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Environmental Monitoring and Assessment

, Volume 56, Issue 1, pp 97–112 | Cite as

Forecasting Daily Maximum Ozone Concentrations in the Athens Basin

  • A. Chaloulakou
  • D. Assimacopoulos*
  • T. Lekkas
Article

Abstract

In the work ozone data from the Liossion monitoring station of the Athens/PERPA network are analysed. Data cover the months May to September for the period 1987–93. Four statistical models, three multiple regression and one ARIMA (0,1,2), for the prediction of the daily maximum 1-hour ozone concentrations are developed. All models together, with a persistence forecast, are evaluated and compared with the 1993's data, not used in the models development. Validation statistics were used to assess the relative accuracy of models. Analysis, concerning the models' ability to forecast real ozone episodes, was also carried out. Two of the three regression models provide the most accurate forecasts. The ARIMA model had the worst performance, even lower than the persistence one. The forecast skill of a bivariate wind speed and persistence based regression model for ozone episode days was found to be quite satisfactory, with a detection rate of 73% and 60% for O3 >180 μg m-3 and O3 >200 μg m-3, respectively.

air pollution in Athens ozone concentration prediction of episodes statistical modelling 

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References

  1. Abatzoglou, G., Chaloulakou, A., Assimacopoulos, D. and Lekkas, T.: 1998, 'Prediction of air pollution episodes: Extreme value theory applied in Athens', Environ. Technol. 17, 349–359.Google Scholar
  2. Box, G. E. P. and Jenkins, G.M.: 1976, Time Series Analysis, Forecasting and Control, San Francisco, Holden Day.Google Scholar
  3. Chock, D. P., Terrell, T. R. and Levitt, S. B.: 1975, 'Time series analysis of Riverside, California air quality data', Atmos. Environ. 9, 978–989.Google Scholar
  4. Gusten, H., Heinrich, G., Cvitas, T., Klasing, L., Ruscic, B., Lalas, P. D. and Petrakis, M.: 1988, 'Photochemical formation and transport of ozone in Athens, Greece', Atmos. Environ. 22, 1855–1861.Google Scholar
  5. Lalas, D. P., Karras, G., Pissimanis, K., Notaridou, V. and Kassomenos, P.: 1985, Air Pollution in the Athens Area. Study of Conditions and Mechanisms, Ministry of Physical Planning, Housing and the Environment (PERPA), EEC, DG XI (Final Report).Google Scholar
  6. Lorenzini, G., Nali, G. and Panicucci, A.: 1994, 'Surface ozone in Pisa (Italy): A six-year study', Atmos. Environ. 28, 3155–3164.Google Scholar
  7. Mertz, P. H., Painter, L. G. and Ryason, R. P.: 1972, 'Aerometric data analysis. Time series analysis and forecast and an atmospheric smog diagram', Atmos. Environ. 6, 319–342.Google Scholar
  8. McCollister, G. and Wilson, K.: 1975, 'Linear stochastic models for forecasting daily maxima and hourly concentrations of air pollutants', Atmos. Environ. 9, 417–423.Google Scholar
  9. Pankratz, A.: 1983, Forecasting with Univariative Box-Jenkins Models: Concepts and Cases, New York, John Wiley and Sons.Google Scholar
  10. Prior, E. J., Schiess, J. R. and McDougal, D. S.: 1981, 'Approach to forecasting daily maximum ozone levels in St. Louis', Env. Sci. Technol. 15, 430–436.Google Scholar
  11. Rao, S. T. and Visalli, J. R.: 1981, 'On the comparative assessment of the performance of air-quality models', J. Air Pollut. Control Assoc. 31, 851–860.Google Scholar
  12. Remsberg, E. E. and Woodbury, G. E.: 1983, 'Stability of the surface layer and its relation to the dispersion of primary pollutants in St. Louis', J. Clim. Appl. Met. 22, 244–255.Google Scholar
  13. Revlett, G.: 1978, 'Ozone forecasting using Empirical Modeling', J. Air Pollut. Control Assoc. 28, 338–343.Google Scholar
  14. Robeson, S. and Steyn, D.: 1989, 'Evaluation and comparison of statistical forecast models for daily maximum ozone concentrations', Atmos. Environ. 24B, 303–312.Google Scholar
  15. Ryan, W. F.: 1995, 'Forecasting severe ozone episodes in the Baltimore Metropolitan Area', Atmos. Environ. 29(17), 2387–2398.Google Scholar
  16. Simpson, R. and Layton, A.: 1983, 'Forecasting peak ozone levels', Atmos. Environ. 17, 1649–1654.Google Scholar
  17. Surman, P. G., Bodero, J. and Simpson, R. W.: 1987, 'The prediction of the numbers of violations and the frequency of air pollution episodes using extreme value theory', Atmos. Environ. 21, 1843–1848.Google Scholar
  18. Tiao, G. C., Phadke, M. S. and Box, G. E. P.: 1976, 'Some empirical models for the Los Angeles photochemical smog data', J. Air Pollut. Control Assoc. 26, 485–490.Google Scholar
  19. Willmott, C. J., Acckleson, S. G., Davis, R. E. Feddema, J. J., Klink, K. M., Legates, D. R., O'Donnell, J. and Rowe, C. M.: 1985, 'Statistics for the evaluation and comparison of models', J. Geophys. Res. 90, 8995–9005.Google Scholar
  20. Wolff, G. and Lioy, P.: 1978, 'An empirical model for forecasting Maximum daily Ozone levels in the NE U.S.', J. Air Pollut. Control Assoc. 28, pp1034–1038.Google Scholar

Copyright information

© Kluwer Academic Publishers 1999

Authors and Affiliations

  • A. Chaloulakou
  • D. Assimacopoulos*
  • T. Lekkas

There are no affiliations available

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