  Drift-diffusion analysis has been introduced in physics as a method to study
turbulent flows. In the current study, it is proposed to use the method to
identify underlying dynamical models of particulate matter smog, ozone and
nitrogen dioxide concentrations. Data from Chiangmai are considered, which is a
major city in the northern part of Thailand that recently has witnessed a
dramatic increase of hospitalization that are assumed to be related to extreme
air pollution levels. Three variants of the drift-diffusion analysis method
(kernel-density, binning, linear approximation) are considered. It is shown
that all three variants explain the annual pollutant peaks during the first
half of the year by assuming that the parameters of the physical-chemical
evolution equations of the pollutants vary periodically throughout the year.
Therefore, our analysis provides evidence that the underlying dynamical models
of the three pollutants being considered are explicitly time-dependent.
