Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.

Back-trajectories Show Export of Airborne Fungal Spores (Ganoderma sp.) From Forests to Agricultural and Urban Areas in England

We propose here the hypothesis that all of United Kingdom (UK) is likely to be affected by Ganoderma sp. spores, an important plant pathogen. We suggest that the main sources of this pathogen, which acts as a bioaerosol, are the widely scattered woodlands in the country, although remote sources must not be neglected. The hypothesis is based on related studies on bioaerosols and supported by new observations from a non-forest site and model calculations to support our hypothesis. Hourly concentrations of Ganoderma sp. spores were measured from 2006 to 2010 using a 7-day volumetric spore trap at the city of Worcester. The concentrations peak during the night and early in the morning. This suggests that the main spore sources are located a few hours away with respect to air masses transport and reach urban areas thanks to air masses transport. The back-trajectory analysis was applied to determine the location of Ganoderma sp. spore sources. The analysis of back-trajectories demonstrated that 78% of the air masses reached Worcester from a 180° arc direction from the East to West. Three episodes were selected for detailed investigation and they revealed that during the episodes air masses always passed main UK woodlands before the arrival in Worcester, independently of their origin, but the long distance transport under certain conditions might be possible. Our studies suggest that the sources of UK Ganoderma sp. spores are mainly to be found in UK. Hence our studies suggest that research and mitigation strategies in UK should give their main attention to national sources, without neglecting the contribution from long distance transport.