title: Statistical analysis of environmental data as the basis of forecasting: an air quality application.
abstract: 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.
authors: Aristotle University, Laboratory of Heat Transfer and Environmental Engineering, Thessaloniki, Greece. kostas@aix.meng.auth.gr
authors: Th
authors: T
authors: Slini
authors: K
authors: K
authors: Karatzas
authors: N
authors: N
authors: Moussiopoulos
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D005544:Forecasting; D015233:Models, Statistical; D010083:Oxidants, Photochemical / Q000032:analysis*; D010126:Ozone / Q000032:analysis*; D012680:Sensitivity and Specificity
chemical_list: D000393:Air Pollutants; D010083:Oxidants, Photochemical; D010126:Ozone