that the stratospheric injection was coefficients of SO2 with CO and NO2,andthemuchlowerSO2 34 JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42

– Fig. 6 Monthly variations of SO2,NO2,O3, CO, PM2.5 and PM10 concentrations. PM2.5 and PM10: inhalable particulate matter.

levels in summertime indicated different emission sources of 1998 to 2012 (Ran et al., 2014). In the present study, the highest μ 3 SO2 with CO and NO2, which were mainly from petrol and O3 concentration was 134.8 g/m in May, which was higher biomass burning in the warm season, as well as reduced coal than the value of about 121.7 μg/m3 in May 2012. This may combustion in summertime. imply that O3 photochemistry should be paid more attention Although Lhasa is well known as a non-industrial city with in the future due to increasing precursor emission and intense relative good air quality, it has undergone rapid urbanization solar radiation in this region. in recent years. Along with rapid urbanization process, increasing pollutants are expected to be accumulated in the 2.3. The effect of long-range transport urban air. Therefore, a comparison was made between the

NO2,SO2 and O3 levels measured in 1998 by a previous study It was well known that the long-range transport of air (Ran et al., 2014). It was found that during the measurement in pollutants would affect the sources at the sampling site μ 3 1998, NO2 concentration never exceeded 2.05 g/m , and the (Zhang et al., 2014a, 2014b). Lagrangian Integrated Trajectory

NO2 level in the present study was about 20 times of that in (HYSPLIT) model was used to calculate 72 hr back-trajectories

1998. The average SO2 concentration in the present study was for each day during different seasons. All of spring, autumn and about 22 times of that observed in 1998 (about 0.43 μg/m3). winter posed similar long-range trajectories from western Asia, The result clearly indicated a significant increase in emissions with proportions of 35%, 19% and 46%, respectively. The of NO2 and SO2 in the past 17 years. Municipal statistical data transport of pollutants from these countries via the air masses showed that the automobiles have increased by more than could significantly promote the level of pollutants at Lhasa. Air ten times (from less than 10 thousand in 1998 to over 150 masses originated from Nepal and northern India were also thousand in 2012) in the recent ten odd years (Ran et al., 2014). identified in these three seasons, accounting for 26%, 38% and

The increasing emissions of NO2 and SO2 were might 26% of all trajectories, respectively. Substantial evidence had attributed to a substantial growth in energy consumption demonstrated that the air pollutants (Atmospheric Brown and transformation of biomass into fossil fuels. With increas- Clouds) over South Asia could penetrate into the Himalayas ing precursor emissions during the urbanization process, as and impact the TP (Cong et al., 2015b). Thus the air masses well as sufficient solar radiation at Lhasa, O3 concentration might have transported a certain amount of pollutants to Lhasa. was expected to enhance. The previous study showed that O3 Another type of air mass was very short and mainly from local experienced obvious enhancement during summertime from emission, which occupied for about 39%, 43% and 28% in spring, JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 35

Table 1 – Gray correlation degrees between atmospheric autumn and winter, respectively. The air masses in summer pollutants and meteorological factors. were entirely different from that of the other three seasons.

CO SO2 PM2.5 NO2 PM10 O3 Three different types of source regions were identified according to pathways of the air: 84% was originated from Spring Southeast Asia, while 10% from India and 6% from Northwest Temperature (°C) 0.88 0.87 0.82 0.83 0.82 0.89 Wind speed (m/sec) 0.80 0.80 0.75 0.73 0.78 0.81 of China. The dominant air masses from India and Southeast Mean wind speed (m/sec) 0.84 0.83 0.80 0.80 0.81 0.82 Asia were related to the Southern Asia (Indian) monsoon, and Pressure (hPa) 0.74 0.86 0.81 0.84 0.82 0.88 diluted pollutants in the atmosphere (Xu et al., 2011; Ma et al., Relative humidity (%) 0.73 0.74 0.76 0.75 0.71 0.74 2014).

