Articles | Volume 20, issue 4
https://doi.org/10.5194/acp-20-2099-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-2099-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Feb 2020
Research article |
| 26 Feb 2020
| 26 Feb 2020
Incorporation of pollen data in source maps is vital for pollen dispersion models
Alexander Kurganskiy
CORRESPONDING AUTHOR
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Department of Meteorology, Russian State Hydrometeorological University, St. Petersburg, Russia
School of Science and the Environment, University of Worcester, Worcester, UK
now at: University of Exeter, Penryn Campus, Penryn, Cornwall, UK
Carsten Ambelas Skjøth
School of Science and the Environment, University of Worcester, Worcester, UK
Alexander Baklanov
Science and Innovation Department, World Meteorological Organization, Geneva, Switzerland
Mikhail Sofiev
Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
Annika Saarto
Biodiversity Unit, University of Turku, Turku, Finland
Elena Severova
Biological Faculty, Department of Higher Plants, Lomonosov Moscow State University, Moscow, Russia
Sergei Smyshlyaev
Department of Meteorology, Russian State Hydrometeorological University, St. Petersburg, Russia
Eigil Kaas
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
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Cited
25 citations as recorded by crossref.
- The impact of data assimilation into the meteorological WRF model on birch pollen modelling M. Werner et al. 10.1016/j.scitotenv.2021.151028
- Climate change and global issues in allergy and immunology S. Pacheco et al. 10.1016/j.jaci.2021.10.011
- Measurement report: Characterization of the vertical distribution of airborne Pinus pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain M. Sicard et al. 10.5194/acp-21-17807-2021
- Predicting reproductive phenology of wind-pollinated trees via PlanetScope time series Y. Song et al. 10.1016/j.srs.2025.100205
- Establishment, operation and development of the electronic Pollen Information Network (ePIN) in Bavaria, Germany S. Kutzora et al. 10.1038/s41598-025-90275-x
- Quantifying co-benefits and disbenefits of Nature-based Solutions targeting Disaster Risk Reduction J. Ommer et al. 10.1016/j.ijdrr.2022.102966
- Microscale pollen release and dispersal patterns in flowering grass populations C. Frisk et al. 10.1016/j.scitotenv.2023.163345
- Stochastic flowering phenology in Dactylis glomerata populations described by Markov chain modelling C. Frisk et al. 10.1007/s10453-020-09685-1
- Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe A. Kurganskiy et al. 10.1126/sciadv.abd7658
- Development and verification of a taxa-specific gridded pollen modelling system for the UK L. Neal et al. 10.1007/s10453-025-09858-w
- Association between local airborne tree pollen composition and surrounding land cover across different spatial scales in Northern Belgium M. Stas et al. 10.1016/j.ufug.2021.127082
- Modeling airborne pollen concentrations at an urban scale with pollen release from individual trees D. Katz et al. 10.1007/s10453-023-09784-9
- The impact of the spatial resolution of vegetation cover on the prediction of airborne pollen concentrations over northern Italy S. Tagliaferro et al. 10.1016/j.agrformet.2024.110153
- Modelling grass pollen levels in Belgium W. Verstraeten et al. 10.1016/j.scitotenv.2020.141903
- The influence of source maps on SILAM performance in modeling ragweed pollen concentrations in the area of a major European source G. Mimić et al. 10.1007/s00484-021-02075-3
- Atmospheric transport reveals grass pollen dispersion distances C. Frisk et al. 10.1016/j.scitotenv.2021.152806
- Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. 10.1007/s00484-020-02045-1
- Chemistry module for the Earth system model S. Smyshlyaev et al. 10.1515/rnam-2024-0030
- Modeling past and future spatiotemporal distributions of airborne allergenic pollen across the contiguous United States X. Ren et al. 10.3389/falgy.2022.959594
- Spatial and temporal variations in the distribution of birch trees and airborne Betula pollen in Ireland J. Maya-Manzano et al. 10.1016/j.agrformet.2020.108298
- Unveiling the intricacies of Amaranthaceous pollen diversity: Advancing ultra sculpture analysis throughLMandSEM W. Al‐Qahtani 10.1002/jemt.24408
- Air Pollution Affecting Pollen Concentrations through Radiative Feedback in the Atmosphere C. Skjøth et al. 10.3390/atmos12111376
- Application of the HYSPLIT model for birch pollen modelling in Poland D. Bilińska-Prałat et al. 10.1007/s10453-021-09737-0
- Specific Characteristics of Karelian Birch Population Structure L. Vetchinnikova & A. Titov 10.1134/S2079086421040095
- Importance of the quality management of aerobiological monitoring networks: The case study of Madrid Region in Spain P. Cervigón et al. 10.1016/j.scitotenv.2024.176544
25 citations as recorded by crossref.
