Ground-Level NO 2 in Urban Beijing : Trends , Distribution , and Effects of Emission Reduction Measures

The characteristic of nitrogen dioxide (NO2) concentrations, including the long-term trends, spatial distribution, and effects of emission reduction measures-particularly those related to traffic management-were analyzed in Beijing by multimethods. The annual mean concentration of NO2 in Beijing decreased significantly from 71.0 μg m in 2000 to 49.0 μg m in 2008 while it fluctuated between 49.0 and 58.0 μg m and decreased slightly from 2008 to 2015. Unfavorable diffusion conditions could increase NO2 concentrations while emission reduction measures especially the reduced vehicle NOx emissions could decrease NO2 concentrations significantly. The observed mean concentration of NO2 was 54.47 ± 7.71 μg m from 2013 to 2015, while it changed to 94.62 ± 7.99 μg m for 149 heavily polluted days. The NO2 concentration was lower in the northern and western regions and higher in the urban and southern areas in Beijing. After the implementation of air quality assurance measures (particularly traffic management) during the Asia-Pacific Economic Cooperation Summit (APEC, 1–12 November, 2014) and the Parade on the 70th Victory Memorial Day for the Chinese People’s War of Resistance against Japanese Aggression (PARADE, 20 August–3 September, 2015), the mean NO2 concentrations during the APEC summit and PARADE decreased 46.2% and 39.5% respectively compared with those before and after these major activities while diurnal NO2 peaks decreased 24.5%–85.3% and 4.1%–70.8%, respectively during the APEC summit and PARADE period. To decrease NO2 concentrations, a high level of commitment must be given to promote coordinated regional air pollution prevention and control mechanisms in Beijing and its surrounding areas.


INTRODUCTION
Nitrogen dioxide (NO 2 ) is the precursor of ozone, and it participates in complex chemical reactions to generate nitrate (NO 3 -) (Bowman et al., 1994;An et al., 2006;Anttila et al., 2011).Increasing atmospheric NO 2 concentrations from large amounts of nitrogen oxide emitted by the increasing vehicle population in China can directly affect the ecological environment and adversely impact human health (Boersma et al., 2009;Sachin et al., 2009).Variation in NO 2 concentrations has been mostly studied in megacities and regions in China, particularly in the Pearl River Delta, Yangtze River Delta, and Beijing-Tianjin-Hebei (BTH) region (Hao et al., 2000;Kunhikrishnan et al., 2004;Liu et al., 2005;Shao et al., 2006;Chan et al., 2008;Van et al., 2008;Tie et al., 2009;Zhang et al., 2012a;Guo et al., 2014;Wang et al., 2015).
Beijing has a human population of more than 20 million and a vehicle population of more than 5 million, and a high number of production and service activities also occur within the plain area of only 6,000 km 2 ; hence, severe air pollution episodes have been recorded in Beijing in recent years (Cao et al., 2014).The air quality and air pollution control policies implemented in Beijing have been widely studied (Shao et al., 2006;Chan et al., 2008;Ma et al., 2011;Hilboll et al., 2013;CAAC, 2015;Chen et al., 2015;Chen et al., 2016Chen et al., , 2017)).Chinese and Beijing local governments have spent considerable efforts to improve the air quality in Beijing and its surrounding areas, and since 2013, the Beijing local government has been officially releasing monitoring data according to the New Ambient Air Quality Standard in China (GB3095-2012, National Ambient Air Quality Standards [NAAQS]) (MEP, 2013).As one important air pollutant and a short lifetime of 1-2 days, NO 2 in Beijing is mainly affected by local transport rather than long-range transport (Cheng et al., 2012).With Beijing's economic development and rapid urbanization, motor vehicles have become the primary source of NO 2 emissions (Fu et al., 2000).The changes, emission sources, and control of NO 2 have become the most crucial environmental issue in Beijing (Streets et al., 2000;Richter et al., 2005;Meng et al., 2008;Xu et al., 2008).
Most studies evaluating NO 2 concentrations in Beijing focused on the spatiotemporal distribution of NO 2 retrieved from satellite data (Verders et al., 2001;Richter et al., 2002;Li et al., 2011;Yang et al., 2011) such as Global Ozone Monitoring Experiment (GOME) data or SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) data.Other studies focused on the influencing factors such as anthropogenic NO x emissions and consumption (Kang et al., 2009;Wang et al., 2009;Wei et al., 2011).These studies mostly applied the data from only a few monitoring stations or satellites and few of them analyzed the NO 2 trends and the benefits of vehicle emission control measures for lacking long-time series experiments (Lal et al., 2000;Tang et al., 2009;Zhang et al., 2012b).
During several major activities held in Beijing, such as the Asia-Pacific Economic Cooperation (APEC, 1-12 November, 2014) summit in 2014 and the Parade on the 70th Victory Memorial Day for the Chinese People's War of Resistance against Japanese Aggression (PARADE, 20 August-3 September, 2015) in 2015, Beijing and its neighboring cities have implemented numerous control strategies, including suspending factory operations and implementing the odd-and-even license plate rule.These strategies provide a unique opportunity to study the spatiotemporal changes in NO 2 levels in Beijing.This research analyzed the trends of NO 2 concentrations from 2000 to 2015 and its influencing factors and then studied the spatiotemporal patterns of NO 2 concentrations during heavily polluted days under severe weather conditions and some mega events due to emergency emission control and reduction measures in Beijing.

