NO2 feature during the 2008 Beijing Olympics: Implications for ozone production sensitivity

Atmospheric Environment 45 (2011) 3103e3111

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The unique OMI HCHO/NO2 feature during the 2008 Beijing Olympics: Implications for ozone production sensitivity J.C. Witte a, b, *, B.N. Duncan b, A.R. Douglass b, T.P. Kurosu c, K. Chance c, C. Retscher d a

Science Systems and Applications Incorporated, 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, USA Atmospheric Chemistry and Dynamics Branch, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA c Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138, USA d Goddard Earth Sciences and Technology Center, University of Maryland Baltimore County, 5523 Research Park Drive, Suite 320, Baltimore, MD 21228, USA b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 8 October 2010 Received in revised form 1 March 2011 Accepted 2 March 2011

In preparation of the Beijing Summer Olympic and Paralympics Games, strict emission control measures (ECMs) were imposed between July and September 2008 on motor vehicle traffic and industrial emissions to improve air quality. We estimated changes in the chemical sensitivity of ozone production to these ECMs using Ozone Monitoring Instrument (OMI) column measurements of formaldehyde (HCHO) and nitrogen dioxide (NO2), where their ratio serves as a proxy for the sensitivity. During the ECMs, OMI NO2 significantly decreased, subsequently increasing the HCHO/NO2. For the first half of the ECM time period, the ratios maintained values greater than two indicating that ozone production became primarily NOx-limited. In contrast, ozone production was predominantly volatile organic compound (VOC)-limited or mixed VOC-NOx-limited during the same period in the preceding three years. After the ECMs were lifted, NO2 and HCHO/NO2 returned to their previous values. The 2005e2008 OMI record shows that this transition to a predominantly NOx-limited regime during the ECMs was unique. Meteorological factors likely explain the variability in HCHO/NO2, particularly the transition to a mixed NOx-VOC-limitation in mid-August during the Olympics, where ozone production became sensitive to both NOx and VOCs until the end of the ECMs. The mixed VOC-NOx-limited regime observed during the Paralympics is also unique because previous years show that Beijing in September is predominantly VOC-limited. Beijing’s largescale tree-planting program was expected to increase levels of biogenic VOCs, but this is not supported by OMI HCHO data. However, MODIS vegetation indices show a small increase in vegetation cover from 2003 leading up to the Games in 2008. After the Games, however, there was a downturn in the indices (2009 and 2010) to levels similar to 2006. Ó 2011 Elsevier Ltd. All rights reserved.

Keywords: Air quality OMI NO2 HCHO Beijing Olympics

1. Introduction In 2001, Beijing, China won the bid to host the 2008 Olympics (August 8e24, 2008) and Paralympics (September 6e17, 2008) (hereafter referred to as the ‘Games’), prompting health concerns because of the city’s poor air quality. Beijing’s air quality has worsened in the past several decades because of rapid industrialization, population growth, and urbanization (Akimoto, 2003; Molina and Molina, 2004; Hao and Wang, 2005). Addressing this issue was a top priority in bidding successfully for the Games. Therefore, the Chinese government implemented aggressive shortterm strategies to improve air quality from July through September * Corresponding author. Science Systems and Applications Incorporated, 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, USA. Tel.: þ1 301 614 5991; fax: þ1 301 614 5903. E-mail address: [email protected] (J.C. Witte). 1352-2310/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2011.03.015

2008. Beijing’s air quality standards were guided by the World Health Organization (WHO) 2000 Air Quality Guidelines which sets limits for sulfur dioxide (SO2), carbon monoxide (CO), PM10 (Particulate Matter with a diameter of 10 microns or smaller) and nitrogen dioxide (NO2). However, the Chinese government did not attempt to control surface ozone during the Games, nor was it part of Beijing’s monitoring activities during the Games (UNEP, 2009). Despite this, we show that the emission control measures (ECMs) during the Games did have a significant impact on the sensitivity of ozone formation to ozone’s precursors, nitrogen oxides (NOx ¼ NO þ NO2) and volatile organic compounds (VOCs). In the presence of sunlight, NOx and VOCs are the main ingredients for the formation of high levels of ozone (Haagen-Smit, 1952; Seinfeld, 1989), which has detrimental effects on human health (Hallet, 1965; Young et al., 1964; Stokinger, 1965). The photochemical oxidation of VOCs, primarily initiated by the hydroxyl radical (OH), produces peroxy (HO2) and organic peroxy radicals

