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NASA Tropospheric Emissions: Monitoring of Pollution

Description

NASA’s TEMPO (Tropospheric Emissions: Monitoring of Pollution) project page at the Atmospheric Science Data Center provides access to data and documentation for the TEMPO instrument, a UV–visible grating spectrometer in geostationary orbit that measures key air pollutants over North America. From its fixed position above 91°W, TEMPO scans the continent hourly during daylight, using reflected sunlight to retrieve ozone, nitrogen dioxide, formaldehyde, aerosols, and related atmospheric constituents that are critical for understanding air quality and its impacts. The site offers mission descriptions, data product access (Level 1–3), user guides, and algorithm documents to support research, forecasting, and applications in health and environmental management.

Questions this resource can help answer

How do pollution levels vary hour by hour over specific cities or regions?
How do pollution patterns differ between weekday and weekend, or across seasons and episodes (e.g., wildfires, heat waves)?
Which urban or industrial areas show the strongest tropospheric pollution enhancements?
How well do chemical transport models or inventories match observed spatial and temporal patterns from TEMPO?
How are regional transport vs. local emissions contributing to observed pollution episodes?

How do I use this resource?

To use the TEMPO resource at NASA’s Atmospheric Science Data Center, go to the project page, follow the “Data” / “Data Access” links, and select the product level and variable you need (e.g., NO2, ozone, formaldehyde, aerosols). Choose a time range and geographic subset (if available), then download files (usually in NetCDF or HDF format). Open them in compatible software to visualize and analyze hourly air?quality fields over North America, using the product documentation for variable names, units, and quality flags.

Pro tips

Start with higher-level products (Level 2/3) rather than raw Level 1 radiances unless you’re an algorithm developer.
Always read the Product User Guide for your variable to understand retrieval limits, quality flags, and recommended filters.
Use quality flags and cloud masks to screen out poor or cloudy retrievals before analysis.
Begin with simple visualization tools to build intuition, then move into scripted analysis.
Pay attention to local time vs. UTC and the instrument’s daytime-only sampling when comparing with ground data.

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