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Nitrogen dioxide (NO2)
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page last modified:
October 2005
   
Data on TEMIS: Contents of this page:

 

 

Introduction Nitrogen dioxide

Nitrogen oxides play a central role in tropospheric chemistry, and there are several reasons why an improved knowledge of the global tropospheric distribution of NOx (NO+NO2) is important:
  • NOx and volatile organic compounds are emitted in large quantities due to human activities such as traffic and industry. In the summer months this mixture produces photochemical smog.

  • The chemical budget of ozone in the troposphere is largely determined by the concentration of NOx. The knowledge of the ozone distribution and its budgets is strongly limited by a severe lack of observations of NO and NO2 in the troposphere.

  • The variability of NOx concentrations in the lower troposphere in industrialised areas and near biomass burning sites is very large. The few available point observations of NOx, on the ground or from aircraft measurements, are therefore difficult to translate to regional scale concentrations.

    The residence time of NOx in the lower troposphere is short. Therefore observations of boundary layer NOx contain important information on the emissions of nitric oxide, and the trends in these emissions.

  • The free troposphere is also of great importance for the ozone budget, and for CH4 and CO oxidation processes. Again these budgets are uncertain due to a limited knowledge of NOx. The degree of NOx transfer from the boundary layer is difficult to model, and NOx emissions from lightning are very uncertain.


 

Observing NO2 from space

An important step in filling the gap in our knowledge of tropospheric NOx has been made by the GOME instrument on ERS-2. The prime advantage of satellites is their capability of providing a full global mapping of the atmospheric composition. After cloud filtering, GOME provides global coverage NO2 maps rougly every week. Column amounts of NO2 can be derived from the detailed spectral information provided by GOME in the wavelength range 420-450 nm.

Good signal-to-noise ratio's (of about 20) are obtained for NO2 with the Differential Optical Absorption Spectroscopy (DOAS) retrieval technique. This is related to the absence of strong other absorbers (e.g. ozone) in this spectral interval. GOME has also demonstrated the ability to observe boundary layer NO2: on top of a stratospheric background enhanced column NO2 amounts are observed that correlate well with known industrialised areas. GOME has also detected NO2 plumes originating from biomass burning events. Furthermore, there are signatures of lightning-produced NO2 in the GOME data set.

 

OMI NO2 columns
World map of the averaged tropospheric NO2 column measured by OMI in the period May 2006 till February 2007.

 

Uncertainties in retrieval

A major challenge is the derivation of good quality quantitative tropospheric NO2 column amounts for individual ground pixels based on the satellite data. The retrieval of tropospheric trace gas species is characterised by large uncertainties, related to clouds, the surface albedo, the trace gas profile, the stratospheric column of NO2, and aerosols:
  1. The largest uncertainties are due to clouds, as they will shield near-surface NO2 from the view of the satellite. The retrieval depends very sensitively on the presence of clouds, and even small coud fractions (between 5 to 20%) have a major impact. High quality observations of the cloud properties (at least cloud fraction and cloud top height) are necessary for a quantitative retrieval.

  2. The surface albedo directly influences the sensitivity of GOME for boundary layer NO2. High quality albedo maps in the relevant spectral range are essential.

  3. Profiles of NO2 are characterised by a large range of variability. At emission areas the NO2 concentration will peak at the surface, while downstream of such areas the pollution plume will peak at higher altitudes. The profile of NO2 will be determined by aspects like the distribution of emission sources, the stability and height of the boudary layer, wet removal of nitric acid, deep convection and long-range transport by the wind. All these aspects are strongly varying in time and space.

  4. The NO2 columns measured by GOME consist of comparable stratospheric and tropospheric contributions. The stratospheric background has to be quantified carefully in order to derive the tropospheric column. Atmospheric dynamics is well known to generate significant variability in stratospheric tracer amounts, consistent with for instance HALOE observations of NO2. A standard approach applied to GOME is based on the assumption that stratospheric NO2 is zonally uniform, or at least has only a small longitudinal variation. Such simplification makes the retrieval of small tropospheric NO2 columns practically impossible.

