Modeling the dispersion of Ambrosia artemisiifolia L. pollen with the model system COSMO-ART

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.

China-US grain trade shapes the spatial genetic pattern of common ragweed in East China cities

Common ragweed is an invasive alien species causing severe allergies in urban residents. Understanding its urban invasion pathways is crucial for effective control. However, knowledge is limited, with most studies focusing on agricultural and natural areas, and occurrence record-based studies exhibiting uncertainties. We address this gap through a study in East China cities, combining population genetics and occurrence records. Leaf samples from 37 urban common ragweed populations across 15 cities are collected. Genomic and chloroplast DNA extraction facilitate analysis of spatial genetic patterns and gene flows. Additionally, international grain trade data is examined to trace invasion sources. Results indicate spatial genetic patterns impacted by multiple introductions over time. We infer the modern grain trade between the United States and China as the primary invasion pathway. Also, cities act as transportation hubs and ports of grain importation might disperse common ragweed to urban areas. Invasive species control should account for cities as potential landing and spread hubs of common ragweed.

Sensitization characteristics in allergic rhinitis and transport pathway for Artemisia pollen in northern Beijing, China

The genus Artemisia, an important allergen related to Allergic Rhinitis (AR), is widespread in temperate regions. However, the sensitization rate of Artemisia pollen varies significantly, and the source of Artemisia pollen is not clear. Based on continuous daily airborne pollen monitoring in the summer and autumn of 2019 and 2020 in northern Beijing, the daily number of AR patient visits during the same period, and the detection of allergen serum-specific immunoglobulin E (sIgE) in some AR patients, this study discusses the sensitization rate of Artemisia pollen and its transmission pathway and possible source area. The results show that (1) Artemisia pollen is the most important airborne pollen in summer and autumn in northern Beijing, and the pollen concentration is significantly related to the daily number of AR patient visits; (2) the rate of AR patients testing positive for Artemisia pollen allergens is 32.35 %, which is the first risk allergen and is consistent with the high sensitization rate of Artemisia pollen in northern China; and (3) in addition to local sources, central and southern Inner Mongolia, southern Mongolia and northwestern China are potential source areas of Artemisia pollen within the study area. This study provides first-hand data for accurately understanding the allergenic characteristics and sources of Artemisia pollen in northern Beijing and provides a scientific basis for the prevention of AR induced by Artemisia pollen in patients in China.

Climate change, airborne allergens, and three translational mitigation approaches

One of the important adverse impacts of climate change on human health is increases in allergic respiratory diseases such as allergic rhinitis and asthma. This impact is via the effects of increases in atmospheric carbon dioxide concentration and air temperature on sources of airborne allergens such as pollen and fungal spores. This review describes these effects and then explores three translational mitigation approaches that may lead to improved health outcomes, with recent examples and developments highlighted. Impacts have already been observed on the seasonality, production and atmospheric concentration, allergenicity, and geographic distribution of airborne allergens, and these are projected to continue into the future. A technological revolution is underway that has the potential to advance patient management by better avoiding associated increased exposures, including automated real-time airborne allergen monitoring, airborne allergen forecasting and modelling, and smartphone apps for mitigating the health impacts of airborne allergens.

Unusual early peaks of airborne ragweed (Ambrosia L.) pollen in the Pannonian Biogeographical Region

Early peaks of airborne ragweed (Ambrosia L.) pollen concentrations were observed at several monitoring stations in Hungary in June 2017 and 2018, one month before the usual start of the pollen season at the end of July. Backward trajectories were calculated to simulate potential sources of pollen collected at different locations in the Pannonian Biogeographical Region. In a collaboration between aerobiological and phenological networks, a nationwide campaign was conducted to collect field data of ragweed blooming. During field surveys, ragweed plants having extremely early blooming were found most abundantly in a rural site near Vaja (North-East Hungary) and other locations in Hungary. Field observations matched with source areas identified by trajectory analyses; i.e., early-flowering ragweed plants were found at some of these locations. Although similar peaks of airborne pollen concentrations were not detected in other years (e.g., 2016, 2019-2021), alarming results suggest the possibility of expanding seasons of ragweed allergy.

