Airborne pollen and fungal spores (bioaerosols) are important for organisms’ reproduction and at the same time they are also bio-indicators of environmental change and they may have serious impacts on human health, as they can trigger respiratory symptoms. Monitoring bioaerosols in urban settings provides information on the quality of the atmospheric environment, which can be used by urban planners for adopting measures towards optimizing the ecosystem services of the urban greenery. As people reside, work and recreate both outdoors and indoors and at different heights above the ground, three-dimensional bioaerosol monitoring is necessary to capture this spatial variability. The aim of this research was to assess bioaerosol diversity and abundance in a typical urban setting, namely along the height gradient of a multi-storey building of workplaces, in Thessaloniki, Greece, both outdoors and indoors. Two portable Hirst-type volumetric samplers were used simultaneously at the two settings and at four sampling heights, from near ground level and up to 25 m, twice per week, during January-December 2020, collecting a total of 392 outdoor and 392 indoor samples. Both the diversity and abundance of pollen grains and fungal spores decreased with increasing height; this was more pronounced for herbaceous plants (e.g., Poaceae and Urticaceae, p < 0.001) and all fungi (p < 0.001), which implies sources of their particles mostly of local origin, whereas woody plants showed variable patterns suggesting medium or long-range transport. Pollen and fungal spore total abundance was lower indoors than outdoors for all sampling heights, while indoor-outdoor dissimilarity (β-diversity) increased with height for both bioaerosol types. Our findings highlight the complexity of bioaerosol diversity and abundance at different heights and the need for height-specific three-dimensional monitoring.

Precise airborne pollen forecasting is essential for mitigating exposure risks in individuals with pollen-related respiratory diseases such as allergic rhinitis and asthma and for supporting timely public health warning. Moreover, long-term accurate pollen forecasts could also support biodiversity conservation, ecosystem functions, and public-health protection. We developed an ensemble forecasting model for airborne grass (Poaceae) pollen concentrations in three climatically distinct European cities: Augsburg (Germany, transitional temperate-continental), Córdoba (Spain, dry Mediterranean), and Thessaloniki (Greece, humid Mediterranean). Pollen data (2018-2024) from Hirst-type volumetric traps were combined with meteorological parameters (temperature, humidity, precipitation). The 2024 pollen data were used for validation. Of 61 candidates, seven representative model families (Regularized Linear Regression, Extreme Gradient Boosting, Neural Network Autoregression [NNETAR], Random Forest, Support Vector Regression, Prophet-XGBoost hybrid, and Autoregressive Integrated Moving Average [ARIMA]) were selected for the ensemble. Model weights were assigned according to predictive performance. The ensemble achieved R2 values of 0.66 in Augsburg, 0.62 in Córdoba and 0.84 in Thessaloniki, with NNETAR and/or ARIMA contributing most strongly during the pollen season. Lagged pollen concentrations and previous-day temperature emerged as key predictors. When incorporating data from an automatic pollen monitor (BAA500, Helmut Hund GmbH) in Augsburg, the model achieved higher predictive performance (R2 = 0.89). Our findings demonstrate that ensemble-based pollen forecasting may generalize across contrasting bioclimatic regions, while remaining sensitive to local ecological and climatic controls. This framework provides a foundation for more powerful (real-time) forecasting systems aimed primarily at improving daily allergy risk management, while potentially offering complementary insights into longer-term vegetation dynamics under climate variability.

Urban environments constitute of spaces in which the majority of humankind reside, work and recreate [...]

Vertically retrieved optical properties by Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were investigated in the case of three selected events over Athens and Thessaloniki with documented high pollen concentrations. Hirst-type volumetric samplers were used to detect and characterize the pollen during the CALIPSO overpasses. Only cases with a total pollen concentration greater than 400 grains m−3 for at least two hours per day were considered severe pollen events, while model simulations were used to exclude the presence of other depolarizing aerosol types. This study provides mean values of lidar-derived optical properties inside the detected pollen layers; i.e., optical values represent the atmosphere with the presence of pollen, in urban cities of Greece. Specifically, three observed aerosol layers, one over Athens and two over Thessaloniki with particulate color ratios of 0.652 ± 0.194, 0.638 ± 0.362, and 0.456 ± 0.284, and depolarization ratios of 8.70 ± 6.26%, 28.30 ± 14.16%, and 8.96 ± 6.87%, respectively, were misclassified by CALIPSO as marine-dusty marine, dust, and polluted dust. In cases of intense pollen presence, CALIPSO vertical profiles and aerobiological monitoring methods may be used synergistically to better characterize the atmospheric pollen layers.

