The pollen season dynamics and the relationship among some season parameters (start, end, annual total, season phases) in Kraków, Poland, 1991–2008

The dynamics of 15 taxa pollen seasons in Kraków, in 1991–2008 was monitored using a Burkard volumetric spore trap of the Hirst design. The highest daily pollen concentrations were achieved in the first half of May, and they were caused mainly by Betula and Pinus pollen. The second period of the high concentrations took place from the middle of July to the end of August (mainly Urtica pollen). Tree pollen seasons were shorter (18–24 days) in comparison with the most herbaceous pollen seasons (73–89 days), except at Artemisia and Ambrosia seasons (30 and 24 days, respectively). The season phases (percentyles) of the spring and late-summer taxa were the most variable in the consecutive years. The highest annual sums were noted for Urtica, Poaceae (herbaceous pollen seasons) and for Betula, Pinus, Alnus (tree pollen seasons), and the highest variability of annual totals was stated for Urtica, Populus, Fraxinus and the lowest for Ambrosia, Corylus, Poaceae. For the plants that pollinate in the middle of the pollen season (Quercus, Pinus and Rumex), the date of the season start seems not to be related to the season end, while for late pollen seasons, especially for Ambrosia and Artemisia, the statistically negative correlation between the start and the end season dates was found. Additionally, for the most studied taxa, the increase in annual pollen totals was observed. The presented results could be useful for the allergological practice and general botanical knowledge

Risk of Exposure to Airborne Ambrosia Pollen from Local and Distant Sources in Europe – an Example from Denmark

Background. Ambrosia artemisiifolia L. is a noxious invasive alien species in Europe. It is an important aeroallergen and millions of people are exposed to its pollen. Objective. The main aim of this study is to show that atmospheric concentrations of Ambrosia pollen recorded in Denmark can be derived from local or more distant sources. Methods. This was achieved by using a combination of pollen measurements, air mass trajectory calculations using the HYPLIT model and mapping all known Ambrosia locations in Denmark and relating them to land cover types. Results. The annual pollen index recorded in Copenhagen during a 15-year period varied from a few pollen grains to more than 100. Since 2005, small quantities of Ambrosia pollen has been observed in the air every year. We have demonstrated, through a combination of Lagrangian back-trajectory calculations and atmospheric pollen measurements, that pollen arrived in Denmark via long-distance transport from centres of Ambrosia infection, such as the Pannonian Plain and Ukraine. Combining observations with results from a local scale dispersion model show that it is possible that Ambrosia pollen could be derived from local sources identified within Denmark. Conclusions. The high allergenic capacity of Ambrosia pollen means that only small amounts of pollen are relevant for allergy sufferers, and just a few plants will be sufficient to produce enough pollen to affect pollen allergy sufferers within a short distance from the source. It is necessary to adopt control measures to restrict Ambrosia numbers. Recommendations for the removal of all Ambrosia plants can effectively reduce the amount of local pollen, as long as the population of Ambrosia plants is small

Temporal and spatiotemporal autocorrelation of daily concentrations of Alnus, Betula, and Corylus pollen in Poland

The aim of the study was to determine the characteristics of temporal and space–time autocorrelation of pollen counts of Alnus, Betula, and Corylus in the air of eight cities in Poland. Daily average pollen concentrations were monitored over 8 years (2001–2005 and 2009–2011) using Hirst-designed volumetric spore traps. The spatial and temporal coherence of data was investigated using the autocorrelation and cross-correlation functions. The calculation and mathematical modelling of 61 correlograms were performed for up to 25 days back. The study revealed an association between temporal variations in Alnus, Betula, and Corylus pollen counts in Poland and three main groups of factors such as: (1) air mass exchange after the passage of a single weather front (30–40 % of pollen count variation); (2) long-lasting factors (50–60 %); and (3) random factors, including diurnal variations and measurements errors (10 %). These results can help to improve the quality of forecasting models