  5. Another source of uncertainty are aerosols. Thick aerosol layers influence the radiation field and the sensitivity of GOME for near-surface NO2.

More info:

  • Boersma, K.F., H.J. Eskes and E.J. Brinksma, 2004. Error analysis for troposheric NO2 retrieval from space. J. Geophys. Res., 109, 4311, doi: 10.1029/2003JD003961.


 

Retrieval of tropospheric NO2

Satellite instruments (such as GOME, SCIAMACHY and OMI) use spectroscopy to retrieve atmospheric trace gas concentrations in the atmosphere. By comparing the measured spectrum of the backscattered light from the Earth's atmosphere with a reference spectrum, the column density of nitrogen dioxide along the light path can be determined. The NO2 stratospheric column is deduced from a chemistry-transport model assimilation run of the NO2 column data. Subsequently, the assimilated stratospheric column is subtracted from the retrieved total column, resulting in a tropospheric column. Information about the global tropospheric NO2 columns is publicly available on the TEMIS website http://www.temis.nl. More details about the satellite observations and the retrieval technique can be found in

  • Eskes, H.J. and K.F. Boersma, 2003. Averaging Kernels for DOAS total-column satellite retrievals. Atm. Chem. Phys., 3, 1285 - 1291.
  • Boersma, K.F., H.J. Eskes and E.J. Brinksma, 2004. Error analysis for troposheric NO2 retrieval from space. J. Geophys. Res., 109, 4311, doi: 10.1029/2003JD003961.
  • Boersma, K.F., 2005. Satellite observations of tropospheric nitrogen dioxide; retrieval interpretation and modelling, Ph.D Thesis, Universiteitsdrukkerij Technische Universiteit Eindhoven, Eindhoven.
NO2 has been monitored by satellite since 1995 with GOME, since 2002 with SCIAMACHY, and since 2004 with the OMI instrument; the latter two instruments having the advantage of a high spatial resolution.

In the Figure above the mean tropospheric NO2 is shown as measured by OMI in the period May 2006 till February 2007. Clearly visible are the industrial regions in China, Europe, South-Africa and the USA. The yearly averaged NO2 column for 2005 measured with SCIAMACHY zoomed-in over China can be seen in the Figure below. It shows high concentrations of NO2 above highly populated regions like Beijing, Shanghai, Hong Kong and South Korea. It can also be seen that the satellite detects the emissions around the Yellow river (Huang He). Over the sparsely populated western part of China, low NO2 concentrations are observed, except over the large city Urumqi in the Northwest.

NO2 in China
The yearly averaged tropospheric NO2 column measured by SCIAMACHY for 2004 in China. High values are measured above the major cities. The industrial area around the Yellow River (Huang He) is also noticeable and highlights the river stream.

 

Air quality monitoring

In Blond et al. it is shown that SCIAMACHY provides detailed information on the nitrogen dioxide content in the planetary boundary layer. The cloud free satellite observations were compared with surface measurements and simulations over Western Europe performed with the regional air-quality model CHIMERE (shown in Figure below). The model has a resolution of 50 km similar to the satellite observations. CHIMERE underestimates surface NO2 concentrations for urban and suburban stations which we mainly attribute to the low representativeness of point observations. No such bias is found for rural locations. The yearly-average SCIAMACHY and CHIMERE spatial distributions of NO2 show a high degree of quantitative agreement over rural and urban sites: a bias of 5% (relative to the retrievals) and a correlation coefficient of 0.87 (n=2003). The consistency of both SCIAMACHY and CHIMERE outputs over sites where surface measurements are available gives confidence in evaluations of the model over large areas not covered by surface observations. The NO2 columns show a high daily variability. Still, the daily NO2 pollution plumes observed by SCIAMACHY are often well described by CHIMERE both in extent and in location. This result demonstrates the capabilities of a satellite instrument such as SCIAMACHY to monitor the NO2 concentrations over large areas on a regular basis. It provides evidence that present and future satellite missions, in combination with a regional air quality model and surface data, will contribute to improve quantitative air quality analyses at a continental scale.
More info:
  • Blond, N., K.F. Boersma, H.J. Eskes, R.J. van der A, M. Van Roozendael, I. De Smedt, G. Bergametti and R. Vautard, 2007. Intercomparison of SCIAMACHY nitrogen dioxide observations, in-situ measurements, and air quality modeling results over Western Europe. J. Geophys. Res, in press.