As the effects of anthropogenic climate change have become more apparent, the influences of climate and extreme weather events on health have continued to gain attention. The fact Earth has warmed over the past century is indisputable and the rate of warming is more alarming. As a result of anthropogenic climate change, an alteration in the air mixture has occurred over time. These changes have increased human exposures to respiratory irritants such as ground-level ozone, volatile organic compounds, nitrogen dioxide, sulfur dioxide, carbon monoxide, and polycyclic aromatic hydrocarbons. A significant amount of research has investigated the effects of climate change on aeroallergens, which has shown that elevated temperatures and increased carbon dioxide levels have produced prolonged and more robust pollen seasons for most taxa studied. In addition, it appears possible that exposure of some plants to air pollution may result in more allergenic pollen. Increased human exposures to these respiratory irritants and aeroallergens appears to disproportionality effect vulnerable populations throughout the world. It is essential to understand that climate change is more than an environmental inconvenience and realize the effects to human health are directly related and conceivably immeasurable. It is vital to conduct additional research related to climate change and health that is collaborative, multisectoral, and transdisciplinary. There should be a focus on risk reduction, mitigation, and preparedness for climate change and extreme weather events for all populations around the globe.

Urban green spaces are a vital element of sustainable cities. Nonetheless, there are associated disservices, one most important being pollen induced allergies. To examine how much vegetation analysis of urban green spaces can be an efficient indicator of the pollen-related qualitative and quantitative features of their atmospheric environment, we studied six such spaces, in Thessaloniki, Greece. We made a full analysis of their woody vegetation and collected aerobiological data, with sampling at breast height. Cupressaceae, Platanus, Quercus, Pinaceae and the herbaceous Urticaceae were the main pollen providers in almost all of them, when the main woody components of their vegetation were Cupressaceae, Rosaceae, Pinaceae and Fabaceae, with Quercus having only sporadic occurrence. The number of taxa represented in pollen and vegetation were not correlated, and pollen from external sources was detected even at high concentrations. Pollen similarity was higher than vegetation similarity, with taxa identity being more important than abundance in differentiating the green spaces. Pollen incidence was synchronized in many cases but, like concentration, duration of the pollen season also varied largely among green spaces, even when in proximity. Positive relationships between pollen concentration and vegetation abundance were detected for a few taxa, primarily Cupressaceae, and for green spaces that covered a large area (around 40 ha) or had an element of isolation. Vegetation analysis is not a reliable indicator of the pollen related atmospheric environment at the local scale. Aerobiological surveys are additionally needed locally to provide the necessary information regarding the prevailing conditions and the associated risks.

BackgroundThere is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero-allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts.MethodsThe study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values.ResultsThe best pollen forecasts include Mexico City (R2(DL_7) approximate to .7), and Santiago (R2(DL_7) approximate to .8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) approximate to .4) and Seoul (R2(DL_7) approximate to .1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28-100 cm depth, and past soil temperature in 0-7 cm depth. City-related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan.ConclusionsThis new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts. CatBoost is a preferable model for short-term forecasts, while Deep Learning is for longer ones, but there is no definite answer to what the better model is for every day or city. Past pollen trends are strong indicators of future pollen concentrations. CatBoost can be used to determine the importance of environmental variables in forecasting daily total pollen concentration. Abbreviations: 2mT, 2 m temperature; CB, CatBoost; DL, Deep Learning; DOY, day of the year; ERA5, the fifth generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis dataset; pevap, potential evapotranspiration; st, soil temperature.image

