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Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom

International Journal of Biometeorology volume 58, pages 529–545 (2014)Cite this article

Abstract

Constructing accurate predictive models for grass and birch pollen in the air, the two most important aeroallergens, for areas with variable climate conditions such as the United Kingdom, require better understanding of the relationships between pollen count in the air and meteorological variables. Variations in daily birch and grass pollen counts and their relationship with daily meteorological variables were investigated for nine pollen monitoring sites for the period 2000–2010 in the United Kingdom. An active pollen count sampling method was employed at each of the monitoring stations to sample pollen from the atmosphere. The mechanism of this method is based on the volumetric spore traps of Hirst design (Hirst in Ann Appl Biol 39(2):257–265, 1952). The pollen season (start date, finish date) for grass and birch were determined using a first derivative method. Meteorological variables such as daily rainfall; maximum, minimum and average temperatures; cumulative sum of Sunshine duration; wind speed; and relative humidity were related to the grass and birch pollen counts for the pre-peak, post peak and the entire pollen season. The meteorological variables were correlated with the pollen count data for the following temporal supports: same-day, 1-day prior, 1-day mean prior, 3-day mean prior, 7-day mean prior. The direction of influence (positive/negative) of meteorological variables on pollen count varied for birch and grass, and also varied when the pollen season was treated as a whole season, or was segmented into the pre-peak and post-peak seasons. Maximum temperature, sunshine duration and rainfall were the most important variables influencing the count of grass pollen in the atmosphere. Both maximum temperature (pre-peak) and sunshine produced a strong positive correlation, and rain produced a strong negative correlation with grass pollen count in the air. Similarly, average temperature, wind speed and rainfall were the most important variables influencing the count of birch pollen in the air. Both wind speed and rain produced a negative correlation with birch pollen count in the air and average temperature produced a positive correlation.

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Acknowledgements

The authors would like to thank the National Pollen and Aerobiology Research Unit (NPARU) of the University of Worcester for providing pollen count data. We are also grateful to: (i) The Queen’s University Belfast pollen monitoring group, coordinated by Dr Chris Hunt for collecting and compiling the pollen count data at the Belfast site, (ii) Miss Ursula Allitt for collecting and compiling pollen count data at the Cambridge site, ( iii) The Cardiff School of Health Sciences, Cardiff Metropolitan University for collecting and compiling pollen count data at the Cardiff site, (iv) Peter and The David Hide Asthma and Allergy Research Centre, St Mary’s Hospital, Newport, Isle of Wight, PO30 5TG for collecting and compiling pollen count data at the Isle of Wight site, and (v) Dr Gavin Ramsay for collecting and compiling the pollen count data at Invergowrie (near Dundee) site. The authors are also grateful to the UK Meteorological Office for making the time-series weather parameters available through the Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current) database. And the last but not the least we are grateful to (BADC) British Atmospheric Data Centre, which is part of the NERC National Centre for Atmospheric Science (NCAS), for providing access to this data via http://badc.nerc.ac.uk/view/badc.nerc.ac.uk__ATOM__dataent_ukmo-midas. Finally, we would like to thank the Kurdistan Regional Government (KRG) for providing funding through a PhD studentship to NK.

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Authors and Affiliations

  1. Global Environmental Change and Earth Observation Research Group, Geography and Environment, University of Southampton, Highfield, Southampton, SO17 1BJ, UK

    Nabaz Khwarahm, Jadunandan Dash & Peter M. Atkinson

  2. School of Geography, Environment & Earth Sciences, Victoria University of Wellington, PO Box 600, Wellington, New Zealand

    R. M. Newnham

  3. National Pollen and Aerobiology Research Unit, University of Worcester, Henwick Grove, Worcester, WR2 6AJ, UK

    C. A. Skjøth & B. Adams-Groom

  4. Scottish Centre for Pollen Studies, School of Life Science, Edinburgh Napier University, Edinburgh, UK

    Eric Caulton

  5. School of Geography, Earth & Environmental Sciences, University of Plymouth, Plymouth, UK

    K. Head

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  1. Nabaz Khwarahm
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  2. Jadunandan Dash
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  3. Peter M. Atkinson
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  4. R. M. Newnham
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  5. C. A. Skjøth
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  6. B. Adams-Groom
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  7. Eric Caulton
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Correspondence to Nabaz Khwarahm.

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Khwarahm, N., Dash, J., Atkinson, P.M. et al. Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom. Int J Biometeorol 58, 529–545 (2014). https://doi.org/10.1007/s00484-013-0739-7

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  • DOI: https://doi.org/10.1007/s00484-013-0739-7

Keywords

  • Hay fever
  • Grass pollen
  • Birch pollen
  • Predicting model
  • Phenology
  • Meteorological variable