In Situ Observations
Beijing (115.7°-117.4°E, 39.4°-41.6°N) is located at the northwest edge of the North China Plain and is near the edge of the semi-desert zone.Its terrain exhibits a dustpan shape, and it is surrounded by mountains in three directions (north, west, east).The average altitude of Beijing is 43.5 m, and the general altitude of the mountainous areas is between 1,000 and 1,500 m, which is not conducive to pollutant diffusion.The total area of Beijing is 16,410.54km 2 , and its forest coverage in the plain region accounts for only 15% of the total area.Beijing has a temperate continental monsoon climate.It is hot and rainy in summer and cold and dry in winter.The annual mean rainfall is less than 450 mm, and 80% of rainfall occurs in June, July and August (BMBS, 2014).
In Beijing, an automatic NO 2 ground monitoring network comprising 35 monitoring stations was established by the Beijing Municipal Environmental Monitoring Center (BJMEMC, http://zx.bjmemc.com.cn/,Fig. 1).The 35 monitoring stations cover all districts, and there are 12 monitoring sites (DL, DS, GY, TT, WSXG, AT, NZG, WL, GC, SY, CP, and HR) in urban Beijing and average values of the 12 sites represents the level of air pollution in the city.
Monitoring instruments from Thermo Fisher Corp. (USA) were used to measure air pollutants (SO 2 , NO 2 , CO, PM 2.5 and O 3 ) in Beijing.SO 2 was monitored using a TE-43C UV fluorescence analyzer.CO was monitored using a 48C infrared absorption analyzer.O 3 was monitored using a 49C UV spectrophotometry O 3 analyzer.PM 2.5 was monitored with a Thermo Fisher 1405F analyzer.NO, CO, and SO 2 standard samples were from the China National Institute of Standardization to calibrate the instruments.A 49IPS O 3 calibrator traceable to the standard reference photometer maintained by the WMO World Calibration Center was used to calibrate the O 3 analyzer.The detection limits of O 3 (49C), SO 2 (43C) and CO (48C) were 1.0 × 10 -9 , 0.5 × 10 -9 and 40 × 10 -9 (volume fraction), respectively, and a 42C NO-NO 2 -NO x analyzer was set to a limit of 0.05 × 10 -9 , zero drift of 0.025 × 10 -9 /24 h, and span drift of ± 1%/24 h.Regular calibration was done every 2 days, and a multipoint calibration was done every week to ensure the accuracy of monitoring.

