Influence of meteorological variables and air pollutants on measurements from automatic pollen sampling devices.

This study examines the influence of meteorological factors and air pollutants on the performance of automatic pollen monitoring devices, as part of the EUMETNET Autopollen COST ADOPT-intercomparison campaign held in Munich, Germany, during the 2021 pollen season. The campaign offered a unique opportunity to compare all automatic monitors available at the time, a Plair Rapid-E, a Hund-Wetzlar BAA500, an OPC Alphasense, a KH-3000 Yamatronics, three Swisens Polenos, a PollenSense APS, a FLIR IBAC2, a DMT WIBS-5, an Aerotape Sextant, to the average of four manual Hirst traps, under the same environmental conditions. The investigation aimed to elucidate how meteorological factors and air pollution impact particle capture and identification efficiency. The analysis showed coherent results for most devices regarding the correlation between environmental conditions and pollen concentrations. This reflects on one hand, a significant correlation between weather and airborne pollen concentration, and on the other hand the capability of devices to provide meaningful data under the conditions under which measurements were taken. However, correlation strength varied among devices, reflecting differences in design, algorithms, or sensors used. Additionally, it was observed that different algorithms applied to the same dataset resulted in different concentration outputs, highlighting the role of algorithm design in these systems (monitor + algorithm). Notably, no significant influence from air pollutants on the pollen concentrations was observed, suggesting that any potential difference in effect on the systems might require higher air pollution concentrations or more complex interactions. However, results from some monitors were affected to a minor degree by specific weather variables. Our findings suggest that the application of real-time devices in urban environments should focus on the associated algorithm that classifies pollen taxa. The impact of air pollution, although not to be excluded, is of secondary concern as long as the pollution levels are similar to a large European city like Munich.

From MASK-air and SILAM to CATALYSE (Climate Action To Advance HeaLthY Societies in Europe).

Plant species vary under different climatic conditions and the distribution of pollen in the air. Trends in pollen distribution can be used to assess the impact of climate change on public health. In 2015, the Mobile Airways Sentinel networK for rhinitis and asthma (MASK-air®) was launched as a project of the European Innovation Partnership on Active and Healthy Ageing (EIP-on-AHA, DG Santé and DG CONNECT). This project aimed to develop a warning system to inform patients about the onset of the pollen season, namely, the System for Integrated modeLling of Atmospheric coMposition (SILAM). A global-to-meso-scale dispersion model was developed by the Finnish Meteorological Institute (FMI). It provides quantitative information on atmospheric pollution of anthropogenic and natural origins, particularly on allergenic pollens. Impact of Air Pollution on Asthma and Rhinitis (POLLAR, EIT Health) has combined MASK-air clinical data with SILAM forecasts. A new Horizon Europe grant (Climate Action to Advance HeaLthY Societies in Europe [CATALYSE]; grant agreement number 101057131), which came into force in September 2022, aims to improve our understanding of climate change and help us find ways to counteractit. One objective of this project is to develop early warning systems and predictive models to improve the effectiveness of strategies for adapting to climate change. One of the warning systems is focused on allergic rhinitis (CATALYSE Task 3.2), with a collaboration between the FMI (Finland), Porto University (Portugal), MASK-air SAS (France), ISGlobal (Spain), Hertie School (Germany), and the University of Zurich (Switzerland). It is to be implemented with the support of the European Academy of Allergy and Clinical Immunology. This paper reports the planning of CATALYSE Task 3.2.

Estimated health impacts from maritime transport in the Mediterranean region and benefits from the use of cleaner fuels.

Ship traffic emissions degrade air quality in coastal areas and contribute to climate impacts globally. The estimated health burden of exposure to shipping emissions in coastal areas may inform policy makers as they seek to reduce exposure and associated potential health impacts. This work estimates the PM2.5-attributable impacts in the form of premature mortality and cardiovascular and respiratory hospital admissions, from long-term exposure to shipping emissions. Health impact assessment (HIA) was performed in 8 Mediterranean coastal cities, using a baseline conditions from the literature and a policy case accounting for the MARPOL Annex VI rules requiring cleaner fuels in 2020. Input data were (a) shipping contributions to ambient PM2.5 concentrations based on receptor modelling studies found in the literature, (b) population and health incidence data from national statistical registries, and (c) geographically-relevant concentration-response functions from the literature. Long-term exposure to ship-sourced PM2.5 accounted for 430 (95% CI: 220-650) premature deaths per year, in the 8 cities, distributed between groups of cities: Barcelona and Athens, with >100 premature deaths/year, and Nicosia, Brindisi, Genoa, Venice, Msida and Melilla, with tens of premature deaths/year. The more stringent standards in 2020 would reduce the number of PM2.5-attributable premature deaths by 15% on average. HIA provided a comparative assessment of the health burden of shipping emissions across Mediterranean coastal cities, which may provide decision support for urban planning with a special focus on harbour areas, and in view of the reduction in sulphur content of marine fuels due to MARPOL Annex VI in 2020.