- The impact of data assimilation into the meteorological WRF model on birch pollen modelling M. Werner et al. 10.1016/j.scitotenv.2021.151028
- Climate change and global issues in allergy and immunology S. Pacheco et al. 10.1016/j.jaci.2021.10.011
- Measurement report: Characterization of the vertical distribution of airborne Pinus pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain M. Sicard et al. 10.5194/acp-21-17807-2021
- Predicting reproductive phenology of wind-pollinated trees via PlanetScope time series Y. Song et al. 10.1016/j.srs.2025.100205
- Establishment, operation and development of the electronic Pollen Information Network (ePIN) in Bavaria, Germany S. Kutzora et al. 10.1038/s41598-025-90275-x
- Quantifying co-benefits and disbenefits of Nature-based Solutions targeting Disaster Risk Reduction J. Ommer et al. 10.1016/j.ijdrr.2022.102966
- Microscale pollen release and dispersal patterns in flowering grass populations C. Frisk et al. 10.1016/j.scitotenv.2023.163345
- Stochastic flowering phenology in Dactylis glomerata populations described by Markov chain modelling C. Frisk et al. 10.1007/s10453-020-09685-1
- Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe A. Kurganskiy et al. 10.1126/sciadv.abd7658
- Development and verification of a taxa-specific gridded pollen modelling system for the UK L. Neal et al. 10.1007/s10453-025-09858-w
- Association between local airborne tree pollen composition and surrounding land cover across different spatial scales in Northern Belgium M. Stas et al. 10.1016/j.ufug.2021.127082
- Modeling airborne pollen concentrations at an urban scale with pollen release from individual trees D. Katz et al. 10.1007/s10453-023-09784-9
- The impact of the spatial resolution of vegetation cover on the prediction of airborne pollen concentrations over northern Italy S. Tagliaferro et al. 10.1016/j.agrformet.2024.110153
- Modelling grass pollen levels in Belgium W. Verstraeten et al. 10.1016/j.scitotenv.2020.141903
- The influence of source maps on SILAM performance in modeling ragweed pollen concentrations in the area of a major European source G. Mimić et al. 10.1007/s00484-021-02075-3
- Atmospheric transport reveals grass pollen dispersion distances C. Frisk et al. 10.1016/j.scitotenv.2021.152806
- Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. 10.1007/s00484-020-02045-1
- Chemistry module for the Earth system model S. Smyshlyaev et al. 10.1515/rnam-2024-0030
- Modeling past and future spatiotemporal distributions of airborne allergenic pollen across the contiguous United States X. Ren et al. 10.3389/falgy.2022.959594
- Spatial and temporal variations in the distribution of birch trees and airborne Betula pollen in Ireland J. Maya-Manzano et al. 10.1016/j.agrformet.2020.108298
- Unveiling the intricacies of Amaranthaceous pollen diversity: Advancing ultra sculpture analysis throughLMandSEM W. Al‐Qahtani 10.1002/jemt.24408
- Air Pollution Affecting Pollen Concentrations through Radiative Feedback in the Atmosphere C. Skjøth et al. 10.3390/atmos12111376
- Application of the HYSPLIT model for birch pollen modelling in Poland D. Bilińska-Prałat et al. 10.1007/s10453-021-09737-0
- Specific Characteristics of Karelian Birch Population Structure L. Vetchinnikova & A. Titov 10.1134/S2079086421040095
- Importance of the quality management of aerobiological monitoring networks: The case study of Madrid Region in Spain P. Cervigón et al. 10.1016/j.scitotenv.2024.176544
Latest update: 29 May 2025
Short summary
The aim of the study was to evaluate three birch pollen source maps using a state-of-the-art atmospheric model Enviro-HIRLAM. Enviro-HIRLAM is a so-called online model where both weather and air pollution are calculated at all time steps.
The evaluation has been performed for 12 pollen observation sites located in Denmark, Finland, and Russia.
The aim of the study was to evaluate three birch pollen source maps using a state-of-the-art...
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