go to TEMIS Home Page

Regional nitrogen dioxide (NO2)

data products
Air pollution
UV radiation
Support to Protocol
Support to
Aviation control
Data product
Data product

page last modified:
Wed 24 November 2004

Data access


Access to regional nitrogen dioxide (NO2) data

Maps and ascii data from GOME and SCIAMACHY are provided together with trajectory analysis and 
auxiliary information (e.g., Meteo-wind fields, lightening, DOAS measurements)
to facilitate user applications.

Product description

Below, the provided data are described in detail :


Nitrogen dioxide from satellite for air quality purposes

NO2 is a key species for photochemical air pollution and a precursor for ozone. Primary emitted is mostly NO, which reaches a photochemical equilibrium with NO2 within minutes. At some distance from the immediate source, the bulk of planetary boundary layer NOx (=NO+NO2) is constituted by NO2. Thus the knowledge of NO2 distribution is highly relevant for air quality related applications. Both the background and the peak load of NO2 are relevant to access the air pollution situation and possible political measures to confine the pollution. For the interpretation of the NO2 as observed from GOME and SCIAMACHY (data provided by the workpackage “Global NO2 fields”) the meteorological conditions are essential.

Here, for the “Regional NO2 fields”,

•    the NO2 satellite observation is edited to a user friendly format (ascii) easily to be downloaded together with meteorological transport information and a quality flag derived from the cloud parameters provided

•    a potential source region is provided to each particular case of observed NO2 based on meteorological transport modelling by Lagrangian air mass trajectories

•    the height analysis of the trajectories give hints in which height the bulk of observed NO2 may reside in the troposphere. This is of importance when the satellite derived NO2 is desired to be used for estimation of boundary layer NO2 concentrations.

This detailed modelling based on numerical weather prediction wind fields requires a large amount of computing time and storage, thus it is done here for the European region only where user requirements focus. In principle, the method can be applied globally.

Fig. 1:  For example, chose the date of interest (here 16 April 1997)  from "Maps" of GOME and click on the "Back trajectories" at, e.g.,  900 hPa for source region assessment.


Trajectory calculation and source region visualisation for GOME/SCIAMACHY NO2 columns

From the provided trajectory analysis, the potential source regions of NO2 pollution and the potential ground contact of elevated air masses can be deduced.


Backward trajectory calculation


Backward trajectories are calculated for every high quality GOME/SCIAMACHY column in the region of interest (alpine area from 5°E to 14°E and 44°N to 49°N). The retrieved columns are defined to be of high quality if the following criteria are fulfilled:

•    The flag “fltrop” in the KNMI data has to indicate a meaningful tropospheric retrieval (fltrop=0; clear sky case), or
•    The cloud fraction from FRESCO (“clfrac” in the KNMI data) exceeds a critical value of 0.75 (overcast case).

Because of the complicated interpretation of intermediate cloud cover, i.e. more than about 10-15% cloud fraction (decision criterion fltrop=-1) or less than 75% cloud fraction (clfrac≤0.75), such cases were abstained from trajectory calculation.

As the NO2 distribution within the GOME/SCIAMACHY columns is unknown, the backward trajectory arrival points cover the columns both horizontally and vertically in order to account for its whole tropospheric volume (Tab. 1). In the vertical, 11 height levels between 950 hPa and 450 hPa in 50 hPa steps are used. This vertical resolution allows distinguishing cases where boundary layer air has been transported into the middle troposphere from cases where no such transport is expected and thus the tropospheric NO2 amount can be assumed to linger in the lower layers. In this trajectory analysis, the possibility of air above 450 hPa which experienced ground contact is not covered. Further, the NO2 produced by lightning is not accounted for. If NO2 production by lightning has to be considered, reference to lightning archives (e.g., http://www.wetterzentrale.de/topkarten/tkbeoblar.htm) is suggested.

                                                       Tab. 1: Distribution of the backward trajectory arrival points

                                                                   in the GOME/SCIAMACHY NO2 columns

Number of trajectory
arrival points





Across track 12 3
Along track  3 3
In the vertical 11 11
Total   396 99

The trajectories are calculated with analysed wind fields with a six hour temporal and 1° x 1° geographical resolution provided by the model of the European Centre for Medium-Range Weather Forecast (ECMWF). Three dimensional kinematic 4-day backward trajectories are calculated with the software package “Lagranto” (Wernli and Davies, 1997). The arrival time point is chosen to be on 9:00 UTC.


