Relative impact of short-term emissions controls on gas and particle-phase oxidative potential during the 2015 China Victory Day Parade in Beijing, China

Atmospheric Environment 183 (2018) 49–56

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Relative impact of short-term emissions controls on gas and particle-phase oxidative potential during the 2015 China Victory Day Parade in Beijing, China

T

Wei Huanga,b, Dongqing Fangb, Jing Shangb, Zhengqiang Lie, Yang Zhangb,c, Peng Huob,c, Zhaoying Liuf, James J. Schauerg,h, Yuanxun Zhangb,c,d,∗ a

Institute for Environmental Reference Materials of Ministry of Environmental Protection, Beijing, China College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China Huairou Eco-Environmental Observatory, Chinese Academy of Sciences, Beijing, China d CAS Center for Excellence in Urban Atmospheric Environment, Chinese Academy of Sciences, Xiamen, China e State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China f Beijing Municipal Environmental Monitoring Center, Beijing, China g Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, WI, USA h Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA b c

G R A P H I C A L A B S T R A C T

A R T I C LE I N FO

A B S T R A C T

Keywords: Short-term emissions controls Parade blue Reactive oxygen species Online measurement Field observation

A field observation focusing on reactive oxygen species (ROS) was conducted before, during, and after the 2015 China Victory Day Parade to understand the influence of short-term emissions controls on atmospheric oxidative activity. The hourly average concentrations of PM2.5, SO2, NO, NO2, CO, O3, as well as gas and particle-phase ROS, were measured using a series of online instruments. PM2.5 concentrations during control days were significantly lower than non-control days, which directly lead to the “Parade Blue”, yet reductions of most gaseous pollutants except SO2 were not so obvious as PM. Similarly, the control measures also led to a great loss of particle-phase ROS throughout the control period, while the reduction of ROS in gas phase was not obvious until the more stringent measures implemented since September 1. Furthermore, only weak positive correlations were observed among ROS and some other measured species, indicating ROS concentrations were affected by a number of comprehensive factors that single marker could not capture. Meanwhile, meteorological condition and regional transportation were also shown to be the minor factors affecting atmospheric oxidizing capacity. The results of this observation mainly revealed the control measures were conducive to reducing particle-related ROS. However, the reduction of gas-phase ROS activity was less effective given the menu of controls employed for the 2015 China Victory Day Parade. Therefore, short-term emissions controls only aimed to PM reduction and

∗

Corresponding author. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China. E-mail address: [email protected] (Y. Zhang).

https://doi.org/10.1016/j.atmosenv.2018.03.046 Received 5 November 2017; Received in revised form 13 March 2018; Accepted 20 March 2018 Available online 22 March 2018 1352-2310/ © 2018 Elsevier Ltd. All rights reserved.

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visibility improvement will produce the blue sky but will not equivalently reduce the gas-phase ROS. Supplemental control measures will be needed to further reduce gas-phase ROS concentrations.

