A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe.

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.

Using Front-Face Fluorescence Spectroscopy and Biochemical Analysis of Honey to Assess a Marker for the Level of Varroa destructor Infestation of Honey Bee (Apis mellifera) Colonies.

Varroa destructor is a parasitic mite responsible for the loss of honey bee (Apis mellifera) colonies. This study aimed to find a promising marker in honey for the bee colony infestation level using fluorescence spectroscopy and biochemical analyses. We examined whether the parameters of the honey samples' fluorescence spectra and biochemical parameters, both related to proteins and phenolics, may be connected with the level of honey bee colonies' infestation. The infestation level was highly positively correlated with the catalase activity in honey (r = 0.936). Additionally, the infestation level was positively correlated with the phenolic spectral component (r = 0.656), which was tentatively related to the phenolics in honey. No correlation was found between the diastase activity in honey and the colonies' infestation level. The results indicate that the catalase activity in honey and the PFC1 spectral component may be reliable markers for the V. destructor infestation level of the colonies. The obtained data may be related to the honey yield obtained from the apiaries.

Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy.

Pollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning models with a focus on deep learning, have an essential role in the pollen classification task. Within this study we developed an explainable framework to unveil a deep learning model for pollen classification. Model works on data coming from single particle detector (Rapid-E) that records for each particle optical fingerprint with scattered light and laser induced fluorescence. Morphological properties of a particle are sensed with the light scattering process, while chemical properties are encoded with fluorescence spectrum and fluorescence lifetime induced by high-resolution laser. By utilizing these three data modalities, scattering, spectrum, and lifetime, deep learning-based models with millions of parameters are learned to distinguish different pollen classes, but a proper understanding of such a black-box model decisions demands additional methods to employ. Our study provides the first results of applied explainable artificial intelligence (xAI) methodology on the pollen classification model. Extracted knowledge on the important features that attribute to the predicting particular pollen classes is further examined from the perspective of domain knowledge and compared to available reference data on pollen sizes, shape, and laboratory spectrofluorometer measurements.

Towards European automatic bioaerosol monitoring: Comparison of 9 automatic pollen observational instruments with classic Hirst-type traps.

To benefit allergy patients and the medical practitioners, pollen information should be available in both a reliable and timely manner; the latter is only recently possible due to automatic monitoring. To evaluate the performance of all currently available automatic instruments, an international intercomparison campaign was jointly organised by the EUMETNET AutoPollen Programme and the ADOPT COST Action in Munich, Germany (March-July 2021). The automatic systems (hardware plus identification algorithms) were compared with manual Hirst-type traps. Measurements were aggregated into 3-hourly or daily values to allow comparison across all devices. We report results for total pollen as well as for Betula, Fraxinus, Poaceae, and Quercus, for all instruments that provided these data. The results for daily averages compared better with Hirst observations than the 3-hourly values. For total pollen, there was a considerable spread among systems, with some reaching R2 > 0.6 (3 h) and R2 > 0.75 (daily) compared with Hirst-type traps, whilst other systems were not suitable to sample total pollen efficiently (R2 < 0.3). For individual pollen types, results similar to the Hirst were frequently shown by a small group of systems. For Betula, almost all systems performed well (R2 > 0.75 for 9 systems for 3-hourly data). Results for Fraxinus and Quercus were not as good for most systems, while for Poaceae (with some exceptions), the performance was weakest. For all pollen types and for most measurement systems, false positive classifications were observed outside of the main pollen season. Different algorithms applied to the same device also showed different results, highlighting the importance of this aspect of the measurement system. Overall, given the 30 % error on daily concentrations that is currently accepted for Hirst-type traps, several automatic systems are currently capable of being used operationally to provide real-time observations at high temporal resolutions. They provide distinct advantages compared to the manual Hirst-type measurements.

Real-time automatic detection of starch particles in ambient air.