Aerobiological modelling II: A review of long-range transport models

The long-range atmospheric transport models of pollen and fungal spores require four modules for their development: (i) Meteorological module: which contain the meteorological model, and it can be coupled to transport model with the same output configuration (spatio-temporal resolution), or uncoupled does not necessarily have the same output parameters. (ii) Emission module: settles the mass fluxes of bioaerosol, it can be done with a complex parameterization integrating phenological models and meteorological factors or by a simple emission factor. (iii) Sources of emission module, specifically refers to forestry/agronomy maps or, in the case of herbs and fungi, to potential geographical areas of emission. Obtaining the highest possible resolution in these maps allows establishing greater reliability in the modelling. (iv) Atmospheric transport module, with its respective established output parameters. The review and subsequent analysis presented in this article, were performed on published electronic scientific articles from 1998 to 2016. Of a total of 101 models applied found in 64 articles, 33 % performed forward modelling (using 15 different models) and 67 % made backward modelling (with three different models). The 88 % of the cases were applied to pollen (13 taxa) and 12 % to fungal spores (3 taxa). Regarding the emission module, 22 % used parametrization (four different parameters) and 10 % emission factors. The most used transport model was HYSPLIT (59 %: 56 % backward and 3 % forward) following by SILAM 10 % (all forward). Main conclusions were that the models of long-range transport of pollen and fungal spores had high technical-scientific requirements to development and that the major limitations were the establishment of the flow and the source of the emission.

Modeling past and future spatiotemporal distributions of airborne allergenic pollen across the contiguous United States

Exposures to airborne allergenic pollen have been increasing under the influence of changing climate. A modeling system incorporating pollen emissions and atmospheric transport and fate processes has been developed and applied to simulate spatiotemporal distributions of two major aeroallergens, oak and ragweed pollens, across the contiguous United States (CONUS) for both historical (year 2004) and future (year 2047) conditions. The transport and fate of pollen presented here is simulated using our adapted version of the Community Multiscale Air Quality (CMAQ) model. Model performance was evaluated using observed pollen counts at monitor stations across the CONUS for 2004. Our analysis shows that there is encouraging consistency between observed seasonal mean concentrations and corresponding simulated seasonal mean concentrations (oak: Pearson = 0.35, ragweed: Pearson = 0.40), and that the model was able to capture the statistical patterns of observed pollen concentration distributions in 2004 for most of the pollen monitoring stations. Simulation of pollen levels for a future year (2047) considered conditions corresponding to the RCP8.5 scenario. Modeling results show substantial regional variability both in the magnitude and directionality of changes in pollen metrics. Ragweed pollen season is estimated to start earlier and last longer for all nine climate regions of the CONUS, with increasing average pollen concentrations in most regions. The timing and magnitude of oak pollen season vary across the nine climate regions, with the largest increases in pollen concentrations expected in the Northeast region.

Pollen forecasting and its relevance in pollen allergen avoidance

Pollinosis and allergic asthma are respiratory diseases of global relevance, heavily affecting the quality of life of allergic subjects. Since there is not a decisive cure yet, pollen allergic subjects need to avoid exposure to high pollen allergens concentrations. For this purpose, pollen forecasting is an essential tool that needs to be reliable and easily accessible. While forecasting methods are rapidly evolving towards more complex statistical and physical models, the use of simple and traditional methods is still preferred in routine predictions. In this review, we summarise and explain the main parameters considered when forecasting pollen, and classify the different forecasting methods in two groups: observation-based and process-based. Finally, we compare these approaches based on their usefulness to allergic patients, and discuss possible future developments of the field.

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.