Bioaerosols, such as pollen and fungal spores, are routinely monitored for agricultural, medical or urban greening practices, but sampling methodology is largely relying on techniques more than half a century old. Moreover, biomonitoring campaigns often take place in urban environments, although sources can be located outside cities' borders with ampler vegetation. Therefore, the question arises whether we are accurately picturing the biodiversity and abundance of regional bioaerosols and whether those locally detected might derive from long-distance transport, horizontally or vertically. To answer the above, we used novel, mobile monitoring devices, and aerial measurement units, like aircrafts, so as to explore bioaerosol concentrations at a variety of altitudes. An ultralight aircraft was equipped with a sampling device for bioaerosols. The device consisted of duplicate isokinetic impactors that match the physical functioning and the microscopic quantification method of the widely used ground-based Hirst-type impactors. Isokinetic airflow was realized by adjusting the air flux at the impactors' inlet to the airspeed of the aircraft. Three campaigns were made, where the comparability, efficiency and accuracy of different sampling devices were determined, namely of the abovementioned impactor, and of the mobile conventional Hirst-type pollen sampler. The campaigns involved measurements from ground level (0 m altitude) up to 900 m (above ground level (agl)) via flights. Our results showed that aircraft-based airborne pollen concentration measurements were consistently higher than those of all other devices, regardless of the altitude and sampling time. It is noteworthy that the pollen concentration exceeded 500 pollen grains/m3 at >900 m of altitude, this concentration being 1.77 times higher than that simultaneously measured at ground level. Likewise, the diversity of pollen was also higher at higher altitude. Our results indicate the usability and superiority of small aircraft and high-flow impactors for research, achieving higher biodiversity and abundance over a shorter sampling interval compared to conventional volumetric techniques. Higher pollen amounts at higher altitudes also point at the necessity to monitor bioaerosols across the vertical dimension, especially in densely populated areas and high-traffic air space.

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.

Viruses are frequently a microbial biocontaminant of healthy plants. The occurrence of the infection can be also due to environmental stress, like urbanisation, air pollution and increased air temperature, especially under the ongoing climate change. The aim of the present study was to investigate the hypothesis that worsened air quality and fewer green areas may favour the higher frequency of common viral infections, particularly in a common tree in temperate and continental climates, Betula pendula ROTH. We examined 18 trees, during the years 2015-2017, the same always for each year, in the region of Augsburg, Germany. By specific PCR, the frequency of two viruses, Cherry leaf roll virus (CLRV, genus Nepovirus, family Secoviridae), which is frequent in birch trees, and a novel virus tentatively named birch idaeovirus (BIV), which has been only recently described, were determined in pollen samples. The occurrence of the viruses was examined against the variables of urban index, air pollution (O3 and NO2), air temperature, and tree morphometrics (trunk perimeter, tree height, crown height and diameter). Generalized Non-linear models (binomial logit with backward stepwise removal of independent variables) were employed. During the study period, both CLRV and BIV were distributed widely throughout the investigated birch individuals. CLRV seemed to be rather cosmopolitan and was present independent of any abiotic factor. BIV's occurrence was mostly determined by higher values of the urban index and of NO2. Urban birch trees, located next to high-traffic roads with higher NO2 levels, are more likely to be infected by BIV. Increased environmental stress may lead to more plant viral infections. Here we suggest that this is particularly true for urban spaces, near high-traffic roads, where plants may be more stressed, and we recommend taking mitigation measures for controlling negative human interventions.

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.

The study is aimed at determining the potential spatiotemporal risk of the co-occurrence of airborne pollen and fungal spores high concentrations in different bio-climatic zones in Europe. Birch, grass, mugwort, ragweed, olive pollen and Alternaria and Cladosporium fungal spores were investigated at 16 sites in Europe, in 2005-2019. In Central and northern Europe, pollen and fungal spore seasons mainly overlap in June and July, while in South Europe, the highest pollen concentrations occur frequently outside of the spore seasons. In the coldest climate, no allergy thresholds were exceeded simultaneously by two spore or pollen taxa, while in the warmest climate most of the days with at least two pollen taxa exceeding threshold values were observed. The annual air temperature amplitude seems to be the main bioclimatic factor influencing the accumulation of days in which Alternaria and Cladosporium spores simultaneously exceed allergy thresholds. The phenomenon of co-occurrence of airborne allergen concentrations gets increasingly common in Europe and is proposed to be present on other continents, especially in temperate climate.

