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dc.contributor.authorGibergans Bàguena, José
dc.contributor.authorHervada Sala, Carme
dc.contributor.authorJarauta Bragulat, Eusebio
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtiques
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Física
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2019-11-04T10:50:37Z
dc.date.available2019-11-04T10:50:37Z
dc.date.issued2019
dc.identifier.citationGibergans-Báguena, J.; Hervada-Sala, C.; Jarauta-Bragulat, E. The expression of air quality in urban areas: going further on a Compositional Data Analysis approach. A: International Workshop on Compositional Data Analysis. "Proceedings of the 8th International Workshop on Compositional Data Analysis (CoDaWork2019): Terrassa, 3-8 June, 2019". Universitat Politècnica de Catalunya (UPC), 2019, p. 63-68.
dc.identifier.isbn978-84-947240-2-2
dc.identifier.urihttp://hdl.handle.net/2117/171438
dc.description.abstractThe quality of atmospheric air in large cities is a matter of great importance because of its impact on the environment and on the health of the population. Recently, measures restricting access of private vehicles to the centre of large cities and other measures to prevent atmospheric air pollution are currently topical (Hervada-Sala et al., 2018). The knowledge of air quality acquires special relevance to be able to evaluate the impact of those great social and economic measures. There are many indices to express air quality. In fact, quite every country has its own, depending on the main pollutants, they have as Plaia and Ruggeri (2011) pointed out. In general, all indices ignore the compositional nature of the concentrations of air pollutants and do not apply methods of Compositional Data Analysis; those indices also have some other weak points such as leak of standardized scale. A first approach applying Compositional Data Analysis methods has been developed in Jarauta-Bragulat et al., 2016. In the present work, we try to go some step further to improve the understanding and manageability of air quality. The air quality index proposed here takes into account the compositional nature of the data, it has an adequate correlation between input (concentrations) and output (air quality index), it distinguishes between air pollution and air quality and it has a 0-100 reference scale which makes easier interpretation and management of air quality expression. To illustrate the proposed method, an application is made to a series of air pollution data (Barcelona, 2001-2015)
dc.format.extent6 p.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya (UPC)
dc.rightsAttribution-NonCommercial 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Mètodes estadístics
dc.subject.lcshAir -- Pollution -- Measurement -- Statistical methods
dc.subject.lcshAir quality -- Measurement -- Statistical methods
dc.subject.otherAir pollution
dc.subject.otherAir quality
dc.subject.otherAir quality index
dc.subject.otherHealth impact
dc.subject.otherCompositional Data Analysis
dc.subject.otherLog-ratio.
dc.titleThe expression of air quality in urban areas: going further on a Compositional Data Analysis approach
dc.typeConference report
dc.subject.lemacAire -- Contaminació -- Mesurament -- Mètodes estadístics
dc.subject.lemacAire -- Qualitat -- Mesurament -- Mètodes estadístics
dc.contributor.groupUniversitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
local.identifier.drac25875280
dc.description.versionPostprint (published version)
local.citation.authorGibergans-Báguena, J.; Hervada-Sala, C.; Jarauta-Bragulat, E.
local.citation.contributorInternational Workshop on Compositional Data Analysis
local.citation.publicationNameProceedings of the 8th International Workshop on Compositional Data Analysis (CoDaWork2019): Terrassa, 3-8 June, 2019
local.citation.startingPage63
local.citation.endingPage68


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial 3.0 Spain