Tropospheric ozone and nitrogen dioxide measurements in urban and rural regions as seen by IASI and GOME-2

Authors


Abstract

[1] Tropospheric ozone (O3) columns in urban and rural regions as seen by the Infrared Atmospheric Sounding Interferometer (IASI) are analyzed along with the Global Ozone Monitoring Experiment (GOME-2) tropospheric nitrogen dioxide (NO2) columns. Results over nine cities of the Northern Hemisphere for the period 2008–2011 show a typical seasonal behavior of tropospheric O3, with a first maximum reached in late spring because of stratospheric intrusion mainly and a continuous rise till the summer because of the anthropogenic-based ozone production. Over the East Asian cities, a decrease in the O3 tropospheric column is detected during the monsoon period. Seasonal cycling of tropospheric NO2 shows consistent higher values during winter because of the higher anthropogenic sources and longer lifetime. In rural regions, a complex relation between the O3 and NO2 columns is found, with good correlation in summer and winter. O3 concentrations in rural sites are found to be comparable to those closest to the anthropogenic emission sources, with peak values in spring and summer. Furthermore, the effect of the reduction of pollutant emissions in the Beijing region during the Olympic Games of 2008 compared to the same summer period in the following 3 years is studied. GOME-2 NO2 measurements show a reduction up to 54% above Beijing during this period compared to the following 3 years. IASI O3 measurements show an increase of 12% during July 2008 followed by a decrease of 5–6% during the months of August and September.

1 Introduction

[2] Global monitoring of tropospheric O3 is essential as it is an important greenhouse gas and air pollutant [Jacobson, 2012]. It is a significant absorber of infrared and ultraviolet (UV) radiation and a primary source of the most important oxidant in the atmosphere, the hydroxyl radical OH, that is highly reactive with organic and inorganic compounds [Levy et al., 1985; Finlayson-Pitts and Pitts, 1997; Jacob, 2000]. Exposure to high levels of O3 is associated with pulmonary and chronic respiratory diseases as well as premature mortality [Bell et al., 2004, 2007; Ito et al., 2005; Ebi and McGregor, 2008]. Economic concerns are also raised because of the negative effect of O3 on vegetation, ecosystems, crops production, and yield [Reich, 1983; Chappelka et al., 1999; Collins et al., 2000; Fuhrer and Booker, 2003; Schaub et al., 2005; Karnosky et al., 2007].

[3] Sources of O3 in the troposphere are due to either natural intrusion from the stratosphere, where most of the O3 resides, or photochemical production from precursors. These precursors are pollutants emitted mainly during anthropogenic urban activities and include carbon monoxide (CO), peroxy radicals generated by the photochemical oxidation of the Volatile Organic Compounds (VOCs), such as hydrocarbons and aldehydes, and nitrogen oxides (NOx = NO + NO2). The main sources of NOx are either anthropogenic, such as the result of the combustion of fossil fuels and biomass burning, or natural from wildfires, soil emissions, and lighting. Most of the NO2 in urban air results from the rapid oxidation of NO which is the major nitrogenous product emitted from combustion [Finlayson-Pitts and Pitts, 1997; Klonecki and Levy, 1997; Jacob, 2000; Seinfeld and Pandis, 2006; Jacobson, 2012]. One can distinguish two regimes with different O3-NOx-VOC sensitivity. The first one is the NOx-limited regime where O3 concentrations increase with increasing NOx, and the second one is the VOC-limited (NOx-saturated) regime, where O3 production rate increases with increasing VOCs concentrations. Generally, urban centers are found to be in a VOC-limited regime, while rural regions downwind are found to be in a NOx-limited regime [Milford et al., 1989, 1994; Sillman, 1999; Duncan et al., 2010]. In fact, O3 concentrations in rural sites are frequently found to be higher than the values found near anthropogenic activity, with peak values in spring and summer [Logan, 1985, 1989; Sillman et al., 1990]. The measurement of tropospheric O3 and NO2 by satellite is shown to be efficient since it provides a good way to get regional and global information on O3 and NO2 distributions, transport, and variability [Tie et al., 2007]. Tropospheric O3 retrievals from satellites have been possible by subtracting the stratospheric O3 column with UV sounders [e.g., Fishman and Larsen, 1987; Schoeberl et al., 2007], directly from measurements in the UV [Liu et al., 2006], and from high-resolution infrared sounders like the Interferometric Monitor for Greenhouse gases (IMG), the Tropospheric Emission Spectrometer (TES), and IASI [Coheur et al., 2005; Worden et al., 2007; Eremenko et al., 2008].