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(RO2), increasing the rate of catalytic cycling of NO to NO2 and formation of high levels of surface ozone. The oxidation of NO2 to nitric acid (HNO3) and the conversion of RO2 to peroxides terminates this catalytic cycle. The ozone production efficiency (OPE) is defined as the number of ozone molecules produced from a molecule of NOx and is nonlinearly related to concentrations of its precursors, so that ambient levels of ozone depend on both the absolute and relative amounts of NOx and VOCs (Duncan and Chameides, 1998 and references therein). In polluted environments, such as Beijing, the OPE is low because the titration of ozone by NO and the formation of HNO3 are competitive with the conversion of NO to NO2 by peroxy radicals. Thus, a reduction in NOx emissions may actually lead to an increase in ozone. Sillman (1995) used correlations between the afternoon concentrations of various trace gases (e.g., formaldehyde (HCHO) and total reactive nitrogen (NOy)) to determine the chemical sensitivity of ozone production (PO3) to changes in VOCs and NOx. Martin (2004) and Duncan et al. (2010) applied the technique of Sillman (1995) to space-based observations, demonstrating that HCHO and NO2 from the Global Ozone Monitoring Experiment (GOME) and Ozone Monitoring Instrument (OMI) serve as reasonable proxies for in situ observations of VOC and NOy in polluted environments and their ratio is a reasonable indicator of the chemical sensitivity of local PO3. The ambitious ECMs in and around Beijing during the Games provided a unique opportunity to examine their effectiveness in improving ambient air quality, including ozone. In this study, we use satellite data from OMI for a top-down approach to assess the impact of the ECMs on the chemical sensitivity of PO3. We construct 7-day running means from daily tropospheric NO2 and total HCHO column data from OMI. We first examine changes in OMI HCHO/NO2 [hereafter referred to as the Formaldehyde to Nitrogen Dioxide Ratio (FNR)] within the Beijing metro region (i.e. 1 1 grid around the city center ¼ 39.9 N,116.92 E) during the ECMs (July 1 through September 21, 2008) and compare this FNR with other similar urban cities in China. We describe the satellite data in the following section. In Section 3, we outline the ECMs, with a focus on NOx and VOC controls. In Section 4, we describe the local meteorology. In Section 5, we discuss the effect of the ECMs on the FNR, HCHO and NO2. The summary follows in Section 6. 2. OMI HCHO and NO2 columns OMI is a nadir-viewing moderate resolution UV/Vis spectrometer. It is one of four instruments on NASA’s Aura satellite that was launched in July 2004 into a sun-synchronous orbit with an equator crossing-time of 13:38 in the ascending node. OMI has a full crosstrack swath of 2600 km, containing 60 pixels ranging from 15  30 km2 at nadir to 42  162 km2 at the edge of the swath and provides daily global coverage. All OMI data used in this study have been filtered to remove cloudy scenes, i.e. filtering reflectivities greater than 30%. We use the tropospheric NO2 columns reported as the vertical column density between the ground and the estimated mean tropopause pressure height of 150 hPa. The gridding technique of Wenig et al. (2008) weights the NO2 vertical column densities where multiple pixels overlap and is used to produce gridded data at a horizontal resolution of 0.05  0.05 , smaller than the pixel size. Data were taken from the Aura Validation Data Center (AVDC; http://avdc.gsfc.nasa.gov). Bucsela et al. (2006) report retrieval accuracy estimates for the tropospheric columns to be 25%, with a precision error of 0.25  1015 mol cm2. OMI HCHO total column data are binned into 0.25  0.25 grids. Chance et al. (2000) showed that HCHO measurements are a very good indicator of VOCs in regions of elevated biogenic activity. Millet

et al. (2008) estimated an overall error in the HCHO column data of 25e31%. Kurosu et al. (2004) provides information on the nonlinear least-squares fitting retrieval algorithm that was originally developed for GOME and SCIAMACHY and adapted for OMI. The HCHO dataset in this study has been de-trended to remove a growing positive trend in the background values over the lifetime of OMI, i.e. a growing dark current effect in the radiance and irradiance spectra. We calculate 7-day running means and monthly averages for HCHO and NO2 from 2005 to 2008. Temporal averaging has been shown to reduce the HCHO measurement uncertainty and noise (Millet et al., 2008). We consider 2005e2007 in order to quantify changes in 2008 relative to previous years. We do not include OMI data after 2008 because of the growing dark current that is producing enhanced across-track striping and hot spots over ocean regions in the HCHO measurements and is too big to correct at present. 3. Emission control measures (ECMs) affecting HCHO and NO2 We highlight the relevant ECMs summarized by the United Nations Environment Program (UNEP) (UNEP, 2009). From July through September 21, 2008, stringent vehicle traffic controls were adopted, such as i) permitting entry into Beijing for vehicles with odd or even license plates on alternate days, and ii) banning vehicles with high emissions from entering the downtown. Other ECMs included i) reducing power plant emissions by 30% from their levels in June, well beneath the Chinese emission standard, ii) reducing output or shutting down several heavily-polluting factories, and iii) halting all construction activities. Several studies have shown that regional emissions significantly impact Beijing’s air quality during summer (An et al., 2007; Streets et al., 2007; Wang et al., 2009). Therefore, some ECMs were also applied in neighboring, heavily industrialized provinces upwind of Beijing (e.g., Henan, Shanxi, and Hebei) and in the neighboring city of Tianjin, where traffic restrictions similar to Beijing’s were instituted. Streets et al. (2003) showed that a growing fraction of NOx emissions in China is due to the rapid growth in vehicle ownership since the latter part of the 1990s. Since 2000, the number of vehicles in Beijing has doubled, contributing to the city’s poor air quality (UNEP, 2009). Although there are natural sources of NOx (e.g., forest fires, lightning), the combustion of fossil fuels is the major contributor to photochemical pollution in Eastern China (Ohara et al., 2007; Zhang et al., 2007). Song et al. (2007) used a positive matrix factorization (PMF) model to perform source apportionment of VOC in Beijing during the summer and found that vehicle emissions were the dominant source, accounting for 52% of ambient VOCs, followed by the petrochemical industry (20%). Biogenic VOCs, mostly in the form of isoprene, comprised a small portion of the ambient VOCs. However, Song et al. found that the role of isoprene in ozone formation was comparable to that of the anthropogenic sources because of isoprene’s large contribution to total VOC reactivity (Chameides et al., 1992). As part of Beijing’s bid for the 2008 Games, an ambitious treeplanting (“greening”) program was initiated in 2001, with the goal of increasing the green coverage in Beijing by up to 40% (UNEP, 2009). Between 2001 and 2007, approximately 8800 ha of green space were developed using more than 30 million trees and bushes. Consequently, the vegetation cover in Beijing increased significantly over the past decade. The proportion of green space in 2006 increased by 42.5% of the total urban area as compared to 2001 (Beijing Bureau of Statistics, 2007). The main plant species are various broad-leaf deciduous trees, with many of them being strong isoprene emitters (Zhang et al., 2000). Pang et al. (2009) and Xie et al. (2008) found that the contribution of isoprene to local HCHO formation in Beijing is significant during the summer months and can account for 23e38% of the local

