Several airborne fungal spores, such as Alternaria and Epicoccum, are known for their allergenic potential, yet accurately predicting their atmospheric concentrations remains a challenge. This study presents predictive models for estimating daily concentrations and clinically relevant threshold exceedance events of Alternaria and Epicoccum spores, using long-term aerobiological and meteorological data from five cities in Central Europe. Key meteorological predictors, including time-lagged variables, were identified for each location, and interpretable lasso linear and lasso logistic regression models were developed to forecast spore levels up to seven days in advance. The lasso logistic models achieved high accuracy in threshold exceedance predictions, with F1 scores reaching up to 88.6% for Epicoccum. While lasso linear models effectively captured seasonal patterns and timing, they tended to underestimate peak concentrations, likely due to the sporadic nature of spore release events. Notably, this is the first predictive model developed for Epicoccum, underscoring the need for clinical validation of allergological thresholds. Regional variability in model performance highlights the importance of local calibration and sustained aerobiological monitoring. These models offer a promising foundation for operational spore forecasting systems, supporting both public health advisories and agricultural decision-making.

Airborne pollen of the Poaceae family is a major trigger of seasonal allergic diseases in Europe, yet its prediction remains challenging due to strong spatial variability and complex environmental controls. This study developed and evaluated predictive models of daily Poaceae pollen concentrations across eight Central European cities representing diverse climatic and geomorphological conditions. Using long-term aerobiological and meteorological data, we applied lasso-penalised logistic regression to forecast exceedance of three clinically relevant thresholds (>10, >20, and >30 pollen/m & sup3;) and a two-stage lasso approach to estimate continuous pollen concentrations up to seven days in advance. Significant differences in seasonal intensity were observed, with the highest annual pollen integrals recorded in Bansk & aacute; Bystrica, likely reflecting local land use and topography. Threshold exceedance models performed best at the lowest threshold (>10 pollen/m & sup3;) and at sites with pronounced local source influence. Continuous concentration models improved upon a persistence baseline by 2.9-21.4% in mean absolute error but consistently underestimated peak values due to log-normal regression properties. Meteorological predictors, especially temperature and sunshine duration, were associated with pollen dynamics, although their added predictive value beyond seasonal structure proved limited and site-dependent, with optimal lag structures varying by location. The results highlight the necessity of site-specific modelling and demonstrate that combining threshold-based and continuous approaches provides a practical framework for operational pollen forecasting. The key novelty lies in the systematic, harmonised evaluation of both modelling approaches across eight stations with diverse bioclimatic and land-use settings, covering three clinically relevant thresholds and seven forecast horizons.

Climate change is altering the flowering phenology of allergenic trees, with growing implications for human health and ecosystems. In Central Europe, Alnus, Corylus, and Betula (Betulaceae) are key spring-flowering taxa and major sources of airborne allergens. This study integrates long-term airborne pollen records to: (i) detect long-term trends in the start of main pollen seasons across five cities in Slovakia and the Czech Republic, (ii) fit phenological models to predict pollen exposure with the PhenoFlex model, and (iii) project future flowering shifts under two climate scenarios (SSP2-4.5 and SSP5-8.5). Our results reveal a significant advancement in Alnus and Corylus flowering, while Betula shows no clear trend. Projections suggest that warming will accelerate flowering in Betula but may delay or reverse current trends in Alnus and Corylus due to disrupted chilling accumulation. By integrating this model with aerobiological data, this study offers critical insights for allergen forecasting, urban greenery planning, and climate adaptation strategies in a region with limited prior coverage.

Ambrosia artemisiifolia is a climate-sensitive invasive species whose airborne pollen constitutes a major allergenic burden across Central Europe. Operational forecasting is constrained by monitoring system design: conventional Hirst-type samplers involve processing delays that preclude real-time data availability, whereas automated systems provide near-instantaneous data. This study evaluates exceedance-based forecasting under these two paradigms across eight urban sites in Slovakia and the Czech Republic, spanning a gradient from high to minimal ragweed abundance. The real-time scenario was simulated by assuming immediate availability of Hirst-type data rather than using measurements from automated pollen monitors. Four elastic net-penalised logistic regression models incorporating seasonal, meteorological, and Ambrosia pollen history predictors were evaluated across forecast horizons of 1-7 days using an expanding window cross-validation. Exceedance thresholds were 20 pollen/m3 (Slovak sites) and 5 pollen/m3 (Czech sites). Forecast performance was strongly governed by exceedance prevalence. At Slovak sites (prevalence 8-17%), the best real-time models generally achieved higher F1 scores at a 1-day horizon (0.67-0.82) than the best delayed-reporting models (0.59-0.72). At Czech sites (prevalence below 3%), F1 scores rarely exceeded 0.30, and sensitivity was a more informative metric under severe class imbalance. The real-time advantage diminished progressively with forecast horizon, converging towards delayed-reporting performance at day 7. Sunshine duration and maximum temperature were the most consistently positive predictors, relative humidity was predominantly positive across most sites, whereas precipitation and wind speed showed weaker, less consistent associations. These findings provide a transferable framework for ragweed pollen early warning systems adaptable to heterogeneous monitoring infrastructure.