[4] In this paper we analyze the seasonal variations of O3 and NO2 in the troposphere, over 4 years (2008–2011) above specific urban and rural areas of the Northern Hemisphere (NH), using data provided by the IASI and GOME-2 instruments on the MetOp-A (Meteorological Operational) satellite along with wind patterns provided by ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis (ERA). Section 2 details the study area selection and how measurements data are collocated above cities. In section 3 we explain the method used to extract wind directions and the tropospheric O3 retrieval from the IASI mission as well as GOME-2 retrievals of the tropospheric NO2 columns. We discuss the results in section 4 and list our conclusions in section 5.

2 Study Area Selection

[5] In order to understand the effect of local pollution, we chose to focus in this study on a selected set of big cities, listed in Table 1, known for their high anthropogenic emissions in different locations in the NH and over three continents: North America, Europe, and Asia. Over the period from January 2008 to December 2011, monthly averaged gridded tropospheric O3 and NO2 columns were calculated, over a grid size of 0.25° × 0.25°. The corresponding rural area for each city was defined as the area downwind the city (see section 3.1).

Table 1. Cities Locations Used in This Study and the Corresponding Rural Areas (the Latter According to the Prevailing Wind Directions From the Urban Center)
Urban RegionRural Region
CityLatitude Range (°N)Longitude Range (°E)Wind DirectionLatitude Range (°N)Longitude Range (°E)
Mexico City1919.75−99.5−98.75SW18.2519−100.25−99.5
Los Angeles33.534.25−118.5−117.75East33.534.25−117.75−117
Istanbul40.7541.528.7529.5SW4040.752828.75
Madrid4040.75−4−3.25East4040.75−3.25−2.5
New York40.2541−74.5−73.75East40.2541−73.75−73
Tehran35.25365151.75NE3636.7551.7552.5
New Delhi28.25297777.75SE27.528.2577.7578.5
Shanghai30.7531.5121121.75SE3030.75121.75122.5
Beijing39.540.25116116.75SE38.7539.5116.75117.5

3 Measurements

[6] High-pollution episodes are notably detected above and around cities. During such events, elevated values of NO2 and O3 can be observed by satellite in the troposphere [e.g., Tie et al., 2007; Dufour et al., 2010]. In this study we aim at investigating the relation between O3 and NO2 pollution over cities and their corresponding rural areas using satellite data: We use in particular IASI tropospheric O3 column and GOME-2 tropospheric NO2 column data. In addition we use wind fields from ECMWF Reanalysis to locate the rural areas where the formation or transport of O3 is important.

3.1 Wind Directions

[7] Wind direction patterns used in this study are from the ERA-Interim archive at ECMWF (u and v components of horizontal wind). The data assimilation produces four analyses per day at 00:00, 06:00, 12:00, and 18:00 UTC at 37 pressure levels from 1000 to 1 hPa with a Gaussian grid with a resolution of 0.7° at the equator. Data Services associated with wind data sets apply an interpolation scheme to make it adaptable to requested resolutions and representation forms [Berrisford et al., 2009; Dee et al., 2011]. In the ERA-Interim database, monthly means of wind direction patterns are interpolated and extracted over a grid size of 0.75° × 0.75°. In this study, we attempt to analyze the prevailing wind directions from each studied urban city in Table 1. We averaged monthly wind patterns over the 4 year period of the study in the boundary layer (surface to 750 hPa) where the production and transport of pollutants are the most important. The result is inserted as “rural” region in Table 1.

3.2 IASI Ozone Measurements

3.2.1 Instrumentation

[8] The IASI instrument launched on board the MetOp-A platform on 19 October 2006 is a nadir-looking Fourier transform spectrometer that probes the Earth's atmosphere in the thermal infrared spectral range between 645 and 2760 cm−1, with a spectral resolution of 0.5 cm−1 (apodized) and a 0.25 cm−1 spectral sampling. Three IASI instruments have been assigned for a span of at least 15 years. The second one was launched on 17 September 2012 on board the MetOp-B, and the third instrument is scheduled for 2016–2017. The IASI footprint is a matrix of 2 × 2 pixels, each with 12 km diameter at nadir. IASI monitors the atmospheric composition at any location two times per day with a swath width of 2200 km corresponding to a total of 120 views. IASI can as well measure many of the chemical components that play a key role in the climate system and are responsible for atmospheric pollution [Clerbaux et al., 2009; Coheur et al., 2009; Turquety et al., 2009; Clarisse et al., 2011]. As far as O3 is concerned, vertical information has been demonstrated to be sufficient to study separately stratospheric O3 [Scannell et al., 2012], O3 in the upper troposphere/lower stratosphere [Barret et al., 2011], and O3 in the troposphere [Boynard et al., 2009; Dufour et al., 2010; Wespes et al., 2012].

3.2.2 Retrievals

[9] The IASI level 1C radiance data (1.3 million spectra per day) are distributed by EumetCast, the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)'s Data Distribution system, and global distributions of O3 vertical profiles are retrieved in near real time using an exclusive radiative transfer and retrieval software for the IASI O3 product, the Fast Optimal Retrievals on Layers for IASI (FORLI-O3) [Hurtmans et al., 2012]. The FORLI radiative transfer model uses precalculated tables of absorbance of the O3 band (1025–1075 cm−1) at different pressures and temperatures. It provides profiles over 39 layers from the surface up to 39 km based on the inversion scheme of the Optimal Estimation Theory [Rodgers, 2000]. Details and description of FORLI are given by Hurtmans et al. [2012], and a comparison of performances with other retrieval algorithms is provided by Dufour et al. [2012]. The IASI FORLI-O3 observations are selected for scenes with cloud coverage below 13% and with root mean square (RMS) of the spectral fit residual lower than 3.5 × 10−8 W/(cm2 sr cm−1). The O3 a priori profile (plotted in black in Figure 1) and associated a priori covariance matrix are constructed from the McPeters/Labow/Logan climatology of O3 profiles, which combines long-term satellite limb measurements and measurements from ozonesondes [Turner, 2004; Hurtmans et al., 2012]. The constraint on the measurement has an average value of 2 × 10−8 W/(cm2 sr cm−1) which is close to the instrumental noise. Profiles and partial column products have been validated and compared with available ground-based, aircraft, O3 sonde, and other satellite observations [Anton et al., 2011; Gazeaux et al., 2012; Parrington et al., 2012; Pommier et al., 2012]. These analyses show a good agreement in the troposphere (below 10 km) and middle stratosphere (25–40 km), where the differences are lower than 10% on average. However, a significant positive bias of about 10–26% is found between 10 and 25 km. The same bias is reported when using different retrieval algorithms [Dufour et al., 2012].

Figure 1.

(a) IASI mean O3 mixing ratio (ppb) profile for the urban cities listed in Table 1 during January 2011 (in blue) and June 2011 (in red), with the a priori profile plotted in black. (b) Averaging kernel functions for the merged 0–8 km IASI O3 partial columns for the same locations and period. Note that some cities have altitudes > 0.

[10] Interestingly, Eremenko et al. [2008] have shown that it was possible to study, with infrared sounders, the variation of the tropospheric O3 column around cities in particular since high thermal contrast (the temperature difference between that of the surface and that of the first atmospheric layer), and thus more information in the boundary layer, is usually associated to the spring-summer photochemical pollution events.

