Spatial Bi-hourly Variation of Alternaria Spore Concentration in Worcester, UK

Alternaria species are ubiquitous fungi affecting food security and human health. They are pathogenic on many economically important crops and allergenic to many sensitive people worldwide. Studies from Worcester, UK have shown high a concentration of Alternaria spores, most likely caused by agricultural activities. However, it is unknown whether Alternaria spore concentrations vary geographically throughout Worcestershire. An investigation on the spatial variation in bi-hourly concentration of Alternaria spores in Worcestershire during 2016 and 2017 was conducted. Spores were sampled using two Hirst-type Burkard spore traps at the University of Worcester. One on the rooftop of a building at St John’s Campus and another at Lakeside Campus approximately 7 km away. St John’s Campus is located in the centre of Worcester (52.1970, -2.2421), while Lakeside Campus is located in an agricultural environment (52.2537, -2.2535) with regularly cut grass in the near surroundings. Slides were counted using bi-hourly traverse at x 400 magnification. The total number of spores per slide were converted to the daily mean of spores m¯³ of air. There was a highly positive correlation in the concentration of Alternaria spores between the two sites in both 2016 and 2017. St John’s had the highest peak of spore concentration (213 m¯³) in 2016 and Lakeside had the peak concentration in 2017 (184 m¯³). Concentrations above 100 m¯³ of air were observed more frequently at Lakeside. The study revealed that Alternaria spore concentrations were higher at Lakeside than at St John’s. This could be attributed to spores released from either crops or agricultural activities (e.g. haying or harvesting) or from decomposed grass since the surrounding area is routinely managed. Further work in 2018 will include spore correlations with weather variables from a pair of weather stations located at each site, enabling studies caused by variations in weather and climate. Spatial variation in bi-hourly spore concentrations is useful information to atopic subjects, health experts and crop pathologists. Keywords: Harvesting. Allergy. Fungal Spores

Understanding Emissions of Ammonia from Buildings and Application of Fertilizers: An Example from Poland

A Europe-wide dynamic ammonia (NH3) emissions model has been applied for one of the large agricultural countries in Europe, and its sensitivity on the distribution of emissions among different agricultural functions was analyzed by comparing with observed ammonia concentrations and by implementing all scenarios in a CTM model. The results suggest that the dynamic emission model is most sensitive to emission from animal manure, in particular how this is connected to national regulations. In contrast, the model is most robust with respect to emission from buildings and storage. To do this, we obtained activity information on agricultural operations at the sub-national level for Poland, information about infrastructure on storages and current regulations on manure practice from Polish authorities. The information was implemented in the existing emission model and was connected directly with the NWP calculations from the Weather Research and Forecasting model (WRF-ARW). The model was used to calculate four emission scenarios with high spatial (5 km x 5 km) and temporal resolution (3h) for the entire year 2010. In the four scenarios, we have compared the European-wide default model settings against: 1) a scenario that focuses on emission from agricultural buildings, 2) the existing emission method used in WRF-Chem in Poland, and 3) a scenario that takes into account Polish infrastructure and agricultural regulations. The ammonia emission was implemented into the chemical transport model FRAME and modelled ammonia concentrations was compared with measurements. The results suggest that the default setting in the dynamic model is an improvement compared to a non-dynamical emission profile. The results also show that further improvements can be obtained on the national scale by replacing the default information on manure practice with information that is connected with local practice and national regulations. Implementing a dynamical approach for simulation of ammonia emission is a viable objective for all CTM models that continue to use fixed emission profiles. Such models should handle ammonia emissions in a similar way to other climate dependent emissions (e.g. Biogenic Volatile Organic Compounds). Our results, compared with previous results from the DEHM and the GEOS-CHEM models, suggest that implementing dynamical approaches improves simulations in general even in areas with limited information about location of the agricultural fields, livestock and agricultural production methods such as Poland

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

Aerobiology Meets Ecology: Development of Low-Cost Passive Gravitational Samplers

Access to proper and reliable research equipment is crucial in all natural science disciplines. This is especially true in biological research since experiments and observations require equipment that will show the same thing consistently. One method often utilized is called sampling, and it means collecting something by using a strict protocol. Our research is focused around sampling pollen and other biological particles from the air around us. If we want to sample particles in the air from locations where there is no electricity, the type of devices we can use limits us. This has led us to develop a sampler that does not require any electrical power; this technique is often referred to as passive sampling. We have created samplers with the design Sigma-2. It works by using a double wall and apertures with strategic placement to deflect the wind, and particles it carries, which then fall into a collection container within the sampler. In this poster we detail the construction, use and analysis using this passive sampler along with methods used to conduct quality control, to ensure that the results we acquire are reliable, replicable and comparable to other samplers

Footprint Areas of Pollen From Alder (Alnus) and Birch (Betula) in the UK (Worcester) and Poland (Wrocław) During 2005–2014