Climate change is affecting the timing and intensity of pollen seasons for allergenic plant species. This creates a growing need to monitor pollen season trends and update tools for allergy management. In this study, we analysed pollen season characteristics – onset, end, duration, and intensity (seasonal pollen integral and peak pollen concentration) – over a 20-year period (2002–2023) in five cities across Slovakia and the Czech Republic. By comparing two timeframes (2002–2012 and 2013–2023), we constructed progressive pollen calendars to visualise the shifts over time. We identified regional differences, including an earlier start to woody plant pollen seasons in Slovak cities, contrasted with a delayed onset in Czech cities. We also observed an intensification of the Ambrosia pollen season in Slovakia, while its intensity remained stable or declined in the Czech Republic. The most consistent trends included earlier and extended pollen seasons for Alnus and Cupressaceae and a reduced intensity of the Artemisia pollen season. These findings highlight the importance of localised pollen monitoring and the need to regularly update pollen calendars, providing valuable tools for urban healthcare planning and public awareness of climate-driven allergenic risks.

The dataset presents a 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980-2022. The model applied an extended 4-dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen production. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related applications.

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant’s reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating annual total pollen concentrations than those of the GM approach. These are the first published modeled maps using altitude correction and phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.

The sooty bark disease (SBD) is an emerging disease affecting sycamore maple trees (Acer pseudoplatanus) in Europe. Cryptostroma corticale, the causal agent, putatively native to eastern North America, can be also pathogenic for humans causing pneumonitis. It was first detected in 1945 in Europe, with markedly increasing reports since 2000. Pathogen development appears to be linked to heat waves and drought episodes. Here, we analyse the conditions of the SBD emergence in Europe based on a three-decadal time-series data set. We also assess the suitability of aerobiological samples using a species-specific quantitative PCR assay to inform the epidemiology of C. corticale, through a regional study in France comparing two-year aerobiological and epidemiological data, and a continental study including 12 air samplers from six countries (Czechia, France, Italy, Portugal, Sweden and Switzerland). We found that an accumulated water deficit in spring and summer lower than -132 mm correlates with SBD outbreaks. Our results suggest that C. corticale is an efficient airborne pathogen which can disperse its conidia as far as 310 km from the site of the closest disease outbreak. Aerobiology of C. corticale followed the SBD distribution in Europe. Pathogen detection was high in countries within the host native area and with longer disease presence, such as France, Switzerland and Czech Republic, and sporadic in Italy, where the pathogen was reported just once. The pathogen was absent in samples from Portugal and Sweden, where the disease has not been reported yet. We conclude that aerobiological surveillance can inform the spatial distribution of the SBD, and contribute to early detection in pathogen-free countries.

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we have developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant's reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating seasonal pollen integrals than those of the GM approach. These are the first published modelled maps using altitude correction and flowering phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.

Alternaria spores are pathogenic to agricultural crops, and the longest and the most severe sporulation seasons are predominantly recorded in rural areas, e.g. the Pannonian Plain (PP) in South-Central Europe. In Poland (Central Europe), airborne Alternaria spore concentrations peak between July and August. In this study, we test the hypothesis that the PP is the source of Alternaria spores recorded in Poland after the main sporulation season (September-October). Airborne Alternaria spores (2005-2019) were collected using volumetric Hirst spore traps located in 38 locations along the potential pathways of air masses, i.e. from Serbia, Romania and Hungary, through the Czech Republic, Slovakia and Ukraine, to Northern Poland. Three potential episodes of Long Distance Transport (LDT) were selected and characterized in detail, including the analysis of Alternaria spore data, back trajectory analysis, dispersal modelling, and description of local weather and mesoscale synoptic conditions. During selected episodes, increases in Alternaria spore concentrations in Poznań were recorded at unusual times that deviated from the typical diurnal pattern, i.e. at night or during morning hours. Alternaria spore concentrations on the PP were very high (>1000 spores/m3) at that time. The presence of non-local Ambrosia pollen, common to the PP, were also observed in the air. Air mass trajectory analysis and dispersal modelling showed that the northwest part of the PP, north of the Transdanubian Mountains, was the potential source area of Alternaria spores. Our results show that Alternaria spores are transported over long distances from the PP to Poland. These spores may markedly increase local exposure to Alternaria spores in the receptor area and pose a risk to both human and plant health. Alternaria spores followed the same atmospheric route as previously described LDT ragweed pollen, revealing the existence of an atmospheric super highway that transports bioaerosols from the south to the north of Europe.