Pollen Geochronology from the Atlantic Coast of the United States during the Last 500 Years

Building robust age–depth models to understand climatic and geologic histories from coastal sedimentary archives often requires composite chronologies consisting of multi-proxy age markers. Pollen chronohorizons derived from a known change in vegetation are important for age–depth models, especially those with other sparse or imprecise age markers. However, the accuracy of pollen chronohorizons compared to other age markers and the impact of pollen chronohorizons on the precision of age–depth models, particularly in salt marsh environments, is poorly understood. Here, we combine new and published pollen data from eight coastal wetlands (salt marshes and mangroves) along the Atlantic Coast of the United States (U.S.) from Florida to Connecticut to define the age and uncertainty of 17 pollen chronohorizons. We found that 13 out of 17 pollen chronohorizons were consistent when compared to other age markers (radiocarbon, radionuclide 137Cs and pollution markers). Inconsistencies were likely related to the hyperlocality of pollen chronohorizons, mixing of salt marsh sediment, reworking of pollen from nearby tidal flats, misidentification of pollen signals, and inaccuracies in or misinterpretation of other age markers. Additionally, in a total of 24 models, including one or more pollen chronohorizons, increased precision (up to 41 years) or no change was found in 18 models.

Building an automatic pollen monitoring network (ePIN): Selection of optimal sites by clustering pollen stations

Airborne pollen is a recognized biological indicator and its monitoring has multiple uses such as providing a tool for allergy diagnosis and prevention. There is a knowledge gap related to the distribution of pollen traps needed to achieve representative biomonitoring in a region. The aim of this manuscript is to suggest a method for setting up a pollen network (monitoring method, monitoring conditions, number and location of samplers etc.). As a case study, we describe the distribution of pollen across Bavaria and the design of the Bavarian pollen monitoring network (ePIN), the first operational automatic pollen network worldwide. We established and ran a dense pollen monitoring network of 27 manual Hirst-type pollen traps across Bavaria, Germany, during 2015. Hierarchical cluster analysis of the data was then performed to select the locations for the sites of the final pollen monitoring network. According to our method, Bavaria can be clustered into three large pollen regions with eight zones. Within each zone, pollen diversity and distribution among different locations does not vary significantly. Based on the pollen zones, we opted to place one automatic monitoring station per zone resulting in the ePIN network, serving 13 million inhabitants. The described method defines stations representative for a homogeneous aeropalynologically region, which reduces redundancy within the network and subsequent costs (in the study case from 27 to 8 locations). Following this method, resources in pollen monitoring networks can be optimized and allergic citizens can then be informed in a timely and effective way, even in larger geographical areas.

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.

Transport pathway and source area for Artemisia pollen in Beijing, China

Artemisia pollen is an important allergen responsible for allergic rhinitis in Beijing, China. To explore the transport pathways and source areas of Artemisia pollen, we used Burkard 7-day traps to monitor daily pollen concentrations in 2016 in an urban and suburban locality. Backward trajectories of 24- and 96-h and their cluster analysis were performed to identify transport pathways of Artemisia pollen using the HYSPLIT model on 0.5° × 0.5° GADS meteorological data. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were calculated to further identify the major potential source areas at local, regional, and long-range scales. Our results showed significant differences in Artemisia pollen concentration between urban and suburban areas, attributed to differences in plant distribution and altitude of the sampling locality. Such differences arisen from both pollen emission and air mass movements, hence pollen dispersal. At local or regional scales, source area of northwestern parts of Beijing City, Hebei Province and northern and northwestern parts of Inner Mongolia influenced the major transport pathways of Artemisia pollen. Transport pathway at a long-range scale and its corresponding source area extended to northwestern parts of Mongolia. The regional-scale transport affected by wind and altitude is more profound for Artemisia pollen at the suburban than at the urban station.

Development of a semi-mechanistic allergenic pollen emission model

Modeling pollen emission processes is crucial for studying the spatiotemporal distributions of airborne allergenic pollen. A semi-mechanistic emission model was developed based on mass balance of pollen grain fluxes in the surroundings of allergenic plants. The emission model considers direct emission and resuspension and accounts for influences of temperature, wind velocity, and relative humidity. Modules of this emission model have been developed and parameterized with multiple years of pollen count observations to provide pollen season onset and duration, hourly flowering likelihood, and vegetation coverage for oak and ragweed, as two examples. The simulated spatiotemporal pattern of pollen emissions generally follows the corresponding pattern of area coverage of allergenic plants and diurnal pattern of hourly flowering likelihood. It is found that oak pollen emissions start from the Southern part of the Contiguous United States (CONUS) in March and then shift gradually toward the Northern CONUS, with a maximum emission flux of 5.8 × 10⁶ pollen/(m² h). On the other hand, ragweed pollen emissions start from the Northern CONUS in August and then shift gradually toward the Southern CONUS. The mean ragweed emission flux during August to September can increase up to 2.4 × 10⁶ pollen/(m² h). This emission model is robust with respect to the input parameters for oak and ragweed. Qualitative evaluations of the model performance indicated that the simulated pollen emission is strongly correlated with the plant coverages and observed pollen counts. This model could also be applied to other pollen species given the relevant parameters.