Considerable amounts of starch granules can be present in the atmosphere from both natural and anthropogenic sources. The aim of this study is to investigate the variability and potential origin of starch granules in ambient air recorded at six cities situated in a region with dominantly agricultural land use. This is achieved by using a combination of laser spectroscopy bioaerosol measurements with 1 min temporal resolution, traditional volumetric Hirst type bioaerosol sampling and atmospheric modelling. The analysis of wind roses identified potential sources of airborne starch (i.e., cereal grain storage facilities) in the vicinity of all aerobiological stations analysed in this study. The analysis of the CALPUFF dispersion model confirmed that emission of dust from the location of storage towers situated about 2.5 km north of the aerobiological station in Novi Sad is a plausible source of high airborne concentrations of starch granules. This study is important for environmental health since it contributes body of knowledge about sources, emission, and dispersion of airborne starch, known to be involved in phenomena such as thunderstorm-triggered asthma. The presented approach integrates monitoring and modelling, and provides a roadmap for examining a variety of bioaerosols previously considered to be outside the scope of traditional aerobiological measurements.

Integration of reference data from different Rapid-E devices supports automatic pollen detection in more locations.

Pollen is the most common cause of seasonal allergies, affecting over 33 % of the European population, even when considering only grasses. Informing the population and clinicians in real-time about the actual presence of pollen in the atmosphere is essential to reduce its harmful health and economic impact. Thus, there is a growing network of automatic particle analysers, and the reproducibility and transferability of implemented models are recommended since a reference dataset for local pollen of interest needs to be collected for each device to classify pollen, which is complex and time-consuming. Therefore, it would be beneficial to incorporate the reference dataset collected from other devices in different locations. However, it must be considered that laser-induced data are prone to device-specific noise due to laser and detector sensibility. This study collected data from two Rapid-E bioaerosol identifiers in Serbia and Italy and implemented a multi-modal convolutional neural network for pollen classification. We showed that models lost their performance when trained on data from one and tested on another device, not only in terms of the recognition ability but also in comparison with the manual measurements from Hirst-type traps. To enable pollen classification with just one model in both study locations, we first included the missing pollen classes in the dataset from the other study location, but it showed poor results, implying that data of one pollen class from different devices are more different than data of different pollen classes from one device. Combining all available reference data in a single model enabled the classification of a higher number of pollen classes in both study locations. Finally, we implemented a domain adaptation method, which improved the recognition ability and the correlations of transferred models only for several pollen classes.

Characterization of preimaginal developmental stages of two cryptic South African species of the Merodon planifacies complex (Diptera: Syrphidae: Eristalinae: Merodontini), with differentiation through morphometry analysis.

Merodon capi Vujic et Radenkovic, 2020 and Merodon roni Radenkovic et Vujic, 2020 are two cryptic species belonging to the Merodon planifacies Bezzi, 1915 species complex that have recently been described, with the differences between them being revealed by molecular and geometric morphometry studies of adult specimens. In the present study, the preimaginal morphology of both species is described and displayed, with the material used corresponding to samples taken from bulbs of Merwilla plumbea (Lindl.) Speta plants at two locations in KwaZulu-Natal province (South Africa). The preimaginal stages were compared, looking for morphological evidence supporting species divergence. Linear and geometric morphometric analyses of the larval posterior respiratory process were conducted for the first time and the results of these analyses support the separation of the two taxa. Information about the life cycle and the relation with the host plant is also provided. In addition, we carried out a preliminary study of the adult feeding requirements of the species, based on the description of the mouthparts and an analysis of the pollen present in the gut and on the integument of adults. The results of the study supports a close relationship between the preimaginal stages and plant species of the Hyacinthaceae family.

Why should we care about high temporal resolution monitoring of bioaerosols in ambient air?