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PO3. Li et al. (2010) found that photo-oxidation of biogenic VOCs were the major source of HCHO during the Games, with HCHO contributing 22% to the total VOC mass. 4. Local weather conditions We use balloon-borne rawinsonde data collected at the Beijing International Airport from 2005 to 2008 and stored in the NOAA/ Earth System Research Laboratory (ESRL) data archive. Fig. 1 shows the 7-day running mean of surface temperature, relative humidity (RH), wind speed and wind direction from June to September at 1000 hPa. The weather between July and September 2005e2008 exhibited a mean temperature range from 26  C at the surface to

a

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17  C at 850 hPa, high RH (>50% from the surface to 850 hPa), relatively low wind speeds (2.2 m s1 at the surface to 5.8 m s1 at 850 hPa), and surface winds typically from the southwest to southeast. Table 1 summarizes the predominant wind directions for various pressure levels. Prevailing southerly winds at the surface cause Beijing to be regularly impacted by pollution from the heavily industrialized provinces. Hot and humid weather helps to create a favorable environment for ozone formation (Chameides and Walker, 1973; Sillman et al., 1990). July through September 2008 exhibited typical weather patterns, although UNEP (2009) reported higher than average rainfall in Beijing during the August 2008 Olympics; such higher than average rainfall would be expected to improve air quality.

Surface Temperature 35

Celsius

30 25 20

|---------------------------Emission Controls---------------------------|

15 June

b

July

August

Sept.

Relative Humidity 100 80

%

60 40 20 0 June

c

July

August

Sept.

Wind Speed 5

m/s

4 3 2 1 0 June

Degrees

d

July

August

Sept.

Wind Direction 360 (North) 270 (West) 180 (South) 90 (East) 0 (North) June

July

2005 [ C],

2006

August

Sept.

2007 1

2008

Fig. 1. 7-day running mean of (a) surface temperature (b) relative humidity (RH) [%], (c) wind speed [m s ], and (d) wind direction [degrees] for June through September of 2005e2008 at 1000 hPa. Black open bars and asterisks show the time periods of the Olympic and Paralympics, respectively. Data are taken from balloon-borne rawinsondes launched daily at 12Z at the Beijing International Airport located w30 km northeast of the Beijing city center. The x-axis divides the data into its respective months.

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Table 1 Predominant wind direction between July and September 2008 at 12Z. The Southern quadrant includes the 90e270 hemisphere and the Northern quadrant includes 0e90 and 270e360 . Year

2008 2007 2006 2005

Surface (0.06 km)

925 hPa (0.8 km)

850 hPa (w1.5 km)

700 hPa (w3 km)

500 hPa (w5.7 km)

% South

% North

% South

% North

% South

% North

% South

% North

% South

% North

75.8 75.0 71.7 66.3

14.2 8.7 9.8 13.0

85.7 82.6 72.8 71.7

13.2 17.4 23.9 27.2

61.5 63.0 62.0 60.9

36.3 37.0 34.8 38.0

36.3 30.4 41.3 33.7

54.9 67.4 54.4 65.2

40.2 32.6 41.3 41.3

54.4 58.7 51.1 54.3

Wang et al. (2010) reported that there was little precipitation from mid-July to August 9 and there were five days with measurable rain from August 10e15. Nonetheless, the Beijing Meteorological Bureau showed significant improvement in air quality (e.g., NO2) even during rain-free days, attributing these reductions to the ECMs (UNEP, 2009).

