OBJECTIVE:Evidence linking pollen exposure to asthma exacerbations is limited and inconsistent across regions, pollen types, and age groups. We assessed the association between pollen concentrations and asthma-related hospital admissions across England at high spatial resolution. MATERIALS AND METHODS:We use unplanned asthma admissions records (2008-2022) from Hospital Episode Statistics, linked to 10-km gridded data on alder and birch pollen. Tree pollen exposure was categorised as low, medium, or high. Age-specific case time series analyses were conducted using conditional Poisson regression, controlling for temperature and air pollutants (PM2.5 and NO2). Analyses were restricted to January-August, when tree pollen is present. RESULTS:Elevated asthma admission risk was associated with both pollen types, with a non-linear exposure-response that increased sharply at low levels and attenuated at higher exposures. For alder pollen, relative risks (RRs) across all ages were 1.014 (95%CI: 0.998, 1.031) for low, 1.026 (1.007, 1.046) for medium, and 1.019 (0.995, 1.044) for high exposure. For birch, RRs were 1.016 (0.996, 1.037), 1.041 (1.019, 1.06), and 1.032 (1.005, 1.060), respectively. Risks were mostly limited to children, with medium alder pollen exposure associated with RRs of 1.047 (0.993, 1.105) and 1.112 (1.066, 1.159), and birch with RRs of 1.131 (1.066, 1.201) and 1.079 (1.029, 1.131) in 0-4 and 5-14-year-olds, respectively. No evidence of association was found in older groups. CONCLUSION:Moderate tree pollen levels are associated with increased asthma admissions in younger populations in England. Further work is needed to understand group and individual susceptibility.

ABSTRACT Allergic Rhinitis and its Impact on Asthma (ARIA) was, up until 2017, a guideline using the best evidence (Grading of Recommendations, Assessment, Development and Evaluation, GRADE) and developed as a change management strategy. A second change management strategy—in collaboration with the European Academy of Allergy and Clinical Immunology (ARIA‐EAACI)—was developed as a person‐centred, digitally enabled, artificial intelligence‐assisted care (person‐centred care) with strong political involvement. The digital tools of ARIA are mainly based on MASK‐air, an Organisation for Economic Co‐operation and Development (OECD) Best Practice for integrated care for chronic diseases. Artificial intelligence was used, in particular, to approach the patients' views and expectations. The current paper describes the steps to build and achieve a new change management strategy. The future of the Change Management strategy is (i) a collaboration between ARIA and EAACI, (ii) the development of ARIA 2024‐2025 guidelines, (iii) the new ARIA‐MeDALL classification of multimorbid airway diseases and (iv) embedding MASK‐air in a registry for severe allergic diseases. The ultimate goals of the ARIA‐EAACI change management strategy will be (i) the transformation of health and care in rhinitis and asthma multimorbidity and (ii) the development of novel guidelines and policies in a cost‐effective manner, improving shared‐decision‐making.

Abstract. We analyze the MODIS and VIIRS active-fire Fire Radiative Power (FRP) products and suggest an approximation for the FRP detection limit as a linear function of a pixel area and develop analytical observation operators for both pixel-level and gridded FRP products. We have shown that the collection-6.1 of MODIS has the FRP detection limit at 3.7 MW in case of a nadir retrieval at a clear-sky night. For a daytime sideview, it reaches as high as 40 MW. For VIIRS, the smallest fire reliably detected at night is 0.5 MW. Application of the developed operators for the cross-mapping the MODIS and VIIRS datasets at the pixel/granule level confirmed their consistency. Applying the grid-level operators alongside satellite overpass and weather data, we generated global maps of fire detection probabilities, revealing regional variations. As a global average, probability of detection of powerful fires is 78 % for MODIS (88 % for VIIRS). Variations between regions are large: in some equatorial areas this probability is less than 30 % for MODIS (40% for VIIRS).