On impact of transport conditions on variability of the seasonal pollen index.

This discussion paper reveals the contribution of pollen transport conditions to the inter-annual variability of the seasonal pollen index (SPI). This contribution is quantified as a sensitivity of the pollen model predictions to meteorological variability and is shown to be a noticeable addition to the SPI variability caused by plant reproduction cycles. A specially designed SILAM model re-analysis of pollen seasons 1980-2014 was performed, resulting in the 35 years of the SPI predictions over Europe, which was used to compute the SPI inter-annual variability. The current paper presents the results for birch and grass. Throughout the re-analysis, the source term formulations and habitation maps were kept constant, which allowed attributing the obtained variability exclusively to the pollen release and transport conditions during the flowering seasons. It is shown that the effect is substantial: it amounts to 10-20% (grass) and 20-40% (birch) of the observed SPI year-to-year changes reported in the literature. The phenomenon has well-pronounced spatial- and species-specific patterns. The findings were compared with observation-based statistical models for the SPI prediction, showing that such models highlight the same processes as the analysis with the SILAM model.

Defining pollen exposure times for clinical trials of allergen immunotherapy for pollen-induced rhinoconjunctivitis - an EAACI position paper.

BACKGROUND: Clinical efficacy of pollen allergen immunotherapy (AIT) has been broadly documented in randomized controlled trials. The underlying clinical endpoints are analysed in seasonal time periods predefined based on the background pollen concentration. However, any validated or generally accepted definition from academia or regulatory authorities for this relevant pollen exposure intensity or period of time (season) is currently not available. Therefore, this Task Force initiative of the European Academy of Allergy and Clinical Immunology (EAACI) aimed to propose definitions based on expert consensus. METHODS: A Task Force of the Immunotherapy and Aerobiology and Pollution Interest Groups of the EAACI reviewed the literature on pollen exposure in the context of defining relevant time intervals for evaluation of efficacy in AIT trials. Underlying principles in measuring pollen exposure and associated methodological problems and limitations were considered to achieve a consensus. RESULTS: The Task Force achieved a comprehensive position in defining pollen exposure times for different pollen types. Definitions are presented for 'pollen season', 'high pollen season' (or 'peak pollen period') and 'high pollen days'. CONCLUSION: This EAACI position paper provides definitions of pollen exposures for different pollen types for use in AIT trials. Their validity as standards remains to be tested in future studies.

Airborne olive pollen counts are not representative of exposure to the major olive allergen Ole e 1.

Pollen is routinely monitored, but it is unknown whether pollen counts represent allergen exposure. We therefore simultaneously determined olive pollen and Ole e 1 in ambient air in Córdoba, Spain, and Évora, Portugal, using Hirst-type traps for pollen and high-volume cascade impactors for allergen. Pollen from different days released 12-fold different amounts of Ole e 1 per pollen (both locations P < 0.001). Average allergen release from pollen (pollen potency) was much higher in Córdoba (3.9 pg Ole e 1/pollen) than in Évora (0.8 pg Ole e 1/pollen, P = 0.004). Indeed, yearly olive pollen counts in Córdoba were 2.4 times higher than in Évora, but Ole e 1 concentrations were 7.6 times higher. When modeling the origin of the pollen, >40% of Ole e 1 exposure in Évora was explained by high-potency pollen originating from the south of Spain. Thus, olive pollen can vary substantially in allergen release, even though they are morphologically identical.

A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module.

A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper.

Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study.

This paper considers the feasibility of numerical simulation of large-scale atmospheric transport of allergenic pollen. It is shown that at least small grains, such as birch pollen, can stay in the air for a few days, which leads to a characteristic scale for their transport of approximately 10(3) km. The analytical consideration confirmed the applicability of existing dispersion models to the pollen transport task and provided some reference parameterizations of the key processes, including dry and wet deposition. The results were applied to the Finnish Emergency Dispersion Modelling System (SILAM), which was then used to analyze pollen transport to Finland during spring time in 2002-2004. Solutions of the inverse problems (source apportionment) showed that the main source areas, from which the birch flowering can affect Finnish territory, are the Baltic States, Russia, Germany, Poland, and Sweden-depending on the particular meteorological situation. Actual forecasting of pollen dispersion required a birch forest map of Europe and a unified European model for birch flowering, both of which were nonexistent before this study. A map was compiled from the national forest inventories of Western Europe and satellite images of broadleaf forests. The flowering model was based on the mean climatological dates for the onset of birch forests rather than conditions of any specific year. Utilization of probability forecasting somewhat alleviated the problem, but the development of a European-wide flowering model remains the main obstacle for real-time forecasting of large-scale pollen distribution.

Can the confidence in long range atmospheric transport models be increased? The pan-european experience of ensemble.

Is atmospheric dispersion forecasting an important asset of the early-phase nuclear emergency response management? Is there a 'perfect atmospheric dispersion model'? Is there a way to make the results of dispersion models more reliable and trustworthy? While seeking to answer these questions the multi-model ensemble dispersion forecast system ENSEMBLE will be presented.