5. Analysis Duncan et al. (2010) was the first to use the OMI FNR to determine the chemical sensitivity of PO3 in Los Angeles (LA), which exhibits similar photochemistry and meteorology as Beijing in summer. Examining LA, they found that FNRs < 1 indicate VOC-

1ox1o around Beijing City Center (116W, 40N) 4

HCHO/NO2 (FNR)

3

2005 2006 2007 2008

2

1

-Emission Controls-

0 3.0

HCHO [1016 mol cm-2]

2.5 2.0 1.5 1.0 0.5 -Emission Controls-

NO2 [1015 mol cm-2]

0.0 40

30

20

10

-Emission Controls0 Jan

Feb

Mar

Apr

May 16

Jun 2

Jul

Aug

Sep

Oct 15

Nov

Dec 2

Fig. 2. 7-day running means of (a) FNR, (b) HCHO total columns [10 mol cm ], and (c) tropospheric NO2 columns [10 mol cm ] for 2005e2008. The spatial average is for a 1 1 area around the Beijing city center and color coded by year similar to Fig. 1. The grey shading in (a) identifies the VOC-NOx-limited regime (FNRs between 1 and 2).

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limited conditions, while FNRs > 2 indicate NOx-limited conditions. FNRs between 1 and 2 represent a transition regime (i.e. a mixed VOC-NOx-limited regime) where both NOx and VOCs can change PO3. For this work, we applied these regime definitions to Beijing since both cities are predominantly VOC-limited (Wang et al., 2008; Zhao et al., 2009; Duncan et al., 2010), have similar VOC speciation (Song et al., 2007; Brown et al., 2007), and experience stagnant meteorological conditions in summer. Fig. 2 shows 7-day running means of the OMI FNR, and HCHO and NO2 columns calculated for a 1 1 box around the Beijing city center (for reference, Fig. 3 shows the spatial extent of our area of interest). In general, the FNRs indicate that VOC-limited and mixed VOC-NOx-limited conditions (highlighted in grey shading in Fig. 2a) occurred in summer from 2005 to 2007. There was a prolonged period in 2008 (45 days; June 29eAugust 11) where the FNR indicates PO3 was NOx-limited (Fig. 2a); hereafter, referred to as the “NOx-limited period”. Table 2 shows that the average FNR for the NOx-limited period was 2.32 in 2008 and between 1.10 and 1.32 for 2005e2007. We repeated the analyses for a smaller 0.5  0.5 grid over Beijing’s downtown and our overall conclusions remain unchanged, indicating reasonable spatial homogeneity within our sampling domain. The major advantage of choosing the larger 1 1 grid size is that there are fewer data gaps. After the ECMs were lifted at the end of September, the FNR returned to values typical of previous years.

5.1. Decrease in OMI NO2 during the ECMs As shown in Fig. 2c and Table 2, the transition to a predominantly NOx-limited regime in 2008 was due to the decrease in NO2 in

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Table 2 The mean, standard deviation, skewness, maximum and minimum values of the FNR (HCHO/NO2), HCHO, and NO2 calculated during the NOx-limited period between June 29 and August 11 for 2005 through 2008. Temporal averages are calculated over a 1 1 box around the Beijing city center.

FNR (HCHO/NO2)

HCHO (1016 mol cm2)

NO2 (1015 mol cm2)

Mean Std. Deviation Skewness Max Value Min Value Mean Std. Deviation Skewness Max Value Min Value Mean Std. Deviation Skewness Max Value Min Value

2008

2007

2006

2005

2.32 0.69 1.12 5.09 1.00 1.46 0.34 0.03 2.34 0.75 6.44 0.88 0.17 7.96 3.73

1.26 0.27 1.15 2.19 0.82 1.37 0.33 0.12 2.29 0.68 11.00 2.43 0.34 16.30 7.75

1.32 0.34 1.47 2.59 0.78 1.35 0.34 0.49 2.37 0.65 10.49 2.47 0.72 19.00 6.68

1.10 0.22 1.15 1.71 0.82 1.33 0.37 0.73 2.24 0.66 12.20 2.62 0.73 18.59 8.81

response to the ECMs. The mean NO2 column was 6.44  1015 mol cm2 in 2008, but was between 10.49 and 12.20  1015 mol cm2 in 2005e2007. Table 2 shows that the standard deviation and skewness of NO2 during the period are a relative minimum indicating reduced variability, and greater clustering about the mean, i.e. fewer occurrences of higher than average values of NO2 that would contribute to lower FNRs. Witte et al. (2009) found an average 43% reduction in the OMI NO2 column during the ECMs as compared to previous years. Using a different analyses approach, Mijling et al. (2009) calculated a 59% reduction of OMI NO2 in August 2008. Changes in OMI HCHO did not significantly

June 29 - August 11 HCHO/NO2 Mean 2006

116.80

1ox1o Domain

40.60

40.60

116.00

2005

3

39.80

39.80

116.00

2007

116.80

2008

HCHO/NO2

2

1

0

Fig. 3. The FNR averaged over the June 29eAugust 11 NOx-limited period for 2005, 2006, 2007, and 2008 over Beijing. The black box is our 1 1 domain centered around the Beijing city center (asterisk). The thick black outline highlights the provincial boundary of Beijing.

