Understanding hourly patterns of Olea pollen concentrations as tool for the environmental impact assessment.
Aerobiology
Clustering
Hourly data
Neural networks
Olea pollen
Journal
The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500
Informations de publication
Date de publication:
20 Sep 2020
20 Sep 2020
Historique:
received:
09
04
2020
revised:
06
05
2020
accepted:
09
05
2020
pubmed:
3
6
2020
medline:
11
7
2020
entrez:
3
6
2020
Statut:
ppublish
Résumé
Bioinformatics clustering application for mining of a large set of olive pollen aerobiological data to describe the daily distribution of Olea pollen concentration. The study was performed with 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/m
Identifiants
pubmed: 32485367
pii: S0048-9697(20)32880-1
doi: 10.1016/j.scitotenv.2020.139363
pii:
doi:
Substances chimiques
Air Pollutants
0
Allergens
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
139363Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.