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

Sci Total Environ. 2002 Apr 15;288(3):227-37. doi: 10.1016/s0048-9697(01)00991-3.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants / analysis*
  • Environmental Monitoring / statistics & numerical data*
  • Forecasting
  • Models, Statistical*
  • Oxidants, Photochemical / analysis*
  • Ozone / analysis*
  • Sensitivity and Specificity

Substances

  • Air Pollutants
  • Oxidants, Photochemical
  • Ozone