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contribute to the increase in FNRs during the NOx-limited period (Fig. 2b; Table 2). Although HCHO was slightly higher during this period in 2008 than in previous years (Table 2), the enhancement was small compared to the reduction in NO2 during the ECMs. Interestingly, Wang et al. (2010) showed that despite the reductions in NOx and anthropogenic VOCs during the ECMs, surface ozone increased by 16%, citing regional transport of photochemically aged air and decreased NO-titration of ozone (i.e. NO þ O3 / NO2 þ O2). This result is not surprising as ozone concentrations are depressed when NO concentrations are very high (e.g., in power plants and vehicular traffic; Sillman, 2003). This result suggests that the NOx emission controls in effect for the Games were not strict enough in order to decrease levels of ozone. Fig. 3 shows the spatial variability of the FNR around Beijing averaged over the NOx-limited period. We note that the spatial sampling of HCHO (0.25  0.25 ) is more coarse then NO2 (0.05  0.05 ). Thus spatial variations in FNR will be more strongly influenced by changes

in NO2. Within our 1 1 domain around Beijing, PO3 was predominantly VOC-limited (FNR < 1, dark blue) between 2005 and 2007. The FNRs indicate a shift to a mixed VOC-NOx-limited regime (green) moving away from the city center. This is consistent with previous measurements showing that PO3 in the Beijing urban area is VOC-limited (Chou et al., 2009), while PO3 in surrounding suburban and rural areas is NOx-limited (Wang et al., 2006). During the ECMs in 2008, the significant reductions in NO2 caused the FNRs to transition to higher values throughout the domain and were mostly greater than one. The regions outside the city center were also impacted becoming more NOx-limited relative to previous years. We obtain a sense of the uniqueness of the NOx-limited period by comparing the FNR over Beijing during the Games to FNRs for other polluted urban cities in China (Fig. 4). We applied the same set of analyses in Fig. 2 to TianjineQinhuangdao, the ShanyangeYingkou region, the Shijiazhuang to Zhenghou urban/ industrial corridor, ShanghaieNanking, and Hong Kong. Fig. 4

Fig. 4. JulyeAugust mean of the FNRs for 2005 through 2008. The blue areas show FNRs < 1, green for FNRs between 1 and 2, and red for FNRs > 2. Numbers in the top left panel indicate the white-boxed regions of interest: 1 ¼ Beijing province, 2 ¼ Tianjin-Qinhuangdao, 3 ¼ Shanyang-Yingkou region, 4 ¼ Shijiazhuang to Zhenghou industrial corridor, 5 ¼ Shanghai-Nanking region, and 6 ¼ Hong Kong.

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4

June 29 - Aug. 11, 2008 (NOx-limited Period) Aug. 12 - Sept. 21, 2008 (VOC-NOx-limited Period)

FNR

3

2

1

0 20

22

24 26 28 Surface Temperature [oC]

30

32

Fig. 5. FNR vs. surface temperatures from rawinsondes. The horizontal dashed line indicates the boundary between the NOx-limited (black) and VOC-NOx-limited (red) regimes. Table 3 Mean and standard deviation of the FNR (HCHO/NO2), HCHO, and NO2 calculated for the NOx-limited and VOC-NOx-limited periods, and the Olympics and Paralympic time periods. FNR NOx-limited period (June 29eAug. 11) VOC-NOx-limited period (Aug. 12eSept. 21) Olympics (Aug. 8e24) Paralympics (Sept. 6e17)

HCHO [1016 NO2 [1015 Tsfc [ C] mol cm2] mol cm2]

2.24  0.71 1.49  0.32

6.37  0.80 28.72  1.25

1.33  0.31 1.07  0.23

8.02  1.65 24.80  1.45

1.85  0.62 1.11  0.37 1.24  0.27 1.07  0.31

6.01  1.11 26.54  1.11 8.60  0.79 23.84  0.25

shows the FNR for JulyeAugust means each year over China. The FNRs indicate that PO3 in these cities had both VOC-limited and mixed VOC-NOx-limited regions in all years, including 2008. The maximum summertime OMI FNRs rarely exceeded 2. 5.2. Variations in the FNR during the ECMs Why did the NOx-limited period end August 11th, during the middle of the Olympics, when the ECMs were in effect through September? Fig. 2 shows that the OMI NO2 column increased and the FNR subsequently decreased during the remaining period of the ECMs (August 12eSeptember 21, 2008); hereafter, we refer to this

