Nitrogen oxides (NOx) and ozone play a central role in atmospheric chemistry and represent a key target for air pollution control. A complete understanding of their cycling is challenging due to competing dynamical and chemical effects.
Observation data alone is insufficient to assess and quantify the principal polluting sources (e.g. traffic exhaust emissions).
David Gurarie, a professor in the Department of Mathematics, Applied Mathematics and Statistics at the College of Arts and Sciences, was part of a research team that explored this topic through different means.
The paper combines observational data with mathematical modeling to develop novel tools of assessment. In particular, the researchers showed the conventional methods significantly overestimate primary NOx emissions.