Effect of intra-urban temperature variation on tree flowering phenology, airborne pollen, and measurement error in epidemiological studies of allergenic pollen

Temperature gradients in cities can cause inter-neighborhood differences in the timing of pollen release. However, most epidemiological studies examining allergenic pollen utilize daily measurements from a single pollen monitoring station with the implicit assumption that the measured time series of airborne pollen concentrations applies across the study areas, and that the temporal mismatch between concentrations at the counting station and elsewhere in the study area is negligible. This assumption is tested by quantifying temperature using satellite imagery, observing flowering times of oak (Quercus) and mulberry (Morus) trees at multiple sites, and collecting airborne pollen. Epidemiological studies of allergenic pollen are reviewed and temperatures within their study areas are quantified. In this one-year study, peak oak flowering time was well explained by average February nighttime temperature (R2 = 0.94), which varied by 6 °C across Detroit. This relationship was used to predict flowering phenology across the study region. Peak flowering ranged from April 20-May 13 and predicted a substantial portion of relative airborne oak pollen concentrations in Detroit (R2 = 0.46) and at the regional pollen monitoring station (R2 = 0.61). The regional pollen monitoring station was located in a cooler outlying area where peak flowering occurred around May 12 and peak pollen concentrations were measured on May 15. This provides evidence that the timing of pollen release varies substantially within a metropolitan area and challenges the assumption that pollen measurements at a single location are representative of an entire city. Across the epidemiological studies, 50% of study areas were not within 1 °C (equal to a lag or lead of 4 days in flowering time) of temperatures at the pollen measurement location. Epidemiological studies using a single pollen station as a proxy for pollen concentrations are prone to significant measurement error if the study area is climatically variable.

Mapping allergenic pollen vegetation in UK to study environmental exposure and human health

Allergenic pollen is produced by the flowers of a number of trees, grasses and weeds found throughout the UK. Exposure to such pollen grains can exacerbate pollen-related asthma and allergenic conditions such as allergic rhinitis (hay fever). Maps showing the location of these allergenic taxa have many applications: they can be used to provide advice on risk assessments; combined with health data to inform research on health impacts such as respiratory hospital admissions; combined with weather data to improve pollen forecasting systems; or as inputs to pollen emission models. In this study we present 1km resolution maps of 12 taxa of trees, grass and weeds found in the UK. We have selected the main species recorded by the UK pollen network. The taxa mapped in this study were: Alnus (alder), Fraxinus (ash), Betula (birch), Corylus (hazel), Quercus (oak), Pinus (pine) and Salix (willow), Poaceae (grass), Artemisia (mugwort), Plantago (plantain), Rumex (dock, sorrels) and Urtica (nettle). We also focus on one high population centre and present maps showing local level detail around the city of London. Our results show the different geographical distributions of the 12 taxa of trees, weeds and grass, which can be used to study plants in the UK associated with allergy and allergic asthma. These maps have been produced in order to study environmental exposure and human health, although there are many possible applications. This novel method not only provides maps of many different plant types, but also at high resolution across regions of the UK, and we uniquely present 12 key plant taxa using a consistent methodology. To consider the impact on human health due to exposure of the pollen grains, it is important to consider the timing of pollen release, and its dispersal, as well as the effect on air quality, which is also discussed here.

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.