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period as the VOC-NOx-limited period. Table 3 shows that NO2 was 6.37  1015 mol cm2 during the NOx-limited period and increased to 8.02  1015 mol cm2 during the VOC-NOx-limited period. Despite this increase, the NO2 columns were still lower than the same period in previous years. There was also a sharp decrease in the OMI HCHO columns after August 11 to the end of the Olympics (Fig. 2b) that also contributed to the decrease in the FNR. The average HCHO in the VOC-NOx-limited period was lower than in the NOx-limited period (Table 3), which is consistent with the normal seasonal decline in HCHO. The Olympic time period includes both limitations where the range of FNR values based on the 1-sigma standard deviation (0.62 from Table 3) is between 1.23 and 2.47. The VOC-NOx-limited period during the Paralympics is also unique because previous years show that the sensitivity of PO3 is predominantly VOC-limited in September (Fig. 2a). A change in meteorological regime may explain most of the decrease in the FNR after August 11 and subsequent shift to a mixed VOC-NOx-limited regime. For example, Wang et al. (2010) reported measurable rain on most days during August 10e16, but little rainfall before that. The RH from rawinsondes peaked at 74.2% on August 11 and notably decreased to an average of 65.0% during the VOC-NOx-limited period. Table 3 shows that the average surface temperature of the NOx-limited period was higher than the VOCNOx-limited period. We calculate a high correlation (r2 ¼ 0.71) between OMI HCHO and the rawinsonde Tsfc (from Fig. 1a) during the period of the ECMs. This temperature dependence may be associated with the known temperature dependence of biogenic VOC emissions and evaporative emissions of VOCs from vehicles. Duncan et al. (2010) found that the FNR generally increases (i.e. become more NOx-limited) with temperature in regions where biogenic VOCs contribute significantly to the total VOC reactivity. Fig. 5 shows that there is a general positive correlation between the FNR and surface temperature, where the FNRs in the NOx-limited period (black symbols) occurred typically above 28  C. Other meteorological factors that could play a role in the transition from the NOx-limited to the VOC-NOx-limited periods include changes in boundary layer height and rainfall rates. For instance, Li et al. (2010) reported a higher rainfall rate and mixed layer height of 8.89 mm and 1709 m, respectively, during the Olympics, compared to other time periods during the ECMs. 5.3. Impact of Beijing’s greening initiative There is speculation that an increase in biogenic VOCs due to Beijing’s greening initiative contributes to the local ozone

Fig. 6. JuneeAugust MODIS NDVI and EVI mean indices computed by the NASA GES DISC. The means are plotted per year between 2003 and 2010. The average of the Aqua and Terra V005 MODIS NDVI and EVI 3-month averages are shown. The area average encompasses the Beijing provincial borders and vicinity from 38e41 N to 115e118 E.

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formation (Xie et al., 2008). However, we calculated no significant trend in OMI HCHO from 2005 to 2008 over Beijing (1 1 area). We calculated this trend by subtracting the monthly mean from the monthly mean for all years in the OMI HCHO record, then performing a linear fit to the data by minimizing the chi square error statistic. Can we detect an enhancement in vegetation from space? We used the 2003e2010 MODIS Aqua and Terra 1 1 monthly mean Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) over the Beijing province. The vegetation indices (VIs) give a measure of ‘greenness’ of the Earth’s land surface. The VIs complement each other in detecting vegetation changes (Huete et al., 2002). NDVI is chlorophyll sensitive with values ranging from 1 to 1. Values above 0.6 indicate dense green vegetation (Huete et al., 2002). EVI is more responsive to variations in the canopy structure, including leaf area with values greater than 0.4 indicating a high leaf area and greater canopy cover (Huete et al., 2006). These analyses were produced with the Giovanni online data system, developed and maintained by the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) (Acker and Leptoukh, 2007). Fig. 6 shows the 2003e2010 JulyeAugust mean VIs. We observe that (i) there is a gradual increase in both indices since 2003 which peaks in 2008 suggesting a slight increase in vegetation cover, (ii) since 2006, values of NDVI exceed 0.6 indicating a shift toward more dense vegetation cover, (iii) EVI exceeds 0.4 only in 2008, and (iv) after 2008 there is a downturn in the VIs toward values similar to 2006 suggesting a return to the pre-“greening” VOC environment. These changes are subtle but provide qualitative evidence that there was a change in the vegetation cover leading up to the Games. Testing the significance of these changes will require looking at other vegetation data sets over Beijing that will provide greater sampling statistics, i.e. daily measurements and higher spatial coverage. 6. Summary The emission control measures (ECMs) implemented before and during the Games in Beijing offered a real-world experiment of the effectiveness of VOC and NOx emission reductions on the chemical sensitivity of ozone formation as detected from space. Following Duncan et al. (2010), we used the long-term records of OMI HCHO and NO2 to show that the formaldehyde to NO2 ratio (FNR) increased in Beijing from July through September 2008 mainly as a result of significant reductions of NOx emissions. FNRs greater than 2 were frequently observed, indicating a NOxlimited regime where ozone formation is more sensitive to changes in NOx. This change in the limitation of ozone formation is unique for Beijing in the OMI data record. During the same period in the preceding three years, VOC-limited and mixed VOC-NOx-limited conditions were more typical, in general agreement with limitations estimated from in situ observations reported in the literature (Wang et al., 2008; Chou et al., 2009). During the ECMs, variations in the FNR are mainly explained by variations in weather. The mixed VOC-NOx-limited regime in Beijing during the Paralympics is also unique because in previous years ozone production in September was predominantly VOClimited. After the ECMs were lifted, NO2 returned to values typical of previous years and the FNR indicated a return to a VOC-limited regime. We do not observe from space-based data that Beijing’s greening initiative had a significant impact on OMI HCHO. However, the MODIS vegetation indices show small increases in the EVI and NDVI from 2003 leading up to the Games in 2008, but a post-Game decrease in the 2009e2010 to 2006 levels.

