3-Day-Ahead Forecasting of Regional Pollution Index for the Pollutants NO2, CO, SO2, and O3 Using Artificial Neural Networks in Athens, Greece

The difficulty in forecasting concentration trends with a reasonable error is still an open problem. In this paper, an effort has been made to this purpose. Artificial Neural Networks are used in order to forecast the maximum daily value of the European Regional Pollution Index as well as the number of consecutive hours, during the day, with at least one of the pollutants above a threshold concentration, 24 to 72 h ahead. The prediction concerns seven different places within the Greater Athens Area, Greece. The meteorological and air pollution data used in this study have been recorded by the network of the Greek Ministry of the Environment, Physical Planning, and Public Works over a 5-year period, 2001–2005. The hourly values of air pressure and global solar irradiance for the same period have been recorded by the National Observatory of Athens. The results are in a very good agreement with the real-monitored data at a statistical significance level of p < 0.01.

[1]  R. Peled,et al.  Prediction of emergency department visits for respiratory symptoms using an artificial neural network. , 2002, Chest.

[2]  J Schwartz,et al.  Air Pollution and Hospital Admissions for Respiratory Disease , 1996, Epidemiology.

[3]  Joseph Rynkiewicz,et al.  A 24-h forecast of ozone peaks and exceedance levels using neural classifiers and weather predictions , 2007, Environ. Model. Softw..

[4]  Dimitrios Melas,et al.  Development and Assessment of Neural Network and Multiple Regression Models in Order to Predict PM10 Levels in a Medium-sized Mediterranean City , 2007 .

[5]  Robert E. Davis,et al.  Statistics for the evaluation and comparison of models , 1985 .

[6]  Giorgio Corani,et al.  Air quality prediction in Milan: feed-forward neural networks, pruned neural networks and lazy learning , 2005 .

[7]  Chun-Yuh Yang,et al.  Relationship between air pollution and daily mortality in a subtropical city: Taipei, Taiwan. , 2004, Environment international.

[8]  Nicolas Moussiopoulos,et al.  PM10 forecasting for Thessaloniki, Greece , 2006, Environ. Model. Softw..

[9]  J Schwartz,et al.  Air pollution and daily mortality: associations with particulates and acid aerosols. , 1992, Environmental research.

[10]  A. Comrie.  Comparing Neural Networks and Regression Models for Ozone Forecasting , 1997 .

[11]  R. Simpson,et al.  Forecasting peak ozone levels , 1983 .

[12]  Johanna J. Heymans,et al.  A carbon flow model and network analysis of the northern Benguela upwelling system, Namibia , 2000 .

[13]  M. Kolehmainen,et al.  Neural networks and periodic components used in air quality forecasting , 2001 .

[14]  Roy M. Harrison,et al.  Regression modelling of hourly NOx and NO2 concentrations in urban air in London , 1997 .

[15]  J Schwartz,et al.  Increased mortality in Philadelphia associated with daily air pollution concentrations. , 1992, The American review of respiratory disease.

[16]  Oleg Antonić,et al.  Modelling groundwater regime acceptable for the forest survival after the building of the hydro-electric power plant , 2001 .

[17]  J. L. Carrasco-Rodriguez,et al.  Effective 1-day ahead prediction of hourly surface ozone concentrations in eastern Spain using linear models and neural networks , 2002 .

[18]  Jose Torres-Jimenez,et al.  Short-term ozone forecasting by artificial neural networks , 1995 .

[19]  Giuseppe Nunnari,et al.  The application of neural techniques to the modelling of time-series of atmospheric pollution data , 1998 .

[20]  Joel Schwartz,et al.  Simultaneous immunisation with influenza vaccine and pneumococcal polysaccharide vaccine in patients with chronic respiratory disease , 1997, BMJ.

[21]  H. L. Gray,et al.  Applied time series analysis , 2011 .

[22]  Christos Zerefos,et al.  Forecasting peak pollutant levels from meteorological variables , 1995 .

[23]  Victor R. Prybutok,et al.  Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations , 2000, Eur. J. Oper. Res..

[24]  Gavin C. Cawley,et al.  A rigorous inter-comparison of ground-level ozone predictions , 2003 .

[25]  T. J. Lyons,et al.  Comparison of the Revised Air Quality Index with the PSI and AQI indices. , 2007, The Science of the total environment.

[26]  S J Pocock,et al.  Short-term effects of air pollution on daily mortality in Athens: a time-series analysis. , 1994, International journal of epidemiology.

[27]  PAUL J. WERBOS,et al.  Generalization of backpropagation with application to a recurrent gas market model , 1988, Neural Networks.

[28]  P. Viotti,et al.  Atmospheric urban pollution: applications of an artificial neural network (ANN) to the city of Perugia , 2002 .

[29]  V. Prybutok,et al.  A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area. , 1996, Environmental pollution.

[30]  M. W Gardner,et al.  Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences , 1998 .

[31]  S. Soyupak,et al.  Case studies on the use of neural networks in eutrophication modeling , 2000 .

[32]  D. Melas,et al.  Neural Network Model for Predicting Peak Photochemical Pollutant Levels , 2000, Journal of the Air & Waste Management Association.

[33]  F. Valero,et al.  STATISTICAL FORECAST MODELS FOR DAILY AIR PARTICULATE IRON AND LEAD CONCENTRATIONS FOR MADRID, SPAIN , 1992 .

[34]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[35]  Mohd Nasir Hassan,et al.  Review of air pollution and health impacts in Malaysia. , 2003, Environmental research.

[36]  Jorge Reyes,et al.  Prediction of PM2.5 concentrations several hours in advance using neural networks in Santiago, Chile , 2000 .

[37]  J Pekkanen,et al.  Fine particulate air pollution, resuspended road dust and respiratory health among symptomatic children. , 1999, The European respiratory journal.

[38]  G Touloumi,et al.  Evidence for interaction between air pollution and high temperature in the causation of excess mortality. , 1993, Archives of environmental health.

[39]  M. Gardner,et al.  Neural network modelling and prediction of hourly NOx and NO2 concentrations in urban air in London , 1999 .