Alternaria Spores in the Air Across Europe: Abundance, Seasonality and Relationships with Climate, Meteorology and Local Environment

We explored the temporal and spatial variations in airborne Alternaria spore quantitative and phenological features in Europe using 23 sites with annual time series between 3 and 15 years. The study covers seven countries and four of the main biogeographical regions in Europe. The observations were obtained with Hirst-type spore traps providing time series with daily records. Site locations extend from Spain in the south to Denmark in the north and from England in the West to Poland in the East. The study is therefore the largest assessment ever carried out for Europe concerning Alternaria. Aerobiological data were investigated for temporal and spatial patterns in their start and peak season dates and their spore indices. Moreover, the effects of climate were checked using meteorological data for the same period, using a crop growth model. We found that local climate, vegetation patterns and management of landscape are governing parameters for the overall spore concentration, while the annual variations caused by weather are of secondary importance but should not be neglected. The start of the Alternaria spore season varies by several months in Europe, but the peak of the season is more synchronised in central northern Europe in the middle of the summer, while many southern sites have peak dates either earlier or later than northern Europe. The use of a crop growth model to explain the start and peak of season suggests that such methods could be useful to describe Alternaria seasonality in areas with no available observations

Predicting tree pollen season start dates using thermal conditions

Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data of Alnus, Corylus and Betula were obtained in 1991–2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (for Alnus and Corylus) and mean (for Betula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991–2010

The phenology of winter rye in Poland: an analysis of long-term experimental data

The study of the phenology of crops, although quite popular, has limitations, mainly because of frequent changes to crop varieties and management practices. Here, we present data on the phenology and yield of winter rye in western Poland collected between 1957 and 2012 from a long-term field experiment. Data were examined for trends through time and compared to climatological factors using regression analysis. Both annual air temperature and precipitation increased during the study period, equivalent to 2 °C and 186 mm, respectively, over the 52-year period for which met data were available. We detected significant delays in sowing date and recently in emergence, but significant advances were apparent in full flowering date equivalent to 4 days/decade. Yield and plant density experienced a step like change in 1986; yield increasing by ca. 70 % and plant density increasing by ca. 50 %, almost coinciding with a similar change in annual mean temperature, but most likely caused by a changed seed rate and use of herbicides. Future climate change is expected to have a greater impact on this crop, but farmers may be able to adapt to these changes by modifying water regimes, using new machinery and sowing new rye varieties

Extension of WRF-Chem for birch pollen modelling – a case study for Poland.

In recent years, allergies due to airborne pollen have shown an increasing trend, along with the severity of allergic symptoms in most industrialised countries, while synergism with other common atmospheric pollutants has also been identified as affecting the overall quality of citizenly’ life. In this study we propose the state-of-the-art WRF-Chem model, which is a complex Eulerian meteorological model integrated on-line with atmospheric chemistry. We used a combination of the WRF-Chem extended towards birch pollen, and the emission module based on heating degree days, which has not been tested before. The simulations were run for the moderate season in terms of birch pollen concentrations (year 2015) and high season (year 2016) over Central Europe, which were validated against 11 observational stations located in Poland. The results show that there is a big difference in the model’s performance for the two modelled years. In general, the model overestimates birch pollen concentrations for the moderate season and highly underestimates birch pollen concentrations for the year 2016. The model was able to predict birch pollen concentrations for first allergy symptoms (above 20 pollen m-3) as well as for severe symptoms (above 90 pollen m-3) with Probability of Detection at 0.78 and 0.68 and Success Ratio at 0.75 and 0.57, respectively for the year 2015. However, the model failed to reproduce these parameters for the year 2016. The results indicate the potential role of correcting the total seasonal pollen emission in improving the model’s performance, especially for specific years in terms of pollen productivity. The application of chemical transport models such as WRF-Chem for pollen modelling provides a great opportunity for simultaneous simulations of chemical air pollution and allergic pollen with one goal, which is a step forward for studying and understanding the co-exposure of these particles in the air