Application of Space-Time Series Model to the Prediction of Air Pollution Levels

Abstract

This paper deals with a prediction method of air pollution levels by using the space-time series model which considers both time lag and spatial lag to introduce the concept of spatial spread. As it is considered that the prediction accuracy is influenced by the wind direction, We propose a new method to take the information of wind direction in the model. From the simulation results, it is shown that the prediction accuracy based on the space-time series model is superior to that based on the ordinary time series model which considers time lag only.