ECHO-AIR
Description
The ECHO-AIR website documents an open-source modeling tool that converts changes in emissions into estimates of PM2.5 concentration and health impacts using the InMAP Source Receptor Matrix. Developed initially for California, it provides code, setup instructions, and methodological details for running scenario analyses that quantify how incremental emission changes affect population exposure and excess mortality, with an emphasis on environmental justice and climate policy evaluation.
Questions this resource can help answer
How would a specific change in emissions (e.g., from a sector or region) alter PM2.5 exposure and premature deaths?
Which emission?reduction options deliver the largest health benefits per ton reduced?
How are air quality and health benefits distributed across different communities or demographic groups?
What are the comparative health impacts of alternative climate or air quality policy designs?
How do I use this resource?
To use ECHO-AIR, start from the GitHub/website documentation, install the required software (R or Python environment, dependencies) and download the InMAP Source Receptor Matrix (SRM) files and example data. Prepare an emissions scenario file that specifies baseline emissions and the changes you want to test (by pollutant, sector, and geography), then run the ECHO-AIR scripts to translate those emission deltas into estimated changes in PM2.5 concentrations and associated health impacts (e.g., excess mortality), which you can then summarize or map.
Pro tips
Begin with the example scenarios and reproduce their results before creating your own.
Keep emissions units, pollutants, and spatial references exactly as specified in the documentation.
Use version control (e.g., Git) and clear file naming so you can track different scenarios.
Start with simple, single?sector changes to build intuition, then layer in more complex, multi?sector scenarios.
Pair output with demographic and EJ data to interpret equity impacts, not just totals.
