Ragweed Pollen Source Inventory for France - the Second Largest Centre of Ambrosia in Europe

France, in particular the Rhône-Alpes region, is one of the three main centres of ragweed (Ambrosia) in Europe. The aim of this study is to develop a gridded ragweed pollen source inventory for all of France that can be used in assessments, eradication plans and by atmospheric models for describing concentrations of airborne ragweed pollen. The inventory combines information about spatial variations in annual Ambrosia pollen counts, knowledge of ragweed ecology, detailed land cover information and a Digital Elevation Model. The ragweed inventory consists of a local infection level on a scale of 0–100% (where 100% is the highest plant abundance per area in the studied region) and a European infection level between 0% and 100% (where 100% relates to the highest identified plant abundance in Europe using the same methodology) that has been distributed onto the EMEP grid with 5 km × 5 km resolution. The results of this analysis showed that some of the highest mean annual ragweed pollen concentrations were recorded at Roussillon in the Rhône-Valley. This is reflected by the inventory, where the European infection level has been estimated to reach 67.70% of the most infected areas in Europe i.e. Kecskemét in central Hungary. The inventory shows that the Rhône Valley is the most heavily infected part of France. Central France is also infected, but northern and western parts of France are much less infected. The inventory can be entered into atmospheric transport models, in combination with other components such as a phenological model and a model for daily pollen release, in order to simulate the dispersion of ragweed pollen within France as well as potential long-distance transport from France to other European countries.

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.

An Analysis of Local Wind and Air Mass Directions and Their Impact on Cladosporium Distribution Using HYSPLIT and Circular Statistics

Ecological studies that examine species-environment relationships are often limited to several meteorological parameters, i.e. mean air temperature, relative humidity, precipitation, vapour pressure deficit and solar radiation. The impact of local wind, its speed and direction are less commonly investigated in aerobiological surveys mainly due to difficulties related to the employment of specific analytical tools and interpretation of their outputs. Identification of inoculum sources of economically important plant pathogens, as well as highly allergenic bioaerosols like Cladosporium species, has not been yet explored with remote sensing data and atmospheric models such as Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT). We, therefore, performed an analysis of 24 h intra-diurnal cycle of Cladosporium spp. spores from an urban site in connection with both the local wind direction and overall air mass direction computed by HYSPLIT. The observational method was a volumetric air sampler of the Hirst design with 1 h time resolution and corresponding optical detection of fungal spores with light microscopy. The atmospheric modelling was done using the on-line data set from GDAS with 1° resolution and circular statistical methods. Our results showed stronger, statistically significant correlation (p ≤ 0.05) between high Cladosporium spp. spore concentration and air mass direction compared to the local wind direction. This suggested that a large fraction of the investigated fungal spores had a regional origin and must be located more than a few kilometers away from the sampling point.

Future Air Quality Related Health Effects in Europe and the Nordic Region—Sensitivity to Changes in Climate, Anthropogenic Emissions, Demography and Building Stock

Future changes in population exposures to ambient air pollution are inherently linked with long-term trends in outdoor air quality, but also with changes in the building stock. Moreover, the burden of disease is further driven by the ageing of the European populations. This study aims to assess the impact of changes in climate, emissions, building stocks and population on air pollution related human health impacts across Europe in the future. Therefore an integrated assessment model combining atmospheric models and health impacts has been setup for projections of the future developments in air pollution related premature mortality. The focus is here on the regional scale impacts of exposure to surface ozone (O3), Secondary Inorganic Aerosols (SIA) and primary particulate matter (PPM).

Modelling Atmospheric Concentrations of Ragweed Pollen From Local and Distant Sources

Pollen grains from the genus ragweed (Ambrosia spp.) are important aeroallergens. In Europe, the largest sources of atmospheric ragweed pollen are the Rhône Valley (France), parts of Northern Italy, the Pannonian Plain and Ukraine. Episodes of Long Distance Transport (LDT) of ragweed pollen from these centres can cover large parts of Europe and are predominantly studied using receptor based models (Smith et al., (2013) and references therein). The clinical impact of allergenic ragweed pollen arriving from distant sources remains unclear (Cecchi et al. 2010). Although a recent study has found the major allergens of ragweed in air samples collected in Poznań, Poland, during episodes of long-distance transport from the Pannonian Plain (Grewling et al. 2013). The source orientated models SILAM, DEHM, COSMO-Art, METRAS and ENVIRO-HIRLAM currently report having the capability of modelling atmospheric concentrations of pollen in Europe. The performance of such source-orientated models is strongly dependent on the quality of the emissions data, which is a focus of current research (e.g. Thibaudon et al. (2014)). The output from these models are important for warning allergy sufferers in areas polluted by ragweed, but could also be used to warn the public of ragweed pollen being transported into areas where the plant is not abundant. Areas outside of the main areas of ragweed infection that contain considerable local populations must, however, also include local scale models. These models can be used to predict local concentrations, even when LDT is not present. This concept of combined LDT and local scale calculations has been shown to be work for air pollutants and is considered usable for urban scale calculations of aeroallergens once urban scale maps of aeroallergen sources have been produced.

Investigating and Predicting Atmospheric Concentrations of Allergenic Fungal Spores (Alternaria, Cladosporium, Didymella and Ganoderma)

Air quality is an increasing concern of the European Union, local authorities, scientists and most of all inhabitants that become more aware of the quality of the surrounding environment. Bioaerosols may be consisted of various elements, and the most important are pollen grains, fungal spores, bacteria, viruses. More than 100 genera of fungal spores have been identified as potential allergens that cause immunological response in susceptible individuals. Alternaria and Cladosporium have been recognised as the most important fungal species responsible for respiratory tract diseases, such as asthma, eczema, rhinitis and chronic sinusitis. While a lot of attention has been given to these fungal species, a limited number of studies can be found on Didymella and Ganoderma, although their allergenic properties were proved clinically. Monitoring of allergenic fungal spore concentration in the air is therefore very important, and in particular at densely populated areas like Worcester, UK. In this thesis a five year spore data set was presented, which was collected using a 7-day volumetric spore trap, analysed with the aid of light microscopy, statistical tests and geographic information system techniques. Although Kruskal-Wallis test detected statistically significant differences between annual concentrations of all examined fungal spore types, specific patterns in their distribution were also found. Alternaria spores were present in the air between mid-May/mid-June until September-October with peak occurring in August. Cladosporium sporulated between mid-May and October, with maximum concentration recorded in July. Didymella spores were seen from June/July up to September, while peaks were found in August. Ganoderma produced spores for 6 months (May-October), and maximum concentration could be found in September. With respect to diurnal fluctuations, Alternaria peaked between 22:00h and 23:00h, Cladosporium 13:00-15:00h, Didymella 04:00-05:00h and 22:00h-23:00h and Ganoderma from 03:00h to 06:00h. Spatial analysis showed that sources of all fungal species were located in England, and there was no evidence for a long distance transport from the continent. The maximum concentration of spores was found several hours delayed in comparison to the approximate time of the spore release from the crops. This was in agreement with diurnal profiles of the spore concentration recorded in Worcester, UK. Spores of Alternaria, Didymella and Ganoderma revealed a regional origin, in contrast to Cladosporium, which sources were situated locally. Hence, the weather conditions registered locally did not exhibit strong statistically significant correlations with fungal spore concentrations. This has had also an impact on the performance of the forecasting models. The best model was obtained for Cladosporium with 66% of the accuracy.