This is the first time that atmospheric concentrations of individual pollen types have been recorded by an automatic sampler with 1-hour and sub-hourly resolution (i.e. 1-minute and 1-second data). The data were collected by traditional Hirst type methods and state-of the art Rapid-E real-time bioaerosol detector. Airborne pollen data from 7 taxa, i.e. Acer negundo, Ambrosia, Broussonetia papyrifera, Cupressales (Taxaceae and Cupressaceae families), Platanus, Salix and Ulmus, were collected during the 2019 pollen season in Novi Sad, Serbia. Pollen data with daily, hourly and sub-hourly temporal resolution were analysed in terms of their temporal variability. The impact of turbulence kinetic energy (TKE) on pollen cloud homogeneity was investigated. Variations in Seasonal Pollen Integrals produced by Hirst and Rapid-E show that scaling factors are required to make data comparable. Daily average and hourly measurements recorded by the Rapid-E and Hirst were highly correlated and so examining Rapid-E measurements with sub-hourly resolution is assumed meaningful from the perspective of identification accuracy. Sub-hourly data provided an insight into the heterogenous nature of pollen in the air, with distinct peaks lasting ~5-10 min, and mostly single pollen grains recorded per second. Short term variations in 1-minute pollen concentrations could not be wholly explained by TKE. The new generation of automatic devices has the potential to increase our understanding of the distribution of bioaerosols in the air, provide insights into biological processes such as pollen release and dispersal mechanisms, and have the potential for us to conduct investigations into dose-response relationships and personal exposure to aeroallergens.

Bioaerosols on the atmospheric super highway: An example of long distance transport of Alternaria spores from the Pannonian Plain to Poland.

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 Poznan 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.

The need for Pan-European automatic pollen and fungal spore monitoring: A stakeholder workshop position paper.

BACKGROUND: Information about airborne pollen concentrations is required by a range of end users, particularly from the health sector who use both observations and forecasts to diagnose and treat allergic patients. Manual methods are the standard for such measurements but, despite the range of pollen taxa that can be identified, these techniques suffer from a range of drawbacks. This includes being available at low temporal resolution (usually daily averages) and with a delay (usually 3-9 days from the measurement). Recent technological developments have made possible automatic pollen measurements, which are available at high temporal resolution and in real time, although currently only scattered in a few locations across Europe. MATERIALS & METHODS: To promote the development of an extensive network across Europe and to ensure that this network will respond to end user needs, a stakeholder workshop was organised under the auspices of the EUMETNET AutoPollen Programme. Participants discussed requirements for the groups they represented, ranging from the need for information at various spatial scales, at high temporal resolution, and for targeted services to be developed. RESULTS: The provision of real-time information is likely to lead to a notable decrease in the direct and indirect health costs associated with allergy in Europe, currently estimated between €50-150 billion/year.1 DISCUSSION & CONCLUSION: A European measurement network to meet end user requirements would thus more than pay for itself in terms of potential annual savings and provide significant impetus to research across a range of disciplines from climate science and public health to agriculture and environmental management.

The influence of source maps on SILAM performance in modeling ragweed pollen concentrations in the area of a major European source.

The Pannonian Plain is one of the centers of ragweed distribution in Europe. The province of Vojvodina (Serbia) is located on the southern part of the Pannonian Plain, representing a highly infested region. In this study, we have used the SILAM atmospheric dispersion model to simulate ragweed pollen concentrations during the season 2016 in the Vojvodina region. SILAM was tested with three different source maps of ragweed distribution in Vojvodina only: (1) map used in operational SILAM, which was calibrated with the SILAM model and observations, (2) map derived using "top-down" approach with land cover data inventory, and (3) map obtained with "top-down" approach using crop classification from the satellite data. Additionally, the sensitivity studies were done using two modified maps to study the effect of the source strength and long-range transport. Results of simulations were validated with the bi-hourly, daily, and seasonal pollen concentrations measured at five stations in Vojvodina. Overall Pearson correlation coefficients were 0.51 (Map 1), 0.50 (Map 2), and 0.42 (Map 3), while debiased scores were 232.95 pollen m-3 (Map 1), 245.59 pollen m-3 (Map 2), and 258.24 pollen m-3 (Map 3). Even though Vojvodina is in the area of a major European source, regional transport of ragweed pollen from a few hundred kilometers of the surrounding area was important in explaining the presence of pollen in the afternoon hours, although it could not completely explain total pollen quantity. The results confirmed that it is vital to calibrate source maps using atmospheric dispersion model with the observed pollen data.

