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dc.contributor.author | Pérez Bartolomé, Isidro Alberto | |
dc.contributor.author | García Pérez, María Ángeles | |
dc.contributor.author | Sánchez Gómez, María Luisa | |
dc.contributor.author | Pardo Gómez, Nuria | |
dc.date.accessioned | 2023-02-13T10:01:53Z | |
dc.date.available | 2023-02-13T10:01:53Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Science of The Total Environment, 2022, vol. 819, p. 153129 | es |
dc.identifier.issn | 0048-9697 | es |
dc.identifier.uri | https://uvadoc.uva.es/handle/10324/58628 | |
dc.description | Producción Científica | es |
dc.description.abstract | CO2 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.mimetype | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject.classification | Skewed distributions | es |
dc.subject.classification | Greenhouse gases | es |
dc.subject.classification | Efficiency estimators | es |
dc.subject.classification | Distribution fitting | es |
dc.subject.classification | Outlier distribution | es |
dc.subject.classification | Emissions statistical control | es |
dc.title | Trend analysis and outlier distribution of CO2 and CH4: A case study at a rural site in northern Spain | es |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.holder | © 2022 The Author(s) | es |
dc.identifier.doi | 10.1016/j.scitotenv.2022.153129 | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0048969722002194 | es |
dc.identifier.publicationfirstpage | 153129 | es |
dc.identifier.publicationtitle | Science of The Total Environment | es |
dc.identifier.publicationvolume | 819 | es |
dc.peerreviewed | SI | es |
dc.description.project | Ministerio de Economía y Competitividad y fondos FEDER, (project numbers CGL-2009-11979 and CGL2014-53948-P) | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es |
dc.subject.unesco | 22 Física | es |
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