3-day-ahead forecasting of regional pollution index for the pollutants NO2, CO, SO2, and O3 using artificial neural networks in athens, Greece

Moustris, KP; Ziomas, IC; Paliatsos, AG

dc.contributor.author	Moustris, KP	en
dc.contributor.author	Ziomas, IC	en
dc.contributor.author	Paliatsos, AG	en
dc.date.accessioned	2014-03-01T01:32:25Z
dc.date.available	2014-03-01T01:32:25Z
dc.date.issued	2010	en
dc.identifier.issn	0049-6979	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20121
dc.subject	Air pollution forecasting	en
dc.subject	Artificial Neural Networks	en
dc.subject	Athens	en
dc.subject	Greece	en
dc.subject.classification	Environmental Sciences	en
dc.subject.classification	Meteorology & Atmospheric Sciences	en
dc.subject.classification	Water Resources	en
dc.subject.other	Air pressures	en
dc.subject.other	Artificial Neural Network	en
dc.subject.other	Athens	en
dc.subject.other	Athens , Greece	en
dc.subject.other	Concentration trends	en
dc.subject.other	Greater athens area , greece	en
dc.subject.other	Open problems	en
dc.subject.other	Regional pollution	en
dc.subject.other	Solar irradiances	en
dc.subject.other	Statistical significance	en
dc.subject.other	Threshold concentrations	en
dc.subject.other	Air quality	en
dc.subject.other	Atmospheric pressure	en
dc.subject.other	Pollution	en
dc.subject.other	Public works	en
dc.subject.other	Weather forecasting	en
dc.subject.other	Neural networks	en
dc.subject.other	cobalt	en
dc.subject.other	nitrogen dioxide	en
dc.subject.other	ozone	en
dc.subject.other	sulfur dioxide	en
dc.subject.other	artificial neural network	en
dc.subject.other	atmospheric pollution	en
dc.subject.other	carbon monoxide	en
dc.subject.other	chemical pollutant	en
dc.subject.other	concentration (composition)	en
dc.subject.other	nitrogen dioxide	en
dc.subject.other	ozone	en
dc.subject.other	pollution monitoring	en
dc.subject.other	prediction	en
dc.subject.other	sulfur dioxide	en
dc.subject.other	threshold	en
dc.subject.other	urban pollution	en
dc.subject.other	air pollutant	en
dc.subject.other	air pollution	en
dc.subject.other	air quality	en
dc.subject.other	ambient air	en
dc.subject.other	article	en
dc.subject.other	artificial neural network	en
dc.subject.other	atmospheric pressure	en
dc.subject.other	chemical analysis	en
dc.subject.other	concentration (parameters)	en
dc.subject.other	controlled study	en
dc.subject.other	forecasting	en
dc.subject.other	Greece	en
dc.subject.other	mathematical computing	en
dc.subject.other	meteorological phenomena	en
dc.subject.other	pollution monitoring	en
dc.subject.other	prediction	en
dc.subject.other	reliability	en
dc.subject.other	solar radiation	en
dc.subject.other	Athens [Attica]	en
dc.subject.other	Attica	en
dc.subject.other	Greece	en
dc.title	3-day-ahead forecasting of regional pollution index for the pollutants NO2, CO, SO2, and O3 using artificial neural networks in athens, Greece	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s11270-009-0179-5	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11270-009-0179-5	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	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. © 2009 Springer Science+Business Media B.V.	en
heal.publisher	SPRINGER	en
heal.journalName	Water, Air, and Soil Pollution	en
dc.identifier.doi	10.1007/s11270-009-0179-5	en
dc.identifier.isi	ISI:000277450300004	en
dc.identifier.volume	209	en
dc.identifier.issue	1-4	en
dc.identifier.spage	29	en
dc.identifier.epage	43	en