Biological weed control to relieve millions from Ambrosia allergies in Europe.

Invasive alien species (IAS) can substantially affect ecosystem services and human well-being. However, quantitative assessments of their impact on human health are rare and the benefits of implementing IAS management likely to be underestimated. Here we report the effects of the allergenic plant Ambrosia artemisiifolia on public health in Europe and the potential impact of the accidentally introduced leaf beetle Ophraella communa on the number of patients and healthcare costs. We find that, prior to the establishment of O. communa, some 13.5 million persons suffered from Ambrosia-induced allergies in Europe, causing costs of Euro 7.4 billion annually. Our projections reveal that biological control of A. artemisiifolia will reduce the number of patients by approximately 2.3 million and the health costs by Euro 1.1 billion per year. Our conservative calculations indicate that the currently discussed economic costs of IAS underestimate the real costs and thus also the benefits from biological control.

Polyphenol profile of buckwheat honey, nectar and pollen.

A focus of research in recent years is the comparison of honey as the final product of bees with pollen and nectar of the plant from which the honey originates, as the main food source for bees. Buckwheat honey is recognized as a nutritionally valuable product, which provides a scientifically proven health benefit and is confirmed as a functional food. The quality of this type of honey is attributed to high levels of phytochemicals in buckwheat. The purpose of this study was the examination of similarity between buckwheat honey and buckwheat nectar and pollen, as well as simultaneous investigation of their chemical profiles and the origin of the honey. The phenolic profile of buckwheat pollen showed a lower number of flavonoids and phenolic acids than those of nectar and honey samples, but confirmed the presence of the most characteristic polyphenols derived from the buckwheat plant. The notable difference was found to be the presence of (epi)catechin units, its galloylated derivatives and procyanidin dimers, which were not present in honey. Honey polyphenols displayed a pronounced correlation with those of nectar, but not with those of pollen. Finally, by comparing the polyphenolic profiles of honey, nectar and pollen sharing the same geographical origin, new data could be provided for a potential assessment of the botanical origin of buckwheat honey.

Phenolic Composition Influences the Health-Promoting Potential of Bee-Pollen.

Information on compositional, nutritional and functional properties of bee-pollen, as a health-promoting food, is essential for defining its quality. Concerning the nutritional importance of phenolic compounds, the aim of this study was to determine the phenolic profile and antioxidant activity of twenty-four bee-pollen samples collected from different regions of Serbia. High-performance thin-layer chromatographic (HPTLC) fingerprinting was used for profiling of bee-pollen samples according to the botanical type. HPTLC hyphenated with image analysis and a pattern recognition technique confirmed the grouping of samples caused by the specific phenolic composition of pollens of different botanical origin. Flavonoid glycosides in bee-pollen samples were identified by applying ultra-high-performance liquid chromatography (UHPLC) coupled with linear ion trap-Orbitrap mass spectrometry (LTQ Orbitrap MS). Eight out of twenty-seven flavonol glycosides were identified in bee-pollen samples for the first time. All analyzed bee-pollen samples showed a high number of phenolic compounds which may have therapeutic potential.

Concomitant occurrence of anthropogenic air pollutants, mineral dust and fungal spores during long-distance transport of ragweed pollen.

