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dc.contributor.authorLaña, Ibai
dc.contributor.authorDel Ser, Javier
dc.contributor.authorPadró, Ales
dc.contributor.authorVélez, Manuel
dc.contributor.authorCasanova-Mateo, Carlos
dc.date.accessioned2016-12-02T11:20:33Z
dc.date.available2016-12-02T11:20:33Z
dc.date.issued2016-11
dc.identifier.citationIbai Laña, Javier Del Ser, Ales Padró, Manuel Vélez, Carlos Casanova-Mateo, The role of local urban traffic and meteorological conditions in air pollution: A data-based case study in Madrid, Spain, Atmospheric Environment, Volume 145, November 2016, Pages 424-438, ISSN 1352-2310, http://dx.doi.org/10.1016/j.atmosenv.2016.09.052.en
dc.identifier.issn1352-2310en
dc.identifier.urihttp://hdl.handle.net/11556/350
dc.description.abstractUrban air pollution is a matter of growing concern for both public administrations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions can make pollution levels increase or diminish dramatically. In this context an upsurge of research has been conducted towards functionally linking variables of such domains to measured pollution data, with studies dealing with up to one-hour resolution meteorological data. However, the majority of such reported contributions do not deal with traffic data or, at most, simulate traffic conditions jointly with the consideration of different topographical features. The aim of this study is to further explore this relationship by using high-resolution real traffic data. This paper describes a methodology based on the construction of regression models to predict levels of different pollutants (i.e. CO, NO, NO2, O3 and PM10) based on traffic data and meteorological conditions, from which an estimation of the predictive relevance (importance) of each utilized feature can be estimated by virtue of their particular training procedure. The study was made with one hour resolution meteorological, traffic and pollution historic data in roadside and background locations of the city of Madrid (Spain) captured over 2015. The obtained results reveal that the impact of vehicular emissions on the pollution levels is overshadowed by the effects of stable meteorological conditions of this city.en
dc.description.sponsorshipThis work has been funded in part by the Basque Government under the ELKARTEK program (BID3A project, grant ref. KK-2015/0000080).en
dc.language.isoengen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLANDen
dc.titleThe role of local urban traffic and meteorological conditions in air pollution: A data-based case study in Madrid, Spainen
dc.typearticleen
dc.identifier.doi10.1016/j.atmosenv.2016.09.052en
dc.isiYesen
dc.rights.accessRightsembargoedAccessen
dc.subject.keywordsUrban air pollutionen
dc.subject.keywordsTraffic flowen
dc.subject.keywordsMeteorological conditionsen
dc.subject.keywordsSupervised learningen
dc.subject.keywordsRandom forestsen
dc.identifier.essn1873-2844en
dc.journal.titleAtmospheric Environmenten
dc.page.final438en
dc.page.initial424en
dc.volume.number145en


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