Daily Census Tract-Level PM2.5 Concentrations, 2021-2022

Modeled predictions of daily PM2.5 air pollution concentrations at the census tract level for the years 2021 and 2022. The data are generated by the EPA's Downscaler model and used by the CDC's National Environmental Public Health Tracking Network. Each record includes the mean predicted concentration and its associated standard error.

Use Cases

• Analyze temporal trends in PM2.5 levels using the `date` and `ds_pm_pred` columns.
• Map air pollution exposure disparities by census tract using `ctfips`, `latitude`, `longitude`, and `ds_pm_pred`.
• Assess prediction uncertainty for health risk models using `ds_pm_pred` and `ds_pm_stdd`.
• Compare air quality across states or counties using `statefips`, `countyfips`, and `ds_pm_pred`.

Strengths

• Data is modeled at a fine geographic resolution (census tract level).
• Includes both a predicted concentration value (`ds_pm_pred`) and a measure of its uncertainty (`ds_pm_stdd`).
• Covers a defined two-year period (2021-2022) with daily granularity (`date`).

Limitations

• Data contains modeled predictions, not direct measurements, which may introduce bias.
• Row count is unknown, which may limit suitability assessment.
• The dataset is part of a planned 5-year series (2021-2025) and is not yet complete for that full period.

Provenance

Source

Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network, using the EPA's Downscaler model.

Collection Method

Modeled predictions from the EPA's Downscaler model.

Time Range

2021-2022

Freshness

Last updated 2026-04-13 21:07:25; freshness should be verified.

Geography

United States at the census tract level.