Incorporation of pollen data in source maps is vital for pollen dispersion models

Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining land cover data and forest inventory; (2) a map obtained from land cover data and calibrated using model simulations and pollen observations; (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment – High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark and Russia.We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies

Air Pollution Affecting Pollen Concentrations through Radiative Feedback in the Atmosphere

Episodes with high air pollution and large amounts of aeroallergens expose sensitive individuals to a health damaging cocktail of atmospheric particles. Particulate matter (PM) affects the radiative balance and atmospheric dynamics, hence affecting concentrations of pollutants. The aim of the study is to estimate feedback between meteorology and particles on concentrations of aeroallergens using an extended version of the atmospheric model WRF-Chem. The extension, originally designed for PM and dust, concerns common aeroallergens. We study a birch pollen episode coinciding with an air pollution event containing Saharan dust (late March to early April 2014), using the model results, pollen records from Southern UK and vertical profiles of meteorological observations. During the episode, increased concentrations of birch pollen were calculated over the European continent, causing plumes transported towards the UK. The arrival of these plumes matched well with observations. The lowest parts of the atmospheric boundary layer demonstrate a vertical profile that favours long distance transport, while the pollen record shows pollen types that typically flower at another time. The model calculations show that feedback between meteorology and particles changes pollen concentrations by ±30% and in some cases up to 100%. The atmospheric conditions favoured meteorological feedback mechanisms that changed long distance transport of air pollution and aeroallergens

Incorporation of pollen data in source maps is vital for pollen dispersion models (Discussion Paper)

Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining land cover data and forest inventory; (2) a map obtained from land cover data and calibrated using model simulations and pollen observations; (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment – High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark and Russia.We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies

Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health

This is the final version. Available on open access from Elsevier via the DOI in this recordData and Code Availability Statement: Data collected using qPCR is archived and on NERC EIDC [https://doi.org/10.5285/28208be4-0163-45e6-912c-2db205126925]. Standard pollen monitoring ‘count’ data were sourced from the MEDMI database, with the exception of data from Bangor which were produced as part of the present study and are available on request. Prescribing datasets are publicly available, as are weather, air pollution, deprivation (IMD) and rural-urban category data. Hospital episode statistics (HES) datasets are sensitive, individual-level health data, which are subject to strict privacy regulations and are not publicly available. The study did not generate any unique codeGrass (Poaceae) pollen is the most important outdoor aeroallergen, exacerbating a range of respiratory conditions, including allergic asthma and rhinitis (‘hay fever’). Understanding the relationships between respiratory diseases and airborne grass pollen with view to improving forecasting has broad public health and socioeconomic relevance. It is estimated that there are over 400 million people with allergic rhinitis and over 300 million with asthma, globally, often comorbidly . In the UK, allergic asthma has an annual cost of around US$ 2.8 billion (2017). The relative contributions of the >11,000 (worldwide) grass species to respiratory health have been unresolved, as grass pollen cannot be readily discriminated using standard microscopy. Instead, here we used novel environmental DNA (eDNA) sampling and quantitative PCR (qPCR) , to measure the relative abundances of airborne pollen from common grass species, during two grass pollen seasons (2016 and 2017), across the UK. We quantitatively demonstrate discrete spatiotemporal patterns in airborne grass pollen assemblages. Using a series of generalised additive models (GAMs), we explore the relationship between the incidences of airborne pollen and severe asthma exacerbations (sub-weekly) and prescribing rates of drugs for respiratory allergies (monthly). Our results indicate that a subset of grass species may have disproportionate influence on these population-scale respiratory health responses during peak grass pollen concentrations. The work demonstrates the need for sensitive and detailed biomonitoring of harmful aeroallergens in order to investigate and mitigate their impacts on human health.Natural Environment Research Council (NERC)National Institute for Health Research (NIHR)Public Health EnglandUniversity of ExeterUniversity College LondonMet Offic

Temperate airborne grass pollen defined by spatio-temporal shifts in community composition

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.Grass pollen is the world’s most harmful outdoor aeroallergen. However, it is unknown how airborne pollen assemblages change across time and space. Human sensitivity varies between different species of grass that flower at different times, but it is not known whether temporal turnover in species composition match terrestrial flowering or whether species richness steadily accumulates over the grass pollen season. Here, using targeted, high-throughput sequencing, we demonstrate that all grass genera displayed discrete, temporally restricted peaks of incidence, which varied with latitude and longitude throughout Great Britain, revealing that the taxonomic composition of grass pollen exposure changes substantially across the grass pollen season.Natural Environment Research CouncilBiotechnology and Biological Sciences Research Council (BBSRC

Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe

Allergic rhinitis is an inflammation in the nose caused by overreaction of the immune system to allergens in the air. Managing allergic rhinitis symptoms is challenging and requires timely intervention. The following are major questions often posed by those with allergic rhinitis: How should I prepare for the forthcoming season? How will the season's severity develop over the years? No country yet provides clear guidance addressing these questions. We propose two previously unexplored approaches for forecasting the severity of the grass pollen season on the basis of statistical and mechanistic models. The results suggest annual severity is largely governed by preseasonal meteorological conditions. The mechanistic model suggests climate change will increase the season severity by up to 60%, in line with experimental chamber studies. These models can be used as forecasting tools for advising individuals with hay fever and health care professionals how to prepare for the grass pollen season