Global Land Use Regression Model for Nitrogen Dioxide Air Pollution

Nitrogen
dioxide is a common air pollutant with growing evidence
of health impacts independent of other common pollutants such as ozone
and particulate matter. However, the worldwide distribution of NO2 exposure and associated impacts on health is still largely
uncertain. To advance global exposure estimates we created a global
nitrogen dioxide (NO2) land use regression model for 2011
using annual measurements from 5,220 air monitors in 58 countries.
The model captured 54% of global NO2 variation, with a
mean absolute error of 3.7 ppb. Regional performance varied from R2 = 0.42 (Africa) to 0.67 (South America). Repeated
10% cross-validation using bootstrap sampling (n =
10,000) demonstrated a robust performance with respect to air monitor
sampling in North America, Europe, and Asia (adjusted R2 within 2%) but not for Africa and Oceania (adjusted R2 within 11%) where NO2 monitoring
data are sparse. The final model included 10 variables that captured
both between and within-city spatial gradients in NO2 concentrations.
Variable contributions differed between continental regions, but major
roads within 100 m and satellite-derived NO2 were consistently
the strongest predictors. The resulting model can be used for global
risk assessments and health studies, particularly in countries without
existing NO2 monitoring data or models.