Allergenic Asteraceae in air particulate matter: quantitative DNA analysis of mugwort and ragweed

Mugwort (Artemisia vulgaris) and ragweed (Ambrosia artemisiifolia) are highly allergenic Asteraceae. They often cause pollen allergies in late summer and fall. While mugwort is native to Europe, ragweed reached Europe as a neophyte from North America about 150 years ago and continued spreading ever since. To understand possible relationships between the spread of ragweed, its abundance in air, and to judge possible health risks for the public, we quantified ragweed DNA in inhalable fine as well as in coarse air particulate matter. Mugwort was chosen for comparison, as it is closely related to ragweed and grows in similar, though mainly not identical, habitats but is native to Germany. The DNA quantification was performed on atmospheric aerosol samples collected over a period of 5 years in central Europe. The DNA concentrations were highest during the characteristic pollination periods but varied greatly between different years. In the inhalable fine particle fraction, ragweed exceeds the mugwort DNA concentration fivefold, while the coarse particle fraction, bearing intact pollen grains, contains more mugwort than ragweed DNA. The higher allergenic potential of ragweed might be linked to the humidity or long-range transport-induced bursting of ragweed pollen into smaller allergenic particles, which may reach the lower airways and cause more intense allergic reactions. Airborne ragweed DNA was detected also outside the local pollination periods, which can be explained by atmospheric long-range transport. Back-trajectory analyses indicate that the air masses containing ragweed DNA during winter had originated in regions with milder climate and large ragweed populations (Southern France, Carpathian Basin).

Mapping the birch and grass pollen seasons in the UK using satellite sensor time-series

Grass and birch pollen are two major causes of seasonal allergic rhinitis (hay fever) in the UK and parts of Europe affecting around 15-20% of the population. Current prediction of these allergens in the UK is based on (i) measurements of pollen concentrations at a limited number of monitoring stations across the country and (ii) general information about the phenological status of the vegetation. Thus, the current prediction methodology provides information at a coarse spatial resolution only. Most station-based approaches take into account only local observations of flowering, while only a small number of approaches take into account remote observations of land surface phenology. The systematic gathering of detailed information about vegetation status nationwide would therefore be of great potential utility. In particular, there exists an opportunity to use remote sensing to estimate phenological variables that are related to the flowering phenophase and, thus, pollen release. In turn, these estimates can be used to predict pollen release at a fine spatial resolution. In this study, time-series of MERIS Terrestrial Chlorophyll Index (MTCI) data were used to predict two key phenological variables: the start of season and peak of season. A technique was then developed to estimate the flowering phenophase of birch and grass from the MTCI time-series. For birch, the timing of flowering was defined as the time after the start of the growing season when the MTCI value reached 25% of the maximum. Similarly, for grass this was defined as the time when the MTCI value reached 75% of the maximum. The predicted pollen release dates were validated with data from nine pollen monitoring stations in the UK. For both birch and grass, we obtained large positive correlations between the MTCI-derived start of pollen season and the start of the pollen season defined using station data, with a slightly larger correlation observed for birch than for grass. The technique was applied to produce detailed maps for the flowering of birch and grass across the UK for each of the years from 2003 to 2010. The results demonstrate that the remote sensing-based maps of onset flowering of birch and grass for the UK together with the pollen forecast from the Meteorology Office and National Pollen and Aerobiology Research Unit (NPARU) can potentially provide more accurate information to pollen allergy sufferers in the UK.

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.

Numerical ragweed pollen forecasts using different source maps: a comparison for France

One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably.

Phenological Variation in Ambrosia artemisiifolia L. Facilitates Near Future Establishment at Northern Latitudes