Large-scale synoptic conditions are able to transport considerable amounts of airborne particles over entire continents by creating substantial air mass movement. This phenomenon is observed in Europe in relation to highly allergenic ragweed (Ambrosia L.) pollen grains that are transported from populations in Central Europe (mainly the Pannonian Plain and Balkans) to the North. The path taken by atmospheric ragweed pollen often passes through the highly industrialised mining region of Silesia in Southern Poland, considered to be one of the most polluted areas in the EU. It is hypothesized that chemical air pollutants released over Silesia could become mixed with biological material and be transported to less polluted regions further North. We analysed levels of air pollution during episodes of long-distance transport (LDT) of ragweed pollen to Poland. Results show that, concomitantly with pollen, the concentration of air pollutants with potential health-risk, i.e. SO2, and PM10, have also significantly increased (by 104% and 37%, respectively) in the receptor area (Western Poland). Chemical transport modelling (EMEP) and air mass back-trajectory analysis (HYSPLIT) showed that potential sources of PM10 include Silesia, as well as mineral dust from the Ukrainian steppe and the Sahara Desert. In addition, atmospheric concentrations of other allergenic biological particles, i.e. Alternaria Nees ex Fr. spores, also increased markedly (by 115%) during LDT episodes. We suggest that the LDT episodes of ragweed pollen over Europe are not a "one-component" phenomenon, but are often related to elevated levels of chemical air pollutants and other biotic and abiotic components (fungal spores and desert dust).

Predicting abundances of invasive ragweed across Europe using a "top-down" approach.

Common ragweed (Ambrosia artemisiifolia L.) is a widely distributed and harmful invasive plant that is an important source of highly allergenic pollen grains and a prominent crop weed. As a result, ragweed causes huge costs to both human health and agriculture in affected areas. Efficient mitigation requires accurate mapping of ragweed densities that, until now, has not been achieved accurately for the whole of Europe. Here we provide two inventories of common ragweed abundances with grid resolutions of 1 km and 10 km. These "top-down" inventories integrate pollen data from 349 stations in Europe with habitat and landscape management information, derived from land cover data and expert knowledge. This allows us to cover areas where surface observations are missing. Model results were validated using "bottom-up" data of common ragweed in Austria and Serbia. Results show high agreement between the two analytical methods. The inventory shows that areas with the lowest ragweed abundances are found in Northern and Southern European countries and the highest abundances are in parts of Russia, parts of Ukraine and the Pannonian Plain. Smaller hotspots are found in Northern Italy, the Rhône Valley in France and in Turkey. The top-down approach is based on a new approach that allows for cross-continental studies and is applicable to other anemophilous species. Due to its simplicity, it can be used to investigate such species that are difficult and costly to identify at larger scales using traditional vegetation surveys or remote sensing. The final inventory is open source and available as a georeferenced tif file, allowing for multiple usages, reducing costs for health services and agriculture through well-targeted management interventions.

Near-ground effect of height on pollen exposure.

The effect of height on pollen concentration is not well documented and little is known about the near-ground vertical profile of airborne pollen. This is important as most measuring stations are on roofs, but patient exposure is at ground level. Our study used a big data approach to estimate the near-ground vertical profile of pollen concentrations based on a global study of paired stations located at different heights. We analyzed paired sampling stations located at different heights between 1.5 and 50 m above ground level (AGL). This provided pollen data from 59 Hirst-type volumetric traps from 25 different areas, mainly in Europe, but also covering North America and Australia, resulting in about 2,000,000 daily pollen concentrations analyzed. The daily ratio of the amounts of pollen from different heights per location was used, and the values of the lower station were divided by the higher station. The lower station of paired traps recorded more pollen than the higher trap. However, while the effect of height on pollen concentration was clear, it was also limited (average ratio 1.3, range 0.7-2.2). The standard deviation of the pollen ratio was highly variable when the lower station was located close to the ground level (below 10 m AGL). We show that pollen concentrations measured at >10 m are representative for background near-ground levels.