1. Introduction

largely reduced. Since oxidative stress in the lung caused by reactive oxygen species (ROS) is believed to be a major contributor to air pollutant-related adverse health effects (Fischer and Maier, 2015; Gupta et al., 2014; Li et al., 2003; Seifried et al., 2007), ROS can be regarded as an important indicator to evaluate the health risks of air pollution. For this reason, ROS, whether directly inhaled from ambient air (exogenous ROS) or formed within cells when stimulated by introduced air pollutants (endogenous ROS), has gradually gained more and more attention among atmospheric researchers (Chen et al., 2011; Chung et al., 2006; Lin and Yu, 2011; Verma et al., 2012; Zhang et al., 2008). Atmospheric ROS, a series of oxygen-containing species with strong oxidizing abilities containing hydroxyl radical (HO∙), superoxide anion (O2∙-), and hydrogen peroxide (H2O2) (Halliwell and Cross, 1994), can be formed in gas and particle phases. The traditional methods for ROS measurement, including dithiothreitol (DTT) assay (Lin and Yu, 2011; Verma et al., 2012), 2′,7′-dichlorofluorescin (DCFH) assay (See et al., 2007; Venkatachari et al., 2005), and respiratory tract lining fluid (RTLF) assay (Mudway et al., 2005), were usually performed after the longtime sampling and pretreatment, which may lead to an underestimation of true ROS concentration due to the great loss of short-life species. To avoid the artifacts associated with these offline methods, a few ROS online systems were developed recently based on DCFH assay (Fuller et al., 2014; Huang et al., 2016b; King and Weber, 2013; Venkatachari and Hopke, 2008; Wang et al., 2011). Among these online instruments, the GAC-ROS which refers to a ROS analysis system equipped with a GAC (gas and aerosol collector) sampler was the first to realize the simultaneous measurement of gas and particle-phase ROS (Huang et al., 2016b), while others can only analyze ROS related with particulate matter (PM). In this study, a field observation was conducted during the 2015 China Victory Day Parade to characterize the concentration of atmospheric ROS using GAC-ROS and investigate the effects of short-term control measures on atmospheric oxidative activity. Meanwhile, PM and some gaseous pollutants were observed to reveal the influential factors of ROS concentration. This study was the first time to simultaneously obtain the concentrations of both gas and particle-phase ROS during the field observation associated with short-term air quality control measures, which will give applicable suggestions for future short-term policies.

Air quality issue has become a very big concern in megacities of China following the rapid economic growth and urbanization nationwide (Chan and Yao, 2008; Fang et al., 2009; Zhao, 2012). In consideration of the adverse effects on eco-environment and human health attributed to air pollution (Ayres et al., 2008; Gauderman et al., 2007; Peters et al., 2006; Pope et al., 2004; Schwartz et al., 2002), a series of air quality control measures were implemented during the 11th and 12th Five Year Plan (2006–2010 and 2011–2015), including afforestation, traffic restriction, and energy upgrading for motor vehicles (eg: upgrading the quality of gasoline product and application of new energy vehicles) (Wang and Hao, 2012; Zhang et al., 2016). In addition to these long-term measures, short-term policies with more stringent measures were also conducted to ensure the air quality during some specific periods, such as the 2008 Beijing Olympic Games (Guo et al., 2012; Huang et al., 2010), 2010 Shanghai World Expo (Huang et al., 2012, 2013), 2010 Guangzhou Asian Games (Ting-Yuan et al., 2012; Yao et al., 2013), and 2014 Asia-Pacific Economic Cooperation (APEC) conference (Huang et al., 2015; Wang and Dai, 2016). Using the successful experiences of previous policies as the references, Beijing government and China's Ministry of Environmental Protection enacted similar air pollution mitigation measures to improve air quality during the 2015 China Victory Day Parade. These measures were implemented between August 20 and September 3, including the odd-and-even license plate rule for vehicle use, polluting industry restriction, construction sites shutdown, delay of school opening, vacation days off for the public, and more frequent road sprinkling (BMPC, 2015). The efficiency of the control measures has been demonstrated by “Parade Blue” and the results of some field observations (Wang et al., 2017; Xu et al., 2017). Gui et al. (2016) investigated aerosol optical properties in Beijing from August 6 to September 17 using a series of ground-based monitors, revealing significant reductions in aerosol optical depth (AOD) and PM2.5 mass concentration. Han et al. (2016) and Shen et al. (2016) observed similar results about PM concentrations, as well as some other pollution parameters like particle number concentration and water-soluble ions. Generally, most of the short-term control measures were aimed to PM and visibility which were directly associated with “blue sky”, and the related literature also mainly focused on the reductions of PM2.5 and its chemical compositions (Han et al., 2016; Yang et al., 2016). Therefore, the excellent efficiencies of such short-term policies were always obtained in the form of PM reduction and visibility improvement. However, considering the lack of monitoring parameters which can reflect the health impact related to air quality, it cannot be concluded that the adverse health risks exerted by air pollutants were

2. Experimental methods 2.1. Study design Field observation was conducted from August 16 through September 10, 2015 at the Institute of Remote Sensing and Digital Earth

Table 1 Control measures implemented in different phases. “✓” means the control measure was implemented in this period.

long-term routine measures short-term routine measures

odd-and-even license plate rule for vehicle use polluting industry restriction construction sites shutdown delay of school opening vacation days off more frequent road sprinkling road traffic control around Tiananmen Square museum and tourist attraction closedowns enhanced measures in surrounding cities

50

Phase I

Phase II

Phase III

Phase IV

✓

✓ ✓ ✓ ✓ ✓

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

✓

✓

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Fig. 1. Time series of PM2.5 and gas pollutant concentrations during the 2015 China Victory Day Parade study period.

