Stochastic model to forecast ground-level ozone concentration at urban and rural areas
Stochastic models that estimate the ground-level ozone concentrations in air at an urban and rural sampling points in South-eastern Spain have been developed. Studies of temporal series of data, spectral analyses of temporal series and ARIMA models have been used. The ARIMA model (1, 0, 0) × (1, 0,...
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Veröffentlicht in: | Chemosphere (Oxford) 2005-12, Vol.61 (10), p.1379-1389 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Stochastic models that estimate the ground-level ozone concentrations in air at an urban and rural sampling points in South-eastern Spain have been developed. Studies of temporal series of data, spectral analyses of temporal series and ARIMA models have been used. The ARIMA model (1,
0,
0)
×
(1,
0,
1)
24 satisfactorily predicts hourly ozone concentrations in the urban area. The ARIMA (2,
1,
1)
×
(0,
1,
1)
24 has been developed for the rural area. In both sampling points, predictions of hourly ozone concentrations agree reasonably well with measured values. However, the prediction of hourly ozone concentrations in the rural point appears to be better than that of the urban point. The performance of ARIMA models suggests that this kind of modelling can be suitable for ozone concentrations forecasting. |
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ISSN: | 0045-6535 1879-1298 |
DOI: | 10.1016/j.chemosphere.2005.04.079 |