Neural modelling of the spatial distribution of air pollutants

Atmospheric Environment

Volumn 43, Issue 20, 2009, Pages 3289-3297

  Pfeiffer, H ^a   Baumbach, G ^a   Sarachaga Ruiz, L ^a   Kleanthous, S ^b   Poulida, O ^b   Beyaz, E ^b  

^a UNIVERSITY OF STUTTGART   (Germany)

^b Greek Cypriot Community   (Cyprus)

Author keywords

Air quality modelling; Artificial neural networks; Diffusive sampling evaluation; Nitrogen oxides; Spatial approximation

Indexed keywords

AIR POLLUTANTS; AIR QUALITY MEASUREMENTS; AIR QUALITY MODELLING; ANNUAL AVERAGES; ARTIFICIAL NEURAL NETWORKS; AVERAGE CONCENTRATIONS; BEST FITS; DIFFUSIVE SAMPLERS; DIFFUSIVE SAMPLING EVALUATION; DISTRIBUTION PARAMETERS; EMISSION SOURCES; EMISSIONS INVENTORIES; GASEOUS SPECIES; INPUT NODES; INTERPOLATION ALGORITHMS; MEASUREMENT DATUM; METEOROLOGICAL PARAMETERS; MULTI-LAYER PERCEPTRON; POLLUTANT LEVELS; POPULATION DENSITIES; SPATIAL APPROXIMATION; SPATIAL DISTRIBUTIONS;

AIR QUALITY; ATMOSPHERICS; BACKPROPAGATION; LAND USE; NITRIC OXIDE; NITROGEN OXIDES; POPULATION STATISTICS; SIZE DISTRIBUTION;

NEURAL NETWORKS;

NITROGEN DIOXIDE; NITROGEN OXIDE;

AIR QUALITY; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC MODELING; MEASUREMENT METHOD; NITROGEN OXIDES; SAMPLING; SPATIAL DISTRIBUTION;

AIR POLLUTANT; AIR POLLUTION; AIR QUALITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CYPRUS; GEOGRAPHIC DISTRIBUTION; PLUME; PRIORITY JOURNAL;

ASIA; CYPRUS; EURASIA; MIDDLE EAST;

EID: 65649141299     PISSN: 13522310     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2008.05.073     Document Type: Article

References (18)

1. 2 hourly levels. Ecology and the Environment 74 (2004) United Kingdom
2. Agirre-Basurko, G., Ibarra-Barestegi, G., Madariaga, I., 2003. Regression and multilayer perceptron-based models to forecast hourly O3 and NO2 levels in the Bilbao area. In: Proceedings of the Fourth International Conference on Urban Air Quality, Prague, University of Hertfordshire.
3. Bahmann, W., Schmonsees, N., Oestereicher, R., 2003. TA Luft 2002 - Neue Anforderungen an meteorologische Daten für Ausbreitungsrechnungen. Immissionsschutz, 8. Jahrgang, Heft Nr. 1, Berlin, Bielefeld, München.
4. Baumbach G., and Pfeiffer H. Preliminary Assessment of Ambient Air Quality in Cyprus. Final report (2004), Department of Air Quality Control in the Institute of Process Engineering and Power Plant Technology, Universität Stuttgart
5. Beier R., and Doppelfeld A. Spatial Interpolation and Representativeness of Air Quality Data: An Intuitive Approach. International Conference Air Quality in Europe: Challenges for the 2000s (2000), Stampe Violato, Padova, Italy
6. 2. In: International Conference Measuring Air Pollutants by Diffusive Sampling - Proceedings, Montpellier, pp. 273-277.
7. Hartung J. Statistik. Lehr- und Handbuch der angewandten Statistik. ninth ed. (1993), Oldenbourg Verlag, München, Wien
8. Nagel T., Flassak T., Bächlin W., and Lohmeyer A. Optimierung des Luftmessnetzes von Baden-Württemberg - Teil A Verfahren für Flächenhafte Immissionsdarstellung und Immissionsbezogene Klassifizierung (2002), UMEG, Karlsruhe
9. Partanen, L. et al., 2003 Intercomparison of neural network, statistical and deterministic models for predicting the concentration of NO2 and PM10 in urban air. In: Proceedings of the 4th International Conference on Urban Air Quality, University of Hertfordshire, Prague.
10. Pellicioni, A., Tirabassi, T., Gariazzo, C., 2003. Improving of a dispersion model by neural network filter. In: Proceedings of the 4th International Conference on Urban Air Quality, University of Hertfordshire, Prague.
11. Pelliocioni A., Tirabassi T., and Gariazzo C. Coupling of neural network and dispersion models: a novel methodology for air pollution models. 8th International Conference on Harmonisation Within Atmospheric Dispersion Modelling for Regulatory Purposes - Proceedings (2002), National Institute of Meteorology and Hydrology, Sofia
12. Rojas R. Theorie der neuronalen Netze. Eine systematische Einführung (1993), Springer Verlag, Heidelberg
13. 2 concentration using artificial neural networks. Water, Air, and Soil Pollution - Focus 3 (2003) Netherlands
14. Schwinger, J., Elbern, H., Botchorisvili, R., 2005. Assimilation of ENVISAT stratospheric trace gas observations into the new SACADA global chemistry circulation model. Poster presentation at European Geosciences UnionGeneral Assembly 2005.
15. x and Ozone measurements over domains ranging from 100 m to 100 km. In: Proceedings of the Fourth International Conference on Urban Air Quality, University of Hertfordshire, University of Hertfordshire, Prague.
16. Van Aalst R., et al. Guidance Report on Preliminary Assessment Under EC Air Quality Directives (1998), European Environment Agency, Copenhagen Technical report No. 11
17. Van den Hout D., et al. Guidance on Assessment under the EU Air Quality Directives (2002), European Environment Agency, Copenhagen
18. Willmott C.J. On the validation of models. Physical Geography 2 (1981) 184-194