We present a DNA extraction protocol for atmospheric bioaerosol samples collected on glass-fiber filters widely used in air quality monitoring. The protocol produces high-quality molecules suitable for third-generation sequencing and other applications. The initial protocol was developed and applied in a Bioaerosol campaign performed in Finland and Lithuania in 2021 using low-volume air samplers, which posed stringent requirements to the method sensitivity. The protocol included a phenol-chloroform step for DNA purification, thus involving aggressive reagents; it was also quite time consuming and laborious. The present study advances this protocol to exclude the use of hazardous chemicals by using the SPRI paramagnetic bead technology for DNA purification and compares it to several commercial extraction methods. Despite trailing in efficiency to the initial method, the new development proved to be more efficient than several column-based commercial kits. The updated protocol was effective for a relatively high mass ratio of biological material to filter material: 70 nanograms of potential DNA on the filter to one milligram of filter fiber, as detected with the initial phenol-chloroform-based method. However, the new approach was not effective for a mass ratio lower than 15 nanograms of potential DNA per milligram of the filter material. The applicability of the new protocol for preparation of samples for the 3rd generation sequencing was confirmed by subsequent processing of the samples with the Oxford Nanopore (ONT) GridION sequencer.

We demonstrate that the proportionality between a deposition flux and a corresponding concentration usually does not hold for ambient aerosol. Therefore the deposition velocity Vd, defined as the proportionality coefficient, while might exist for some components of the aerosol, is not applicable to aerosol as a bulk substance or to a size mode of it. Insufficient attention to the proportionality requirement leads to large discrepancies between field and wind-tunnel measurements of Vd of aerosols with aerodynamic diameters ranging from approximately 0.1 to 2 & micro;m. In seemingly similar conditions, the deposition velocities reported in different experiments may differ by up to two orders of magnitude, with field measurements showing much higher values than experiments performed in controlled environments with known particle properties. We demonstrate that the bulk of the discrepancy can be explained by gas-particle partitioning in the immediate vicinity of the surface. With the chemistry-transport model SILAM equipped with gas-particle partitioning for ammonium nitrate, we demonstrate that in presence of even small amounts of ammonium nitrate, the vertical flux of total aerosol mass is not controlled by particle deposition but rather by aerosol-gas partitioning in the vicinity of the surface. Under these conditions, the deposition flux is not proportional to the concentration, and the concept of deposition velocity as a proportionality coefficient between concentration and deposition flux falls apart. Presence of other semi-volatile components in ambient aerosols may further complicate the case, but ammonium nitrate alone is sufficient to invalidate the concept for ambient aerosol. By simulating a renowned field experiment with the SILAM model, we are able to reproduce the magnitudes and temporal behaviors of ambient particle fluxes using the deposition parameterization derived from wind-tunnel studies. Combining these simulations with a set of computational experiments, we suggested guidelines for accounting for the relevant processes in regional atmospheric composition models.

Different herbaceous plant species release allergenic pollen that can have adverse effects on human health. Climate change, which alters plant physiology and phenology, can affect airborne pollen levels, increasing the risk for allergy sufferers. This study examines trends in airborne pollen concentrations and seasonal characteristics, aiming to identify potential shifts in the onset, end, and duration of the main pollen seasons of herbaceous plant species over the last few decades, with particular attention to exploring the association between phenological changes and climate parameters. Moreover, forecasting scenarios of pollen season features trends concerning the meteorological variables we presented. To this purpose, data from the aerobiological station of the Milan area (Legnano, Lombardy, Italy), located in one of the most invaded parts by Ambrosia artemisiifolia in Italy and Europe, and characterized by a time series of nearly 30 years, from 1995 to 2022, were analysed. The results showed a clear correlation between main pollen season features and meteorological variables for Poaceae, Urticaceae, Artemisia and Ambrosia. Generally, increasing temperature and solar radiation were linked to an anticipated onset of the pollen season, while precipitation and relative humidity to an earlier end date. Moreover, in the study areas, a strong increase in annual average temperature has been observed since 1975, projected to continue over the next 60 years. This increase was predicted to lead to an earlier start and longer duration of the pollen season for weed species, potentially advancing by up to 2 weeks over 60 years. These findings indicate an elevated risk of exposure for individuals with allergies in the short term and underscore the urgent need to implement long-term monitoring frameworks for both ecological and public health purposes.