The invasive weed Ambrosia artemisiifolia (common ragweed) constitutes a great threat to public health and agriculture in large areas of the globe. Climate change, characterized by higher temperatures and prolonged vegetation periods, could increase the risk of establishment in northern Europe in the future. However, as the species is a short-day plant that requires long nights to induce bloom formation, it might still fail to produce mature seeds before the onset of winter in areas at northern latitudes characterized by short summer nights. To survey the genetic variation in flowering time and study the effect of latitudinal origin on this trait, a reciprocal common garden experiment, including eleven populations of A. artemisiifolia from Europe and North America, was conducted. The experiment was conducted both outside the range limit of the species, in Sweden and within its invaded range, in Croatia. Our main hypothesis was that the photoperiodic-thermal requirements of A. artemisiifolia constitute a barrier for reproduction at northern latitudes and, thus, halts the northern range shift despite expected climate change. Results revealed the presence of a north-south gradient in flowering time at both garden sites, indicating that certain European populations are pre-adapted to photoperiodic and thermal conditions at latitudes up to, at least, 60° N. This was confirmed by phenological recordings performed in a region close to the northern range limit, the north of Germany. Thus, we conclude that there exists a high risk for establishment and spread of A. artemisiifolia in FennoScandinavia in the near future. The range shift might occur independently of climate change, but would be accelerated by it.

Field Evaluation of a Competitive Lateral-Flow Assay for Detection of Alternaria brassicae in Vegetable Brassica Crops

On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.

Airborne Microalgae: Insights, Opportunities, and Challenges

Airborne dispersal of microalgae has largely been a blind spot in environmental biological studies because of their low concentration in the atmosphere and the technical limitations in investigating microalgae from air samples. Recent studies show that airborne microalgae can survive air transportation and interact with the environment, possibly influencing their deposition rates. This minireview presents a summary of these studies and traces the possible route, step by step, from established ecosystems to new habitats through air transportation over a variety of geographic scales. Emission, transportation, deposition, and adaptation to atmospheric stress are discussed, as well as the consequences of their dispersal on health and the environment and state-of-the-art techniques to detect and model airborne microalga dispersal. More-detailed studies on the microalga atmospheric cycle, including, for instance, ice nucleation activity and transport simulations, are crucial for improving our understanding of microalga ecology, identifying microalga interactions with the environment, and preventing unwanted contamination events or invasions.

Quantitative DNA Analyses for Airborne Birch Pollen

Birch trees produce large amounts of highly allergenic pollen grains that are distributed by wind and impact human health by causing seasonal hay fever, pollen-related asthma, and other allergic diseases. Traditionally, pollen forecasts are based on conventional microscopic counting techniques that are labor-intensive and limited in the reliable identification of species. Molecular biological techniques provide an alternative approach that is less labor-intensive and enables identification of any species by its genetic fingerprint. A particularly promising method is quantitative Real-Time polymerase chain reaction (qPCR), which can be used to determine the number of DNA copies and thus pollen grains in air filter samples. During the birch pollination season in 2010 in Mainz, Germany, we collected air filter samples of fine (<3 μm) and coarse air particulate matter. These were analyzed by qPCR using two different primer pairs: one for a single-copy gene (BP8) and the other for a multi-copy gene (ITS). The BP8 gene was better suitable for reliable qPCR results, and the qPCR results obtained for coarse particulate matter were well correlated with the birch pollen forecasting results of the regional air quality model COSMO-ART. As expected due to the size of birch pollen grains (~23 μm), the concentration of DNA in fine particulate matter was lower than in the coarse particle fraction. For the ITS region the factor was 64, while for the single-copy gene BP8 only 51. The possible presence of so-called sub-pollen particles in the fine particle fraction is, however, interesting even in low concentrations. These particles are known to be highly allergenic, reach deep into airways and cause often severe health problems. In conclusion, the results of this exploratory study open up the possibility of predicting and quantifying the pollen concentration in the atmosphere more precisely in the future.

A new approach used to explore associations of current Ambrosia pollen levels with current and past meteorological elements

The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.

Ragweed (Ambrosia) pollen source inventory for Austria

This study improves the spatial coverage of top-down Ambrosia pollen source inventories for Europe by expanding the methodology to Austria, a country that is challenging in terms of topography and the distribution of ragweed plants. The inventory combines annual ragweed pollen counts from 19 pollen-monitoring stations in Austria (2004-2013), 657 geographical observations of Ambrosia plants, a Digital Elevation Model (DEM), local knowledge of ragweed ecology and CORINE land cover information from the source area. The highest mean annual ragweed pollen concentrations were generally recorded in the East of Austria where the highest densities of possible growth habitats for Ambrosia were situated. Approximately 99% of all observations of Ambrosia populations were below 745m. The European infection level varies from 0.1% at Freistadt in Northern Austria to 12.8% at Rosalia in Eastern Austria. More top-down Ambrosia pollen source inventories are required for other parts of Europe.

