Data Mining Methods to Detect Airborne Pollen of Spring Flowering Arboreal Taxa

Variations in the airborne pollen load are among the current and expected impacts on plant pollination driven by climate change. Due to the potential risk for pollen-allergy sufferers, this study aimed to analyze the trends of the three most abundant spring-tree pollen types, Pinus, Platanus and Quercus, and to evaluate the possible influence of meteorological conditions. An aerobiological study was performed during the 1993–2020 period in the Ourense city (NW Spain) by means of a Hirst-type volumetric sampler. Meteorological data were obtained from the ‘Ourense’ meteorological station of METEOGALICIA. We found statistically significant trends for the Total Pollen in all cases. The positive slope values indicated an increase in pollen grains over the pollen season along the studied years, ranging from an increase of 107 to 442 pollen grains. The resulting C5.0 Decision Trees and Rule-Based Models coincided with the Spearman’s correlations since both statistical analyses showed a strong and positive influence of temperature and sunlight on pollen release and dispersal, as well as a negative influence of rainfall due to washout processes. Specifically, we found that slight rainfall and moderate temperatures promote the presence of Pinus pollen in the atmosphere and a marked effect of the daily thermal amplitude on the presence of high Platanus pollen levels. The percentage of successful predictions of the C5.0 models ranged between 62.23–74.28%. The analysis of long-term datasets of pollen and meteorological information provides valuable models that can be used as an indicator of potential allergy risk in the short term by feeding the obtained models with weather prognostics.

Aeroallergens and Climate Change in Tulsa, Oklahoma: Long-Term Trends in the South Central United States

Climate change is having a significant effect on many allergenic plants resulting in increased pollen production and shifts in plant phenology. Although these effects have been well-studied in some areas of the world, few studies have focused on long-term changes in allergenic pollen in the South Central United States. This study examined airborne pollen, temperature, and precipitation in Tulsa, Oklahoma over 25 to 34 years. Pollen was monitored with a Hirst-type spore trap on the roof of a building at the University of Tulsa and meteorology data were obtained from the National Weather Service. Changes in total pollen intensity were examined along with detailed analyses of the eight most abundant pollen types in the Tulsa atmosphere. In addition to pollen intensity, changes in pollen season start date, end date, peak date and season duration were also analyzed. Results show a trend to increasing temperatures with a significant increase in annual maximum temperature. There was a non-significant trend toward increasing total pollen and a significant increase in tree pollen over time. Several individual taxa showed significant increases in pollen intensity over the study period including spring Cupressaceae and Quercus pollen, while Ambrosia pollen showed a significant decrease. Data from the current study also indicated that the pollen season started earlier for spring pollinating trees and Poaceae. Significant correlations with preseason temperature may explain the earlier pollen season start dates along with a trend toward increasing March temperatures. More research is needed to understand the global impact of climate change on allergenic species, especially from other regions that have not been studied.

757Using smartphone technology to characterise associations between respiratory symptoms and pollen

Background Pollen is a well-established trigger of asthma and allergic rhinoconjunctivitis, yet key gaps in our understanding remain. These include knowledge of concentration thresholds for symptoms, exposure-response associations through time, and the potential for interactions with other environmental stressors such as air pollution. Smartphone technology offers an opportunity to address these challenges using large datasets that capture individual symptoms in real time. Methods We analysed 44,820 symptom reports logged by 2,272 users of the AirRater app over four years to evaluate associations between daily respiratory symptoms and atmospheric concentrations of pollen in Tasmania, Australia. We used case time series, a novel methodology developed for app-sourced data. We adjusted for seasonality and meteorology and tested for interactions with particulate pollution (PM2.5). Results There was a non-linear association between pollen concentrations and respiratory symptoms for up to three days following exposure. Risk ratios (RR) were greatest on the same day, for total pollen increased steeply to a RR of 1.31 (95% CI: 1.26-1.37) at a concentration of 50 grains/m3 before plateauing. Associations with individual pollen taxa showed similar non-linear trends. There was an interaction with PM2.5, with effect estimates significantly higher when PM2.5 was >50 µg/m3 (p for interaction < 0.001). Conclusions The association between respiratory symptoms and airborne pollen was non-linear, greatest in magnitude on the day of exposure, and synergistic with air pollution. Key messages Smartphone symptom tracking offers a useful means of assessing dose-response relationships in environmental epidemiology.

Lidar depolarization ratio of atmospheric pollen at multiple wavelengths

Lidar observations during the pollen season 2019 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio, Finland, were analyzed in order to optically characterize atmospheric pollen. Pollen concentration and type information were obtained by a Hirst-type volumetric air sampler. Previous studies showed the detectability of non-spherical pollen using depolarization ratio measurements. We present lidar depolarization ratio measurements at three wavelengths of atmospheric pollen in ambient conditions. In addition to the depolarization ratio detected with the multiwavelength Raman polarization lidar PollyXT at 355 and 532 nm, depolarization measurements of a co-located Halo Doppler lidar at 1565 nm were utilized. During a 4 d period of high birch (Betula) and spruce (Picea abies) pollen concentrations, unusually high depolarization ratios were observed within the boundary layer. Detected layers were investigated regarding the share of spruce pollen to the total pollen number concentration. Daily mean linear particle depolarization ratios of the pollen layers on the day with the highest spruce pollen share are 0.10 ± 0.02, 0.38 ± 0.23 and 0.29 ± 0.10 at 355, 532 and 1565 nm, respectively, whereas on days with lower spruce pollen share, depolarization ratios are lower with less wavelength dependence. This spectral dependence of the depolarization ratios could be indicative of big, non-spherical spruce pollen. The depolarization ratio of pollen particles was investigated by applying a newly developed method and assuming a backscatter-related Ångström exponent of zero. Depolarization ratios of 0.44 and 0.16 at 532 and 355 nm for the birch and spruce pollen mixture were determined.

Association between lung function of school age children and short-term exposure to air pollution and pollen: the PARIS cohort

BackgroundDaily levels of ambient air pollution and pollen may affect lung function but have rarely been studied together. We investigated short-term exposure to pollen and air pollution in relation to lung function in school-age children from a French population-based birth cohort.MethodsThis study included 1063 children from the PARIS (Pollution and Asthma Risk: an Infant Study) cohort whose lung function and FeNO measurements were performed at age 8 years old. Exposure data were collected up to 4 days before testing. We estimated daily total pollen concentration, daily allergenic risk indices for nine pollen taxa, as well as daily concentrations of three air pollutants (particulate matter less than 10 µm (PM10), nitrogen dioxide (NO2), ozone (O3)). Children with similar pollen and air pollution exposure were grouped using multidimensional longitudinal cluster analysis. Associations between clusters of pollen and air pollution exposure and respiratory indices (FEV1, FVC, FeNO) were studied using multivariable linear and logistic regression models adjusted for potential confounders.ResultsFour clusters of exposure were identified: no pollen and low air pollution (Cluster 1), grass pollen (Cluster 2), PM10 (Cluster 3) and birch/plane-tree pollen with high total pollen count (Cluster 4). Compared with children in Cluster 1, children in Cluster 2 had significantly lower FEV1 and FVC levels, and children from Cluster 3 had higher FeNO levels. For FEV1 and FVC, the associations appeared stronger in children with current asthma. Additional analysis suggested a joint effect of grass pollen and air pollution on lung function.ConclusionDaily ambient chemical and biological air quality could adversely influence lung function in children.

Lidar Depolarization Ratio of Atmospheric Pollen at Multiple Wavelengths

Lidar observations during the pollen season 2019 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio, Finland were analyzed in order to optically characterize atmospheric pollen. Previous studies showed the detectability of non-spherical pollen using depolarization ratio measurements. We present lidar depolarization ratio measurements at three wavelengths of atmospheric pollen in ambient conditions. In addition to the depolarization ratio detected with the multiwavelength Raman polarization lidar PollyXT at 355 and 532 nm, depolarization measurements of a co-located HALO Photonics Streamline Doppler lidar at 1565 nm were utilized. During a four days period of high birch (Betula) and spruce (Picea abies) pollen concentrations, unusually high depolarization ratios were observed within the boundary layer. Detected layers were investigated regarding the share of spruce pollen to the total pollen number concentration. Daily mean particle depolarization ratios of the pollen layers on the day with the highest spruce pollen share are 0.10 ± 0.02, 0.38 ± 0.23 and 0.29 ± 0.10 at 355, 532 and 1565 nm, respectively. Whereas on days with lower spruce pollen share, depolarization ratios are lower with less wavelength dependence. This spectral dependence of the depolarization ratios could be indicative of big, non-spherical spruce pollen. The depolarization ratio of pollen particles was investigated by applying a newly developed method and assuming a backscatter-related Ångström exponent of zero. Depolarization ratios of 0.44 and 0.16 at 532 and 355 nm for the birch and spruce pollen mixture were determined.

Optimal inaccuracy: estimating male fitness in the movement-assisted dichogamous species Clerodendrum infortunatum

In hermaphroditic species, sexual interference can drive the evolution of dichogamy, where sporophylls (reproductive parts) are separated in time. However, the separation of sporophylls can lead to pollination inaccuracy, especially in movement-assisted dichogamy, where sporophylls alter their position over time. Is pollination inaccuracy minimised by the second sporophyll taking the exact position of the first? Are the sporophylls optimally positioned and stable in their respective active phases? We address these questions in Clerodendrum infortunatum, a protandrous, movement-assisted dichogamous species. We made predictions from optimality arguments, and tested these by measuring sporophyll angles over time, by experimentally manipulating flowers, and by estimating correlates of the resultant fitness, taking into account pollen export, pollination inaccuracy and the resultant total pollen delivered. Contrary to expectation, anthers do not have a fixed position in the male phase, and pollination inaccuracy is high. Further, when pollen load is highest, anthers are paradoxically not positioned at the pollen export peak. Also, pollen export and pollination accuracy peaks do not align. This seeming maladaptiveness of anther positioning nevertheless results in highest overall male fitness, measured as the total pollen delivered over the entire male phase. Instead of a simple positional exchange of sporophylls, stamens display a more complicated dynamic strategy which appears close to optimal even though naive measures of pollination inaccuracy are high. Such a strategy of maximising overall male fitness, integrating over the dynamics of stamen trajectory, could well be a general characteristic of protandrous movement-assisted dichogamy.

Variability in the Betula pollen concentrations in the atmosphere of six urban areas in Slovakia in 2018

Betula pollen is one of the most important aeroallergens during the spring months in the central European countries. In 2018, pollen monitoring was conducted in six urban areas (Bratislava, Banská Bystrica, Košice, Nitra, Trnava, and Žilina) in Slovakia. Investigations were carried out using a volumetric Hirst-type pollen trap (Burkard). Betula pollen season timing was determined by the 90% method when the start and end of the season were defined as the date when 5% and 95%, respectively of the total pollen sum was reached. The pollen season start date was recorded earliest in Bratislava (April 8th) and latest in Banská Bystrica (April 12th). The highest both seasonal total pollen concentration (7,390 P/m3) and birch pollen allergen risk were found in Banská Bystrica. The shortest pollen season was recorded in Žilina (13 days) and the longest in Košice (25 days). Peak daily pollen concentrations ranged between 1,567 P/m3 in Žilina and 202 P/m3 in Košice.

Pollen Explains Flu-Like and COVID-19 Seasonality

Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be antiviral, anti-influenza and allergenic, plays a role in immuno-activation, and seems to create a bio-aerosol lowering the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics including COVID-19.We tested the Pollen-Flu Seasonality Theory for 2016–2020 flu-like seasons, including COVID-19, in The Netherlands with its 17 million inhabitants. We combined changes in flu-like incidence per 100K/Dutch citizens (code: ILI) with weekly pollen counts and meteorological data. Finally, a discrete, predictive model is tested using pollen and meteorological threshold values displaying inhibitory effects on flu-like incidence.We found a highly significant inverse association of r(224) = –.38 between pollen and changes in flu-like incidence corrected for incubation period, confirming our expectations for the 2019/2020 COVID-19 season. The associations become stronger when taking into account incubation time, which satisfies the temporality criteria. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = –.48 (p < .001) when thresholds of 610 total pollen grains/m3 per week, 120 allergenic pollen grains/m3 per week, and a solar radiation of 510 J/cm2 are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a supportive factor, temperature makes no difference, and relative humidity associates even with flu-like incidence increases.We conclude that pollen is a predictor for the inverse seasonality of flu-like epidemics including COVID-19, and solar radiation is a co-inhibitor. The observed seasonality of COVID-19 during Spring, suggests that COVID-19 may revive in The Netherlands after week 33, the start being preceded by the relative absence of pollen, and follows standard pollen-flu seasonality patterns.