Climatic feedbacks and ecosystem impacts related to dust in the Arctic include direct radiative forcing (absorption and scattering), indirect radiative forcing (via clouds and cryosphere), semi-direct effects of dust on meteorological parameters, effects on atmospheric chemistry, as well as impacts on terrestrial, marine, freshwater, and cryospheric ecosystems. This review discusses our recent understanding on dust emissions and their long-range transport routes, deposition, and ecosystem effects in the Arctic. Furthermore, it demonstrates feedback mechanisms and interactions between climate change, atmospheric dust, and Arctic ecosystems.

Acute exposure to emissions from fires presents a significant and immediate threat to human health. Inhalation of wildfire smoke and other pollutants can lead to various health issues, including respiratory and cardiovascular problems. Our study uses the SILAM chemical transport model, integrated with the IS4FIRES fire information system, to assess population exposure to fire-related PM2.5, along with the health burden from all-cause, respiratory, and cardiovascular deaths. Our results show that while population-weighted all-source PM2.5 exposure has declined in Europe and high-income North America, fire-PM2.5 exposure has increased significantly in Eastern and Central Europe, high-income North America, Tropical Latin America, and sub-Saharan Africa. Extreme fire-PM2.5 events have tripled globally since the 1990s, with more than half of the global population experiencing minimum perpetual fire occurrence (at least 1% of fire-PM2.5 in PM2.5 for 50 instances of 3 consecutive days in a calendar year) in 2010–2018. Acute exposure to fire-PM2.5 contributed to 99,000 (95% CI: 55,000–149,000) all-cause deaths annually in 2010–18, with significant cardiovascular and respiratory disease burdens, particularly in Eastern Europe and sub-Saharan Africa. Our findings highlight the escalating health risks of fire emissions, emphasizing the urgent need for mitigation strategies as fire-PM2.5 becomes a growing contributor to global air pollution-related mortality.

The Copernicus Atmosphere Monitoring Service (CAMS) delivers a wide range of free and open products in relation to atmospheric composition at global and regional scales. The CAMS Regional Service produces daily forecasts, analyses, and reanalyses of air quality in Europe. This service relies on a distributed modelling production by 11 teams in 10 European countries: CHIMERE (France), DEHM (Denmark), EMEP (Norway), EURAD-IM (Germany), GEM-AQ (Poland), LOTOS-EUROS (the Netherlands), MATCH (Sweden), MINNI (Italy), MOCAGE (France), MONARCH (Spain), and SILAM (Finland). The project management and coordination of the service is conducted by a Centralised Regional Production Unit. Every day, each model produces 24 h analyses for the previous day and 97 h forecasts for 19 chemical species over a spatial domain at 0.1 x 0.1 degrees resolution (approximately 10 km x 10 km), with 420 points in latitude and 700 in longitude and 10 vertical levels. Six pollen species are also delivered for the surface forecasts. The 11 individual models are then combined into an ENSEMBLE median. In total, more than 82 billion data points are made available for public use on a daily basis.The design of the system follows clear technical requirements in terms of consistency in the model setup and forcing fields (meteorology, surface anthropogenic emission fluxes, and chemical boundary conditions). But it also benefits from a diversity in the description of atmospheric processes through the design of the 11 European chemistry-transport models (CTMs) involved.The present article aims to provide a comprehensive technical documentation, both for the setup and for the diversity of CTMs involved in the service. We also include an overview of the main output products, their public dissemination, and the related evaluation and quality control strategy.