[11] We plot in Figure 1 the O3 vertical profiles (Figure 1a) and the corresponding averaging kernel functions for the merged 0–8 km columns (Figure 1b) for IASI observations recorded during January and June 2011 above the urban regions in Table 1. The vertical profiles in Figure 1a show expected higher O3 mixing ratio values in June than in January. A significant increase in surface O3 values between January and June is recorded for all the cities, reflecting high surface O3 production in summer along with a high thermal contrast. In this study, we use IASI day observations of the 0–8 km tropospheric O3 column since the information content of IASI data is shown to be higher during the day [Clerbaux et al., 2009].

[12] Figure 1b shows that the averaging kernels are more sensitive to the lower troposphere in summer because of higher surface temperature and better thermal contrast, leading to a smaller contribution of the a priori profile to the retrieved profiles. We chose the 0–8 km column because it provides above 0.5 degree of freedom (the trace of the averaging kernel matrix) in the troposphere and avoids having to define a variable tropopause height, which impacts on quantifying the O3 content in the troposphere [Held, 1981; Bethan et al., 1996; Hoinka, 1997; Reichler et al., 2003]: Since the cities selected for this study (see Table 1) fall in a latitude range between 19°N and 41°N, this choice thus provides a good mean to maximize the tropospheric information content while minimizing the stratospheric contamination.

[13] Figure 2 shows the latitudinal variation of the 0–8 km O3 column over the 4 years of the study. It shows that the selected 0–8 km O3 column captures well the signature of tropospheric O3 at midlatitudes. The high values detected in the northern high latitudes are explained by the integration of stratospheric air into the 0–8 km column due to lower tropopause height especially in winter as well as residual stratospheric intrusions, which inject O3-rich air below the 8 km column during the rest of the year. High concentrations are found in the latitudes between 0°N and 45°N, where the main anthropogenic sources of tropospheric O3 are located. On the other hand, the high values detected between 0°S and 45°S correspond likely to the biomass burning source of O3. The figure also shows that the magnitude of the seasonal variation of the O3 column over the period 2008–2011 is smaller for the Southern Hemisphere (SH) in comparison with the NH all year long. The highest detected O3 values in the two hemispheres are in spring (March-April-May for NH and September-October-November for SH) for the 4 year span of 2008–2011, which coincides to the period where the intrusions from the stratosphere are the highest.

Figure 2.

Latitude-time plot of the zonally averaged 0–8 km O3 column between 2008 and 2011 for the IASI daytime observations. The white vertical lines correspond to days with no data.

[14] The O3 column changes according to the latitude and season. High values are especially detected in populated areas in midlatitudes due to the high emission of O3 precursors and the photochemical production of O3, as seen in Figure 3, which represents the monthly averaged 0–8 km O3 column over a grid of 0.5° × 0.5°. The weakest values for the O3 tropospheric column are observed in the high and middle latitudes of the SH as well as around the tropics, all year long except when fires occur. For the months of January and June, high O3 concentrations are observed in high latitudes of the NH, corresponding to the stratospheric intrusion into the 0–8 km column. Photochemical production of O3 is better highlighted during the month of June, notably in midlatitudes of the NH. The figure also shows the transport of O3, between Northern America and Europe and between Southern America and Africa, as well as the transport of pollution from China to North America.

Figure 3.

IASI daytime tropospheric O3 column averaged over a grid of 0.5° × 0.5° for the months of January and June 2011. The white areas over the desert in North Africa and Saudi Arabia correspond to a filter applied on poor spectral fits, because of emissivity issues in the FORLI radiative transfer.

3.3 GOME-2 Nitrogen Dioxide Measurements

3.3.1 Instrumentation

[15] In this study, we analyze the relationship between the tropospheric O3 columns retrieved from IASI and the GOME-2 NO2 tropospheric columns in a polluted environment. We use GOME-2 data since it is on board the MetOp-A platform as well and offer one of the first opportunities to study the O3-NO2 relationship with coincident measurements. GOME-2 is a nadir-scanning UV/visible spectrometer with a swath width of 1920 km with a nominal ground pixel size of 80 × 40 km2 which allows global coverage every 1.5 days. The spectral range covered by the GOME-2 instrument is from 240 to 790 nm distributed on four main optical channels, with a spectral resolution between 0.26 and 0.51 nm [Munro et al., 2006; Valks et al., 2011].

