This study analyses the spatial and temporal distribution of regional and long-range transported birch (Betula L.) pollen in Lithuania and the neighbouring countries. The potential long-range transport cases of birch pollen in Lithuania were analysed for the whole period of available observations, 2004-2007. The birch pollen was recorded at three measurement stations in Lithuania by using Hirst-type volumetric spore traps. The phenological observations in Lithuania were also used for the detection of potential long-range transport-induced episodes. Two variants of the regional and continental scale atmospheric dispersion model SILAM (Lagrangian and Eulerian) in an adjoint mode (used for inverse dispersion modelling and data assimilation), and the trajectory model HYSPLIT were employed to evaluate the source origins of the observed pollen. During four seasons in 2004-2007, we found in total 24 cases, during which remarkable pollen concentrations were recorded before the local flowering season. According to modelling, most of these were originated from the sources outside Lithuania: Latvia, southern Sweden, Denmark, Belarus, Ukraine and Moldova, possibly, also coastal regions of Germany and Poland. Two episodes were attributed to local early-flowering birch trees. The spatial and temporal patterns of the long-range transport of early pollen to Lithuania were found out to be highly variable; the predicted source regions for the cases considered were similar only for some dates in 2004 and 2006. During the analysed period, we found both cases, in which the predictions of the SILAM model variants and those of the HYSPLIT model were similar, and cases, in which there were substantial differences. In general, for complicated atmospheric circulation patterns the model predictions can be drastically different, with a tendency of trajectory model to fail reproducing the key episode features.

An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction.

To investigate airborne pollen movement aerobiologists use backward air mass trajectories. In the present paper the peculiarities of airborne birch pollen dispersion are analysed. In 2005 at Šiauliai Aerobiology Station pollen was recorded using Hirst‐type spore trap. The situation of birch bloom in neighbouring European countries was evaluated according to the European Aeroallergen Network database. It was generalized and used to prove long‐range pollen transport. Air mass trajectories were calculated according to the HYSPLIT 4 model the trajectory drawing principle of which is based on the integration of the position of air mass with regard to time. The present study has shown that backward air mass trajectory analysis may be applied in investigating relationship among pollen dispersion, meteorological conditions and air mass transport. It is estimated that at Šiauliai Aerobiology Station the dynamics of pollen concentration is determinated by local flora and airborne pollen long‐range transport. The evaluation of pollen dispersion by the backward air mass trajectory method presented in the paper established precondition to look for possibilities of application of the HYSPLIT 4 model to prepare the forecasts of pollen dispersion.

The scientists evaluate the climate change by various methods. The long‐term phonological observation is a quite significant indicator of this phenomenon. Moreover, the forecasting of plants flowering period or changing of amount of pollen production is important for guarantying of social health. The aim of the research ‐ to analyze the interdependence of flowering changes and pollen concentration under the climate change according to the long‐term phenological data and evaluation of aeropalynological situation in Lithuania. For this purpose one based upon the data of birch flowering (1970–1999) and birch flowering and pollen concentration in air (2004–2008). The interpretation of data with statistic methods showed that the start of birch flowering varies in different years (8–32 days) and the regional differences increase (approximately 3 days during 30 years). One phenological station does not reflect the real aerobiological situation in the observation site. Tight analysis of pollen and phenological data basing upon the flowering data allows gathering knowledge about possible change of the pollen seasons in future. Santrauka Klimato kaita mokslininkai vertina ivairiais metodais. Labai reikšmingas šio reiškinio indikatorius ‐ daugiamečiu fenologiniu stebejimu duomenys. Augalu žydejimo laiko ar žiedadulkiu produkcijos kiekio pokyčio prognozavimas yra svarbus visuomenes sveikatai užtikrinti. Tyrimo tikslas ‐ pagal ilgamečius fenologinius duomenis ir ivertinus aeropalinologine situacija Lietuvoje išanalizuoti žydejimo pokyčiu ir žiedadulkiu koncentracijos tarpusavio priklausomuma vykstant klimato kaitai. Šiam tikslui remtasi beržo žydejimo (1970–1999 m.) ir beržo žydejimo bei žiedadulkiu koncentracijos ore (2004–2008 m.) duomenimis. Duomenis interpretuojant statistiniais metodais nustatyta, kad beržo žydejimo pradžia ivairiais metais varijuoja (8–32 dienos), ir dideja regioniniai skirtumai (apytiksliai 3 dienos per 30 metu). Viena fenologine stotis neatspindi realios aerobiologines situacijos stebejimo vietoje. Glaudi žiedadulkiu ir fenologiniu duomenu analize, remiantis žydejimo duomenimis, leidžia daryti prielaidas apie galima žiedadulkiu sezonu kaita ateityje. Резюме Для оценки изменения климата ученые используют различные методы. Значительным показателем этого явления являются многолетние фенологические наблюдения. Кроме того, прогнозирование времени цветения или изменения продукции пыльцы растений является важным этапом в управлении здравоохранением. Целью нашего исследования было на основании многолетних фенологических наблюдений и оценки аеропалинологической ситуации в Литве проанализировать взаимосвязь между изменением цветения и концентрацией пыльцы в воздухе в связи с изменением климата. Для этой цели были использованы данные цветения березы за период 1970– 1999 гг., цветения березы и данные концентраций пыльцы в воздухе, охватывающие период 2004–2008 гг. Благодаря применению статистических методов для интепретаций данныx, было установлено, что началo цветения березы колеблется из года в год (8–32 дня), увеличиваются региональные различия (около 3 дней за 30 лет). Показано, что одна фенологическая станция не отражает реальную аеропалинологическую ситуацию. Сравнительный фенологический и пыльцевой анализ, проведенный на основании данных цветения, свидетельствуeт о возможныx измененияx в пыльцeвыx сезонаx в будущем.

The elements determining the meteorological conditions are the main parameters in processes of airborne pollen modeling. In modern research the influence of different meteorological element or their complex is analyzed basing upon the statistic methods or using dispersion models in which the possible influence of meteorological parameters upon airborne pollen is described in equations. The correlation of meteorological indicators and pollen concentration in the atmosphere fixed in Klaipėda Aerobiological Station is analyzed in this article. The coefficients of correlation of meteorological parameters and pollen concentration are calculated basing upon the Spearman's rank correlation method. The analysis of various factors was used for determining the complex influence of meteorological parameters upon the pollen concentration in the air. After evaluation of influence of meteorological parameters as separate factors one has determined that more than a half of analyzed pollen types showed statistically reliable (p < 0.05) correlation of pollen amount in the air and relative air humidity (89%), air temperature (74%) and amount of precipitation (52%). The investigation results showed that 37% of pollen amount of indicated plants genera and families in the atmosphere was determined by wind velocity. After evaluation of complex influence of meteorological factors on the concentration of pollen spread in the air one has determined that relative humidity and/or air temperature are one of the most significant environmental factors determining the amount of pollen in the atmosphere during the vegetation. Their influence was determined for all the three cases under study.