Pollen seasons progress differently in their timing, course, and intensity in different countries/biogeographical regions depending on regional factors such as vegetation, elevation, urbanization, and others. The variable regional situation often provides obstacles for a standard season definition.1 The season definition of the European Academy of Allergy and Clinical Immunology (EAACI) was published as a pollen concentration season definition depending on the selected pollen type reaching a certain threshold after a certain period of consecutive days,2, 3 and it was demonstrated that they can be correlated with pollen-induced symptom loads.4 The season definition was developed for studies with a medical framework, particularly to allow a prospective approach. However, pollen concentrations do not reach the same level in Europe or globally and affect persons concerned differently.5 Therefore, there is a strong need to expand the scope of application of the EAACI season definition to a retrospective approach if the standard season definition criteria are not met within the site selection or during a clinical trial. Hence, we tried to transfer the EAACI season definition criteria into a percentage definition (EAACI%) for birch and grasses in a first approach herein to include areas where the pollen concentrations do not meet the criteria of the EAACI season definition or small gaps in the data record prevent an EAACI season definition result. For this “backup” season definition, ten pollen monitoring stations across central and eastern Europe were used as the calculation basis for transforming the EAACI season definition. A cumulative relative pollen concentration ( r d ) was calculated for the start, end and peak days of the standard EAACI season definition applying the following formula: r d = ∑ i = 1 d p i ∑ i = 1 365 p i . Summarized, the cumulative pollen concentration ( p i ) from the first day of the year to day d is divided by the yearly total sum of the respective pollen type. For further optimization, these values were calculated for all sites, pollen types, and years to minimize the mean absolute deviation in comparison with the standard EAACI definition. This calculation results in four percentage values ( v) per pollen type, which define the start and the end of the (peak) pollen season. If the relative cumulative pollen concentration exceeds one of the thresholds ( v), the respective date marks the (peak) pollen season start/end of the EAACI% definition. For the result validation, the difference in the season's duration was compared with each of the definitions applied (Table 1). Main season start ( v a , 1 ) Main season end ( v a , 2 ) Peak season start ( v a , 3 ) Peak season end ( v a , 4 ) Birch ( v b , s ) v b , 1 = 0.013 2 (1–2 days) v b , 2 = 0.968 6.4 (2–10 days) v b , 3 = 0.081 1.8 (1–3 days) v b , 4 = 0.868 3.1 (1–5 days) Grass ( v g , s ) v g , 1 = 0.016 4.7 (2–6 days) v g , 2 = 0.962 13.2 (5–21 days) v g , 3 = 0.182 3.6 (1–7 days) v g , 4 = 0.683 7.4 (2–13 days) Additional information regarding the methodology and results as well as a calculation example can be found in the Appendix S1. To evaluate the EAACI% season definition, the Austrian pollen monitoring site of Tamsweg (ATTAMS) was selected as an experimental station to compare both season definitions and to test the application to data, where the EAACI season definition fails (Figure 1). This first attempt demonstrates that the EAACI season definition criteria could successfully be converted into a percentage definition. We recommend using the herein described EAACI% season definition for predictive assistance in site selection or retrospective analysis in sites/countries where the EAACI season definition could not be applied during an ongoing trial. This transformed definition allows an accurate assessment of the pollen season using EAACI criteria in terms of start and end of the pollen season where the EAACI season definition would fail. A moving average season definition usually used in trend analysis, could improve the results of this definition in the future approaches.6 Taking together this calculation may be helpful in trial regions of interest with low pollen concentrations, an exceptional less intense season, or other possible obstacles for pollen concentration-based season definitions. However, further validation with clinical data from hayfever patients is needed. The authors want to thank Christoph Jäger, who takes care of the data base and the data of the European Aeroallergen Network (EAN) from a technical point of view. In addition, the authors want to thank Alexander Kowarik for supporting the study with the statistical analyses. All authors declare no conflicts of interest. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

