This training covers the theoretical approaches and key datasets for estimating the near-surface concentration of particulate matter smaller than 2.5 micrometers in diameter (PM2.5) by using satellite aerosol optical depth (AOD) and other data sources (including ground-based monitors and model estimates).
Participants will acquire knowledge about different methodologies, and their strengths and limitations, for inferring surface PM2.5 from satellite AOD. They will be able to identify access methods for using existing datasets of surface PM2.5 estimated from satellite sensors and other data sources. They will also learn how to compare satellite-based estimates of PM2.5 to in situ measurement data through hands-on coding exercises using a generic code template and suitable co-location methodology. This would be the first step in evaluating the suitability of these datasets for the users’ applications and regions.
Learning Objectives:
- Match the required inputs, strengths, and limitations with different basic methods of inferring surface PM2.5 from satellite AOD.
- Differentiate between available data products for surface PM2.5 from NASA and Washington University in St. Louis based on their methodologies, strengths, and weaknesses.
- Use NASA Earthdata and the SatPM website to access these surface PM2.5 data products for a location and time period of interest.
- Compare these satellite-derived PM2.5 estimates to in situ measurements using appropriate co-location strategies and evaluation metrics.
To Register:
English: https://go.nasa.gov/439dfV7
Spanish: https://go.nasa.gov/4ur87ad
Audience:
- Researchers looking to use surface air quality estimates derived from satellites and looking to better understand the methodologies and limitations
- Air quality managers seeking to understand the potential for satellites to supplement ground-based monitors in remote areas