Deriving potential source regions


From the trajectories, the potential source region maps are derived corresponding to each height level. The trajectories are plotted point wise in the horizontal projection and indicate the geographical region which has contributed ground near air to the tropospheric column of interest. As the first arrival height of the trajectories (950 hPa) is often in the planetary boundary layer anyway, only the trajectories from the levels above (900 – 450 hPa) are investigated for their ground contact.  The ground distance of the trajectories is colour coded. Red marks the most ground near trajectory points (ground distance < 50 hPa), green points have a ground distance 50-100 hPa and blue have a ground distance of 100-150 hPa. Points of trajectories with a higher ground distance are omitted.

For sake of clarity, only every 4 hours a point of the trajectory is plotted. When the density of points is high, a rather stagnant air mass is indicated. On the other hand, scattered points indicate high wind velocities. Occasionally, very high wind velocities lead to an apparent periodical point distribution when the trajectory starting points all exhibit similar trajectories. This artefact of periodicity should be kept in mind when interpreting such maps. Another artefact of displaying the trajectory information may occur when the trajectories of the different starting points stay rather coherent. Then the points associated to the different trajectories can align thread-like. Both artefacts could be eliminated by choosing to plot the trajectory points more than every 4 hours, on the expense to obscure the image for slower velocities. With the above explanation of artefacts the current trade-off should not lead to misinterpretations.  The trajectory files from which the potential source regions have been constructed can be ordered at EMPA.


Auxiliary information with ground-based DOAS measurements and links to web databases

Satellite observations of atmospheric composition need to be validated with independent measurements in order to be usable for air pollution monitoring. Validation, in this sense, means not only comparing numbers of homogeneous quantity (NO2 tropospheric column for example) but also give a correct interpretation to the satellite measurements. Often, the discrepancy between the two independent measurements (satellite and ground-based) are due to the fact that they are measuring different air masses. The extension of ground pixels of GOME (320 km x 60 km) and SCIAMACHY (60 km x 30 km) cause the retrieval to perform a sort of average of the NO2 column present within the field of view (see Petritoli et al., J. Geophys. Res., 2004). Thus often the comparison between the space and the ground-based measurements give a clue on the horizontal distribution of the NO2 in the ground pixels. Here we provide NO2 PBL column measurements (PBL_NO2_C) performed in Bologna between March and September 2003. The PBL_NO2_C is obtained by comparing simultaneous total column measurements of NO2 obtained with two GASCOD (Gas Analyzer Sepctrometer Correlating Optical Differences) installed in Bologna (44.3N, 11.2 E, 50 m asl) and in the Mt. Cimone research station (44.2N, 10.7E, 2165 m asl). The NO2 slant column is obtained using DOAS (Differential Optical Absorption Spectroscopy) methodology and the PBL_NO2_C is retrieved by comparing the simultaneous measurements. A typical plot provided is similar to that shown in Fig. 2 where:
-->Left plot:
---->Black squares = Mt. Cimone slant column measurements
---->Red squares = Mt. Cimone slant column measurements interpolated at Bologna measurement time
---->Continous black line = cloud cover
-->Right plot:
---->Grey area = NO2 tropospheric slant column (PBL_NO2_C)
---->Continous bold black line = hourly average of Grey area
---->Black squares = in situ measurements of NO2 at the ground (right scales in ppbv and 1010molec/cm3)
---->Dashed coloured lines = PBL_NO2_C simulated with the PROMSAR multiple scattering model for a NO2 vertical layer extension up to 1500 m (lower right corner) and different constant values (colour scales)
---->Grey arrows = wind intensity and direction
Meteo information and in situ ground measurements have been kindly provided by the ARPA Emilia Romagna.

Figure 2: NO2 PBL column measured with DOAS methodoloy at Bologna.

For each avaialbe satellite overpass we provide (if avaiable) also links to maps of measurements or simulations of lightning occurence, cloud cover, PV, wind and T fields.


Case studies (Examples of interpretation)

Few case studies on the interpretation of high NO2 levels observed by the satellite sensors will be shown. The goal is to provide some general examples on how to use auxiliary information such as back trajectories, cloud cover, lightings events and ground based measurements to give an interpretation to the NO2 maps from space that is mainly to find an explanation to the observed NO2 tropospheric column field. In fact high NO2 tropospheric column can be due either to local production, or to trasport from other places or to lightings. The events described in the Case Studies section will show how is possible sometimes to identify such phenomena. To access more detailed case studies visit the web page of the POLPO-ESA project.


Schaub et al., "Comparison of GOME tropospheric NO2 columns with NO2 profiles deduced from ground-based in situ measurements", ACP, 2006