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dc.contributor.authorFernández-Rodríguez, Santiago
dc.contributor.authorMaya-Manzano, José María
dc.contributor.authorMonroy-Colín, Alejandro
dc.contributor.authorPecero-Casimiro, Raúl
dc.contributor.authorButers, Jeroen
dc.contributor.authorOteros, José
dc.date.accessioned2024-02-08T20:45:53Z
dc.date.available2024-02-08T20:45:53Z
dc.date.issued2020
dc.identifier.issn0048-9697
dc.identifier.urihttp://hdl.handle.net/10396/27335
dc.description.abstractBioinformatics clustering application for mining of a large set of olive pollen aerobiological data to describe the daily distribution of Olea pollen concentration. The studywas performedwith hourly pollen concentrations measured during 8 years (2011–2018) in Extremadura (Spain). Olea pollen season by quartiles of the pollen integral in preseason (Q1: 0%–25%), in-season (Q2 and Q3: 25%–75%) and postseason (Q4: 75%–100%). Days with pollen concentrations above 100 grains/m3were clustered according to the daily distribution of the concentrations. The factors affecting the prevalence of the different clusters were analyzed: distance to olive groves and the moment during the pollen season and the meteorology. During the season, the highest hourly concentrations during the day where between 12:00 and 14:00, while during the preseason the highest hourly concentrations were detected in the afternoon and evening hours. In the postseason the pollen concentrations were more homogeneously distributed during 9-16 h. The representation shows a well-defined hourly pattern during the season, but a more heterogeneous distribution during the preseason and postseason. The cluster dendrogram shows that all the days could be clustered in 6 groups: most of the clusters shows the daily peaks between 11:00 and 15:00 with a smooth curve (Cluster 1 and 3) or with a strong peak (2 and 5). Days included in cluster 9 shows an earlier peak in the morning (before 9:00). On the other hand, cluster 6 shows a peak in the afternoon, after 15:00. Hourly concentrations show a sharper pattern during the season, with the peak during the hours close to the emission. Out of the season, when pollen is expected to come from farther distances, the hourly peak is located later from the emission time of the trees. Significant factors for predicting the hourly pattern were wind speed and direction and the distance to the olive groves.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.sourceFernández-Rodríguez, S., Maya‐Manzano, J. M., Colín, A. M., Pecero-Casimiro, R., Buters, J., & Oteros, J. (2020). Understanding hourly patterns of Olea pollen concentrations as tool for the environmental impact assessment. Science Of The Total Environment, 736, 139363. https://doi.org/10.1016/j.scitotenv.2020.139363es_ES
dc.subjectOlea pollenes_ES
dc.subjectHourly dataes_ES
dc.subjectAerobiologyes_ES
dc.subjectClusteringes_ES
dc.subjectNeural networkses_ES
dc.titleUnderstanding hourly patterns of Olea pollen concentrations as tool for the environmental impact assessmentes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.scitotenv.2020.139363es_ES
dc.relation.projectIDGobierno de España. CAS 18/00047es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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