We applied five sets of criteria for pollen season (PS) definition, which are associated with the ‘clinical’, ‘grains’, ‘logistic’, ‘moving average’ and ‘percentage’ methods, on a 30-year time series of daily airborne pollen concentration values of Cupressaceae (cypress family), Oleaceae (olive family) and Poaceae (grass family), from Thessaloniki, Greece. These methods could identify a pollen season for more than 90% of the study period for all three taxa, except for the clinical that identified less than 40% for Oleaceae. The estimated values of the PS start, end, and duration varied largely, in a method-specific way. Even significant reverse patterns of change were recorded for the same attribute and taxon, as for the Poaceae PS end date that shows a significant advance earlier in the year with the moving average method and delay with the percentage. As the season peak date is method-independent and, hence, directly comparable, we recommend this attribute to be examined in airborne pollen studies. Results taken with the percentage method could be compared with those of the past for Thessaloniki, with a more than 10-year shorter time series. No climate-related change was detected for Cupressaceae PS attributes, but an earlier peak was now detected for Oleaceae and Poaceae, and a later end and a longer duration for Poaceae, suggesting an increased allergy risk for this taxon. The different criteria concurrently applied for PS definition that led to even greatly diverging results for the same PS attribute is an issue for the science and calls for efforts at standardization.

We studied the diversity and abundance of the airborne fungal spores in the city of Thessaloniki, Greece, for two consecutive years. Air samples were collected at one rooftop station (at 30 m) and six near-ground stations (at 1.5 m) that differed in the size and composition of adjacent green spaces. The effects of meteorological factors on airborne fungal spore concentrations were also explored. Cladosporium spores were dominant everywhere in the air of the city. The total concentration of the airborne fungal spores at 30 m was 10 times lower than near the ground. Differences in concentration and composition were far less pronounced among near-ground stations. The attributes of the fungal spore season did not change in a consistent way among stations and years. Concentrations at the near-ground stations matched the grouping of the latter into stations of high, intermediate, and low urban green space. Minimum air temperature was the primary meteorological factor affecting spore abundance, followed by relative humidity. Airborne fungal spores are more homogeneously distributed in the air of the city, but their concentrations decrease more rapidly with height than pollen.

Pollen is indispensable for life. But, as it may trigger allergic reactions, it can become a biological pollutant, thus requiring monitoring. In urban ecosystems, this is usually done with sampling at rooftop level; exposure to allergenic pollen at ground level is largely unknown. Using the Hirst-type methodology, we explore here how the qualitative, quantitative and phenological features of airborne pollen change horizontally, in different sites of the urban environment, and vertically, when pollen sources are primarily local. We sampled for two years in Thessaloniki, Greece, at six near-ground stations (at 1.5 m) and one at rooftop-level (30 m high). There was a large variability in quantitative pollen features among stations, but Urticaceae, Cupressaceae, Platanus, Pinaceae, and Quercus were the five most abundantly represented taxa in the air, both near the ground and at rooftop level, exceeding there an annual pollen integral of 1000 grains m(-3). We found height to have a clear effect on pollen concentration: near the ground, it was three times higher for the entire pollen spectrum and up to 11 times higher for individual taxa. Assuming an exponential decay of pollen with distance from the ground, we calculated pollen concentration for the entire spectrum to decline to half the near-ground value every 19 m and at higher rates for individual taxa. Pollen season also varied largely among stations; a semi-natural station, next to a peri-urban forest, differed from the purely urban stations in having higher pollen concentration and shorter pollen sea-son. For only two taxa, Urticaceae and Cupressaceae, pollen concentrations exceeded thresholds associated with high risk for more than 5% of the year. We conclude that pollen is far from homogeneously distributed within the urban environment, and that height has a strong effect on the low-altitude vertical profile of pollen. At an applied level, this study provides necessary information for more efficient monitoring of airborne pollen and for designing and managing urban green spaces, particularly under the current climate change and the associated higher demand for urban green.

