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dc.contributor.authorBorrego, Carlos
dc.contributor.authorMiranda, A.I.
dc.contributor.authorMonteiro, Alexandra
dc.contributor.authorCarvalho, A.
dc.contributor.authorRibeiro, I
dc.contributor.authorScotto, M.
dc.contributor.authorBarbosa, S.
dc.contributor.authorAlonso, A.
dc.contributor.authorBaldasano Recio, José María
dc.contributor.authorPay Pérez, M. Teresa
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Projectes d'Enginyeria
dc.date.accessioned2012-06-18T16:16:58Z
dc.date.created2012-09-01
dc.date.issued2012-09-01
dc.identifier.citationMonteiro, A. [et al.]. Trends in ozone concentrations in the Iberian Peninsula by quantile regression and clustering. "Atmospheric environment", 01 Setembre 2012, vol. 56, núm. September, p. 184-193.
dc.identifier.issn1352-2310
dc.identifier.urihttp://hdl.handle.net/2117/16088
dc.description.abstractIn this paper, 10-years of ozone (O3) hourly concentrations collected over the period 2000e2009 in the Iberian Peninsula (IP) are analyzed using records from 11 background sites. All the selected monitoring stations present an acquisition efficiency above 85%. The changes in surface ozone over the Iberian Peninsula are examined by means of quantile regression, which allows to analyse the trends not only in the mean but in the overall data distribution. In addition, the ozone hourly concentrations records are clustered on the basis of their resulting distributions. The analysis showed that high altitude stations (>900 m) have higher background O3 concentrations (w80 mg m 3). The same magnitude of background O3 concentrations is found in stations near the Mediterranean Sea. On the other hand, the rural stations near the Atlantic coast present lower background values (w50e60 mg m 3) than those of Mediterranean influence. The two sub-urban stations exhibit the lowest background concentrations (w45 mg m 3). The results of the quantile regression show a very distinct behaviour of the data distribution, the slopes for a fixed quantile are not the same over IP, reflecting the spatial dependence of O3 trends. Hence the rate of temporal change is not the same for all parts of the data distribution, as implicitly assumed in ordinary regression. The lower quantile (percentile 5) presents higher rates of change than the middle (percentile 50) and the upper quantile (percentile 95). The clustering procedure reveals what has been already detected in the quantile regression. The station with highest rates of decrease on the O3 concentrations (easternmost station of IP) is isolated and then other clusters are formed among the moderately positive/negative O3 trends around the IP. The clustering procedure highlighted that the largest trends are found for the lower ozone O3 values, with largest negative trend at the easternmost station of IP, and also in northern and mainland stations, and an opposite behaviour, with positive O3 trends, is observed at the Atlantic coast stations
dc.format.extent10 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/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
dc.subject.lcshEnvironmental monitoring
dc.subject.lcshAtmospheric ozone
dc.subject.lcshCluster analysis
dc.subject.lcshRegression analysis
dc.titleTrends in ozone concentrations in the Iberian Peninsula by quantile regression and clustering
dc.typeArticle
dc.subject.lemacSeguiment ambiental
dc.subject.lemacOzó atmosfèric
dc.subject.lemacAnàlisi de conglomerats
dc.subject.lemacAnàlisi de regressió
dc.contributor.groupUniversitat Politècnica de Catalunya. MTA - Modelització i Tecnologia Ambiental
dc.identifier.doi10.1016/j.atmosenv.2012.03.069
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac10509363
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorMonteiro, A.; Carvalho, A.; Ribeiro, I.; Scotto, M.; Barbosa, S.; Alonso, A.; Baldasano, J.; Pay, M.; Miranda, A.I.; Borrego, C.
local.citation.publicationNameAtmospheric environment
local.citation.volume56
local.citation.numberSeptember
local.citation.startingPage184
local.citation.endingPage193


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