Data Retrieval
The NO 2 concentrations in surrounding areas, such as Tianjin and Shijiazhuang cities, monitored by Thermo Fisher 42C chemiluminescence NO-NO 2 -NOx analyzers (same to Beijing),were obtained from the real-time publishing platform of the Environmental Monitoring Center of China (http://106.37.208.233:20035/).Ground meteorological factors were observed from the Beijing Municipal Observatory Station (116.4°E,39.8°N) by using WXT520 weather observation instruments.Remote-sensing charts and weather charts were provided by South Korea's live weather center (http://web.kma.go.kr/eng).
The tropospheric vertical column densities of NO 2 in the BTH region were obtained from Ozone Monitoring Instrument (OMI) Level 3 daily global products with a fine spatial resolution of 0.25° × 0.25° (http://giovanni.gsfc.nasa.gov/giovanni) in Beijing and its surrounding areas.The ozone Monitoring Instrument crosses Beijing once a day (near 1330 local solar time) and the columnar NO 2 density typically includes regridding pixel data to a regular latitudelongitude grid, filtering and time averaging procedures with the uncertainty of ± 0.5-1.5 × 10 15 molecules cm -2 and a relative error of between 10% and 40% (Boersma et al., 2009).

Statistical Analysis
A simple linear regression and spearman's correlation coefficient were implemented to investigate the NO 2 trends and influencing factors in urban Beijing.The STL method was applied to analyze the NO 2 trends.The STL method was first proposed by Cleveland et al. (1990).It is a filtering procedure to decompose a time series into trend, seasonality and the remainder variations by the application of loess smoothing models (R1).These variations may be independent each other or partial dependent.The longterm trends component is considered to be relatively stable variations; the seasonal component can be considered high frequency variations caused by the periodic stable perturbation and the remainder component (residuals) is the irregular random disturbance after the removal of the long-term trends component, seasonal component.The STL is a recursive process and each iteration takes three LOESS and one moving average process.STL has been widely used in several disciplines, including environmental science, ecology, epidemiology and public health (Silawan et al., 2008).In this study, the time series of monthly averaged NO 2 concentrations of 12 stations in urban Beijing were analyzed.
where Y t , Trend t , Seasonal t , Residual t represents the original trend, seasonality and the remainder variations at the t moment.We applied the comparative analysis methods to compare the NO 2 patterns during the whole year and heavily polluted days.Kriging interpolation methods (Li et al., 2011) 2015) periods.Calculating the link relative ratios of different air pollutants has been widely used in air quality assurance activities (Tang et al., 2009;Zhang et al., 2012a).

Trends for NO 2 Concentrations
Since 2000, the concentrations of main air pollutants (SO 2 , NO 2 , CO, PM 10 , and PM 2.5 ) in urban Beijing have continuously decreased (BMEPB, 2014).As mentioned before, de-seasonalized and de-cyclic data were performed as shown in Fig. 2. The annual mean concentration of NO 2 (Fig. 3  The major sources of NO 2 are anthropogenic sources including industrial facilities and mobile sources.Because of the national Tenth, Eleventh, and Twelfth Five-Year Plans, as well as the clean action plan proposed by Beijing's local governments, total air pollutant emissions have significantly decreased (Ge et al., 2009).Beijing has promoted energy consumption structural optimization as part of its efforts to improve urban air quality, particularly the suspension of coal burning since 1998.The primary measures include (1) implementation of strict emission standards for coal-fired boilers, subsidized replacement, and after-treatment; (2) retrofitting of coal-fired boilers, mandatory application of low-sulfur coal and the accelerated use of natural gas; and (3) importing electricity and other clean energy.Through these measures, Beijing has greatly improved its energy structure, and coal consumption has decreased significantly in recent years (Fig. 3(a)).Coal consumption contributes to primary air pollutants (e.g., SO 2 and CO) and secondary air pollutants (e.g., PM 2.5 ).For the 2000-2015 periods, the correlation coefficient between annual NO 2 concentrations and coal consumption in Beijing was 0.50 (nonsignificant), indicating that coal consumption is not the main factor influencing the NO 2 concentration in Beijing.
In Beijing, the vehicle population has grown rapidly since 2000, rendering efforts aimed at improving the air quality a serious challenge.Vehicle emissions contribute to primary pollutants (e.g., NO 2 ) and secondary pollutants (e.g., O 3 and PM 2.5 ).To control the vehicle population, integrated vehicle emission control measures in Beijing include new vehicle controls, in-use vehicle controls, fuel quality improvements, promotion of clean energy and new energy vehicles, traffic management measures, and the odd-and-even license plate rule.The vehicle population in Beijing (Fig. 3(b)) increased significantly from approximately 1.57 million in 2000 to approximately 5.62 million in 2015 (an annual increase rate of 31.49× 10 4 yr -1 , R = 0.98, 95% confidence interval, two-tailed).Since 2006, the vehicle population in Beijing has grown rapidly; however, after 2011, the growth rate declined as a result of the Yaohao licensing system.
Official statistics have revealed that total NO x emissions from vehicles in Beijing have been significantly higher than those in neighboring provinces and cities (e.g., Tianjin and Hebei), and NO x emissions from vehicles in Beijing have accounted for 49%-66% of all NO x emissions (Beijing Statistical Yearbook 1997-2005, 1998-2014).According to the official statistics, vehicle NO x emissions decreased continuously from 10.56 × 10 4 t in 2000 to 6.10 × 10 4 t in 2015.The growth rate of vehicle population became smaller while vehicle NO x emissions still decreased relatively slowly which was associated with the improvement of oil standards and the elimination of yellow cars and other control measures since 2009.The correlation coefficient between the annual NO 2 concentration and the vehicle population in Beijing was calculated to be -0.86 (95% confidence interval, two-tailed) for the 2000-2015 period, and the correlation coefficient between vehicle NO x emissions and NO 2 concentrations was 0.86 (95% confidence interval, two-tailed), indicating that decreasing vehicle NO x emissions played a significant effect on the decrease in NO 2 concentrations in Beijing.

