Air quality models resulting from multi-source emissions

  • A. Russo
  • C. Nunes
  • A. Bio
Conference paper


Monitoring Station Neural Network Model Probabilistic Neural Network Industrial Complex Industrial Emission 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Beale MH, Demuth HB (1998) Neural Network Toolbox for Use with MATLAB, User’s Guide, version 3. The MathWorks, Inc.Google Scholar
  2. Beale MH, Demuth HB, Hagan MT (1996) Neural Networks design. PWS Publishing Company, BostonGoogle Scholar
  3. Cobourn WG, Dolcine L, French M and Hubbard MC (2000) Comparison of Nonlinear Regression and Neural Network Models for Ground-Level Ozone Forecasting. J. Air & Waste Manage. Assoc., 50, 1999–2009Google Scholar
  4. Comrie AC (1997) Comparing neural networks and regression models for ozone forecasting. Journal of Air and Waste Management Association, 47, 653–663Google Scholar
  5. De Nevers N (2000) Air Pollution Control Engineering, 2nd edn. McGraw-HillGoogle Scholar
  6. Dorling SR, Gardner MW (1998) Artificial Neural Networks (the Multi-layer Perceptron)-A review of applications in the atmospheric sciences. Atmospheric Environment, 32, 2627–2636Google Scholar
  7. Dorling SR, Gardner MW (1999) Neural network modelling and prediction of hourly Nox and NO2 concentrations in urban air in London. Atmospheric Environment 33 709–719Google Scholar
  8. Gurney K (1997) An Introduction to Neural Networks. UCL press, LondonGoogle Scholar
  9. Haykin S (1994) Neural Networks: A Comprehensive Foundation. Macmillan Pub, New YorkGoogle Scholar
  10. Kolehmainen M, Martikainen H and Ruuskanen J (2000) Neural networks and periodic components used in air quality forecasting. Atmospheric Environment, 35, 815–825Google Scholar
  11. Sarle W (1994) Neural networks and statistical models. Proceedings of the Nineteenth Annual SAS Users Group International Conference, Cary, NC: SAS instituteGoogle Scholar
  12. Seinfeld JH (1986) Atmospheric Chemistry and Physics of Air Pollution. John Wiley & SonsGoogle Scholar
  13. Shi JP and Harrison RM (1997) Regression modelling of hourly NOx and NO2 concentrations in urban air in London. Atmospheric Environment, 31, 4081–4094Google Scholar
  14. Simpson RW and Layton AP (1983) Forecasting peak ozone levels. Atmospheric Environment, 17, 1649–1654Google Scholar
  15. Wassermann PD (1989) Neural Computing theory and Practice. New York Van Nostrand ReinholdGoogle Scholar
  16. Ziomas I, Melas D, Zerefos CS, Bais AF and Paliatsos AG (1995) Forecasting peak pollutant levels from meteorological variables. Atmospheric Environment, 29, 3703–3711CrossRefGoogle Scholar
  17. WHO (1999) Ambient Air Quality Monitoring and Assessment — Guidelines for Air Quality. World Health Organization, GenevaGoogle Scholar
  18. Yi J and Prybutok VR (1996) A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area. Environmental Pollution, 92, 349–357CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • A. Russo
    • 1
  • C. Nunes
    • 1
    • 2
  • A. Bio
    • 1
  1. 1.Environmental Group of the Centre for Modelling Petroleum Reservoirs CMRP-ISTLisbonPortugal
  2. 2.Universidade de ÉvoraPortugal

Personalised recommendations