CAPSULE ABSTRACT

A method for constructing top-down pollen source inventories for invasive ragweed plants in Austria, a country that is challenging in terms of topography and ragweed distribution.

Predicting Onset and Duration of Airborne Allergenic Pollen Season in the United States

Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5% to 30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994-2010 are mostly within 0 to 6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Ambrosia pollen in Tulsa, Oklahoma: aerobiology, trends, and forecasting model development

BACKGROUND

Ambrosia pollen is an important aeroallergen in North America; the ability to predict daily pollen levels may provide an important benefit for sensitive individuals.

OBJECTIVE

To analyze the long-term Ambrosia pollen counts and develop a forecasting model to predict the next day's pollen concentration.

METHODS

Airborne pollen has been collected since December 1986 with a Burkard spore trap at the University of Tulsa. Summary statistics and season metrics were calculated for the 27 years of data. Concentration and previous-day meteorologic data from 1987 to 2011 were used to develop a multiple regression model to predict pollen levels for the following day. Model output was compared to 2012 and 2013 ragweed pollen data.

RESULTS

The Tulsa ragweed season extends from the middle of August to late October. The mean start date is August 22, the mean peak date is September 10, and the mean end date is October 20. The mean cumulative season total is 11,599 pollen/m(3), and the mean daily concentration is 197 pollen/m(3). Previous-day meteorologic and phenologic data were positively related to pollen concentration (P < .001). Precipitation was modeled as a dichotomous variable. The final model included minimum temperature, dichotomous precipitation, dew point, and phenology variable (R = 0.7146, P < .001). Analysis of the model's accuracy revealed that the model was highly representative of the 2012 and 2013 seasons (R = 0.680, P < .001).

CONCLUSION

Multiple regression models may be useful in explaining the variability of Ambrosia pollen levels. Further testing of the modeling parameters in different geographical areas is needed.

Heterogeneity in ragweed pollen exposure is determined by plant composition at small spatial scales

Pollen allergies are one of the most common health problems in the United States and over 20% of Americans are sensitized to the pollen produced by common ragweed (Ambrosia artemisiifolia L.). Despite the importance of allergenic pollen to public health, no research has linked land use and plant populations to spatial heterogeneity in airborne pollen concentrations. In order to quantify these relationships and elucidate the processes which lead to pollen exposure, we surveyed ragweed stem density in Detroit (Michigan, USA) as a function of land use. We then deployed 34 pollen collectors throughout the city and recorded ragweed cover in the immediate vicinity of each pollen collector. We found that ragweed populations were highest in vacant lots, a common land cover type in Detroit. Because ragweed population density was so strongly correlated to vacant lots, for which spatially explicit data were available, we were able to investigate whether observed ragweed pollen concentrations were a function of land use at the spatial scales of 10 m and 1 km. Both relationships were significant, and the combination of these two variables predicts a large portion of airborne ragweed pollen concentrations (R(2)=0.48). These results emphasize the important role of pollen production within the urban environment and show that management of allergenic pollen producing plants must be considered at multiple spatial scales. Our findings also demonstrate that there is too much spatial heterogeneity for a pollen collector at any given site to portray the allergenic pollen load experienced by different individuals within the same city. Finally, we discuss how spatial correlations between socio-economic status, vacant lots, and ragweed could help to explain the disproportionate amount of allergies and ragweed sensitization experienced by low income and minority populations in Detroit.