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(Huang et al., 2016b). The GAC-ROS consists of three sections which were applied to ROS collection, reaction & transportation, and detection, respectively. The principle of this instrument has been described in detail elsewhere (Huang et al., 2016b). In brief, ambient air is pumped through a cyclone separator to remove the particles with aerodynamic diameters larger than 2.5 μm before getting into the dullpolished wet annular denuder of the GAC sampler, where gaseous species are absorbed by the thin water film formed on the inner surface under continuous rotation. Meanwhile, PM2.5 will pass through the denuder to mix with supersaturated water vapor at a temperature of 120 °C and then grow into large droplets as condensation nuclei in the coil aerosol cooler. Finally, the particle slurry and the solution containing gas-phase ROS are injected into two different reactors for reaction with DCFH in the presence of horseradish peroxidase (HRP) based on an optimized DCFH assay (Huang et al., 2016a). The reacted solutions are then transported into the fluorescence detector for analysis with the time interval of 10 min between the measurements of gas and particle-phase ROS. Therefore, the time resolution for ROS measurement is 20 min. Once the GAC-ROS starts running, 1 L of the fresh DCFH and HRP solutions should be prepared at least every two days with the calibration curves built daily to ensure high quality of the ROS concentration data.

of Chinese Academy of Sciences (40°0′15.78″ N, 116°22′44.00″ E), which is located between the North Forth Ring Road and North Fifth Ring Road in Chaoyang District, Beijing. The detailed geographical location of the sampling site is shown in Fig. S1. All instruments were set up in an observation room on the rooftop of a five-story office building with the sampling tube extending about 1.5 m high outside. During the sampling period, the 15th World Championships in Athletics was held in the Bird Nest Stadium from August 22–30. Therefore, the organizing committee and government paid more attention to the air quality of the nearby areas covering our sampling site. According to the detailed short-term control measures enacted by the Beijing government (BMPC, 2015), the sampling period of this observation can be divided into four phases: Phase I, August 16–19, represents air quality before the control period; Phase II, August 20–31, covers air quality effected by short-term control measures; Phase III, September 1–3, reflects the enhanced control period; Phase IV, September 4–10, represents the post-control period. The reduction policies implemented in different phases are described in Table 1. Compared to Phase II, more additional measures such as road traffic control around Tiananmen Square, museum and tourist attraction closedowns, vacation days off, and odd-even traffic restrictions in surrounding cities were enacted during Phase III to ensure blue sky in the 2015 China Victory Day Parade (BMPC, 2015). The concentrations of ROS, PM, and gaseous pollutants were observed all throughout the four phases. Moreover, photos of skies above the study location were taken every morning to get an intuitive feel for the air quality.

2.3. Meteorological data and backward trajectories Meteorological data used in the current study, including ambient temperature, relative humidity, dew point temperature, atmospheric pressure, and wind speed and direction, were collected from a commercial weather service: Weather Underground. Meanwhile, an interactive Hybird Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model provided by the National Oceanic and Atmospheric Administration (NOAA) of the United States was employed to simulate the mean backward trajectories of air parcel during the four sampling phases (Draxler and Rolph, 2003; Stein et al., 2016). The meteorological parameters for trajectory computation and clustering were downloaded from the Global Data Assimilation System (GDAS) one-

2.2. Instruments For acquisition of real-time data with high time resolution, a series of online instruments were used in the field observation including an ambient particulate monitor (TEOM 1405, Thermo Scientific, USA), an ozone analyzer (Model 49i, Thermo Scientific, USA), a SO2 analyzer (Model 43i, Thermo Scientific, USA), a NOx analyzer (Model 42i, Thermo Scientific, USA), a CO analyzer (Model 48i, Thermo Scientific, USA), and an own-developed ROS sampling-analysis system: GAC-ROS