Summer Temperature (°C) 0.83 0.80 0.75 0.81 0.77 0.80 2.4. Role of meteorological factors on gaseous pollutants and Wind speed (m/sec) 0.74 0.74 0.70 0.71 0.70 0.78 PM Mean wind speed (m/sec) 0.75 0.75 0.71 0.73 0.73 0.76 Pressure (hPa) 0.83 0.80 0.75 0.82 0.71 0.77 Under the steady emission source conditions, pollutant Relative humidity (%) 0.81 0.75 0.70 0.82 0.77 0.80 concentration depends largely on meteorological conditions. Autumn In the present work, the Grey relational analysis (Table 1) and Temperature (°C) 0.76 0.81 0.66 0.69 0.66 0.83 Pearson correlation coefficients analysis (Table 2) were Wind speed (m/sec) 0.77 0.80 0.73 0.74 0.74 0.80 conducted to elucidate meteorological influence on air pol- Mean wind speed (m/sec) 0.69 0.72 0.64 0.64 0.63 0.73 lutants during different seasons in Lhasa. The results showed Pressure (hPa) 0.76 0.81 0.66 0.69 0.66 0.83 that the effect of meteorological factors on pollutants varied Relative humidity (%) 0.65 0.72 0.63 0.62 0.65 0.70 among seasons and species.

Winter The main meteorological factors influencing on CO, SO2,

Temperature (°C) 0.87 0.88 0.85 0.84 0.83 0.92 PM2.5 and PM10 were similar due to similar agglomeration, Wind speed (m/sec) 0.83 0.84 0.83 0.81 0.80 0.89 diffusion and removal mechanism of these species. In spring, Mean wind speed (m/sec) 0.85 0.85 0.84 0.83 0.80 0.88 temperature was the dominant meteorological factor for most Pressure (hPa) 0.88 0.89 0.85 0.84 0.82 0.92 species. Pearson coefficients showed that PM and O were Relative humidity (%) 0.83 0.83 0.83 0.80 0.80 0.86 10 3 positively related with temperature. High temperature could PM2.5 and PM10: inhalable particulate matter. accelerate air disturbance and was conductive to dust pollution

in spring. The distinct dependence of O3 on temperature

Table 2 – Pearson correlation coefficients among trace gases and PM with meteorological parameters over Lhasa during different seasons from 1st March 2014 to 1st March 2015.

CO SO2 PM2.5 NO2 PM10 O3

Spring ⁎⁎ ⁎⁎ ⁎⁎ ⁎⁎ Temperature (°C) 0.32 0.69 0.01 0.03 0.33 0.55 ⁎⁎ ⁎⁎ Wind speed (m/sec) 0.06 0.11 0.01 −0.36 0.27 0.13 ⁎⁎ ⁎ Mean wind speed (m/sec) 0.15 0.08 0.12 −0.18 0.29 0.23 ⁎ ⁎⁎ Pressure (hPa) −0.03 0.23 0.09 0.45 −0.09 0.03 ⁎⁎ ⁎ ⁎⁎ Relative humidity (%) 0.11 0.33 0.25 0.28 −0.18 0.19

Summer ⁎⁎ ⁎⁎ ⁎ ⁎⁎ ⁎⁎ Temperature (°C) −0.11 0.48 0.67 −0.26 0.70 0.41 ⁎⁎ Wind speed (m/sec) −0.13 0.08 0.06 −0.38 0.05 0.10 ⁎ Mean wind speed (m/sec) −0.01 0.06 0.06 −0.23 −0.02 0.11 ⁎ ⁎⁎ ⁎⁎ ⁎ ⁎⁎ Pressure (hPa) 0.24 65 0.48 0.21 0.51 −0.04 ⁎⁎ ⁎⁎ ⁎ ⁎⁎ ⁎⁎ Relative humidity (%) 0.14 −0.41 −0.72 −0.25 −0.74 −0.43

