  Data used to assess acute health effects from air pollution typically have
good temporal but poor spatial resolution or the opposite. A modified
longitudinal model was developed that sought to improve resolution in both
domains by bringing together data from three sources to estimate daily levels
of nitrogen dioxide ($\mathrm {NO}_2$) at a geographic location. Monthly
$\mathrm {NO}_2$ measurements at 316 sites were made available by the Study of
Traffic, Air quality and Respiratory health (STAR). Four US Environmental
Protection Agency monitoring stations have hourly measurements of $\mathrm
{NO}_2$. Finally, the Connecticut Department of Transportation provides data on
traffic density on major roadways, a primary contributor to $\mathrm {NO}_2$
pollution. Inclusion of a traffic variable improved performance of the model,
and it provides a method for estimating exposure at points that do not have
direct measurements of the outcome. This approach can be used to estimate daily
variation in levels of $\mathrm {NO}_2$ over a region.