Dry deposition is an important process of removal of various airborne substances from the atmospheric boundary layer. In many applications it is convenient to assume that the deposition flux of a substance is proportional to the near-surface concentration, and that the proportionality coefficient does not depend on particle concentration. This assumption is based on the idea of a constant-flux layer between the reference height and the surface, and holds for substances that have no sources/sinks in the layer. The deposition velocity concept is a core part of dry deposition schemes of atmospheric transport models.We address large discrepancies between field and wind-tunnel measurements of deposition velocities of aerosols with aerodynamic diameter between approximately 0.1µm and 2µm. In seemingly similar conditions, deposition velocities derived from field measurements are in range of 1-10 cm/s, while wind-tunnel measurements show a fraction of a millimeter per second. This difference translates to the discrepancy in dry deposition parametrizations. SILAM chemistry transport model features a dry deposition scheme for particles by Kouznetsov and Sofiev (2012, https://doi.org/10.1029/2011JD016366) that predicts 'low' deposition velocities. With such a scheme, simulations that explicitly account for aerosol transformations are able to reproduce the ambient observed fluxes and agree well with the 'high' apparent deposition velocity. A regional simulation covering the period of the Gallagher (2007, https://doi.org/10.1016/S1352-2310(96)00057-X) field campaign was capable of reproducing both magnitude and temporal evolution of aerosol fluxes measured over a forest. We demonstrate that the conservation of aerosol mass in the immediate vicinity of the surface is not fulfilled for ambient aerosols when the aerosols include a fraction of ammonium nitrate. For such a mixture the fluxes of ambient aerosols are not controlled by particle deposition but rather by gas-particle partitioning in the vicinity of the surface and by the deposition flux of nitric acid. The particle flux does not depend on particle concentrations in quite a wide concentration range. For such a mixture the entire concept of deposition velocity is inapplicable. Simulations of atmospheric aerosol composition show that the presence of ammonium nitrate as a part of aerosol is rather common in many places of the world. Moreover, we are not aware of any publication that demonstrates a linear dependency between the flux and concentration for ambient accumulation-mode aerosols. Based on our findings and the results of wind tunnel measurements we suggest that field campaigns could observe detectable fluxes of aerosol only if the fluxes were caused by aerosol processes in air. Therefore, such measurements cannot be used to directly infer particle deposition velocities, and the measurements with known conservative particles should be used instead. Parametrizations of deposition velocities that are based on the field-measured fluxes do not predict flux-concentration relation for particles if ammonium nitrate is present, and strongly over-deposit conservative aerosols. Therefore, the parametrizations based on wind-tunnel measurements with calibrated particles should be used instead, despite high-vegetation cases are not covered by such experiments.

Abstract. The process of dry deposition in chemistry-transport models is usually implemented assuming a proportionality between the deposition flux and the corresponding concentration of a tracer at some reference height. The coefficient of proportionality, called deposition velocity, Vd, is to be parameterized and validated experimentally. We analyse large discrepancies between field and wind-tunnel measurements of Vd of aerosols with aerodynamic diameters ranging from approximately 0.1 μm to 2 μm. In seemingly similar conditions, the deposition velocities reported in different experiments may differ by up to two orders of magnitude, with field measurements showing much higher values than experiments performed in controlled environments with known particle properties. We demonstrate that the bulk of the discrepancy can be explained by fast chemical reactions and a particle-to-gas conversion in the immediate vicinity of the surface. By applying the chemistry-transport model SILAM, equipped with gas-particle partitioning for ammonium nitrate, we demonstrate that in the presence of even small amounts of ammonium nitrate, the vertical flux of total aerosol mass is not controlled by particle deposition but rather by aerosol-gas partitioning in the vicinity of the surface. While there are many other non-conservative components in ambient aerosols apart from ammonium nitrate, we demonstrate that the abundance of ammonium nitrate alone is sufficient to render typical ambient aerosol into a non-conservative substance. Under these conditions, the deposition flux is not proportional to the concentration, and the concept of deposition velocity as a proportionality coefficient between concentration and deposition flux falls apart. By simulating a renowned field experiment with the SILAM model, we are able to reproduce the magnitudes and temporal behaviors of ambient particle fluxes using the deposition parameterization derived from wind-tunnel studies.