Autumn ⁎⁎ ⁎⁎ ⁎⁎ ⁎⁎ Temperature (°C) −0.73 −0.11 −0.64 −0.66 −0.47 −0.20 ⁎⁎ ⁎ ⁎⁎ ⁎⁎ Wind speed (m/sec) −0.45 −0.11 −0.24 −0.38 −0.34 0.04 ⁎⁎ ⁎⁎ ⁎⁎ ⁎⁎ Mean wind speed (m/sec) −0.28 −0.09 −0.29 −0.34 −0.38 0.05 ⁎⁎ ⁎⁎ ⁎ ⁎⁎ ⁎ Pressure (hPa) 0.33 0.17 −0.29 −0.25 0.37 −0.23 ⁎⁎ ⁎⁎ ⁎⁎ ⁎⁎ Relative humidity (%) −0.74 0.05 −0.61 −0.65 −0.64 −0.11

Winter ⁎ ⁎ Temperature (°C) 0.14 −0.11 0.17 0.03 0.27 0.22 Wind speed (m/sec) −0.21 −0.07 −0.12 −0.19 −0.16 0.13 Mean wind speed (m/sec) −0.05 0.11 0.01 −0.02 −0.03 0.02 Pressure (hPa) −0.07 0.12 0.12 −0.07 0.08 −0.05 Relative humidity (%) −0.11 −0.16 −0.05 −0.21 −0.10 −0.03

⁎ The significance level at 95%. ⁎⁎ The significance level at 99%. 36 JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42

suggested that O3 photochemistry played an important role in or India monsoon together with the westerlies were the

O3 formation. SO2 and CO were negatively correlated with prevailing meteorology for TP (Wang et al., 2010a; Wang et al., temperature, both of which might be attributed to local 2010b). More precipitation occurred and air pollutants were hydrothermal conditions; however, the mechanism was un- thus rinsed under the influence of the Asian summer monsoon. clear and remained to be explored. SO2,NO2 and PM2.5 were The formation and accumulation of O3 were also inhabited, positively correlated with RH. The possible reason was that since precipitation could rinse O3 and its precursors in the surface dust was easily carried by wind under low RH in spring. troposphere (Ma et al., 2014). NO2 was negatively correlated

The dust combined with water vapor in the air and formed fog with temperature while both PM10 and PM2.5 posed the opposite and haze, as a result the gaseous pollutants were not easy to situations. Higher temperature made the photochemical reac- diffuse. PM10 and O3 were positively correlated with WS. It was tion very active in the atmosphere. It was well documented that well known that strong wind was conductive to suspension of NO2 reacted with the radicals could generate more secondary fugitive dust and regional transport of O3 (Ran et al., 2014). particles (Gao et al., 2016) (Figs. 7, 8 and 9). In summer, atmospheric pressure was the dominant mete- In autumn, WS was the dominant meteorological factor orological factor for CO, SO2, and PM2.5.RHwasthedominant influencing on CO, NO2,PM2.5 and PM10. Atmospheric pressure factor for PM10 and NO2. Temperature was the dominant factor was the dominant factor for O3.SO2 was most closely related to for O3. Atmospheric pressure was positively correlated with all temperature. CO, NO2,PM2.5 and PM10 were negatively correlat- species, and was relatively low in summer as shown in Fig. 2. ed with WS, indicating that WS played an important role in High atmospheric pressure controlled condition was prone to pollution diffusion in autumn. Temperature was negatively internal air current sinks and deposition. RH showed significant correlated with CO, NO2,PM2.5, and PM10. One reason was the negative correlations with the species except for CO. Southwest domestic heating emission contribution due to monthly

Fig. 7 – Representative types of long-range transport route for air masses for different seasons during 2014–2015. JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 37

Fig. 8 – 72 hr backward trajectories calculated from NOAA (U.S. National Oceanic and Air Administration) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model at 8, 5 and 1 km on 24th April, 12th May, 22nd May, 23rd May and 17th June, 2014.

