How do I add NO2 in EJScreen to see how it impacts specific communities?
How was this NO2 dataset developed?
Complete global estimates of surface-level NO2 concentrations at 1 km x 1 km grid resolution were described by Anenberg, Mohegh, et al. (2022). These estimates, available annually for 2005-2020, are formed by combining a land use regression model described by Larkin et al. (2017) with satellite-derived tropospheric column NO2 from NASA’s Ozone Mapping Instrument. The spatial patterns in NO2 in this dataset matched the patterns observed by EPA air pollution monitors.
We averaged this dataset to underlying census block groups in the United States using boundaries from the 2010 decadal census, obtained from the U.S. Census Bureau’s TIGER/Line geodatabase, and the methodology described by Kerr et al. (2021). About a fifth of census block groups are smaller than the 1 km x 1 km resolution of the gridded NO2 dataset. For these small units, we apply inverse distance weighting to interpolate NO2 concentrations to the centroid of these units. Interpolating NO2 concentrations to block groups that are much smaller than 1 km2 may smooth over fine scale NO2 gradients. Grid cells over water in the gridded NO2 dataset are assigned a missing value. A small number of block groups are primarily located over water (e.g., estuaries, reservoirs, etc.) and therefore have a missing value for NO2 in the census block group version of this dataset.
Who developed this dataset?
This work was funded through the NASA Health and Air Quality Applied Sciences Team “Satellite Data for Environmental Justice” tiger team, led by Susan Anenberg (George Washington University) and Qian Xiao (University of Texas). Arash Mohegh, Dan Goldberg, and Susan Anenberg (George Washington University) created the global gridded NO2 dataset, working with a team of collaborators from Oregon State University and Institute for Health Metrics and Evaluation. Gaige Kerr (George Washington University) regridded this dataset to census block groups. Colleen Heck (University of Wisconsin-Madison) generated the ArcGIS REST Services for the NO2 dataset to facilitate its integration in EJScreen. Emily Richardt (George Washington University) created the visualizations shown on this page.