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dc.contributor.authorKurganskiy, A
dc.contributor.authorAmbelas Skjøth, C
dc.contributor.authorBaklanov, A
dc.contributor.authorSofiev, M
dc.contributor.authorSaarto, A
dc.contributor.authorSeverova, E
dc.contributor.authorSmyshlyaev, S
dc.contributor.authorKaas, E
dc.date.accessioned2021-11-18T14:08:58Z
dc.date.issued2020-02-26
dc.date.updated2021-11-18T11:13:59Z
dc.description.abstractInformation about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important, especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining a land cover data and forest inventory, (2) a map obtained from land cover data and calibrated using model simulations and pollen observations, and (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment - High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. A total of 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark, and Russia. We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies.en_GB
dc.description.sponsorshipScholarship of the President of the Russian Federationen_GB
dc.description.sponsorshipEuropean Unionen_GB
dc.description.sponsorshipRussian Science Foundationen_GB
dc.description.sponsorshipRussian Ministry of High Education and Scienceen_GB
dc.format.extent2099-2121
dc.identifier.citationVol. 20(4), pp. 2099-2121en_GB
dc.identifier.doihttps://doi.org/10.5194/acp-20-2099-2020
dc.identifier.grantnumberES1004en_GB
dc.identifier.grantnumberES1004en_GB
dc.identifier.grantnumber19-17-00198en_GB
dc.identifier.grantnumber95-7843en_GB
dc.identifier.urihttp://hdl.handle.net/10871/127867
dc.language.isoenen_GB
dc.publisherEuropean Geosciences Union / Copernicus Publicationsen_GB
dc.rights© Author(s) 2020. Open access. This work is distributed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/en_GB
dc.titleIncorporation of pollen data in source maps is vital for pollen dispersion modelsen_GB
dc.typeArticleen_GB
dc.date.available2021-11-18T14:08:58Z
dc.identifier.issn1680-7316
dc.descriptionThis is the final version. Available on open access from the European Geosciences Union via the DOI in this recorden_GB
dc.descriptionCode and data availability: The model code and data are available from the authors upon request. The pollen observational data are available by contacting the data owners, i.e. AS, ES, and the Danish Asthma Allergy.en_GB
dc.identifier.eissn1680-7324
dc.identifier.journalAtmospheric Chemistry and Physicsen_GB
dc.relation.ispartofAtmospheric Chemistry and Physics, 20(4)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-12-23
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-02-26
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-11-18T14:04:04Z
refterms.versionFCDVoR
refterms.dateFOA2021-11-18T14:09:05Z
refterms.panelCen_GB
refterms.dateFirstOnline2020-02-26


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© Author(s) 2020. Open access. This work is distributed under
the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's licence is described as © Author(s) 2020. Open access. This work is distributed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/