High-Resolution Geospatial Database: National Criteria-Air-Pollutant Concentrations in the Contiguous U.S.,...

Area of Science:

• Environmental Science
• Public Health
• Geospatial Analysis

Background:

• Ambient air pollution concentration estimates are crucial for environmental epidemiology, health impact assessment, urban planning, and environmental equity.
• Previous efforts have laid the groundwork for developing detailed air quality databases.

Purpose of the Study:

• To develop an updated, high-resolution geospatial database of population-weighted annual-average concentrations for six criteria air pollutants.
• To cover the contiguous U.S. for the five-year period of 2016-2020.

Main Methods:

• Land Use Regression (LUR) models were developed within a partial-least-squares-universal kriging framework.
• Incorporated land use, geospatial, and satellite-based predictor variables.
• Validated models using conventional and clustered cross-validation, with conventional methods showing superior performance.

Main Results:

• Most LUR models demonstrated reliable performance (e.g., MSE-based R² > 0.8, RMSE < 0.1).
• Estimates were developed by Census Block and population-weighted averaged at multiple geographic levels (Block Group, Tract, County).

Conclusions:

• The developed database provides valuable insights into air pollution dynamics.
• The database is useful for environmental risk assessment, public health, policy development, and urban planning.