Chimere/SCIA
Comparisons between annual means of, a) NO2 SCIAMACHY tropospheric columns (1015molecules cm-2), b) NO2 CHIMERE tropospheric columns obtained by using the averaging kernels, c) emissions of nitrogen oxides (NOx) over Western Europe for 10h00 UTC for 1998, and d) NO2 CHIMERE tropospheric columns computed without using the averaging kernels. The emissions are derived from data given by EMEP, interpolated on the CHIMERE grid domain, unit 1010 molecules cm-2 s-1.

 

Trends in tropospheric NOx emissions

The combined measurement series of both GOME and SCIAMACHY almost span a decade, which favours a trend analysis of NO2 concentrations. To do so, the averaged monthly tropospheric NO2 columns are fitted with a linear model that also includes a sinus to represent the seasonal variation of NO2. The seasonal variation for anthropogenic NO2 is mainly determined by the changing day length over the year. In absence of sunlight NO2 has a longer lifetime in the atmosphere, which explains that the NO2 columns are on average higher during wintertime. By applying the model to each grid cell a spatial distribution of the fit parameters is calculated. Furthermore the precision of the trend is calculated. It can be concluded that the 10 years long NO2 dataset from GOME and SCIAMACHY can be used for significant trend analysis in most parts of the world. In highly populated and industrialised areas the trend is large enough to be significant. For instance Shanghai had a yearly increase of tropospheric NO2 of about 29% since 1996.

The Figure below shows the derived annual growth in the tropospheric NO2 columns from this analysis. The largest trend is found in east China, where the economic growth is one of the fastest of the world. The fastest growing city with respect to both economy and tropospheric NO2 is Shanghai. It is interesting to note that the growth in the region around Hong Kong is less than for other regions with a high economical activity. This is probably due to the already high level of economic activity in 1996 when our trend study started, and to a package of measures against air pollution in Hong Kong over the last years. Further results of this trend study are published in:

  • van der A, R.J., D.H.M.U. Peters, H.J. Eskes, K.F. Boersma, M. Van Roozendael, I. De Smedt and H.M. Kelder, 2006. Detection of the trend and seasonal variation in tropospheric NO2 over China. J. Geophys. Res., 111, D12317, doi:10.1029/2005JD006594.

NO2 trends
World map of the linear trend per year for tropospheric NO2 in the period 1996 till 2005 derived from satellite observations by GOME and SCIAMACHY. For the light grey areas no significant trend has been found in the time series. For the dark grey areas not enough observations were available to construct a time series of tropospheric NO2.

 

Global Implications

The fast growing emissions in China lead locally to rapidly increasing NO2 concentrations, which affects the local ozone concentrations. Clearly these large increases will have severe consequences for the local air quality, but even effects on the global scale can be expected, because the lifetime of tropospheric ozone is much larger than the lifetime of NO2. Therefore, ozone can be transported over large distances by the wind. Using a chemical transport model the change in ozone due to increasing emissions in China can be calculated. The Figure below shows increasing ozone concentrations in the Northern hemisphere caused by the growing Chinese emissions in the period 1997-2005. In this period of eight years the global averaged tropospheric ozone column has increased with 0.54 %. The largest growth in tropospheric ozone we find in a plume reaching from China to the East along the direction of the prevailing winds. From the Figure we conclude that the tropospheric ozone concentrations in the entire Northern hemisphere are increased due to the growing emissions in China. These increases seem small, but are still important. In Europe, the air pollution has been increased as a result of intercontinental transport. In addition, since ozone is a strong greenhouse gas, the effects on climate change cannot be neglected.
More info:
  • Kuenen, J.J.P., 2006. Anthropogenic NOx emission estimates for China based on satellite measurements and chemistry-transport modeling, KNMI, Technical Report TR-288, 62p.

delta ozone
The difference in ground-level ozone caused by the increase of Chinese NOx emissions between 1997 and 2005.