Daily Airborne Pollen Concentrations Research Articles

Estimation of historical daily airborne pollen concentrations across Switzerland using a spatio temporal random forest model

High concentrations of airborne pollen trigger seasonal allergies and possibly more severe adverse respiratory and cardiovascular health events. Predicting pollen concentration accurately is valuable for epidemiological studies, in order to study the effects of pollen exposure. We aimed to develop a spatiotemporal machine learning model predicting daily pollen concentrations at a spatial resolution of 1 × 1 km across Switzerland between 2000 and 2019. Daily pollen concentrations for five common, highly allergenic pollen types (hazel, alder, birch ash, and grasses) were available from fourteen measurement sites across Switzerland. We considered several predictors such as elevation, species distribution, wind speed, wind direction, temperature, precipitation, relative humidity, satellite-observed Normalized Difference Vegetation Index, and land-use (CORINE, Landsat satellite) to explain variation in pollen concentration. We employed feature engineering techniques to encode categorical variables and fill in missing values. We applied a random forest machine learning model with 5-fold cross-validation. The 5th–99th percentiles for concentrations of hazel, alder, birch, ash, and grass pollen at the pollen monitoring stations were 0–298, 0–306, 0–1153, 0–800, and 0–290 pollen grains/m3, respectively. The results of a predictive model for these concentrations yielded overall R2 values of 0.87, 0.84, 0.89, 0.88, and 0.91, and temporal root mean squared errors (RMSEs) of 16.07, 16.72, 69.04, 41.50, and 22.45 pollen grains/m3. An analysis of predictor variable importance indicates that the average national daily pollen concentration is the most important predictor of pollen concentrations for all pollen types. Furthermore, meteorological variables including temperature, total precipitation, humidity, boundary layer height, wind speed, and wind direction, as well as date and satellite features, are important factors in pollen concentration prediction. These spatiotemporal pollen models will serve to estimate individual residential pollen exposure for epidemiological studies. Resulting estimates will enable us to study respiratory and cardiovascular mortality and hospital admissions in Switzerland.

PollenNet - a deep learning approach to predicting airborne pollen concentrations

The accurate short-term forecasting of daily airborne pollen concentrations is of great importance in public health. Various machine learning and statistical techniques have been employed to predict these concentrations. In this paper, an RNN-based method called PollenNet is introduced, which is capable of predicting the average daily pollen concentrations for three types of pollen: ragweed (Ambrosia), birch (Betula), and grass (Poaceae). Moreover, two strategies incorporating measurement errors during the training phase are introduced, making the method more robust. The data for experiments were obtained from the RealForAll project, where pollen concentrations were gathered using a Hirst-type 7-day volumetric spore trap.Additionally, five types of meteorological data were utilized as input variables. The results of our study demonstrate that the proposed method outperforms standard models typically used for predicting pollen concentrations, specifically the pollen calendar method, pollen predictions based on patterns, and the naive approach.

Applying wind patterns and land use to estimate the concentrations of airborne pollen of herbaceous taxa in a statistical framework

Airborne pollen concentrations are influenced by wind direction, wind speed, temperature and rainfall among other meteorological variables, but they are conditioned by local land use. Combining land use and wind frequencies within a single variable would allow the estimation of the contribution of the emission sources to the airborne pollen detected. The aim of this study was to develop this new variable and to compare its relevance in estimating airborne pollen concentrations of anemophilous (i.e. wind pollinated) herbaceous taxa versus other meteorological predictors.The airborne pollen concentrations of some herbaceous pollen types were studied in Malaga, Spain (1992–2020). The land-use surfaces were combined with the daily wind direction frequencies to develop an index. This index was relevant for estimating daily airborne pollen concentrations in random forest frameworks since high pollen concentrations were detected on days with high index values. However, the relationship between the index and the pollen concentrations was not linear due to the influence of other variables.Overall, this index constitutes an easy-to-use approach to integrate both land use and wind frequencies in pollen models, and it can be applied to other sampling locations and pollen types.

