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Exploring changes in air quality using Aura tropospheric NO2 data

Access EOS Aura Homepage.
Access tropospheric NO2 data from the NASA EOS-Aura satellite OMI instrument
This DataSheet was created by Brooke L. Carter of NASA/GSFC in consultation with Bojan Bojkov of NASA's EOS Aura mission.

Entered into datasheet template by Sarah Hill, TERC, Cambridge, MA

Author Profile

The Dataset

This site provides processed global data in image form illustrating tropospheric NO2 concentrations.

Use and Relevance

Image of metropolitan smog from EPA AIRnow

At the ground level, NO2 is one of the precursor components that are combined in sunlight to create ozone. NO2 is a byproduct of combustion engines and is a key molecule in smog formation. In addition, NO2 when combined with other chemicals can be harmful to certain body processes.

Use in Teaching

These data can be used to teach or learn the following topics and skills in atmospheric chemistry, physical geography and environmental science.
Image of NO2 concentrations for the Four Corners region from June 2006


Anthropogenic sources of pollution
Relationships between population densities and pollution levels


- Using data to make hypotheses about factors that influence pollution
- Using hypotheses to make predictions about relationships between pollution and population densities
- Using visual representations of data to recognize patterns (topography & population density; seasonal energy consumption patterns)

Exploring the Data

Data Type and Presentation

Geolocated data are processed and represented as graphic images in .kml file. Daily and Monthly averages are also presented in tab-delineated text files.

Accessing the Data

Users select dates for which they want data and click links to access .kml (Google Earh) and .txt files. The .kml images show processed data as a gridded Google Earth file that show tropospheric (ground level) NO2.

Manipulating Data and Creating Visualizations

Google Earth

Tools for Data Manipulation

No custom tool—but data provided in kml (Google Earth) and ASCII format for ease of use

Acronyms, Initials, and Jargon

OMI = Ozone Monitoring Instrument
MLS= Microwave Limb Sounder
TES= Tropospheric Emission Spectrometer

About the Data

Collection Methods

The NASA Aura satellite is a sun-syncronous Low Earth Orbit (LEO) flying over the whole surface of the Earth (14-15 daily orbits with a local overpass time of ~13:30) and has four atmospheric chemistry instruments (HIRDLS, MLS, OMI, and TES). The tropospheric NO2 measurements are derived from ultraviolet backscatter radiation measured by the OMI (Ozone Monitoring Instrument), a nadir viewing instrument with a ground swath of about ~13km*2600km (measured every 2 seconds in the sun exposed area of the globe). The OMI NO2 data production algorithm is designed to retrieve total vertical column densities of NO2 and separate stratospheric and tropospheric column densities using a spectral fitting technique (Differential Optical Absorption Spectroscopy, DOAS) to estimate the NO2 slant column density (SCD), which is the total NO2 density along the optical path (i.e., along the solar beam from the top of the atmosphere to the visible surface-cloud or ground-and then along the instrument's line-of-sight, back to the top of the atmosphere). The stratosphere-troposphere separation is achieved using a low-pass spatial filtering technique; the small gradient portion of the initial estimate of the total NO2 field is identified as the background stratospheric field. Measurements that exceed the constructed stratospheric field are taken to indicate significant tropospheric pollution. This separation is important because the chemistry of NO2 in the stratosphere is different from that in the troposphere. Also, accurate measurements of the tropospheric NO2 are significant for the characterization of air quality, a primary objective of the Aura and OMI missions.

Limitations and Sources of Error

The major sources of uncertainty in the tropospheric NO2 algorithm is the calculation of the Air Mass factor (AMF). The calculation of the AMF rests on certain assumptions, for example, concerning the overall shape of the NO2 vertical profile. It also rest on some other data sets, such as the OMI-derived cloud fraction and cloud-top pressure (currently using the oxygen dimer algorithm product), and the surface albedo.

References and Resources

Education Resources that Use this Dataset

Other Related Scientific References

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