temperature decline in autumn. Topographic inversion may activity was thus more active, which was beneficial to dust be another reason. Lhasa is located in the Lhasa River Valley resuspension (Zheng and Zhou, 2010; Huang, 2001). Plain and is surrounded by mountains. Temperature decline leads to a faster cooling action on mountain slopes than that 2.5. Analysis of typical pollution events and influence of in the river valley, resulting that the mountain breeze sank transported pollutants and conducted to pollutant accumulation. According to Pearson coefficients, increased RH is prone to removing In the present study, we defined pollution weather as AQI species including CO, NO2,PM2.5,andPM10 in autumn. exceeding 100. Based on such criteria, the pollution days were Atmospheric pressure is positively correlated with CO and identified in April, May, June, December of 2014 and January,

PM10, while negatively correlated with PM2.5 and O3.The February of 2015. Generally, the pollution events were complex relationships were possibly explained by changing categorized into four episodes according to pollution charac- pressure anomalies in the autumn. teristics. The meteorological conditions and daily averaged In winter, atmospheric pressure was the dominant mete- concentrations of atmospheric pollutants are shown in orological factor for CO, SO2 and PM2.5, while temperature was Table 3. Backward trajectories at three altitudes of 100, 500 the dominant for PM10 and O3,NO2 was closely related with and 1000 m above ground level were conducted by Hybrid both temperature and atmospheric pressure. However, mete- Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) to orological factors had no significant influence on most of the trace the transport pathways of pollution air masses (Draxler pollutants except PM10 and O3, which indicated that source and Rolph, 2010). Specially, the backward trajectories of O3 emission exerted more obvious impact on pollutants than the were conducted at the altitudes of 8000, 5000 and 1000 m meteorological factors in winter. O3 was positively correlated above the ground level to confirm whether or not input of O3 with temperature, which means O3 photochemical reaction from the stratosphere. The total run time of each trajectory played an important role in O3 formation in winter. Temper- was 72 hr, with arriving time at 0:00 UTC (coordinated ature was positively correlated with PM10, the increase of universal time) every day. temperature caused surface thaw, the particles were relative- During the episode (I), AQI varied from 102 to 118. O3 ly loose due to relative low humidity in winter, the turbulent concentration ranged at 160.6–175.6 μg/m3, which were higher 38 JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42

Fig. 9 – 72 hr backward trajectories calculated from NOAA (U.S. National Oceanic and Air Administration) HYSPLIT model at 1000, 500 and 100 m during the pollution episodes (II), (III) and (IV). HYSPLIT: Hybrid Single-Particle Lagrangian Integrated Trajectory. JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42 39

Table 3 – Meteorological conditions and daily averaged concentrations of atmospheric pollutants during pollution events. μ 3 Pollution Date Temperature Relative Wind Wind O3 ( g/m ) Daily averaged episodes (°C) humidity speed direction (8 hr means) concentrations (μg/m3) (%) (m/sec) SO2 NO2 CO PM2.5 PM10

I 24 April 2014 10 35 3.5 ESE 160.6 14.7 15.6 1200 42.5 107 12 May 2014 14.5 30 2.3 ESE 175.6 13.3 20.5 1200 27.4 84 22 May 2014 18.6 22 2.1 WSW 169.4 13.4 10.6 1400 28 76.6 23 May 2014 17 29 3.9 ESE 161.7 15.4 14.8 1400 30.8 93.3 17 June 2014 18.5 18 2.9 ESE 168.7 12.3 17.9 800 35.1 43.8 II 18 September 2014 −4.1 27 1.7 NE 28 30 85 2680 131 147 20 September 2014 −1.4 26 1.6 NE 42 22 65 2300 71 70 22 September 2014 0.3 23 2 W 41 27 70 2890 103 153 25 September 2014 −0.6 21 1.6 ESE 36 32 83 3220 122 176 14 January 2015 −1.1 35 1.2 ESE 48 28 44 2170 73 100 III 02 January 2015 1.8 27 1.2 SSE 95 13 16 1560 31 265 03 January 2015 4.1 32 2.4 W 100 7 11 1130 43 296 15 January 2015 −0.9 31 1.2 WSW 77 14 78 1150 52 167 19 February 2015 0.1 61 1.5 WSW 80 7 5 480 28 198 31 December 2014 −0.6 22 1.1 E 85 11 16 1140 23 213 01 January 2015 0 28 1.1 ESE 75 12 21 1450 41 245 IV 4 April 2014 4.4 61 2.5 ESE 127.1 12.2 14.4 1200 80.1 58.3