Summary: This study examines how climate-induced health risks influence negative sentiments on European social tweets from 2015 to 2022. Analyzing over 400 million tweets using NLP tools (NLTK, LIWC22) and spatial-temporal aggregation at the NUTS2 weekly level, we applied a Poisson generalized additive model (GAM) with integrated nested Laplace approximation (INLA) and fused lasso regularization to capture sentiment fluctuations. Results show negative sentiments rise by up to 0.36% when maximum temperatures exceed 26.9°C and by 0.49% during severe droughts (SPI < −3.72). Elevated alder pollen counts (>135 grains/m3) also increase risk of negative sentiment by 0.21%, while temperatures below 2.9°C reduce it by 0.63%. No significant association was found with heat-related mortality or West Nile virus incidence. These findings suggest specific climate-related health factors—high temperatures, droughts, and pollen—trigger negative social media reactions, whereas others, such as mortality and infectious outbreaks, appear unnoticed in public sentiment.

Cypress species and other members of the Cupressaceae family are widespread evergreen trees and shrubs, commonly used as ornamental plants. Some species, such as Mediterranean cypress (Cupressus sempervirens), Arizona cypress (Cupressus arizonica), and prickly juniper (Juniperus oxycedrus), widespread in Mediterranean, cause significant allergic reactions. This study aimed to develop a phenological model for Southern and Central Europe to predict the timing of cypress pollen release, enabling integration into atmospheric models for pollen dispersion forecasts. A key challenge is the microscopic similarity of all Cupressaceae pollen grains, which prevents species-level identification. Consequently, pollen observations report total Cupressaceae counts, complicating phenological modeling of allergenic species. For early-flowering species, thermal time models, such as growing degree days (GDD) or growing degree hours (GDH), are suitable. These models require defining a heat accumulation start date, a temperature threshold, and the cumulative heat required for flowering. Geographic variability and ornamental planting further influence flowering patterns, even between neighbouring locations. Pollen data were obtained from the European Aeroallergen Network (EAN), and temperature data from the ERA5 reanalysis dataset. Testing three start dates of the accumulation revealed that the autumn equinox was too early, while January 1st was too late, as J. oxycedrus and C. arizonica may flower before the new year. November 30th was optimal for detailed analysis. GDD/GDH was calculated using thresholds of 0°C, 1°C, 2°C, and 5°C, with normalized GDH (nGDH) yielding the most accurate results. When flowering onset was defined as 5% of the seasonal pollen index (SPI), the median GDH requirements ranged from 0.06–0.15 nGDH0 (SD 0.01–0.05) to 0.01–0.06 nGDH5 (SD 0–0.02). A 5°C threshold was too high leading to insufficient heat accumulation sensitivity, while 0°C was too low due to higher variability between years. Thresholds of 1°C and 2°C provided optimal accuracy with moderate inter-annual variability, making them suitable for forecasting the flowering onset.

The World Health Organization (WHO) updated its Global Air Quality Guidelines in 2021 due to growing evidence on adverse health impacts of air pollution even at low concentrations. We used a suite of regional atmospheric chemistry models to simulate fine particulate matter (PM2.5) and ozone (O3) levels over Europe in 2015–2050 and assessed the compliance of European countries with the new guidelines under different emission scenarios. The results show that 65% of the EU countries will comply with the PM2.5 target value (5 µg m−3) by 2050 under ambitious emission reductions (SSP1-2.6). Under less ambitious mitigation scenarios (SSP2-4.5 and SSP3-7.0), the compliance level is only 10%. In addition, none of the EU countries will comply with the O3 target value (60 µg m−3), while interim values are achieved in most of the EU countries, partly under SSP2-4.5, and to a large extent under SSP1-2.6. These results highlight that reaching the new WHO limit values will be challenging for Europe, partly due to natural contribution to PM2.5 reaching up to 50% in some regions. Our findings imply the necessity of more drastic emission reductions to meet the targets.

