High-order Gaussian Process Models for Prediction of Ozone Concentration in the Air

Ozone is one of the main air pollutants with harmful influence over human health. Therefore, predicting the ozone concentration and informing the population when the air quality standards have been exceeded is an important task. In this paper, firstand high-order Gaussian process models for 1-hour ahead prediction of ozone concentration in the air of Bourgas, Bulgaria are identified and verified. For this purpose, the hourly measurements of the concentrations of ozone, sulfur dioxide, nitrogen dioxide, phenol and benzene in the air and the meteorological parameters, collected at the automatic measurement stations in Bourgas, are used.