Ambrosia pollen source inventory for Italy: a multi-purpose tool to assess the impact of the ragweed leaf beetle (Ophraella communa LeSage) on populations of its host plant.

Here, we produce Ambrosia pollen source inventories for Italy that focuses on the periods before and after the accidental introduction of the Ophraella communa beetle. The inventory uses the top-down approach that combines the annual Ambrosia pollen index from a number of monitoring stations in the source region as well as Ambrosia ecology, local knowledge of Ambrosia infestation and detailed land cover information. The final inventory is gridded to a 5 × 5-km resolution using a stereographic projection. The sites with the highest European Infection levels were recorded in the north of Italy at Busto Arsizio (VA3) (European Infection level 2003-2014 = 52.1) and Magenta (MI7) (European Infection level 2003-2014 = 51.3), whereas the sites with the lowest (i.e. around 0.0) were generally located to the south of the country. Analysis showed that the European Infection level in all of Italy was significantly lower in 2013-2014 compared to 2003-2012, and this decrease was even more pronounced at the sites in the area where Ophraella communa was distributed. Cross-validations show that the sensitivity to the inclusion of stations is typically below 1% (for two thirds of the stations) and that the station Magenta (MI7) had the largest impact compared to all other stations. This is the first time that pollen source inventories from different temporal periods have been compared in this way and has implications for simulating interannual variations in pollen emission as well as evaluating the management of anemophilous plants like Ambrosia artemisiifolia.

Aerobiology in the International Journal of Biometeorology, 1957-2017.

Aerobiology and biometeorology are related fields. Here we provide a broad review of aerobiology articles published in the International Journal of Biometeorology (IJB) over the past 60 years. We consider how the quantity of such work has varied over this period as well as which regions and countries have been the focus of such work, and where there is a relative paucity. We then focus on a number of highlights and themes in this research, including aerobiology and climate change and aerobiological modelling and forecasting. While much of the article focusses on airborne pollen research, we also discuss the extent to which other airborne organic particles such as fungal spores and bacteria have been the focus of research published in IJB. Also considered are knowledge gaps and research needs and priorities with respect to the field of aerobiology. While the IJB has been one of the main platforms for presenting aerobiological research over recent decades, the article highlights the need for the field of aerobiology to embrace new sampling technologies such as spectral analysis and next-generation sequencing to identify and quantify airborne biological particles.

The long distance transport of airborne Ambrosia pollen to the UK and the Netherlands from Central and south Europe.

The invasive alien species Ambrosia artemisiifolia (common or short ragweed) is increasing its range in Europe. In the UK and the Netherlands, airborne concentrations of Ambrosia pollen are usually low. However, more than 30 Ambrosia pollen grains per cubic metre of air (above the level capable to trigger allergic symptoms) were recorded in Leicester (UK) and Leiden (NL) on 4 and 5 September 2014. The aims of this study were to determine whether the highly allergenic Ambrosia pollen recorded during the episode could be the result of long distance transport, to identify the potential sources of these pollen grains and to describe the conditions that facilitated this possible long distance transport. Airborne Ambrosia pollen data were collected at 10 sites in Europe. Back trajectory and atmospheric dispersion calculations were performed using HYSPLIT_4. Back trajectories calculated at Leicester and Leiden show that higher altitude air masses (1500 m) originated from source areas on the Pannonian Plain and Ukraine. During the episode, air masses veered to the west and passed over the Rhône Valley. Dispersion calculations showed that the atmospheric conditions were suitable for Ambrosia pollen released from the Pannonian Plain and the Rhône Valley to reach the higher levels and enter the airstream moving to northwest Europe where they were deposited at ground level and recorded by monitoring sites. The study indicates that the Ambrosia pollen grains recorded during the episode in Leicester and Leiden were probably not produced by local sources but transported long distances from potential source regions in east Europe, i.e. the Pannonian Plain and Ukraine, as well as the Rhône Valley in France.