In 2016, the highest birch ( Betula spp.) pollen concentrations were recorded in Kraków (Poland) since the beginning of pollen observations in 1991. The aim of this study was to ascertain the reason for this phenomenon, taking the local sources of pollen in Poland and long-range transport (LRT) episodes associated with the pollen influx from other European countries into account. Three periods of higher pollen concentrations in Kraków in 2016 were investigated with the use of pollen data, phenological data, meteorological data and the HYSPLIT numerical model to calculate trajectories up to 4 days back (96 h) at the selected Polish sites. From 5 to 8 April, the birch pollen concentrations increased in Kraków up to 4000 Pollen/m 3 , although no full flowering of birch trees in the city was observed. The synoptic situation with air masses advection from the South as well as backward trajectories and the general birch pollen occurrence in Europe confirm that pollen was transported mainly from Serbia, Hungary, Austria, the Czech Republic, Slovakia, into Poland. The second analyzed period (13–14 April) was related largely to the local flowering of birches, while the third one in May (6–7 May) mostly resulted from the birch pollen transport from Fennoscandia and the Baltic countries. Unusual high pollen concentrations at the beginning of the pollen season can augment the symptomatic burden of birch pollen allergy sufferers and should be considered during therapy. Such incidents also affect the estimation of pollen seasons timing and severity. Graphical Abstract

High Ambrosia pollen concentrations in Poland rather rarely come from the local sources. The aim of this study was to define the temporal and spatial differences of the high Ambrosia pollen concentrations by creating models for the pollen transport from the distant sources. This study was thought to determine the direction of the air masses inflow into Poland, carrying Ambrosia pollen, from areas of the bordering countries with the pollen concentrations higher than iSTOTEN_n Poland. Pollen and meteorological datasets at 8 monitoring sites in Poland, and daily pollen concentrations at 11 sites in the Czech Republic, 5 sites in Slovakia and 3 sites in Ukraine were analysed recently. Days with concentrations >= 10 Pollen/m(3) and concurrent meteorological situations were analysed in great deal. The HYSPLIT model was applied to compute backward trajectories up to 4 days backward (96 h) and at three altitudes: 20, 500 and 1000 m above ground level (a.g.l.). High pollen concentrations occur most frequently when the air masses inflow into Poland from southerly (S, SE, SW, 44%) and easterly (E, 6%) directions and in no advection situations (25%). In years with the highest frequency of days over 10 Pollen/m3, the prevailing directions of the pollen influx into Poland were from the South (2004-2006, 2008, 2011) but in one year (2014) from the East. Trajectories for the studied period show that air masses come most frequently from Slovakia and the Czech Republic. Sometimes, the Ambrosia pollen transport happens from Ukraine. (c) 2020 Elsevier B.V. All rights reserved.

The drivers of spatial variation in ragweed pollen concentrations, contributing to severe allergic rhinitis and asthma, are poorly quantified. We analysed the spatiotemporal variability in 16-year (1995–2010) annual total (66 stations) and annual total (2010) (162 stations) ragweed pollen counts and 8 independent variables (start, end and duration of the ragweed pollen season, maximum daily and calendar day of the maximum daily ragweed pollen counts, last frost day in spring, first frost day in fall and duration of the frost-free period) for Europe (16 years, 1995–2010) as a function of geographical coordinates. Then annual total pollen counts, annual daily peak pollen counts and date of this peak were regressed against frost-related variables, daily mean temperatures and daily precipitation amounts. To achieve this, we assembled the largest ragweed pollen data set to date for Europe. The dependence of the annual total ragweed pollen counts and the eight independent variables against geographical coordinates clearly distinguishes the three highly infected areas: the Pannonian Plain, Western Lombardy and the Rhône-Alpes region. All the eight variables are sensitive to longitude through its temperature dependence. They are also sensitive to altitude, due to the progressively colder climate with increasing altitude. Both annual total pollen counts and the maximum daily pollen counts depend on the start and the duration of the ragweed pollen season. However, no significant changes were detected in either the eight independent variables as a function of increasing latitude. This is probably due to a mixed climate induced by strong geomorphological inhomogeneities in Europe.