Variations in Heavily Polluted Days
According to NAAQS, an air quality index (AQI) between 200 and 300 represents severe pollution, whereas an AQI exceeding 300 represents hazardous pollution.According to the new air quality standard, the number of heavy polluted days (AQI > 200) in urban Beijing was 58 in 2013, 45 in 2014 and 46 in 2015.Heavily polluted days were mainly concentrated in the cold season (November, December, January and February), whereas almost no heavily polluted days were recorded in summer (Fig. 4).The mean concentration of NO 2 was 54.47 ± 7.71 µg m -3 between 2013 and 2015.It was 94.62 ± 7.99 µg m -3 for 149 heavily polluted days.The monthly mean concentration of NO 2 in urban Beijing exhibited a wave-shape curve.The highest monthly mean concentration of NO 2 (88.06 µg m -3 ) was observed in January 2013 due to four serious air pollution episodes.The monthly mean concentration of NO 2 was also higher in December 2015 because of regional coal burning and adverse meteorological conditions (13 heavily polluted days were recorded in this month, and two "red alert" air pollution warnings were issued).The calculated seasonal NO 2 concentrations during spring (March-May), summer (June-October), autumn (June-October), and winter (December, January and February) were 55. 51, 43.61,  58.94 and 68.23 µg m -3 in 2013; 42.49, 63.95, 63.05 and  57.53 µg m -3 in 2014; and 46.87, 34.70, 53.03 65.70 µg m -3 in 2015, respectively.Overall, the mean concentrations of NO 2 in autumn and winter were relatively higher than those in spring and summer, and the higher monthly mean concentration of NO 2 is invariable associated with PM 2.5 pollution episodes (Yang et al., 2015).
On heavily polluted days, the monthly mean concentration of NO 2 was 54.0-117.9µg m -3 in 2013, 39.6-120.5 µg m -3 in 2014, and 54.0-117.92µg m -3 in 2015.The monthly mean concentration of NO 2 on heavily polluted days was 1.04-1.68times of the annual mean concentration.Table 1 presents the relationships between meteorological factors in the boundary layer and the observed NO 2 concentrations in urban Beijing.The meteorological factors differed significantly between clean and heavily polluted days.On heavily polluted days, the observed ground meteorological elements were mainly characterized as low wind speeds (1.69 m s -1 ), high humidity (68.63%), negative pressure variations (-2.42 hPa), and positive temperature variations (0.32°C), which are not conducive to the diffusion of air pollutants.The unique weather conditions on heavily polluted days provided a stable atmospheric background that inhibited the dissipation of NO 2 , thus increasing the NO 2 concentration (Guo et al., 2014).The concentrations of NO 2 , NO 2 , CO and PM 2.5 were considerably high on heavily polluted days, whereas the concentrations of O 3 was considerably low on heavily polluted days, because of weak chemical reactions affected by low temperatures and solar radiation (Xu et al., 2011;Ma et al., 2012;Zhang et al., 2013) from 2013 to 2015.Moreover, the significant increase in NO 2 concentrations on heavily polluted days was influenced not only by meteorological elements but also by regional transport (Liu et al., 1999;Van et al., 2008).
As shown in Fig. 5, diurnal variations in NO 2 exhibited two peaks.The first peak was at 07:00-8:00 and the second one appeared about 20:00-22:00; the second peak was significantly higher than the first one.The peak in the morning could be attributed to rush hour traffic, and the peak at night might be related to NO 2 accumulation caused by relatively unfavorable weather conditions and high NO emissions (Fu et al., 2000;Hilboll et al., 2013;Cao et al., 2014).Many diesel vehicles are allowed to enter Beijing at night, resulting in a large amount of nitrogen oxide emissions at night.On heavily polluted days, the diurnal variation in NO 2 also exhibited two peaks, with the first peak at noon and the second peak at 20:00-22:00.High NO 2 concentrations were also observed from 18:00 of the first day to 04:00 of the next day.The hourly concentrations of NO 2 on heavily polluted days in 2015 were significantly higher than those in 2013 and 2014.This phenomenon might be attributable to differences in meteorological conditions.
The NO 2 concentrations in the northern and western mountainous areas were significantly lower than those in the central urban area and southern regsions (Fig. 6).The annual mean concentration of NO 2 in the central urban area and southern region was larger than 50 µg m -3 .On heavily polluted days, the mean concentrations of NO 2 in the central urban area and southern region were approximately 80-110 µg m -3 , whereas those in areas with NO 2 concentrations of > 50 µg m -3 increased significantly by approximately 42%-84%, which may be related to local accumulation and pollution transport caused by adverse weather conditions (Lal et al., 2000;Wang et al., 2009).Compared with the spatial distribution of NO 2 in 2013, NO 2 concentrations in the area northwest of the BaDaling highway were higher in 2014, which might be attributable to traffic pollution from vehicles traveling along this highway.The uncertainties of the Kriging interpolation methods mainly originate from (1) the effects of the unique dustpan terrain and vegetation; (2) interpolation method errors, which are affected by the sampling point range, sampling point density and other parameters; and (3) meteorological conditions and secondary chemical reactions, which were not considered.