Fig. 2. Time series of daily distributions of particle and gas-phase ROS concentrations during the 2015 China Victory Day Parade study period. The dashed line represents the daily mean ROS concentrations and the solid line represents the daily median ROS concentration. The box represents the 25th-75th percentiles of daily ROS concentrations and the whiskers represent the 5th and 95th percentiles of daily ROS concentrations. 52

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degree dataset. Each trajectory was run back for 72 h from the start location of 500 m above the ground level, and all trajectories were clustered within different phases using the offline HYSPLIT-4 software.

Table 2 Correlations between ROS and other pollutants during the 2015 China Victory Day Parade study period.

3. Results and discussion Gas-phase ROS Particle-phase ROS

3.1. PM and gas pollutants

PM2.5

NO

NO2

SO2

O3

CO

0.424∗∗ 0.546∗∗

0.112∗∗ 0.138∗∗

0.134∗∗ 0.243∗∗

0.356∗∗ 0.334∗∗

0.335∗∗ 0.163∗∗

0.226∗∗ 0.304∗∗

*: p < 0.05; **: p < 0.01.

Fig. 1 shows the variations of concentrations for PM2.5 and gas pollutants during the sampling period. As depicted in the figure, the concentration of PM2.5 decreased rapidly at the beginning of Phase II and remained at a low level throughout the control period (Phase II and Phase III), except for a relative high peak in the wee hours of August 23, which reflected an obvious improvement of PM pollution under the strict control. However, as soon as the short-term policy ended at midnight on September 3, the PM2.5 concentration raised immediately due to the unrestricted emission. Similar to PM2.5, the levels of SO2 concentration fell remarkably in Phase II and Phase III, yet variations of other gas pollutants did not present the same trend. As shown in Fig. 1, no significant reduction of these gaseous species was observed in the control period, especially for Phase II, which was probably attributable to the less effective control measures exerted on these gas compounds than SO2. Therefore, while considering the main purpose of coal burning in the non-heating season, the variation of SO2 implied a positive effect from limited use of industrial coal. Meanwhile, the synchronous peaks of PM2.5 and SO2 appearing in Phase II were likely to be caused by temporary emission of some point sources associated with coal burning around the sampling site. In addition, the concentrations of most pollutants especially for NOx, increased sharply during the daytime of a three-day period in Phase IV due to the terrible traffic conditions in back-to-school days of Beijing (September 6–8).

of equivalent H2O2 concentrations. Fig. 2 shows the daily variations of ROS concentrations during the 2015 China Victory Day Parade, which reflects different temporal distributions between gas and particle-phase ROS. The concentrations of particle-phase ROS during Phase II and Phase III were significantly lower than those measured in non-control days, which was nearly in accordance with PM2.5 variation. However, the reduction of ROS in the gas phase was not distinct in Phase II until the more stringent measures were carried out as Phase III began, revealing that the effects of environmental strategies implemented in Phase II were not obvious for reducing gas-phase oxidative potential, and the additional control measures in Phase III were much more effective in weakening the oxidizing activities of gas pollutants compared to Phase II. Due to the discrepancy on distribution patterns of ROS in gas and particle phases, the ratios between concentrations of gas and particle-phase ROS varied among different periods. As shown in Fig. 3, the ratios of gas-phase ROS to particle-phase ROS were significantly higher in Phase II than other sampling periods, as well as more obvious fluctuation within each day. During this period, gas-phase ROS accounted for a considerably higher fraction of atmospheric oxidizing capacity attributable to dramatic reduction of particle-phase ROS vs inconspicuous change of ROS associated with gaseous species. For this reason, the ratio reached the peak on August 26 due to the lowest daily average concentration of particle-phase ROS. From the point of human health, these results indicated the control measures were conducive to reduce the particle-related health impacts, while the improvements towards adverse effects associated with gaseous species were not so

3.2. ROS activity ROS activities observed in the current study were expressed in terms

Fig. 3. Time series of the daily concentration ratios between gas- and particle-phase ROS during the 2015 China Victory Day Parade study period. The dashed line represents the daily mean ROS concentrations and the solid line represents the daily median ROS concentration. The box represents the 25th-75th percentiles of daily ROS concentrations and the whiskers represent the 5th and 95th percentiles of daily ROS concentrations. 53

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Fig. 4. Mean backward trajectories of Beijing during different phases of the 2015 China Victory Day Parade study period.