Airborne pollen are the most important aeroallergens worldwide. Because of climate change, pollen seasonality and abundance have been altering significantly, raising the fundamental question: when and how much is the pollen exposure increasing? To answer this, we applied a multi-resolution study design, from bi-hourly to yearly scale, investigating the diversity, abundance and temporal occurrence of airborne pollen. The whole spectrum of airborne pollen concentrations was registered during 2015-2017, using a 7-day recording Hirst-type volumetric trap. Monitoring took place at ground-level, where we mostly commute and reside, and at the 'gold-standard' rooftop-level (12 m above ground level), at resolutions: A) bi-hourly, B) daily. The biodiversity and the relative abundance of all taxa were assessed, and the first pollen season calendars, along with circadian calendars, for Augsburg, Germany, were developed. More than 40 pollen types were identified, of which 13 were the most abundant (>0.5% relative abundance each, accounting for a total of 91.8%). Biodiversity did not present any striking differences between heights, with pollen from Urticaceae, Betula and Poaceae representing consistently more than half of the regional atmospheric biodiversity. At rooftop-level, pollen abundances often appeared to be higher, particularly for Betula, Picea and Quercus. The main pollen season extended from March to October, with the highest peak occurring April-May. At rooftop-level, the pollen seasons of most taxa were observed earlier and the overall seasons were longer. Within the day, higher pollen concentrations were observed either at midday to early afternoon (Urticaceae, Poaceae, Plantago and mostly taxa at ground-level) or night to early morning, frequently with multi-modal diurnal patterns (Betula, Fraxinus and mostly taxa at rooftop-level). Our findings reveal that generalisation of abundance and temporal distribution patterns between ground-level and 'gold-standard' rooftop-level pollen measurements should be intensively reconsidered. While the pollen

Flowering and pollen seasons are sensitive to environmental variability and are considered climate change indicators. However, it has not been concluded to what extent flowering phenology is indeed reflected in airborne pollen season locally. The aim of this study was to investigate, for a wide spectrum of plant species, the responsiveness of flowering to different environmental regimes and also to check for commensurate changes in the respective pollen seasons. Fourteen taxa were selected representing the families of Corylaceae, Cupressaceae, Fagaceae, Oleaceae, Pinaceae and Platanaceae. Each was studied for at least one full flowering year and in at least two sampling stations differing in elevation or direction within the period 2004-2011. Flowering observations were made 2-3 times a week, from flower differentiation to flower desiccation; >1000 daily observations were made in 225 plant individuals, in total. Data were regressed against meteorological parameters in an attempt to identify the driving factors of flowering onset and offset. Flowering dates were compared with dates of the related airborne pollen seasons per taxon; airborne pollen monitoring took place daily using a Hirst-type volumetric sampler. For all taxa, flowering started earlier at lower elevations or southern direction. Cumulative temperature proved to be the factor most significantly affecting flowering onset and end for all species (p<0.001, R-2 >0.70). For the majority of the taxa examined, airborne pollen season did not coincide locally with the respective flowering periods of the selected species: flowering could precede pollen season, even for more than one month (as in C. avellana), or start after the pollen season onset (as in P. brutia). The strong sensitivity of flowering to air temperature is not the case in the respective pollen seasons. This raises questions on the relationship between flowering times and airborne pollen seasons and on the rather underestimated role of long-distance transport of pollen.

Understanding the mechanisms of pollen release and dispersion in the atmosphere is of high importance, not only for getting an insight on the patterns of movement of these biological particles that are necessary for plants' reproduction, but also because exposure to airborne pollen is a major concern for respiratory allergies worldwide. In this work, a synoptic circulation-to-environment classification method was adopted to elucidate the relationship between distinct atmospheric patterns and pollen levels for the 11 most abundant but also allergenic taxa in Thessaloniki, Greece, for the 15-year period 1987-2001. It was found that the NW1 depressional weather type is associated with the "low winter pollen season" and high levels of pollen from Carpinus spp., Corylus spp., Cupressaceae, Platanus spp., Pinaceae, Quercus spp. and Urticaceae. In contrast, the SW1 cyclonic type is linked to the "high spring-summer pollen season" and high levels of pollen from Oleaceae and Urticaceae. On the other hand, anticyclonic weather is associated with the "summer-autumn pollen season" and high levels of Poaceae and Chenopodiaceae pollen in the atmosphere. Regional transport of Alnus pollen is linked to a strong high-pressure system centered over Italy, giving light NE winds over northern Greece. These findings shed light to the synoptic climatology of airborne pollen in Thessaloniki and could feed early-warning systems for alerting vulnerable groups of the allergic population.