NO 2 Changes due to Emission Reduction Measures
Air quality security programs were implemented from 1 to 12 November in 2014 (during the APEC summit) and from 20 August to 3 September in 2015 (during the PARADE).For air quality assurance during these two major events, the Chinese government implemented numerous emission reduction measures, such as reducing coal burning, industrial adjustment, joint prevention measures, vehicle limitations (particularly on heavy-duty buses and trucks from outside of Beijing), and the odd-and-even license plate policy on roads in Beijing.Traffic management was one of the most crucial emission reduction measures during the air quality assurance period in Beijing, and temporary reduction measures mainly included (1) the banning of yellow-label vehicles from the roads in Beijing, (2) the implementation of the odd-and-even license plate rule for vehicles, (3) the banning of freight vehicles within the Sixth Ring Road, and (4) the removal of an additional 30% of government-owned vehicles from the road (UNEP 2016).Traffic management for the areas surrounding Beijing mainly included the implementation of the odd-and-even license plate rule.Anthropogenic reduction emissions in Beijing were calculated for THC, NO x , PM 2.5 , and CO respectively (Table 2) through a bottom-up investigation (Zhou et al., 2010).The emission reduction benefits achieved during the air quality assurance periods as a result of the temporary traffic management were outstanding.Relative to the baseline scenario of daily average as usual, the total vehicle emissions for THC, CO, NO x , and PM 2.5 decreased by 56%, 57%, 46%, and 52%, respectively.
On the basis of the observed NO 2 concentration at 12 urban stations, this study further analyzed the benefits of the vehicle emission reduction measures by comparing the diurnal variations in NO 2 concentrations (Table 3).After the implementation of reduction measures (particularly the traffic management measures) in Beijing and its surrounding areas, the mean concentration of NO 2 at the urban sites during the APEC period decreased by 46.2% relative to  those in the Pre-and Post-APEC periods.By contrast, the mean concentration of NO 2 decreased by 39.5% during the PARADE period relative to that in the Pre-and Post-PARADE periods.
Regarding the diurnal variations in NO 2 , two NO 2 peaks ranging from 22.85 to 62.88 µg m -3 and 21.50 to 78.70 µg m -3 were recorded at approximately 09:00 and 19:00, respectively, during the APEC period.The NO 2 peak in the morning nearly disappeared because of the frequently weak northerly winds during the APEC period (Huang et al., 2015).The NO 2 peaks in urban Beijing decreased by approximately 24.5%-85.3%during the APEC period relative to those in the Pre-and Post-APEC periods (Table 4).During the PARADE period, the NO 2 peaks ranging from 14.22 to 40.90 µg m -3 and 14.08 to 52.34 µg m -3 at approximately 08:00 and 22:00, respectively, and the two peaks were considerably similar.Moreover, the NO 2 peaks decreased by approximately 4.1%-70.8%during the PARADE period compared with those in the Pre-and Post-PARADE periods.NO 2 accumulation in the early morning and at night was significantly slower during the APEC and PARADE periods, which may be attributable to the reduction in NO x vehicle emissions resulting from the oddand-even number license plate rule being in effect.
NO 2 concentrations were much higher during the APEC period than during the PARADE period.This difference may be related with the differences in degree of emission reduction measures and meteorological conditions.Although the regional emission control policy was implemented during the APEC summit at a large regional scale (Kan et al., 2015), it appears that the regional control measures implemented were not as strong as the abatement actions implemented during the PARADE period.The APEC summit was held in the middle of November, which marked the transition from autumn to winter when the wind speed and precipitation were low; furthermore, the frequency of stagnant synoptic weather also increased, which was not favorable for the dispersion of air pollutants.It is better to analyze the total columnar NO 2 density data due to the changes in the composition of the upper atmosphere during air quality assurance periods.As shown in Fig. 7, the high column concentrations of NO 2 were mainly concentrated in Beijing, Tianjin, and Tangshan, Shijiazhuang and southern Hebei regions.The column concentrations of NO 2 in Beijing, Tianjin, and Hebei Provinces decreased by 44%, 5%, and 20%, respectively compared to those in Pre-APEC period, after the air quality assurance measures were implemented for APEC.Moreover, the column concentrations of NO 2 in Beijing, Tianjin, and Hebei Provinces decreased by 28%, 23% and 45%, respectively, during the PARADE period.The implementation of air quality assurance measures has led to decreases in the high NO 2 column concentration in Beijing and Beijing ceased being the regional center of high NO 2 column concentrations.
Regional prevention and control of air pollution in the BTH region and surrounding areas, such as Shandong, Shanxi, and Inner Mongolia, effectively reduced the emission intensity of air pollutants from anthropogenic activities, leading to the occurrence of the "APEC blue" and "PARADE blue" phenomena in Beijing.Successful air quality assurance during the APEC summit and PARADE proved that governance policies implemented at the time were effective.On the basis of the results of these air quality assurance measures, it is necessary to demonstrate commitment in promoting coordinated regional air pollution prevention and control mechanisms and to improve regional air quality.