3.3.2 Retrievals

[16] The operational tropospheric NO2 product is provided by the German Aerospace Center, in the framework of the EUMETSAT O3M-SAF (Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring). The differential optical absorption spectroscopy method is used to determine NO2 slant columns from GOME-2 (ir)radiance data in the 425–450 nm range. Initial total NO2 columns are computed using stratospheric air mass factors, and GOME-2-derived cloud properties are used to calculate the air mass factors for scenarios in the presence of clouds. To obtain the stratospheric NO2 component, a spatial filtering approach is used. Tropospheric air mass factors are computed using monthly averaged NO2 profiles from the MOZART-2 (Model for OZone and Related chemical Tracers) chemistry transport model [Valks et al., 2011]. Figure 4 shows the GOME-2 tropospheric NO2 column during January and June 2011. Anthropogenic sources of NO2 are notably detected in midlatitudes especially near populated regions with high anthropogenic activity such as in Northern America, Europe, and Eastern Asia. In comparing the two hemispheres, we note that the NH has in both months larger NO2 concentrations. This is also seen in Figure 5, which shows the seasonal variation over the 4 years of the study in the NH and SH. The magnitude of the tropospheric NO2 column is larger in the NH than in the SH, all year long, for the 4 year period. The highest values are detected in winter for each hemisphere, while the lowest values are in summer. Moreover, the figure highlights the yearly increase in the NO2 column from 2008 to 2011: While the NO2 emission sources are expected to be reduced in industrialized countries, the rapid economic growth, in some countries such as China, is leading to an increase in the NO2 emissions [Richter et al., 2005].

Figure 4.

Monthly averaged NO2 tropospheric column over a 0.25° × 0.25° grid for January and June 2011 as seen by GOME-2.

Figure 5.

Seasonal variation of the tropospheric NO2 column for the years of 2008 to 2011 in the Northern and Southern Hemispheres.

4 Results

4.1 Seasonal Cycling of Ozone in Urban Regions

[17] O3 in the troposphere shows a slower photochemistry in winter and a faster photochemistry in spring and summer [Levy et al., 1985; Klonecki and Levy, 1997]. Figure 6 illustrates the seasonal variation of the 0–8 km O3 column over the nine cities listed in Table 1. Both Figures 6a and 6b show a typical seasonal behavior with increasing values of O3 in late spring (April–May) that could be associated with the transport of O3 from the lower stratosphere to the troposphere [Logan, 1985]. Cities located at high latitudes are subject to larger stratospheric contamination. This can be seen in winter for the first three cities in Figure 6a: Mexico City with latitude defined between 19°N and 19.75°N has smaller winter O3 values than Los Angeles whose location is defined between 33.5°N and 34.25°N which, in turn, has a smaller winter column than Istanbul located at a higher latitude (40.75°N–41.5°N). The second prominent peak, seen, for example, in the cities of Los Angeles and Istanbul in summer, is likely due to high anthropogenic activity. Madrid, New York, and Tehran exhibit a slightly shifted seasonal behavior, with increasing O3 values from spring to summer and reaching its maximum in July and August where the solar activity is at its peak. Lower summertime values of O3 such as in Los Angeles and New York could be due to the photochemical destruction of O3, a phenomenon that is less prominent in spring than in summer [Derwent et al., 1998]. Higher values are likely associated with increase in production of O3 by its precursors and seen, for example, in Mexico City, Istanbul, Madrid, and Tehran.

Figure 6.

(a, b) Seasonal distribution of the IASI 0–8 km O3 in selected urban regions. Results are shown for the period 2008–2011. The shaded regions show the minimum and maximum values recorded during this period.

