Atmospheric pollen is one of the main environmental triggers of allergic respiratory diseases, whose prevalence has increased worldwide over the past decades. This study analyses the evolution of atmospheric pollen concentrations and sensitization patterns in the city of Almería (southeastern Iberian Peninsula), a semi-arid Mediterranean region that is particularly vulnerable to environmental changes. The objectives were to assess long-term trends in atmospheric pollen levels, determine the influence of meteorological variables and land-use changes, characterize the seasonal dynamics of pollen, and analyse changes in pollen sensitization over time. Olea pollen was the most abundant taxon in the atmosphere, followed by Quercus and Amaranthaceae. Significant positive trends were detected for several arboreal pollen types, particularly Olea, Quercus, Pinus, Cupressaceae, and Platanus, while Poaceae was the only herbaceous pollen type showing a significant increase. Meteorological variables had a limited influence on pollen concentrations, with significant relationships observed mainly for Amaranthaceae and Artemisia. Land-use analysis revealed an expansion of agricultural, urban, and peri-urban areas, together with a moderate increase in olive groves, which may have contributed to the observed trends. The pollen calendar showed the highest concentrations between April and May. January and February were also important months for patients with pollinosis due to Cupressaceae pollination, while August was relevant because of Artemisia and Amaranthaceae. Clinical data indicated that Olea pollen had the highest sensitization rate, followed by Salsola and Poaceae. A slight increase in sensitization and monosensitization rates to these pollen types was observed during the most recent period.
Bryophyte spores are a routinely overlooked component of airborne bioaerosols, in contrast to well-studied fungal spores. We assessed airborne bryophyte spores in the urban atmosphere of Bratislava (Slovakia) by combining long-term temporal monitoring with a spatial, land-use-based comparison, using complementary methods. Long-term variability was characterised from a ten-year rooftop dataset (2016–2025) collected with a Hirst-type volumetric trap. In 2025, ground-level occurrence was compared across four land-use types (urban core, garden, park, and peri-urban forest park) using personal volumetric samplers, combined with microscopy, cultivation with PCR-based identification, and Oxford Nanopore metabarcoding. Bryophyte spores occurred at consistently low concentrations and were detected sporadically. They were not recovered by metabarcoding, and cultivation yielded the green alga Klebsormidium sp. rather than any moss. Over the ten years, peak daily concentrations showed a significant increasing trend, whereas annual spore integrals rose weakly and non-significantly. Relative humidity was the most consistent environmental driver, with spore concentrations increasing under more humid conditions. In the ground-level samples, fungal spores dominated among the 54 recorded spore types, with Cladosporium most abundant, and the peri-urban forest park showed the highest type richness and concentrations. Metabarcoding confirmed a diverse community dominated by Ascomycota and Basidiomycota. The weak airborne bryophyte signal, evident across every method, reflects ecological constraints on spore production and release, although the relative contributions of ecological and methodological factors could not be fully disentangled. The contrast with the abundant, land-use-structured fungal community underscores how dispersal strategy shapes airborne presence. The study highlights the value of combining microscopy, cultivation, and molecular approaches when targeting low-abundance bioaerosol taxa.
Plane trees (Platanus spp.) provide important ecosystem services but are also among the most allergenic urban tree species. Although local pollen sources are expected to strongly influence pedestrian-level exposure, the spatial relationship between pollen sources and measured pollen concentrations remains poorly understood. In particular, quantitative information on the effective dispersal distance of pollen grains remains limited, constraining the development of high-resolution pollen forecasts. We measured Platanus pollen concentrations at ground level (four sites) and at a rooftop reference site during the 2025 pollen season in Poznań, Poland. Platanus crown volume was estimated from airborne LiDAR data and integrated with wind conditions to calculate a daily pollen source strength index. Incremental buffer analysis (100–1600 m) was performed to identify the distance at which surrounding trees best explained local pollen concentrations. Pollen concentrations showed substantial spatial variability; however, no statistically significant differences were observed between co-located ground- and rooftop-level samplers. The strongest correlation between local pollen concentrations and surrounding pollen sources was observed within an 800 m radius (r = 0.406, p < 0.001), whereas both smaller and larger buffer distances showed weaker relationships. These findings indicate that the effective influence distance of local Platanus pollen sources is approximately 800 m, suggesting that trees beyond this distance have only a limited influence on local pollen concentrations. Our findings provide an evidence-based parameter for source-area delineation in local pollen forecasting models and may support allergy management and urban tree planting strategies.
Airborne pollen is an important environmental trigger of allergic diseases, but evidence on its short-term health effects remains limited in coastal cities of northeastern China. This study investigated the seasonal dynamics of airborne pollen, its associations with meteorological variables and air pollutants, and its short-term lagged associations with outpatient visits for common allergic diseases in Dalian from March to October 2024. Daily pollen deposition density was measured using a gravimetric method, and daily meteorological, air pollution, and outpatient visit data were collected over the same period. Spearman correlation analysis, generalized additive models, and distributed lag non-linear models were used to assess environmental associations and lagged health effects. A bimodal pollen pattern was observed, with a major spring peak dominated by tree pollen and a secondary late summer–autumn peak dominated by herbaceous pollen, especially Artemisia. Pollen deposition density was negatively associated with humidity and precipitation and positively associated with wind force, PM10, SO2, NO2, and CO. Higher pollen exposure was associated with increased outpatient visits for allergic rhinitis and allergic conjunctivitis, with the relative risk peaking at lag 1 day and lag 3 days, respectively. No clear lagged association was identified for allergic asthma. These findings support the use of local pollen monitoring for aerobiological surveillance and short-term early warning of allergy-related health risks in coastal urban settings.
Pollen allergy is an increasing public health concern in Europe, as climate warming alters flowering phenology and airborne pollen dynamics. This study analysed temporal and spatial changes in pollen seasons in Estonia using aerobiological monitoring data from Tartu, Tallinn, and Pärnu. Temporal changes were assessed by comparing two monitoring periods in Tartu (1990–1998 and 2012–2022), while spatial differences were evaluated across stations in contrasting climatic settings. Annual mean air temperature in Tartu increased by 1.1 °C between the two study periods, with the strongest warming occurring in winter and early spring. The results demonstrate a clear advancement of flowering phenology in early-spring taxa. The 1st day of intensive birch (Betula) flowering advanced by approximately 4 days in Tartu, while alder (Alnus) flowering began substantially earlier in warm years, with the first intensive pollen episodes occurring up to 23 days earlier than during the 1990s. Inland Tartu consistently exhibited higher and longer-lasting pollen concentrations than the coastal sites of Tallinn and Pärnu. Statistical modelling showed that flowering onset can be predicted with moderate to very high accuracy using temperature-related variables. The best-performing models included mean temperature and daily degrees above 5 °C (DD5), while precipitation was not a significant predictor. Model prediction uncertainty ranged from 1 to 8 days depending on taxon. These findings highlight the need for updated pollen calendars and continuous aerobiological monitoring under ongoing climate warming. Sustained funding is essential to ensure timely and spatially representative pollen information, particularly in small countries where monitoring networks remain vulnerable to financial constraints.