CONCLUSIONS
The annual mean concentrations of NO 2 decreased from 71.0 µg m -3 in 2000 to 49.0 µg m -3 in 2008 while it decreased not significantly and fluctuated between 49.0 and 58.0 µg m -3 from 2008 to 2015.Albeit with yearly variations, the year 2008 was a change-point for long-term trends of  NO 2 in Beijing.On one hand, vehicle NO x emissions in urban Beijing significantly affected these concentrations; on the other hand, adverse weather conditions were found to be another influential factor.The mean concentration of NO 2 was 54.47 ± 7.71 µg m -3 for the 2013-2015, while it changed to 94.62 ± 7.99 µg m -3 for 149 heavily polluted days.Regarding the spatial distribution, the annual mean concentration of NO 2 was low in the northern and western regions, and it was high in the urban and southern areas.
On heavily polluted days, the NO 2 concentration increased prominently, but the distribution remained relatively similar to that observed on regular days.
After the implementation of air quality assurance measures, particularly the traffic management measures, during the APEC summit and PARADE periods, the mean concentrations of NO 2 decreased significantly, and Beijing ceased being the regional center of high NO 2 concentrations.
Thus, the following several recommendations can be made for controlling NO 2 in Beijing: (1) In addition to adverse weather conditions, vehicle emissions are a crucial contributor to high NO 2 concentration in Beijing.In the future, the government should control the number of motor vehicles, particularly the number of yellow-label vehicles, to suppress vehicle emissions.
(2) Implementing the odd-and-even license plate rule in Beijing and its surrounding areas could reduce NO 2 concentrations significantly in Beijing during major activities.In the future, regional prevention and control mechanisms must be implemented to promote the continuous improvement of regional air quality through committed and coordinated efforts.
(3) Nitrogen oxides is one of the major precursors of PM 2.5 .To achieve the goal of a 25% reduction in annual mean PM 2.5 concentrations from the 2012 level by 2017 in Beijing and to fundamentally prevent heavy air pollution and slow down the air pollutants' accumulation rates, the transformation of the regional economy must be accelerated, and the energy consumption structure must be re-established.
(4) Many of the world's thriving cities are encountering difficulty in managing severe air pollution; Beijing's experience in controlling air pollution in the context of rapid expansion could be used as an example for other emerging economies and burgeoning cities.