[18] Figure 6b shows cities where the summer season is the rainy one, such as in New Delhi, Shanghai, and Beijing. In magnitude, the two Chinese cities presented, Shanghai and Beijing, have the highest tropospheric O3 values, reaching 33 DU over Shanghai for the month of June 2011. The cities in Figure 6b, in particular, New Delhi and Shanghai, are characterized by a strong depletion of O3 values (around 8–9 DU), respectively, between June on the one hand and July and August on the other hand. This could be attributed to the summer monsoon, which brings clean air masses with lower values of tropospheric O3, as well as slower photochemical activity because of clouds and the wet scavenging of O3 precursors by rains. In New Delhi, the monsoon starts in mid-June and lasts until the end of August [Varshney and Aggarwal, 1992]. In Beijing and Shanghai, the East Asian summer monsoon falls in July–August and mid-June–mid-July, respectively [Wang et al., 2008]. The drop observed is latitude dependent: Since New Delhi and Shanghai lie closer to tropical latitudes, the intensity of the drop is larger than the one in Beijing which is, on the other hand, more susceptible to stratospheric contamination [Dufour et al., 2010].

4.2 Seasonal Cycling of Nitrogen Dioxide in Urban Regions

[19] The NO2 lifetime is shorter than the one for O3 and depends on many factors such as meteorological conditions and OH concentrations. Sunlight triggers OH production, causing NO2 to be removed from the atmosphere [Jacobs, 2000; Van der A et al., 2006]. All cities plotted in Figure 7 show indeed minima in summer since anthropogenic NO2 is destroyed when exposed to sunlight. On the other hand, higher values of NO2 are expected in winter, when the days are shorter and the solar activity and OH concentrations are lower. Moreover, winter is the season with the strongest anthropogenic emissions in the NH because of heating. For all the cities, we notice that the NO2 values are relatively higher in winter than in summer. For both tropospheric O3 and NO2, we notice that the columns are the highest in the economic centers of China with the highest industrial activity: Shanghai and Beijing, with average values over the 4 years of 31.2 and 29.3 DU for O3 in June and 32.2 × 1015 and 24.5 × 1015 molecules/cm2 for NO2 in December, respectively. It is important to note that over highly polluted regions, most of the tropospheric NO2 accumulates in the boundary layer [Ma et al., 2006], while the 0–8 km O3 column accounts for the boundary layer contribution as well as the contribution from the long-range transport in the free troposphere.

Figure 7.

Same as Figure 6 but for the GOME-2 tropospheric NO2 column.

4.3 Tropospheric Ozone and Nitrogen Dioxide in Rural Regions

[20] As explained in section 1, production of O3 is directly related to the presence of NOx. For low NOx values observed in rural areas, an increase in NOx values leads to an increase in O3 production. This effect is better seen in Figure 8, which shows the 0–8 km O3 column versus the tropospheric NO2 column over rural areas surrounding the different cities of the study for the span of 2008 to 2011. The figure shows a reasonably linear behavior with Pearson correlation coefficients of 0.52 in summer and 0.61 in winter where O3 increases as NO2 increases. Note that the scatter in the data is likely due in part to the difference in lifetime between the two gases: NO2 in rural areas reflects generally local sources, while O3 is influenced by photochemical formation from NO2, the transport from urban regions, and the long-range transport in the free troposphere that is integrated in the 0–8 km column, add to that the error on IASI and GOME-2 measurements and on wind directions. In fact, the approach used to determine the rural region using the prevailing wind direction may cause further uncertainties since the boundary layer winds can have strong diurnal and seasonal variations [Lin et al., 2008, 2009]. The figure represents the NOx-limited regime (section 1) since in these regions the O3 production is partially dependent on and limited by the availability of NO2 and increases with increasing NO2 values.

Figure 8.

Summertime (1 June to 31 August) and wintertime (1 December to 28 February) O3 and NO2 relationship observed at rural sites for the years of 2008–2011.