Common ragweed: a threat to environmental health in Europe

Common or short ragweed (Ambrosia artemisiifolia L.) is an annual herb belonging to the Asteraceae family that was described by Carl Linnaeus in the 18th century. It is a noxious invasive species that is an important weed in agriculture and a source of highly allergenic pollen. The importance placed on A. artemisiifolia is reflected by the number of international projects that have now been launched by the European Commission and the increasing number of publications being produced on this topic. This review paper examines existing knowledge about ragweed ecology, distribution and flowering phenology and the environmental health risk that this noxious plant poses in Europe. The paper also examines control measures used in the fight against it and state of the art methods for modelling atmospheric concentrations of this important aeroallergen. Common ragweed is an environmental health threat, not only in its native North America but also in many parts of the world where it has been introduced. In Europe, where the plant has now become naturalised and frequently forms part of the flora, the threat posed by ragweed has been identified and steps are being taken to reduce further geographical expansion and limit increases in population densities of the plant in order to protect the allergic population. This is particularly important when one considers possible range shifts, changes in flowering phenology and increases in the amount of pollen and allergenic potency that could be brought about by changes in climate.

Development of a regional-scale pollen emission and transport modeling framework for investigating the impact of climate change on allergic airway disease

Exposure to bioaerosol allergens such as pollen can cause exacerbations of allergenic airway disease (AAD) in sensitive populations, and thus cause serious public health problems. Assessing these health impacts by linking the airborne pollen levels, concentrations of respirable allergenic material, and human allergenic response under current and future climate conditions is a key step toward developing preventive and adaptive actions. To that end, a regional-scale pollen emission and transport modeling framework was developed that treats allergenic pollens as non-reactive tracers within the WRF/CMAQ air-quality modeling system. The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model was used to generate a daily pollen pool that can then be emitted into the atmosphere by wind. The STaMPS is driven by species-specific meteorological (temperature and/or precipitation) threshold conditions and is designed to be flexible with respect to its representation of vegetation species and plant functional types (PFTs). The hourly pollen emission flux was parameterized by considering the pollen pool, friction velocity, and wind threshold values. The dry deposition velocity of each species of pollen was estimated based on pollen grain size and density. An evaluation of the pollen modeling framework was conducted for southern California for the period from March to June 2010. This period coincided with observations by the University of Southern California's Children's Health Study (CHS), which included O₃, PM_2.5, and pollen count, as well as measurements of exhaled nitric oxide in study participants. Two nesting domains with horizontal resolutions of 12 km and 4 km were constructed, and six representative allergenic pollen genera were included: birch tree, walnut tree, mulberry tree, olive tree, oak tree, and brome grasses. Under the current parameterization scheme, the modeling framework tends to underestimate walnut and peak oak pollen concentrations, and tends to overestimate grass pollen concentrations. The model shows reasonable agreement with observed birch, olive, and mulberry tree pollen concentrations. Sensitivity studies suggest that the estimation of the pollen pool is a major source of uncertainty for simulated pollen concentrations. Achieving agreement between emission modeling and observed pattern of pollen releases is the key for successful pollen concentration simulations.

Atmospheric conditions during high ragweed pollen concentrations in Zagreb, Croatia

We examined the atmospheric conditions favourable to the occurrence of maximum concentrations of ragweed pollen with an extremely high risk of producing allergy. Over the 2002-2009 period, daily pollen data collected in Zagreb were used to identify two periods of high pollen concentration (> 600 grains/m(3)) for our analysis: period A (3-4 September 2002) and period B (6-7 September 2003). Synoptic conditions in both periods were very similar: Croatia was under the influence of a lower sector high pressure system moving slowly eastward over Eastern Europe. During the 2002-2009 period, this type of weather pattern (on ~ 70% of days), in conjunction with almost non-gradient surface pressure conditions in the area (on ~ 30% of days) characterised days when the daily pollen concentrations were higher than 400 grains/m(3). Numerical experiments using a mesoscale model at fine resolution showed successful multi-day simulations reproducing the local topographic influence on wind flow and in reasonable agreement with available observations. According to the model, the relatively weak synoptic flow (predominantly from the eastern direction) allowed local thermal circulations to develop over Zagreb during both high pollen episodes. Two-hour pollen concentrations and 48-h back-trajectories indicated that regional-range transport of pollen grains from the central Pannonian Plain was the cause of the high pollen concentrations during period A. During period B, the north-westward regional-range transport in Zagreb was supplemented significantly by pronounced horizontal recirculation of pollen grains. This recirculation happened within the diurnal local circulation over the city, causing a late-evening increase in pollen concentration.