In this study we analyzed daily pollen concentrations of Alnus spp. and Betula spp. from Worcester, UK and Wrocław, Poland. We analyzed seasonality, annual pollen index and footprint areas for the observed pollen concentrations by using the trajectory model hybrid single particle Lagrangian integrated trajectory (HYSPLIT). We examined 10 years of data during the period 2005–2014 and found substantial differences in the seasonality, pollen indices and footprint areas. For both genera, concentrations in Wrocław are in general much higher, the seasons are shorter and therefore more intense than in Worcester. The reasons appear to be related to the differences in overall climate between the two sites and more abundant sources in Poland than in England. The footprint areas suggest that the source of the pollen grains are mainly local trees but appear to be augmented by remote sources, in particular for Betula spp. but only to a small degree for Alnus spp. For Betula spp., both sites appear to get contributions from areas in Germany, the Netherlands and Belgium, while known Betula spp. rich regions in Russia, Belarus and Scandinavia had a very limited impact on the pollen concentrations in Worcester and Wrocław. Substantial and systematic variations in pollen indices are seen for Betula spp. in Wrocław with high values every second year while a similar pattern is not observed for Worcester. This pattern was not reproduced for Alnus spp

Spatial Flowering Patterns in Dactylis glomerata Populations

Background: Dactylis glomerata is thought to be one of the major contributors to the annual grass pollen load in temperate regions due to wide distribution, high abundance and high pollen production. Detailed information about its flowering dynamics may therefore help in assessing the severity of the grass pollen season. Grass flora estimates of the flowering period are not enough to determine when the species is capable or most likely to release pollen. Observing multiple grass populations over time would enhance the detail and understanding of the flowering dynamics and reveal the variation in flowering events within a region. Methods: Eight populations were chosen in Worcestershire, UK in 2018, with minimum 150 individual tillers each to secure full variation within each population. Flowering progression was determined from the BBCH scale adapted from cereal monitoring. The phenology was focused on the percentage of extruded anthers, with equal intervals of 25, 50, 75 and 100%. Senescence was considered reached with the detachment of the last anther to avoid ambiguity in terms of pollen emission. The two main populations were observed every second day while the six secondary populations were observed ten times during the season. Results: A total of 2672 tillers were observed. The spatial investigation highlighted the uniformity of flowering progression between both main and secondary populations, with a mean seasonal difference of less than 1/10th of a phase. Both main populations started to flower on May 29th. The main populations reached peak flowering on June 14th while the average population reached full flowering on June 20th. Peak flowering is reached earlier than average full flowering in all populations due to the divergent growth progression of individual Dactylis tillers. The flowering ended on Aug 9th, 73 days later. Conclusion: This study highlights that Dactylis glomerata flowering is uniform over an entire region. There is little to no difference between populations in the timing of crucial flowering events such as start, peak and full flowering. It also notes the difference between peak and full flowering, which will be of importance in the aspect of pollen release

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

Spatial and temporal variations in ammonia emissions – a freely accessible model code for Europe

Deriving a parameterisation of ammonia emissions for use in chemistry-transport models (CTMs) is a complex problem as the emission varies locally as a result of local climate and local agricultural management. In current CTMs such factors are generally not taken into account. This paper demonstrates how local climate and local management can be accounted for in CTMs by applying a modular approach for deriving data as input to a dynamic ammonia emission model for Europe. Default data are obtained from information in the RAINS system, and it is demonstrated how this dynamic emission model based on these input data improves the NH<sub>3</sub> calculations in a CTM model when the results are compared with calculations obtained by traditional methods in emission handling. It is also shown how input data can be modified over a specific target region resulting in even further improvement in performance over this domain. The model code and the obtained default values for the modelling experiments are available as supplementary information to this article for use by the modelling community on similar terms as the EMEP CTM model: the GPL licencse v3

Spatial and Temporal Variance of Bi-hourly Grass Pollen Concentrations in the Local Surroundings of Worcester, UK

B: Grass pollen is the most important aeroallergen worldwide and the health outcome among sensitive individuals is closely related to exposure. It has been argued that grass pollen concentrations can be expected to vary substantially within the urban environment, partly due to source distribution and partly due to dispersion and deposition mechanisms. Most studies conducted on local spatial and temporal variance of pollen concentrations are from one season. Only a few studies include multiple seasons and the results are inconclusive. The patterns and factors responsible for local spatial and temporal pollen variance are still largely unknown. Bi-hourly pollen data provides finer temporal resolution than the standardized daily data otherwise used. Bi-hourly data collected from two sampling sites are used to investigate local spatial and temporal patterns of grass pollen concentrations in Worcester. M: Grass pollen was sampled from two locations in Worcester during the years 2016 and 2017 using a Burkard sampler. Daily and bi-hourly grass pollen concentrations were investigated for temporal and spatial variance using statistical methods by comparing years and locations. The investigation is being repeated for the year 2018. R: Preliminary results from 2016 and 2017 suggest that there is a high spatial correlation for the bi-hourly concentrations in 2016 but not in 2017. In 2016, all recorded peaks except one coincide with a corresponding peak. In 2017, the highest peak coincided with a corresponding peak but the rest of the data did not. Results from 2018 are currently unknown. C: Spatial and temporal variance in grass pollen concentrations fluctuates between years and locations. Peak concentrations tend to have the highest correlations compared to low concentrations. The results show that at least two years of data are needed to establish potential autocorrelation between nearby sites. Future work needs to include longer time-series, more locations and local grass source maps to understand key underlying factors of localized grass pollen concentrations