The Long Range Transport of Birch (Betula) Pollen from Poland and Germany Causes Significant Pre-season Concentrations in Denmark

Background Birch pollen is highly allergic and has the potential for episodically long range transport. Such episodes will in general occur out of the main pollen season. During that time allergy patients are unprotected and high pollen concentrations will therefore have a full allergenic impact. Objective To show that Denmark obtains significant quantities of birch pollen from Poland or Germany before the local trees start to flower. Methods Simultaneous observations of pollen concentrations and phenology in the potential source area in Poland as well as in Denmark were performed in 2006. The Danish pollen records from 2000-2006 were analysed for possible long range transport episodes and analysed with trajectories in combination with a birch tree source map. Results In 2006 high pollen concentrations were observed in Denmark with bi-hourly concentrations above 500 grains/ m3 before the local trees began to flower. Poland was identified as a source region. The analysis of the historical pollen record from Copenhagen shows significant pre-seasonal pollen episodes almost every year from 2000-2006. In all episodes trajectory analysis identified Germany or Poland as source regions. Conclusion Denmark obtains significant pre-seasonal quantities of birch pollen from either Poland or Germany almost every year. Forecasting of birch pollen quantities relevant to allergy patients must therefore take into account long-range transport. This cannot be based on measured concentrations in Denmark. The most effective way to improve the current Danish pollen forecasts is to extend the current forecasts with atmospheric transport models that take into account pollen emission and transport from countries such as Germany and Poland. Unless long range transport is taken into account pre-seasonal pollen episodes will have a full allergic impact, as the allergy patients in general will be unprotected during that time.

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.

Long-term and Short-term Forecast Models for Poaceae (Grass) Pollen in Poznan, Poland, Constructed Using Regression Analysis

Airborne concentrations of Poaceae pollen have been monitored in Poznań for more than ten years and the length of the dataset is now considered sufficient for statistical analysis. The objective of this paper is to produce long-range forecasts that predict certain characteristics of the grass pollen season (such as the start, peak and end dates of the grass pollen season) as well as short-term forecasts that predict daily variations in grass pollen counts for the next day or next few days throughout the main grass pollen season. The method of forecasting was regression analysis. Correlation analysis was used to examine the relationship between grass pollen counts and the factors that affect its production, release and dispersal. The models were constructed with data from 1994-2004 and tested on data from 2005 and 2006. The forecast models predicted the start of the grass pollen season to within 2 days and achieved 61% and 70% accuracy on a scale of 1-4 when forecasting variations in daily grass pollen counts in 2005 and 2006 respectively. This study has emphasised how important the weather during the few weeks or months preceding pollination is to grass pollen production, and draws attention to the importance of considering large-scale patterns of climate variability (indices of the North Atlantic Oscillation) when constructing forecast models for allergenic pollen.

Identification of Potential Sources of Airborne Olea Pollen in the Southwest Iberian Peninsula

This study aims to determine the potential origin of Olea pollen recorded in Badajoz in the Southwest of the Iberian Peninsula during 2009–2011. This was achieved using a combination of daily average and diurnal (hourly) airborne Olea pollen counts recorded at Badajoz (south-western Spain) and Évora (south-eastern Portugal), an inventory of olive groves in the studied area and air mass trajectory calculations computed using the HYSPLIT model. Examining olive pollen episodes at Badajoz that had distinctly different diurnal cycles in olive pollen in relation to the mean, allowed us to identify three different scenarios where olive pollen can be transported to the city from either distant or nearby sources during conditions with slow air mass movements. Back trajectory analysis showed that olive pollen can be transported to Badajoz from the West on prevailing winds, either directly or on slow moving air masses, and from high densities of olive groves situated to the Southeast (e.g. Andalucía). Regional scale transport of olive pollen can result in increased nighttime concentrations of this important aeroallergen. This could be particularly important in Mediterranean countries where people can be outdoors during this time due to climate and lifestyle. Such studies that examine sources and the atmospheric transport of pollen are valuable for allergy sufferers and health care professionals because the information can be incorporated into forecasts, the outputs of which are used for avoiding exposure to aeroallergens and planning medication. The results of studies of this nature can also be used for examining gene flow in this important agricultural crop.

Application of WRF-Chem to Forecasting PM10 Concentration over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains using the GFS meteorological data and the TNO MACC II emissions. Forecasts, with 48h lead time, were run for a winter and summer period 2014. WRF-Chem in general captures the variability in observed PM10 concentrations, but underestimates some peak concentrations during winter-time. The peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. Such episodes lead to increased combustion in residential heating, where hard coal is the main fuel in Poland. This suggests that a key to improvement in the model performance for the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Chem.

Application of the WRF-Chem Model for a High Ozone Episode in SW Poland – Preliminary Results

The Weather Research and Forecasting model, integrated online with chemistry module, is a multi-scale model suitable for both research and operational forecasts of meteorology and air quality. It is used by many institutions for a variety of applications. In this study, the WRF v3.5 with chemistry (WRF-Chem) is applied to the area of Poland, for a period of 3-20 July 2006, when high concentrations of ground level ozone were observed. The meteorological and chemistry simulations were initiated with ERA-Interim reanalysis and TNO MACC II emissions database, respectively. The model physical parameterization includes RRTM shortwave radiation, Kain-Fritsch cumulus scheme, Purdue Lin microphysics and ACM2 PBL, established previously as the optimal configuration. Chemical mechanism used for the study was RADM2 with MADE/SORGAM aerosols. Simulations were performed for three one-way nested domains covering Europe (36 km x 36 km), Central Europe (12 km x 12 km) and Poland (4 km x 4 km). The results from the innermost domain were analyzed and compared to measurements of ozone concentration at three stations in different environments. The results show underestimation of observed values and daily amplitude of ozone concentrations.