Acknowledgments This work is supported by NASA’s Atmospheric Chemistry, Modeling and Analysis and Applied Sciences Air Quality Programs.

References Acker, J.G., Leptoukh, G., 2007. Online analysis enhances use of NASA earth science data. Eos Trans. 88, 14e17. Akimoto, H., 2003. Global air quality and pollution. Science 302, 1716e1719. doi:10.1126/science.1092666. An, X., Zhu, T., Wang, Z., Li, C., Wang, Y., 2007. A modeling analysis of a heavy air pollution episode occurred in Beijing. Atmos. Chem. Phys. 7, 3103e3114. Beijing Bureau of Statistics, 2007. Beijing Statistics Yearbook 2007. China Statistics Press, Beijing (in Chinese). Brown, S.G., Frankel, A., Hafner, H.R., 2007. Source apportionment of VOCs in the Los Angeles area using positive matrix factorization. Atmos. Environ. 41, 227e237. Bucsela, E., Celarier, E., Wenig, M., Gleason, J., Veefkind, P., Boersma, K.F., Brinksma, E., 2006. Algorithm for NO2 vertical column retrieval from the ozone monitoring instrument. IEEE Trans. Geosci. Rem. Sens. 44, 1245e1258. Chameides, W., Walker, J.C.G., 1973. A photochemical theory of tropospheric ozone. J. Geophys. Res. 78, 8751e8760. Chameides, W., Fehsenfeld, F., Rodgers, M., Cardelino, C., Martinez, J., Parrish, D., Lonneman, W., Lawson, D., Rasmussen, R., Zimmerman, P., Greenberg, J., Middleton, P., Wang, T., 1992. Ozone precursor relationships in the ambient atmosphere. J. Geophys. Res. 97 (D5), 6037e6055. Chance, K., Palmer, P.I., Spurr, R.J.D., Martin, R.V., Kurosu, T.P., Jacob, D.J., 2000. Satellite observations of formaldehyde over North America from GOME. Geophys. Res. Lett. 27, 3461e3464. Chou, C., Tsai, C., Shiu, C., Liu, S., Zhu, T., 2009. Measurement of NOy during the campaign of air quality in Beijing (CAREBeijing-2006): implications for the ozone production efficiency of NOx. J. Geophys. Res. 114 (D00G01). doi:10.1029/ 2008JD010446. Duncan, B.N., Chameides, W.L., 1998. Effects of urban emission control strategies on the export of ozone and ozone precursors from the urban atmosphere to the troposphere. J. Geophys. Res. 103 (D21), 28159e28179. Duncan, B.N., et al., 2010. Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation. Atmos. Environ. 44, 2213e2223. Haagen-Smit, A.J., 1952. Chemistry and physiology of Los Angeles smog. Ind. Eng. Chem. 44 (6), 1342e1346. doi:10.1021/ie50510a045. Hallet, W., 1965. Effect of ozone and cigarette smoke on lung function. Arch. Environ. Health 10, 295e302. Hao, J.M., Wang, L.T., 2005. Improving urban air quality in China: Beijing case study. J. Air Waste Manage. Assoc. 55, 1298e1305. Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., Ferreira, L.G., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Rem. Sens. Environ. 83 (1e2), 195e213. Huete, A., Didan, K., Shimabukuro, Y.E., Ratana, P., Saleska, S.R., Hutyra, L.R., Yang, W., Nemani, R.R., Myneni, R., 2006. Amazon rainforests green-up with sunlight in dry season. Geophys. Res. Lett. 33 (L06405). doi:10.1029/ 2005GL025583. Kurosu, T.P., Chance, K., Sioris, C.E., 2004. Preliminary results for HCHO and BrO from the EOS-aura ozone monitoring instrument. Passive optical remote sensing of the atmosphere and clouds IV. Proc. SPIE 5652. doi:10.1117/ 12.578606. Li, Y., Shao, M., Lu, S., Chang, C.-C., Dasgupta, P.K., 2010. Variations and sources of ambient formaldehyde for the 2008 Beijing Olympic games. Atmos. Environ. 44, 2632e2639. Martin, R.V., 2004. Evaluation of GOME satellite measurements of tropospheric NO and HCHO using regional data from aircraft campaigns in the southeastern United States. J. Geophys. Res. 109 (D24307). doi:10.1029/2004JD004869. Mijling, B., van der, A.R.J., Boersma, K.F., van Roozendael, M., De Smedt, I., Kelder, H.M., 2009. Reductions of NO2 detected from space during the 2008 Beijing Olympic Games. Geophys. Res. Lett. 36 (L13801). doi:10.1029/ 2009GL038943. Millet, D.B., Jacob, D.J., Boersma, K.F., Fu, T.M., Kurosu, T.P., Chance, K., Heald, C.L., Guenther, A., 2008. Spatial distribution of isoprene emissions from North America derived from formaldehyde column measurements by the OMI satellite sensor. J. Geophys. Res. 113 (D02307). doi:10.1029/2007JD008950. Molina, M.J., Molina, L.T., 2004. Megacities and atmospheric pollution. J. Air Waste Manage. Assoc. 54, 644e680. Ohara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X., Hayasaka, T., 2007. An Asian emission inventory for the period 1980e2020. Atmos. Chem. Phys. 7, 4419e4444. Pang, X., Mun, Y., Zhang, Y., Lee, X., Yuan, J., 2009. Contribution of isoprene to formaldehyde and ozone formation based on its oxidation products measurement in Beijing, China. Atmos. Environ. 43, 2142e2147. Seinfeld, J., 1989. Urban air pollution: state of the science. Science 243, 745e752. Sillman, S., 1995. The use of NOy, H2O2, and HNO3 as indicators for ozone-NOxhydrocarbon sensitivity in urban locations. J. Geophys. Res. 100, 14175e14188.

