Mostrar el registro sencillo del ítem

dc.contributor.authorPérez Bartolomé, Isidro Alberto 
dc.contributor.authorSánchez Gómez, María Luisa 
dc.contributor.authorGarcía Pérez, María Ángeles 
dc.contributor.authorPardo Gómez, Nuria 
dc.date.accessioned2024-02-01T09:39:20Z
dc.date.available2024-02-01T09:39:20Z
dc.date.issued2013
dc.identifier.citationScience of the Total Environment 456–457 (2013) 239–245es
dc.identifier.issn0048-9697es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/65495
dc.descriptionProducción Científicaes
dc.description.abstractCO2 concentrations recorded for two years using a Picarro G1301 analyser at a rural site were studied applying two procedures. Firstly, the smoothing kernel method, which to date has been used with one linear and another circular variable, was used with pairs of circular variables: wind direction, time of day, and time of year, providing that the daily cycle was the prevailing cyclical evolution and that the highest concentrations were justified by the influence of one nearby city source, which was only revealed by directional analysis. Secondly, histograms were obtained, and these revealed most observations to be located between 380 and 410 ppm, and that there was a sharp contrast during the year. Finally, histograms were fitted to 14 distributions, the best known using analytical procedures, and the remainder using numerical procedures. RMSE was used as the goodness of fit indicator to compare and select distributions. Most functions provided similar RMSE values. However, the best fits were obtained using numerical procedures due to their greater flexibility, the triangular distribution being the simplest function of this kind. This distribution allowed us to identify directions and months of noticeable CO2 input (SSE and April-May, respectively) as well as the daily cycle of the distribution symmetry. Among the functions whose parameters were calculated using an analytical expression, Erlang distributions provided satisfactory fits for monthly analysis, and gamma for the rest. By contrast, the Rayleigh and Weibull distributions gave the worst RMSE values.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses
dc.subject.classificationRural CO2es
dc.subject.classificationKernel regressiones
dc.subject.classificationDistribution fittinges
dc.subject.classificationTriangular distributiones
dc.titleCarbon dioxide at an unpolluted site analysed with the smoothing kernel method and skewed distributionses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2013 Elsevier B.V. All rights reservedes
dc.identifier.doi10.1016/j.scitotenv.2013.03.075es
dc.relation.publisherversionhttps://doi.org/10.1016/j.scitotenv.2013.03.075es
dc.identifier.publicationfirstpage239es
dc.identifier.publicationlastpage245es
dc.identifier.publicationtitleScience of The Total Environmentes
dc.identifier.publicationvolume456-457es
dc.peerreviewedSIes
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem