Analysis of allergenic pollen data, focusing on a pollen load threshold statement

Airborne allergenic pollen affects a significant part of the population and the information on pollen load is a valuable tool for public health prevention. The messages should be provided in a form easily understandable for the population. The study provides new insight for the categorisation of pollen load by defining thresholds solely from aerobiological data. Using the long-term airborne pollen data of Corylus, Alnus, Betula, Poaceae, and Artemisia have been evaluated the regionality of pollen concentrations in Lithuania. SPIn and peak values of the main pollen season highlighted as regionality indicators. The largest differences between stations were found in the cases of Corylus and Artemisia.The principle enabling a group of pollen concentrations into levels has been analysed based on retrospective aerobiological data of five pollen types. Thresholds were determined by employing the lowest peak value of the pollen season and applying the 25% principle for selected pollen types. The results were verified by performing associations of defined thresholds with retrospective morbidity data of allergic rhinitis and allergic asthma in Lithuania. Determined pollen thresholds can be used in epidemiological studies requiring associations with pollen concentration. Thresholds could also complement air quality information by integrating pollen load data into public messages or contribute to the development of mHealth systems.

Long-Term Pollen Monitoring in the Benelux: Evaluation of Allergenic Pollen Levels and Temporal Variations of Pollen Seasons

Airborne pollen is a major cause of allergic rhinitis, affecting between 10 and 30% of the population in Belgium, the Netherlands, and Luxembourg (Benelux). Allergenic pollen is produced by wind pollinating plants and released in relatively low to massive amounts. Current climate changes, in combination with increasing urbanization, are likely to affect the presence of airborne allergenic pollen with respect to exposure intensity, timing as well as duration. Detailed analysis of long-term temporal trends at supranational scale may provide more comprehensive insight into these phenomena. To this end, the Spearman correlation was used to statistically compare the temporal trends in airborne pollen concentration monitored at the aerobiological stations which gathered the longest time-series (30–44 years) in the Benelux with a focus on the allergenic pollen taxa: Alnus, Corylus, Betula, Fraxinus, Quercus, Platanus, Poaceae, and Artemisia. Most arboreal species showed an overall trend toward an increase in the annual pollen integral and peak values and an overall trend toward an earlier start and end of the pollen season, which for Betula resulted in a significant decrease in season length. For the herbaceous species (Poaceae and Artemisia), the annual pollen integral and peak values showed a decreasing trend. The season timing of Poaceae showed a trend toward earlier starts and longer seasons in all locations. In all, these results show that temporal variations in pollen levels almost always follow a common trend in the Benelux, suggesting a similar force of climate change-driven factors, especially for Betula where a clear positive correlation was found between changes in temperature and pollen release over time. However, some trends were more local-specific indicating the influence of other environmental factors, e.g., the increasing urbanization in the surroundings of these monitoring locations. The dynamics in the observed trends can impact allergic patients by increasing the severity of symptoms, upsetting the habit of timing of the season, complicating diagnosis due to overlapping pollen seasons and the emergence of new symptoms due allergens that were weak at first.

Neural networks for increased accuracy of allergenic pollen monitoring

Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

Establishing the twig method for investigations on pollen characteristics of allergenic tree species

The twig method in climate chambers has been shown to successfully work as a proxy for outdoor manipulations in various experimental setups. This study was conducted to further establish this method for the investigation of allergenic pollen from tree species (hazel, alder, and birch). Direct comparison under outdoor conditions revealed that the cut twigs compared to donor trees were similar in the timing of flowering and the amount of pollen produced. Cut twigs were able to flower in climate chambers and produced a sufficient amount of pollen for subsequent laboratory analysis. The addition of different plant or tissue fertilizers in the irrigation of the twigs did not have any influence; rather, the regular exchange of water and the usage of fungicide were sufficient for reaching the stage of flowering. In the experimental setup, the twigs were cut in different intervals before the actual flowering and were put under warming conditions in the climate chamber. An impact of warming on the timing of flowering/pollen characteristics could be seen for the investigated species. Therefore, the twig method is well applicable for experimental settings in pollen research simulating, e.g., accelerated warming under climate change.

Pollen Monitoring in the City of Ivano-Frankivsk, Western Ukraine

The results of aeropalynological studies in Ivano-Frankivsk during 2013–2015 are presented in this article. The studies were conducted using a specially designed gravimetric Durham pollen trap installed at a height of 24 m from the ground. We determined that pollen grains of the following taxa dominate in the city’s aeropalynological spectrum: <em>Corylus</em>, <em>Alnus</em>, <em>Betula</em>, <em>Populus</em>, <em>Fraxinus</em>, <em>Salix</em>, <em>Carpinus</em>, <em>Quercus</em>, <em>Pinus</em>, <em>Picea</em>, Poaceae, Urticaceae, <em>Artemisia</em>, and <em>Ambrosia</em>. Pollen grains from woody plants dominate the aeropalynological spectrum. The considerable presence of the tree pollen grains in the ambient air is due to the geographical location of Ivano-Frankivsk in the forest-steppe zone of Ukraine. Pollen season of allergenic plants lasts from the second week of February to early October. The most unfavorable period for patients with pollen allergy in Ivano-Frankivsk is April, when there is a simultaneous appearance of high concentrations airborne allergenic pollen of <em>Betula</em>, <em>Fraxinus</em>, and <em>Carpinus</em>. From the second week of May to mid-July, high (&gt;50 pollen grains/m³) concentrations of allergenic pollen of the Poaceae family members are detected in the air. In the second half of August and early September, high concentrations of allergenic <em>Ambrosia </em>pollen were recorded in the city air. Conducting of pollen monitoring in the city is extremely necessary for prevention, diagnosis, and treatment of pollen allergy.