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Statistical Methods and Applications

, Volume 11, Issue 2, pp 227–245 | Cite as

Nonlinear models for ground-level ozone forecasting

  • Silvano BordignonEmail author
  • Carlo Gaetan
  • Francesco Lisi
Statistical Applications

Abstract

One of the main concerns in air pollution is excessive tropospheric ozone concentration. The aim of this work is to develop statistical models giving shortterm forecasts of future ground-level ozone concentrations. Since there are few physical insights about the dynamic relationship between ozone, precursor emissions and/or meteorological factors, a nonparametric and nonlinear approach seems promising in order to specify the forecast models. First, we apply four nonparametric procedures to forecast daily maximum 1-hour and maximum 8-hour averages of ozone concentrations in an urban area. Then, in order to improve the forecast performances, we combine the time series of the forecasts. This idea seems to give encouraging results.

Key words

Ground-level ozone forecasting nonlinear time-series models combination of forecasts 

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Copyright information

© Springer-Verlag 2002

Authors and Affiliations

  • Silvano Bordignon
    • 1
    Email author
  • Carlo Gaetan
    • 1
  • Francesco Lisi
    • 1
  1. 1.Dipartimento di Scienze StatisticheUniversità di PadovaPadovaItaly

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