ESE, WSW, NE, W, and SSE represent the wind directions of east-south-east, west-south-west, northeast, west, and south–south-east, respectively.

than the Grade (II) of NAAQS (GB3095-2012), while the CO concentrations indicated intensive biomass burning dur- concentration of SO2,NO2, CO, PM2.5, and PM10 ranged at ing this period. The pollutants on 18th December were 12.3–15.4, 10.6–20.5, 0.8–1.4, 28.0–42.5, and 43.8–107.0 μg/m3, proposed to have been emitted from the Death of Tsongkapa respectively, all of which were lower than that of the Grade (II) of Tibetan, and pollution on 22nd December was proposed to of NAAQS (GB3095-2012). During this period, the average be caused by emission from Weisang religious ritual. The surface WS varied between 2.1 and 3.9 m/sec, and the Backward trajectories showed that the air masses at height of maximum WS was between 4.2 and 7.3 m/sec. The higher 100, 500 and 1000 m on 18th December were originated from

WS was conductive to the O3 regional transport. The earth's Northwestern China. On 20th, 22nd, and 25th December of ozone is mainly concentrated in the 10 km to the 50 km 2014, the trajectories at the altitudes of 100, 500 and 1000 m region of the stratosphere (Zhang and Zhou, 2008). Backward were originated from Southwest Asian countries, which trajectories indicated that air masses at middle troposphere of arrived at Lhasa with low WS and might impact the air quality 8 km were originated from upper levels of about 14 km, at Lhasa. On 14th January of 2015. The trajectories at height of indicating O3 invasion from the stratosphere at the relative 1000, 500 and 100 m were originated from Bhutan, which was altitude of 8 km. At the relative altitude of 5 km, the air low industrialized with fresh air, therefore, the air was masses traveled from the height exceeding 10 km, indicating polluted by local biomass burning emission. Weisang reli- potential transport at the vertical direction from the strato- gious ritual was conducted on this day, torch burning was the sphere. Trajectories at 1 km were originated from high levels main contributor of air pollution. Research showed that exceeding 5 km on 24th April, 23rd May, 17th June, indicating aerosol optical thickness could increase by 10 times and the exchange of O3 between the surface and the upper levels. caused serious pollution to the local air by torch burning The air masses were originated from upper levels at first, and during Weisang religious activities on religious days (Zhang, then reduced to low levels when passing Lhasa, which might et al., 2014a, 2014b). impact the O3 concentrations on 12th May and 22nd May. During the episode (III), PM10 concentrations sharply in- AQI in the episode (II) ranged from 102 to 219. During this creased up to 198–296 μg/m3, which were much higher than the period, the concentrations of SO2,NO2, CO, PM2.5 and PM10 Grade (II) of NAAQS (GB3095-2012), while concentrations of SO2, – – – – – increased simultaneously and ranged at 28 32, 44 85, 2.17 NO2, CO, O3, and PM2.5 were all stayed at low levels (7 13, 5 78, 3.22, 73–131, and 70–153 μg/m3, which was 2.02–2.94, 2.01– 0.48–1.56, 75–100, and 23–43 μg/m3, respectively). The ratios of – – – 3.88, 2.31 3.43, 2.76 6.84, and 1.14 2.50 times higher than the PM2.5/PM10 ranged at 0.11 to 0.31, indicating domination of yearly means, respectively. The concentrations of NO2 and coarse particles. The pollutants on 31st December were

PM2.5 on 18th and 25th of December were higher than the proposed to have been emitted from Weisang ritual on this

