Comparative spatiotemporal analysis of fine particulate matter pollution

The prime focus of this work is the comparative investigation, theoretical and numerical, of spatiotemporal techniques used in air pollution studies. Space‐time statistics techniques are classified on the basis of a set of criteria and the relative theoretical merits of each technique are discussed accordingly. The numerical comparison involves the applications of two representative techniques. For this purpose, the popular spatiotemporal epistemic knowledge synthesis and graphical user interface (SEKS‐GUI) software of spatiotemporal statistics is used together with a dataset of PM2.5 daily measurements obtained at monitoring stations geographically distributed over the state of North Carolina, USA. The analysis offers valuable insight concerning the choice of an appropriate spatiotemporal technique in air pollution studies.