[21] Figure 9 shows the time series from 2008 to 2011 of urban and rural tropospheric O3 and NO2 in the cities listed in Table 1. Over the 4 years, IASI observations (on the left) show a consistent seasonal behavior for O3 in both urban and rural areas with maxima around spring-summer. The rural values observed are comparable to urban values and exceeding the urban values (up to 7.3 DU in May 2011 in Shanghai City) several times during the study period for all the cities. GOME-2 observations (on the right) show a less marked seasonal behavior for NO2 in the nine cities, with relatively higher winter values in comparison with summer ones. During the whole study period, rural NO2 values were observed to be lower than urban ones, except for Beijing (due perhaps to the transport by strong winds or the availability of important local emissions). The urban-rural detected difference could be due to the absence of local NO2 sources, leading to a decrease in the rural concentrations. The largest difference is seen in New York City, where the difference reached 20.4 × 1015 molecules/cm2 in November 2011.

Figure 9.

Time series (January 2008 to December 2011) for urban and rural tropospheric (left) O3 and (right) NO2 columns for the cities listed in Table 1. Tropospheric O3 in rural areas persists, whereas the rural tropospheric NO2 is lower.

4.4 Case Study of the Beijing Olympic Games of 2008

[22] In this part of the study, we focus on the analysis of the tropospheric NO2 and O3 columns within China by studying the case of the Olympic Games (8–24 August 2008) and the Paralympics (9–17 September 2008). Previous studies have shown, at different background sites, up to 200 km away from urban centers in China, a significant transport of O3 and an enhancement in the surface O3 [Xu et al., 2008]. For the past few decades, Chinese cities, such as Beijing, have been suffering from deterioration of air quality, because of the massive population and industrial growth [Hao and Wang, 2005]. Strict emissions control measures on vehicles and industries have been implemented between July and September 2008 for the summer Olympic and Paralympic Games in Beijing. The World Health Organization 2000 Air Quality Guidelines were used as standards for Beijing's strategy to control air quality [United Nations Environment Programme, 2009]. From 1 July to 20 September, these standards were applied on circulating vehicles, and traffic was reduced by 22% during the Olympics [Wang et al., 2009]. Strict restrictions were applied on polluting industries in Beijing and surrounding provinces, starting 8 August, the first day of the Olympics [Li et al., 2009]. These standards do not include surface O3 limitations; however, because of the limitations on NO2, O3 values were expected to be indirectly affected. During this period, the Ozone Monitoring Instrument showed a significant decrease of around 60% in NO2 concentrations [Mijling et al., 2009]. After the Olympic Games, NO2 values were observed to return comparable to the years before [Witte et al., 2011]. Worden et al. [2012] also detected a significant decrease in CO between the summers of 2007 and 2008 using MOPITT (Measurements of Pollution in the Troposphere) satellite retrievals and WRF-Chem model (Weather Research and Forecasting model coupled with Chemistry). Upon comparing August 2006 and 2007 with the one of 2008, Wang et al. [2009] found a reduction of daytime O3, SO2, CO, and NOy by 20%, 61%, 25%, and 21%, respectively, at a rural site 100 km downwind Beijing. Wang et al. [2010] reported an increase of 16% in the mixing ratio of O3 in downtown Beijing, when comparing it with the period before the restrictions on traffic emissions. Chou et al. [2011] found an increase of 42.2% of the averaged mixing ratio of O3 in August 2008 compared to the one of 2006. In this study, we compare the O3 and NO2 contents in summer 2008 to those of the following 3 years during the same period. Figure 10 shows the percentage difference between 2008 and the average of the years 2009, 2010, and 2011, in the tropospheric NO2 column (on the right) and the 0–8 km column of O3 (on the left) for the different months where the restrictions were applied. It is noted that while the effect of the air quality control for NO2 is local and direct and shows considerable decrease in the area above Beijing, up to 54.3% in August (see Table 2), the effect on the O3 column is not similar. In fact, an increase of around 12% is observed in the month of July and a slight decrease of around 5 and 6% for the months of August and September. The increase in July could be interpreted as either the O3 was transported by winds from nearby polluted areas such as the North China Plain [Wang et al., 2009, 2010] or the fact that O3 was formed in the boundary layer since the photostationary state of the nitrogen cycle was perturbed and the reduction of the emitted NO led to an accumulation of O3 [Wang and Xie, 2009].

