The NO2 land-use regression model estimate data includes national-scale estimates of NO2 in the United States. It provides predictions for annual average NO2 concentrations (ppb) using the land-use regression models. 

In order to predict NO2 estimates at the national level, the following input data were used;  Fixed-site regulatory monitors, Satellite-derived NO2 estimates and GIS-derived land-use data. 

Data Summary

Dataset Name: The NO2 Land-Use Regression Model Estimate Data

Data Source: Empirical Model Database

Years: All Data Contains measures between 2000 and 2010

Geographies: Data are collected at XY coordinates and made available at the census tract level.

Download the Air Pollution: NO2 Land-Use Regression Model Estimate Data documentation HERE.

Suggested Citation:
Jennifer Ailshire and Hyewon Kang. 2018. Contextual Data Resource (CDR): Nitrogen Dioxide LUR Model Estimates, 2000-2010, Version 1.0. Los Angeles, CA: USC/UCLA Center on Biodemography and Population Health.

Data Sources:

Empirical Model Database,

The data were obtained from Bechle et al (2016) whose work was supported by the National Science Foundation under Grant No. 1236800 and by the Minnesota Supercomputing Institute.