The European Commission Cooperation in Science and Technology (COST) Action FA1203 “SMARTER” aims to make recommendations for the sustainable management of Ambrosia across Europe and for monitoring its efficiency and cost-effectiveness. The goal of the present study is to provide a baseline for spatial and temporal variations in airborne Ambrosia pollen in Europe that can be used for the management and evaluation of this noxious plant. The study covers the full range of Ambrosia artemisiifolia L. distribution over Europe (39°N–60°N; 2°W–45°E). Airborne Ambrosia pollen data for the principal flowering period of Ambrosia (August–September) recorded during a 10-year period (2004–2013) were obtained from 242 monitoring sites. The mean sum of daily average airborne Ambrosia pollen and the number of days that Ambrosia pollen was recorded in the air were analysed. The mean and standard deviation (SD) were calculated regardless of the number of years included in the study period, while trends are based on those time series with 8 or more years of data. Trends were considered significant at p < 0.05. There were few significant trends in the magnitude and frequency of atmospheric Ambrosia pollen (only 8% for the mean sum of daily average Ambrosia pollen concentrations and 14% for the mean number of days Ambrosia pollen were recorded in the air). The direction of any trends varied locally and reflected changes in sources of the pollen, either in size or in distance from the monitoring station. Pollen monitoring is important for providing an early warning of the expansion of this invasive and noxious plant.

BACKGROUND:The EC-funded EuroPrevall project examined the prevalence of food allergy across Europe. A well-established factor in the occurrence of food allergy is primary sensitization to pollen. OBJECTIVE:To analyse geographic and temporal variations in pollen exposure, allowing the investigation of how these variations influence the prevalence and incidence of food allergies across Europe. METHODS:Airborne pollen data for two decades (1990-2009) were obtained from 13 monitoring sites located as close as possible to the EuroPrevall survey centres. Start dates, intensity and duration of Betulaceae, Oleaceae, Poaceae and Asteraceae pollen seasons were examined. Mean, slope of the regression, probability level (P) and dominant taxa (%) were calculated. Trends were considered significant at P < 0.05. RESULTS:On a European scale, Betulaceae, in particular Betula, is the most dominant pollen exposure, two folds higher than to Poaceae, and greater than five folds higher than to Oleaceae and Asteraceae. Only in Reykjavik, Madrid and Derby was Poaceae the dominant pollen, as was Oleaceae in Thessaloniki. Weed pollen (Asteraceae) was never dominant, exposure accounted for >10% of total pollen exposure only in Siauliai (Artemisia) and Legnano (Ambrosia). Consistent trends towards changing intensity or duration of exposure were not observed, possibly with the exception of (not significant) decreased exposure to Artemisia and increased exposure to Ambrosia. CONCLUSIONS:This is the first comprehensive study quantifying exposure to the major allergenic pollen families Betulaceae, Oleaceae, Poaceae and Asteraceae across Europe. These data can now be used for studies into patterns of sensitization and allergy to pollen and foods.

To compare the dose‐related bronchodilator efficacy and tolerability of formoterol (Oxis®) Turbuhaler® with salmeterol Diskhaler® and placebo in children with asthma. A single‐dose, randomized, double‐blind, incomplete crossover study of 68 children (7–17 years), with moderate‐to‐severe asthma, 82% receiving inhaled corticosteroids. Patients received four of six treatments [4.5, 9, 18, or 36 μg formoterol (6, 12, 24 or 48 μg metered doses), 50 μg salmeterol (metered dose) or placebo] at 12‐h visits, separated by ≥3 days. Forced expiratory volume in 1 s (FEV1), pulse, blood pressure, electrocardiogram, adverse events and urine formoterol were assessed. The therapeutic ratio of formoterol vs. salmeterol was estimated from the efficacy and systemic effects results. All active treatments significantly improved FEV1 compared with placebo. Formoterol 9–36 μg provided dose‐related increases over salmeterol in lung function: average 12‐h FEV1 (increases of 4.9–8.7%, p < 0.001) and FEV1 at 12 h post‐dose (7.0–12.2%, p < 0.001). The onset of effect of formoterol was also significantly faster than salmeterol for doses ≥9 μg. Salmeterol 50 μg was estimated to be equieffective to 3.3 μg formoterol for 12‐h average FEV1 and the estimated equieffective dose for a variety of systemic effects was 7.8–13.5 μg formoterol. All treatments were well tolerated. Formoterol (Oxis) Turbuhaler 4.5–36 μg provided dose‐related improvements in bronchodilator efficacy in children with asthma. Formoterol ≥9 μg provided superior bronchodilator efficacy over 12 h compared with salmeterol Diskhaler 50 μg with no increase in systemic effects.