Amaranthaceae pollen grains as indicator of climate change in Lublin (Poland)

Previous studies have demonstrated that plants are a very good indicator of global environmental variations. The responses of many plant species to climate change are confirmed by aerobiological research. This paper presents an analysis of many parameters of pollen seasons in the Amaranthaceae family based on measurements of pollen concentrations in atmospheric air. Pollen samples were collected with the volumetric method at a sampling site in Lublin (Poland) in 2001–2019. The obtained data were verified using statistical analyses. Moreover, the presence of pollenkitt on the pollen grain surface was examined in fresh anthers using scanning electron and light microscopes, since there are some difficulties in identification of Amaranthaceae pollen grains deposited on microscopic slides in aerobiological analysis.The pollen season in Amaranthaceae began on average on June 23 and ended on October 5, i.e. it lasted 105 days. The peak value and annual pollen sum were characterized by the highest variability in the study years in comparison with other season characteristics. The annual pollen sum was in the range from 183 to 725. Maximum concentrations were most often recorded in the second half of August, which is associated with the greatest risk of development of pollen allergy symptoms in sensitive subjects during this period. The results obtained in the 19-year study revealed that the pollen seasons began 14 days earlier. Similarly, the end of the season was accelerated by 24 days. The response of these plants to climate change also include the reduced pollen production by representatives of this family, which was manifested by a decrease in the annual sum of daily airborne pollen concentrations, on average by 35%, and a reduction in the maximum pollen concentration, on average by more than 60%. We found that temperature in May and June had an effect on pollen release, and relative air humidity in May influenced pollen concentrations. We noted significant similarities in the pollen release rate during the last 8 years of the study. The scanning electron microscopy examinations showed that the pollen grain surface in the representative of this family was covered completely or partially with pollenkitt. Hence, the apertures characteristic for pollen in this family were poorly visible. The presence of pollenkitt on the surface of these polyaperturate pollen grains may play an important role in preventing water loss during pollen migration in the air. Our research has demonstrated the response of plants flowering in summer to climate change. The results not only have practical importance for public health in the aspect of allergy risk but can also help to assess environmental changes.

Modelling grass pollen levels in Belgium

Biogenic aerosols such as airborne grass pollen affect the public health badly by putting additional distress on people already suffering from cardiovascular and respiratory diseases. In Belgium, daily airborne pollen concentrations are monitored offline at a few sites only, hampering the timely coverage of the country and short-term forecasts. Here we apply the Chemistry Transport Model SILAM to the Belgian territory to model the spatio-temporal airborne grass pollen levels near the surface based on bottom-up inventories of grass pollen emissions updated with the Copernicus land monitoring Service grassland map of 2015. Transport of aerosols in SILAM is driven by ECMWF ERA5 meteorological data. The emitted grass pollen amounts in SILAM are computed by the multiplication of the grass pollen source map with the release rate determined by the seasonal shape production curve during the grass flowering period. The onset and offset of this period follow a location-dependent prescribed calendar days. Here we optimize the grass pollen seasonal start and end in SILAM by comparing a 2008–2018 time series of daily airborne grass pollen concentrations from the Belgian aerobiological surveillance network with the simulations. The effect of the spatial distribution of grass pollen sources is quantified by constructing pollen source-receptor relations using model simulations with varying grass pollen emissions in five areas of the model domain as input. Up to 33% of the airborne grass pollen in one area was transport from others areas inside Belgium. Adjusting the start and end of the grass pollen season improved the model performance substantially by almost doubling the correlation with local observations. By introducing the temporal scaling of the inter-seasonal pollen amounts in the model, an additional R2 increase up to 22% was obtained. Further improvements can be made by including more detailed grass pollen sources and more dynamic start and end dates of the pollen season.

