Statistical analysis of environmental data as the basis of forecasting: an air quality application.

A statistical analysis technique is used for the development of an environmental forecasting tool. More specifically, a stochastic autoregressive integrated moving average (ARIMA) model is developed for maximum ozone concentration forecasts in Athens, Greece. For this purpose, the Box-Jenkins approach is applied for the analysis of a 9-year air quality observation record. The model developed is checked against real data for 1 year. Results show a good index of agreement, accompanied by a weakness in forecasting alarms. Finally, suggestions are made regarding the enrichment of the approach used in order to improve the forecasting performance.