Grade (II) of NAAQS (GB3095-2012), while PM10 on 22nd of day, and pollution during 1st January and 3rd January of 2015 December exceeded the emission standard. The low WS of was caused by firecracker combustion of the Lantern Festival. 1.2–2 m/sec during this period indicated poor dispersion On 31st December of 2014, the trajectories at the three altitudes condition and dominant local anthropogenic pollution. The of 100, 500 and 1000 m were originated from Bhutan, Nepal, ratios of PM2.5/PM10 were between 0.73 and 1.00, suggesting India. The air parcels blew very slowly when arrived at Lhasa that fine particles were dominant. CO arises from incomplete and might impact the air quality near the ground. The air combustion of biofuels (Tiwari et al., 2016), sharply increased masses on 1st, 2nd and 3rd January of 2015 showed similar 40 JOURNAL OF ENVIRONMENTAL SCIENCES 63 (2018) 28– 42

pathways, and those at 500 m and 1000 m were originated from spring. High temperature could accelerate O3 photochemistry, Bhutan, Nepal, India, Bangladesh, while at 100 m were origi- and air disturbance caused by temperature increase was nated from Bhutan, India, Bangladesh and moved slowly when conductive to dust pollution in spring. RH and atmospheric arrived at Lhasa. Bangladesh, Nepal, India suffered from serious pressure were the main meteorological factors in summer. dust pollution, thus the long-path air mass from these countries Higher RH in summer was conductive to washout of pollut- carried dust into Lhasa. Studies showed that high PM loading ants. WS was the dominant factor in autumn, the negative has been observed in South Asia (Liu et al., 2015; Tiwari et al., correlations between WS and pollutants indicated diffusion 2015a). The air masses on 15th January of 2015 were originated effect of wind. Most species showed non-significant correla- from Bhutan with clean air, indicating the pollution by local tions with meteorological factors in winter, indicating more emission. It's worth noting that concentrations of NO2 in- obvious effect of source emission than meteorology. creased obviously on this day, which exceeded the Grade (II) of TP is a western alpine region with harsh climatic conditions,

NAAQS (GB3095-2012). Both PM2.5 and CO concentrations were fragile ecology and underdevelopment economic, thus the relatively high compared with the annual average levels while consequences are unthinkable once air pollution crisis hap-

SO2 was close to the annual average. Biomass combustion may pens. Lhasa is an important city and a direct source of pollution be the main reason. 19th February was the spring festival of in the Qinghai TP. Urban air pollution in Lhasa is a potential risk μ 3 2015, the concentration of PM10 was 198 g/m on this day. to the local ecological environment and natural resources of TP. Backward trajectories showed that the all the air masses at The continuous urbanization and tourism industry develop- height of 100, 500 and 1000 m were originated from the territory ment is no doubt an ordeal to atmospheric environment in of Tibet and Bhutan. The air in Bhutan was clean, indicating Lhasa. It is proposed that purification measures should be taken high local emission of PM10. Static weather condition (WS of against traditional fuel combustion for residents living and 1.5 m/sec as well as RH of 61%) coupled with large amounts of religious activities. In addition, atmospheric reactions, and the firecrackers setting off during spring led to aggregation of PM10. optical properties of aerosols are deserved to be studied to form AQI on 4th April of 2014 showed slight pollution. The effective air quality management strategies for policy-makers μ 3 concentration of PM2.5 was 80.1 g/m , which was higher than and researchers. the Grade (II) of NAAQS (GB3095-2012), while the concentrations of SO2,NO2,O3,CO,andPM10 were 12.2, 14.4, 127.1, 1.2, and 53.8 μg/m3, respectively and were all lower than the Grade (II) of Acknowledgments NAAQS (GB3095-2012). Backward trajectories showed that air masses at the three altitudes of 100, 500 and 1000 m were mainly This work was supported by the National Natural Science originated from Bhutan with good air quality. The pollution of Foundation of China (Nos. 21577022, 21190053, 40975074) and

PM2.5 was suggested to be contributed by torch burning during Ministry of Science and Technology of China (2016YFC0203700). the Weisang religious ritual on this day. RH was 61% on this day, which was not enough for flushing the air pollutants, instead the thick water layer attributed to high RH favors heterogeneous REFERENCES reactions and was conductive to PM2.5 pollutions (Li et al., 2011).

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