ROS to investigate their relationships. As listed in Table 2, results showed that no strong positive correlation was observed between ROS and other species, implying atmospheric oxidizing activity might be affected by a number of comprehensive factors that few markers could not reflect. These results was consistent with the pilot study conducted in the Huairou campus of the University of Chinese Academy of Sciences (Huang et al., 2016b). Nonetheless, weak positive correlations were still found among observation data, indicating some species (e.g., PM2.5, O3, and NO) had direct or indirect impact on ROS generation and transportation. However, some significant positive relationships between ROS and other pollutants were probably obtained due to the

obvious unless the enhanced measures were implemented. 3.3. Relationships between ROS and other species As described in previous studies, the concentrations of particlephase ROS would be related with a series of gaseous or aerosol chemical species (Chen et al., 2011; Cheung et al., 2009; Chung et al., 2006; Verma et al., 2012), while the association between gas-phase ROS and air pollutants remained largely unknown due to the lack of relevant measurements. In the current study, PM2.5 and several gas pollutants containing SO2, NOx, O3, and CO were measured synchronously with 54

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the control days were significantly higher than those during the noncontrol days with only a few exceptions which were probably due to the specific weather conditions such as cloudy and light rain. Furthermore, previous studies have demonstrated that atmospheric visibility is mainly determined by the extinction effect of PM, especially for fine particles (Chan et al., 1999; Sloane, 1986). These results indicate the environmental policies aimed to control PM can make the sky “bluer” and more “beautiful”. Therefore, the short-term control measures carried out during the 2015 China Victory Day Parade are effective from the perspective of visibility improvement and the “blue sky”.

Table 3 Concentrations of measured pollutants in different phases. Phase I

3

PM2.5 (μg/m ) NO (ppb) NO2 (ppb) SO2 (ppb) O3 (ppb) CO (ppm) Gas-phase ROS (nmol H2O2/ m3) Particle-phase ROS (nmol H2O2/ m3)

Phase II

Phase III

Phase IV

Mean

SD

Mean

SD

Mean

SD

Mean

SD

59.38 1.23 21.71 2.16 60.58 0.71 18.60

24.08 1.99 8.92 2.00 33.25 0.17 4.51

19.97 1.07 14.89 0.26 38.74 0.54 13.72

12.46 1.57 6.85 0.96 20.22 0.27 3.20

11.41 0.72 11.66 0.01 29.51 0.41 10.25

4.78 1.00 6.95 0.23 17.67 0.11 3.24

30.81 3.40 22.84 0.57 33.25 0.70 16.62

21.01 7.70 13.66 0.97 21.31 0.50 4.80

13.94

2.62

7.17

2.77

7.28

2.43

13.46

4.79

3.5.2. Emission reduction In order to better understand the effect of the control measures, the concentrations of each pollutant in different phases were compared to evaluate their emission reductions. As listed in Table 3, the results showed that the average concentration of PM2.5 in Phase II and Phase III were significantly lower than other periods, with the emissions reduced by 66.4% and 80.8% compared with Phase I. Likewise, higher reductions (88.1% and 99.4%) were observed for SO2, indicating the limitation of coal burning was most effective during the control period. By comparison, the reductions of NO, NO2, O3, and CO were 13.0%, 31.4%, 36.0%, 23.9% in Phase II, while these values raised to 42.0%, 46.3%, 51.3%, and 42.7% in Phase III due to the more restrictive control. These results demonstrated the control strategies were more effective for SO2 and PM2.5 compared to other gas pollutants. Similar to most gas pollutants, the reduction of gas-phase ROS in Phase II was not so notable compared with particle-phase ROS (26.3% vs. 48.6%). However, the same level of reductions (44.9% vs. 47.7%) were obtained between ROS in gas and particle phases in Phase III, reflecting the additional measures in this period were conducive to reduce the atmospheric oxidizing capacity associated with gaseous species. “Parade Blue” brought back the good memories of “Olympic Blue” and “APEC Blue”, as well as encouraged people's yearning for “Permanent Blue”. However, this effect was mainly caused by the achievement of PM control, while the reductions of gaseous pollutants were not so obvious as PM. From the perspective of human health, the difference between the variation trends of gas- and particle-phase ROS indicates that focusing controls only on PM and visibility will produce the clear sky but will not necessarily reduce the adverse health effects associated with gaseous pollutants.