CONFLICTS OF INTEREST
None declared.

AUTHORS' CONTRIBUTIONS
CN planned the study and wrote the manuscript.WB, LQ and CC did the literature review.CB and WP contributed to the statistical scripts.SF and LY contributed to the data analyses.All authors read and approved the final manuscript.
Fig. 1.Distribution of the 35 air quality observation sites in Beijing (12 sites in the urban area) and a meteorological observation station.
were used to obtain the spatial distribution of NO 2 concentrations in Beijing during 2013-2015 by using data from 35 sites in Beijing and other sites in surrounding areas.In order to evaluate the qualitative and quantitative relationships between emission reductions and changes of different air pollutants to explain the air quality improvements, the air quality guarantee periods was divided into three sections such as the Pre-APEC (15-30 October, 2014), APEC (1-12 November, 2014), Post-APEC (13-30 November, 2014); Pre-PARADE (1-19 August, 2015), PARADE (20 August-3 September, 2015), and Post-PARADE (4-30 September,

Fig. 2 .Fig. 3 .
Fig. 2. A decomposition plot of monthly averaged NO 2 concentrations (µg m -3 ) in urban Beijing from 2000 to 2015.The top layer shows the original monthly averaged NO 2 data and the other layers show the decomposed components, including the long-term trends component, seasonal component and remainder component, respectively.

Fig. 4 .
Fig. 4. Monthly average concentrations of NO 2 in urban Beijing throughout the year and on heavily polluted days (2013-2015).

Fig. 5 .
Fig. 5.Diurnal variations of NO 2 concentrations in urban Beijing throughout the year and on heavily polluted days (2013-2015).

Fig. 6 .
Fig. 6.Spatial distribution of NO 2 concentrations in Beijing throughout the year and on heavily polluted days (2013-2015) by Kriging interpolation methods from Beijing air quality network.

)Fig. 7 .
Fig. 7. Spatial distribution of the total columnar NO 2 density during the APEC, Pre-APEC, PARADE, and Pre-PARADE periods in Beijing and its surrounding areas from the OMI satellite observations.

Table 2 .
Estimated vehicle emission reductions attributed to the temporary traffic management measures implemented during major activities in Beijing.

Table 3 .
Mean concentrations of NO 2 at urban sites at three stages in urban Beijing (µg m −3

Table 4 .
Significantly reduced rates of the NO 2 peaks during the APEC and PARADE compared to those during the adjacent periods in urban Beijing (%).