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Monitoring, Modelling and Forecasting of the Pollen Season

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Allergenic Pollen

Abstract

The section about monitoring covers the development of phenological networks, remote sensing of the season cycle of the vegetation, the emergence of the science of aerobiology and, more specifically, aeropalynology, pollen sampling instruments, pollen counting techniques, applications of aeropalynology in agriculture and the European Pollen Information System. Three data sources are directly related with aeropalynology: phenological observations, pollen counts and remote sensing of the vegetation activity. The main future challenge is the assimilation of these data streams into numerical pollen forecast systems. Over the last decades consistent monitoring efforts of various national networks have created a wealth of pollen concentration time series. These constitute a nearly untouched treasure, which is still to be exploited to investigate questions concerning pollen emission, transport and deposition. New monitoring methods allow measuring the allergen content in pollen. Results from research on the allergen content in pollen are expected to increase the quality of the operational pollen forecasts.

In the modelling section the concepts of a variety of process-based phenological models are sketched. Process-based models appear to exhaust the noisy information contained in commonly available observational phenological and pollen data sets. Any additional parameterisations do not to improve model quality substantially. Observation-based models, like regression models, time series models and computational intelligence methods are also briefly described. Numerical pollen forecast systems are especially challenging. The question, which of the models, regression or process-based models is superior, cannot yet be answered.

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-94-007-4881-1_8

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Abbreviations

AFEDA:

French Association for Ragweed Study

ANN:

Artificial Neural Networks

ARIMA:

Autoregressive Integrated Moving Average

AVHRR:

Advanced Very High Resolution Radiometer

CART:

Classification and Regression Trees

COST725:

COST Action 725: Establishing a European Phenological Data Platform for Climatological Applications

CAgM:

Commission for Agrometeorology

DEM:

Digital Elevation Model

DWD:

Deutscher Wetterdienst

EAN:

European Aeroallergen Network

ELISA:

Enzyme-linked Immunosorbent Assay

EUMETNET:

The Network of European Meteorological Services

GIMMS:

Global Inventory Modeling and Mapping Studies

IC:

Computational Intelligence

IAA:

International Association for Aerobiology

IBP:

International Biological Programme

INERIS:

Industrial Environment and Risks National Institute

IPG:

International Phenological Garden

Landsat TM:

Landsat Thematic Mapper, Satellite

LUT:

Look Up Table

MODIS:

Moderate Resolution Imaging Spectroradiometer

NDVI:

Normalised Difference Vegetation Index

NHMS:

National Hydrometeorological Services

NOAA:

National Oceanic and Atmospheric Administration

PCR:

Polymerase Chain Reaction

PEP725:

Pan European Phenological Database

PM:

Particulate Matter

RMSE:

Root Mean Square Error

SPOT:

Satellite Pour l’Observation de la Terre

SOM:

Self-Organising Maps

SVMs:

Support Vector Machines

TSM:

Temperature Sum Model

UM:

Use and Management of Biological Resources

WCDMP:

World Climate Data and Monitoring Programme

WCP:

World Climate Programme

WIBS:

Wide-Issue Bioaerosol Spectrometer

WMO:

World Meteorological Organisation

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Authors and Affiliations

  1. Zentralanstalt für Meteorologie und Geodynamik, Hohe Warte 38, 1190, Wien, Austria

    Helfried Scheifinger & Elisabeth Koch

  2. CREAF, Universidad Autónoma de Barcelona, 08193, Bellaterra, Spain

    Jordina Belmonte

  3. ZAUM - Center of Allergy & Environment, a joint institute of the Technische Universität München and Helmholtz Zentrum München, Biedersteiner Str. 29, 80802, Munich, Germany

    Jeroen Buters

  4. Science Faculty, Biology Department, Uludag University, Görükle, 16059, Bursa, Turkey

    Sevcan Celenk

  5. Department of Ecology, School of Biology, Aristotle University, GR-54124, Thessaloniki, Greece

    Athanasios Damialis & Despina Vokou

  6. Association Française d’Etude des Ambroisies: A F E D A, 25 Rue Ambroise Paré, F 69 800, Saint-Priest, France

    Chantal Dechamp

  7. Departamento de Biologia Vegetal, Campus de Rabanales, Universidad de Cordoba, 14071, Cordoba, Spain

    Herminia García-Mozo & Carmen Galán-Soldevilla

  8. Bio- and Environmental Meteorology, Climate Division, MeteoSchweiz, Krähbühlstr, 58, CH-8044, Zürich, Switzerland

    Regula Gehrig & Andreas Pauling

  9. Laboratory of Aeropalynology, Faculty of Biology, Adam Mickiewicz University, Umultowska 89, 61-614, Poznan, Poland

    Lukasz Grewling

  10. Department of Biological Applications and Technology, University of Ioannina, GR-45110, Ioannina, Greece

    John M. Halley

  11. NORUT ITEK, 6434, Forskningsparken, N-9294, Tromsø, Norway

    Kjell-Arild Hogda & Stein-Rune Karlsen

  12. HNO Klinik der Medizinischen Universität Wien, Währinger Gürtel 18-20, A-1090, Wien, Austria

    Siegfried Jäger & Matt Smith

  13. Informatics Applications and Systems Group, Faculty of Engineering, Aristotle University, Egnatia Str., 483, 54124, Thessaloniki, Greece

    Kostas Karatzas

  14. National Pollen and Aerobiology Research Unit, Institute of Health, University of Worcester, WR2 6AJ, Worcester, UK

    Roz Peel

  15. Laboratory for Palynology, Faculty of Sciences, University of Novi Sad, Trg Dositeja, Obradovica 2, 21000, Novi Sad, Serbia

    Branko Sikoparija

  16. Réseau National de Surveillance Aérobilogique, Chemin des Gardes, 8, F-69610, Saint Genis L’Argentière, France

    Michel Thibaudon

  17. Department of Pulmonology, Leiden University Medical Centre, 9600, 2300 RC, Leiden, The Netherlands

    Letty A. de Weger

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  1. Helfried Scheifinger
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  2. Jordina Belmonte
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  19. Matt Smith
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  20. Carmen Galán-Soldevilla
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  22. Despina Vokou
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  23. Letty A. de Weger
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Corresponding author

Correspondence to Helfried Scheifinger .

Editor information

Editors and Affiliations

  1. Erik Palmenin Aukio 1, Helsinki, 00561, Finland

    Mikhail Sofiev

  2. Foundation German Pollen Information Ser, Luisenstrasse 2, Berlin, 10117, Germany

    Karl-Christian Bergmann

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Scheifinger, H. et al. (2013). Monitoring, Modelling and Forecasting of the Pollen Season. In: Sofiev, M., Bergmann, KC. (eds) Allergenic Pollen. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4881-1_4

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