Małgorzata Puc

Artificial neural network model of the relationship between Betula pollen and meteorological factors in Szczecin (Poland)

Birch pollen is one of the main causes of allergy during spring and early summer in northern and central Europe. The aim of this study was to create a forecast model that can accurately predict daily average concentrations of Betula sp. pollen grains in the atmosphere of Szczecin, Poland. In order to achieve this, a novel data analysis technique—artificial neural networks (ANN)—was used. Sampling was carried out using a volumetric spore trap of the Hirst design in Szczecin during 2003–2009. Spearman’s rank correlation analysis revealed that humidity had a strong negative correlation with Betula pollen concentrations. Significant positive correlations were observed for maximum temperature, average temperature, minimum temperature and precipitation. The ANN resulted in multilayer perceptrons 366 8: 2928-7-1:1, time series prediction was of quite high accuracy (SD Ratio between 0.3 and 0.5, R > 0.85). Direct comparison of the observed and calculated values confirmed good performance of the model and its ability to recreate most of the variation.

Threat of allergenic airborne grass pollen in Szczecin, NW Poland: the dynamics of pollen seasons, effect of meteorological variables and air pollution

The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004–2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM10 and SO2 was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy.

Forecasting model of Corylus, Alnus, and Betula pollen concentration levels using spatiotemporal correlation properties of pollen count

The aim of the study was to create and evaluate models for predicting high levels of daily pollen concentration of Corylus, Alnus, and Betula using a spatiotemporal correlation of pollen count. For each taxon, a high pollen count level was established according to the first allergy symptoms during exposure. The dataset was divided into a training set and a test set, using a stratified random split. For each taxon and city, the model was built using a random forest method. Corylus models performed poorly. However, the study revealed the possibility of predicting with substantial accuracy the occurrence of days with high pollen concentrations of Alnus and Betula using past pollen count data from monitoring sites. These results can be used for building (1) simpler models, which require data only from aerobiological monitoring sites, and (2) combined meteorological and aerobiological models for predicting high levels of pollen concentration.

Poaceae, Secale spp. and Artemisia spp. pollen in the air at two sites of different degrees of urbanisation

INTRODUCTION Among herbal plants, most cases of allergic reactions, like seasonal inflammation of nasal mucosa, conjunctivitis and pollen asthma, are related to the allergens from grass pollen. As the blossoming and pollination of rye is known to start the pollen season of grasses, information about the airborne rye pollen count permits alerting the people allergic to certain allergens contained in rye pollen. An important cause of allergy is also the pollen from wormwood, blossoming in late summer, as its two main allergens produce cross-reactions with many other plant allergens. OBJECTIVE The aim of the study was to evaluate the risk of allergic reactions in persons with pollinosis on the basis of the pollen calendar, analysis of concentrations of pollen grains of grass and rye, and comparison of diurnal pattern of airborne pollen grain concentrations at two sites with different degrees of urbanisation (Gudowo in the country and the city of Szczecin) in 2012-2014. MATERIALS AND METHODS The concentration of pollen was measured by the volume method. Length of the pollination season was determined by the method of 98%, assuming that the beginning and the end of the pollen season are the days on which 1% and 99% of the annual sum of pollen appeared. RESULTS The first pollen grains to appear in the air are those produced by rye, followed by those produced by grass and wormwood. The pollen seasons of grasses and wormwood started about one week earlier in Gudowo than in Szczecin, while the pollen season of rye started at almost the same time in the country and in the city. Airborne pollen counts of grasses, rye and wormwood were much higher in the country than in the city. The differences most probably result from the different floristic composition at these two sites and reflect the local contribution of the taxa studied in the country. CONCLUSIONS The risk of allergy caused by the pollen of the taxa analysed was much higher in Gudowo (in the country), than in Szczecin city.