J.C. Witte et al. / Atmospheric Environment 45 (2011) 3103e3111 Sillman, S., 2003. Tropospheric ozone and photochemical smog. In: Sherwood Lollar, B. (Ed.), Treatise on Geochemistry. Environmental Geochemistry, vol. 9. Elsevier Ch. 11. Sillman, S., Logan, J., Wofsy, S., 1990. The sensitivity of ozone to nitrogen oxides and hydrocarbons in regional ozone episodes. J. Geophys. Res. 95, 1837e1851. Song, Y., Shao, M., Liu, Y., Lu, S., Kuster, W., Goldan, P., Xie, S., 2007. Source apportionment of ambient volatile organic compounds in Beijing. Environ. Sci. Technol. 41, 4348e4353. Stokinger, H., 1965. Ozone toxicology: a review of research and industrial experience. Arch. Environ. Health 10, 719e731. Streets, D.G., et al., 2003. An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. J. Geophys. Res. 108, 8809. doi:10.1029/2002JD003093. Streets, D.G., et al., 2007. Air quality during the 2008 Beijing Olympic Games. Atmos. Environ. 41, 480e492. United Nations Environment Program (UNEP), 2009. Independent Environmental Assessment: Beijing 2008 Olympic Games. UNEP, ISBN 978-92-807-2888-0. Wang, T., Ding, A., Gao, J., Wu, W.S., 2006. Strong ozone production in urban plumes from Beijing, China. Geophys. Res. Lett. 33, L21806. doi:10.1029/2006GL027689. Wang, Q., Han, Z., Wang, T., Zhang, R., 2008. Impacts of biogenic emissions of VOC and NOx on tropospheric ozone during summertime in eastern China. Sci. Total Environ. 395, 41e49. doi:10.1016/j.scitotenv.2008.01.059. Wang, Y., Hao, J., McElroy, M.B., Munger, J.W., Ma, H., Chen, D., Nielsen, C.P., 2009. Ozone air quality during the 2008 Beijing Olympics e effectiveness of emission restrictions. Atmos. Chem. Phys. 9, 5237e5251.

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Wang, T., et al., 2010. Air quality during the 2008 Beijing Olympics: secondary pollutants and regional impact. Atmos. Chem. Phys. 10, 12433e12463. Wenig, M.O., Cede, A.M., Bucsela, E.J., Celarier, E.A., Boersma, K.F., Veefkind, P., Brinksma, E.J., Gleason, J.F., Herman, J.R., 2008. Validation of OMI tropospheric NO2 column densities using direct-Sun mode Brewer measurements at NASA Goddard Space Flight Center. J. Geophys. Res. 113 (D16S45). doi:10.1029/ 2007JD008988. Witte, J.C., Schoeberl, M.R., Douglass, A.R., Gleason, J.F., Krotkov, N.A., Gille, J.C., Pickering, K.E., Livesey, N., 2009. Satellite observations of changes in air quality during the 2008 Beijing Olympics and Paralympics. Geophys. Res. Lett. 36. doi:10.1029/2009GL039236. Xie, X., Shao, M., Liu, Y., Lu, S., Chang, C., Chen, Z., 2008. Estimate of initial isoprene contribution to ozone formation potential in Beijing, China. Atmos. Environ. 42, 6000e6010. Young, W., Shaw, D., Bates, D., 1964. Effects of low concentrations of ozone on pulmonary function in man. J. Appl. Physiol. 19, 765e768. Zhang, X., Mu, Y., Song, W., Zhuang, Y., 2000. Seasonal variations of isoprene emissions from deciduous trees. Atmos. Environ. 34, 3027e3032. Zhang, Q., et al., 2007. NOx emission trends for China, 1995e2004: The view from the ground and the view from space. J. Geophys. Res. 112 (D22306). doi:10.1029/ 2007JD008684. Zhao, C., Wang, Y., Zeng, T., 2009. East China Plains: a “Basin” of ozone pollution. Environ. Sci. Technol. 43, 1911e1915.