Predictive models for ground ozone and nitrogen dioxide time series

✍ Scribed by Monique Graf-Jaccottet; Marc-Henri Jaunin

• Publisher: John Wiley and Sons
• Year: 1998
• Tongue: English
• Weight: 241 KB
• Volume: 9
• Category: Article
• ISSN: 1180-4009
• DOI: 10.1002/(sici)1099-095x(199807/08)9:4<393::aid-env310>3.0.co;2-w

✦ Synopsis

Predictive models are built for the mean ground concentration of ozone and nitrogen dioxide on data consisting of 5 years of daily averages. We ®nd the smallest averaging time over which a model with a deterministic trend and an autoregressive error distribution passes a number of statistical tests. Such a model implies that the error variance conditioned on the past observations is constant. The ®t is good for the series of weekly averages, but a model with heteroscedastic conditional variance has to be used for daily averages. The application of a generalized autoregressive heteroscedasticity model leads both to a satisfactory ®t and a good predictive power for daily average data.