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dc.contributor.authorPérez Bartolomé, Isidro Alberto 
dc.contributor.authorGarcía Pérez, María Ángeles 
dc.contributor.authorSánchez Gómez, María Luisa 
dc.contributor.authorPardo Gómez, Nuria 
dc.date.accessioned2023-02-13T10:01:53Z
dc.date.available2023-02-13T10:01:53Z
dc.date.issued2022
dc.identifier.citationScience of The Total Environment, 2022, vol. 819, p. 153129es
dc.identifier.issn0048-9697es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/58628
dc.descriptionProducción Científicaes
dc.description.abstractCO2 and CH4 outliers may have a noticeable impact on the trend of both gases. Nine years of measurements since 2010 recorded at a rural site in northern Spain were used to investigate these outliers. Their influence on the trend was presented and two limits were established. No more than 23.5% of outliers should be excluded from the measurement series in order to obtain representative trends, which were 2.349 ± 0.012 ppm year−1 for CO2 and 0.00879 ± 0.00004 ppm year−1 for CH4. Two types of outliers were distinguished. Those above the trend line and the rest below the trend line. Outliers were described by skewed distributions where the Weibull distribution figures prominently in most cases. A qualitative procedure was presented to exclude the worst fits, although five statistics were considered to select the best fit. In this case, the modified Nash-Sutcliffe efficiency is prominent. Finally, three symmetrical distributions were added to fit the observations when outliers are excluded, with the Gaussian and beta distributions providing the best fits. As a result, certain skewed functions, such as the lognormal distribution, whose use is frequent for air pollutants, could be questioned in certain applications.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationSkewed distributionses
dc.subject.classificationGreenhouse gaseses
dc.subject.classificationEfficiency estimatorses
dc.subject.classificationDistribution fittinges
dc.subject.classificationOutlier distributiones
dc.subject.classificationEmissions statistical controles
dc.titleTrend analysis and outlier distribution of CO2 and CH4: A case study at a rural site in northern Spaines
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2022 The Author(s)es
dc.identifier.doi10.1016/j.scitotenv.2022.153129es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0048969722002194es
dc.identifier.publicationfirstpage153129es
dc.identifier.publicationtitleScience of The Total Environmentes
dc.identifier.publicationvolume819es
dc.peerreviewedSIes
dc.description.projectMinisterio de Economía y Competitividad y fondos FEDER, (project numbers CGL-2009-11979 and CGL2014-53948-P)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco22 Físicaes


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