Figure 10.

Percentage change in the tropospheric (left) O3 and (right) NO2 columns between 2008 and the average of the years 2009, 2010, and 2011. A large decrease in NO2 is detected directly above Beijing (indicated with a cross marker), while the same effect is not detected for O3.

Table 2. Percentage Change Between 2008 and the Average of 2009–2011 for the Area Above Beijing Whose Location Is Given in Table 1
 Percentage Change of O3Percentage Change of NO2
July+11.8−37.7
August−5.1−54.3
September−6.1−41.3

5 Conclusions and Perspectives

[23] In this work, 4 years of tropospheric O3 observations provided by the IASI mission are analyzed. Our results show that latitudinal and seasonal variations can be observed at the city scale. This data set was studied along with the NO2 product provided by the GOME-2 mission flying on the same platform, over both urban and rural regions. Our data show that the assessment of tropospheric O3 and NO2 budgets in urban cities and rural regions is not straightforward and depends on complex photochemistry and transport processes. Tropospheric O3 in different cities in the Northern Hemisphere shows a consistent seasonal behavior over the 4 years. Main features correspond to a peak in spring due to stratospheric intrusion and another higher one in summer due to the photochemical production of O3 by its precursors. The seasonal variations of the 0–8 km O3 column over New Delhi, Shanghai, and Beijing show the influence of the Asian summer monsoon that brings clean air masses from the Pacific. Tropospheric NO2 over the same cities shows a different seasonal behavior with higher values during winter and lower values during summer. A reasonable correlation is detected in summer and winter between O3 and NO2. We anticipate that analyzing the effect of VOCs on the formation of O3 would help to better explain and assess this relationship.

[24] By studying the case of the Olympic Games of summer 2008 in Beijing, we show that even when the concentration of NO2 was well decreased in the city and its vicinity, no significant decrease of tropospheric O3 was observed. We also suggest comparing the IASI observations with atmospheric chemistry models to see if the spatial and temporal variability agrees with the satellite observations, such as the comparison made by Wespes et al. [2012].

[25] More generally, the results presented in this paper, which focus on the analyses of the 0–8 km O3 columns, further confirm that IASI is able to discriminate the tropospheric O3 column from the total O3. While tropospheric O3 forecasts nowadays rely solely on regional modeling and ground-based measurements, this work is thus a new step showing that infrared satellite spectrometers, such as IASI, are capable of tracking pollution by tropospheric O3 on a city scale and provide relevant information for air quality studies. From 2014 and onward, the FORLI-O3 profile and partial column products will be operationally distributed through the EumetCast near real time data distribution service in the framework of the O3M-SAF project.

Acknowledgments

[26] IASI is a joint mission of EUMETSAT and the Centre National d'Etudes Spatiales (CNES, France). The IASI and GOME-2 L1 data are distributed in near real time by EUMETSAT through the EumetCast system distribution. The generation of the GOME-2 NO2 operational products has been funded by the O3M-SAF project with EUMETSAT and national contributions. The authors acknowledge the French Ether atmospheric database (http://ether.ipsl.jussieu.fr) for providing the IASI L1C data. This work was undertaken under the auspices of the O3M-SAF project of the EUMETSAT. The authors would like to thank the ESA-MOST Dragon 3 Cooperation Project (ID: 10455). The French scientists are grateful to the feedback of Michel Van Roozendael, and to CNES and the Centre National de la Recherche Scientifique (CNRS) for financial support. P.-F. Coheur and C. Wespes are, respectively, Research Associate and Postdoctoral Researcher with F.R.S.-FNRS. The research in Belgium was also funded by the Belgian State Federal Office for Scientific, Technical and Cultural Affairs and the European Space Agency (ESA Prodex C4000103226).

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