In Europe a quarter of the adult population and a third of all children suffer from allergenic airborne pollen thereby decreasing the quality of life. In order to ease the pollen induced symptoms mitigation measures can be applied. This, however, requires timely information on forthcoming pollen episodes derived from early warning systems. These systems can substantially be improved when pollen observations from strategically well-chosen pollen monitoring stations are assimilated. Here we explore the network quality (i) and network coverage (ii) of the current five pollen monitoring stations in Belgium. As reference dataset we use the spatio-temporal distributions of daily surface airborne birch and grass pollen levels as produced by the operational early warning system for pollen on the website of the Royal Meteorological Institute of Belgium. This system implements the SILAM model (System for Integrated modeLling of Atmospheric coMposition) and ECMWF meteorological data. The ability of the network to reproduce the concentration field over the region of interest is quantified by the RMSE computed from the reference concentration field and the interpolated concentration field for each day of the pollen season. In the first step, time series of the current daily pollen observations in the network are interpolated over space by applying the radial-based function. This results in the daily interpolated concentration fields which we compare with the spatially distributed daily reference data. For evaluating the network coverage of the current five monitoring stations we perform a footprint-based analysis. Footprints relate directly to the fraction of air reaching the monitoring device. By applying pollen emission point sources in the five stations into SILAM that is run in the backward mode (three days back), we can investigate the travelling trajectory of the captured birch and grass pollen in the air observed at the network stations. Nine pollen seasons (2013-2021) were analyzed using ECMWF ERA5 meteorology. First results on the network quality for birch pollen show that over a period of nine pollen seasons more than 60% of the daily RMSE values derived from the interpolated daily concentrations are less than their mean value. This is an indication that the interpolated network performs well compared to the spatio-temporal reference dataset derived from SILAM. For the 2013 birch pollen season more than 80% is reached. In contrast, this is only ~40% for 2020. The applied time scale is of great importance, since at smaller time scales (days, hours) network configurations may degrade faster than on larger time steps (weeks, months, seasons). The footprint-based analysis shows that on average the coverage of the monitoring stations for birch pollen is quite good. There are, however, large differences during the 2013-2022 seasons which might be due to the typical large inter-seasonal variation in birch pollen production. For grass pollen, the average coverage is better, and the inter-seasonal variation much lower.

Accurate estimates of biomass burning (BB) emissions are of great importance worldwide due to the impacts of these emissions on human health, ecosystems, air quality, and climate. Atmospheric modeling efforts to represent these impacts require BB emissions as a key input. This paper is presented by the Biomass Burning Uncertainty: Reactions, Emissions and Dynamics (BBURNED) activity of the International Global Atmospheric Chemistry project and largely based on a workshop held in November 2023. The paper reviews 9 of the BB emissions datasets widely used by the atmospheric chemistry community, all of which rely heavily on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations of fires scheduled to be discontinued at the end of 2025. In this time of transition away from MODIS to new fire observations, such as those from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments, we summarize the contemporary status of BB emissions estimation and provide recommendations on future developments. Development of global BB emissions datasets depends on vegetation datasets, emission factors, and assumptions of fire persistence and phase, all of which are highly uncertain with high degrees of variability and complexity and are continually evolving areas of research. As a result, BB emissions datasets can have differences on the order of factor 2–3, and no single dataset stands out as the best for all regions, species, and times. We summarize the methodologies and differences between BB emissions datasets. The workshop identified 5 key recommendations for future research directions for estimating BB emissions and quantifying the associated uncertainties: development and uptake of satellite burned area products from VIIRS and other instruments; mapping of fine scale heterogeneity in fuel type and condition; identification of spurious signal detections and information gaps in satellite fire radiative power products; regional modeling studies and comparison against existing datasets; and representation of the diurnal cycle and plume rise in BB emissions.