SD: standard deviation.

collinearities among species. For example, PM2.5 was positively correlated with many gas pollutants and thus might present “false correlation” with gas-phase ROS. Therefore, more and more real-time instruments and data such as concentrations of particulate organic matter, volatile organic compounds, trace metals, and other relevance chemical species are required in the future to better understand the main influential factors of ROS concentration. 3.4. Impacts of meteorological condition and regional transportation Meteorological condition and regional transportation can affect air quality indirectly by changing the dilution and diffusion conditions of pollutants (Beckett et al., 2000; Howell et al., 2006). Fig. S2 and Fig. S3 show the relationships between ROS and meteorological factors like ambient temperature, relative humidity, dew point, atmospheric pressure, and wind speed, while the wind roses of ROS concentrations in different phases are depicted in Fig. S4 and Fig. S5. As shown in these figures, no meteorological parameter was observed to be positively correlated with ROS concentrations, which reflects the complex mechanism of ROS generation and indicates that the meteorological condition exerted little influence on ROS concentration during the 2015 China Victory Day Parade. The results of backward trajectory clustering were shown in Fig. 4. The air mass moving from the south of the North China Plain accounted for the largest portion of regional transportation for each phase. This southern area contains several industry cities like Shijiazhuang, Langfang, and Baoding which are considered to be China's biggest haze-affecting cities (Fu et al., 2014; Quan et al., 2011). Furthermore, the speed and altitude of these dominant trajectories were always lower than trajectories from other directions, showing the unfavorable diffusion condition throughout the sampling period. In contrast, diffusion condition in Phase III was even worse than other phases due to the lack of long-range transported air mass from the north, indicating the control measures were effective to a certain extent even though the diffusion condition remained terrible. This result also suggests that source emissions rather than meteorological condition and regional transportation were the key factors affecting air quality and atmospheric oxidizing capacity.

4. Conclusion Our study was the first time to simultaneously obtain the real-time concentrations of gas- and particle-phase ROS during the field observation associated with short-term air quality control. The control measures implemented during the 2015 China Victory Day Parade lead to the great loss of particle-phase ROS throughout the control period. However, the reduction of ROS in gas phase was not obvious until more stringent measures were implemented in Phase III, indicating that the control measures were not so conducive to reducing gas-phase ROS compared with particle-related ROS. Consequently, our study suggests short-term emissions controls only aimed at PM reduction and visibility improvement will produce the blue sky but will not equivalently reduce the gas-phase ROS. Therefore, further studies should focus on gas-phase oxidative potential evaluation and its health effects to give applicable suggestions for future short-term environmental policies.

3.5. Effects of control measures

Acknowledgments

3.5.1. “Parade Blue” Similar to “Olympic Blue” and “APEC Blue”, “Parade Blue” appeared once the control measures implemented and faded away at the beginning of Phase IV (see the photos in Fig. S6 for more details), showing a great improvement of visibility due to PM reduction. As shown in Table S1, the most visibility values obtained in the morning of

This research was supported by the National Natural Science Foundation of China (#41375131 and #91543122) and the Key Research Program of the Chinese Academy of Sciences (#KJZD-EW-TZG06-01-0). We also wish to thank the study participants and field staff of the Institute of Remote Sensing and Digital Earth of the Chinese Academy of Sciences. 55

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Appendix A. Supplementary data

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