Correlation between the visiting rate of patients with allergic rhinitis and airborne pollen concentrations in Beijing in recent 3 years

Objective: To evaluate the daily airborne pollen concentrations and visiting rate of patients with allergic rhinitis (AR) and their correlation during 2012-2014 in Beijing. Methods: Daily airborne pollen concentrations (55 998 numbers in total and 549 numbers in average) and its constitution from April to September each year (2012 to 2014) were compared. The number of patients with AR (44 203 in total) who visited the outpatient department of Otorhinolaryngology Head and Neck Surgery, Peking University Third Hospital between January 2012 and December 2014 was analyzed by month. Using SPSS 22.0 software, Kruskal-Wallis test was done for the comparison of visiting rate of patients with AR and airborne pollen concentrations. Correlation analysis between them was made as well. Results: χ(2) value of airborne pollen concentrations between different months in 2012 to 2014 was 110.7, 108.4 and 121.4, respectively; all P<0.01. The airborne pollen concentrations had two peaks per year, respectively: April to May, August to September. χ(2) value of visiting rate of patients with AR between different months in 2012 to 2014 was 175.0, 185.1 and 134.5, respectively; all P<0.01. Visiting rate of patients with AR showed two scattering peaks each year, respectively: April to May, August to September. The highest pollen concentration of spring (April to May) was in early and middle April. Tree pollen was the major portion in spring, which were poplar pollen, pine tree pollen, ash tree pollen, cypress tree pollen and birch trees pollen. The highest pollen concentration of autumn (August to September) was in late August and early September. Weed pollen was the major portion in summer and autumn, which were artemisia pollen, chenopodiaceae pollen and humulus japonicas pollen. The visiting rate of patients with AR showed significant correlation with airborne pollen concentrations (r value was 0.537, 0.484 and 0.566, respectively; all P<0.01). Conclusion: The visiting rate of patients with AR showed positive correlation with airborne pollen concentrations in recent three years.

Quantitative trends in annual totals of five common airborne pollen types (Betula, Quercus, Poaceae, Urtica, and Artemisia), at five pollen-monitoring stations in western Europe

The existence of long-term (20–33 years) trendsin the annual totals of daily airborne pollenconcentrations of five common and/or allergenicwind pollinating taxa was evaluated at fivepollen-monitoring stations in western Europe:Delmenhorst (D), Helmond (NL), Brussels (B),Leiden (NL), and Derby (UK). At all stations,identical or comparable volumetric traps wereused to sample pollen from the air. For grasspollen no increasing or decreasing trends werefound at any station. Trends for birch pollenand oak pollen are increasing, but notsignificant at the stations with the higherannual totals (Delmenhorst and Helmond),probably due to strong year-to-yearfluctuations. At all five stations significantincreasing trends for stinging nettle pollenwere observed. Trends for mugwort pollen aresignificant at all stations, but in differentdirections. Longer periods of observations areneeded to arrive to more definitive conclusionsabout trends in airborne pollenconcentrations.

Comparison of pollen sampling with a Burkard Spore Trap and a Tauber Trap in a warm temperate climate

Aerobiological data have been widely used by many scientists, including those that study modern flora as well as those wishing to reconstruct past vegetational associations. Burkard (Hirst-type) volumetric spore traps are widely used instruments for studying airborne pollen, while Tauber traps are typically used to analyze pollen deposition. The present study compared the pollen collected by these two methods in Tulsa, Oklahoma a warm temperate area with year-round pollen. There was a strong correlation between the pollen influx from the Tauber traps and cumulative sum of average daily airborne pollen concentrations recorded with the Burkard spore trap over the course of 12 months from 1 Feb 1997 through 1 Feb 1998. The correlation coefficient between all taxa over the 12 months was 0.914; while the correlation coefficient for the monthly totals was 0.972. The data showed that both methods reflected local anemophilous vegetation although variations occurred in the prevalence recorded by both samplers.

Spring airborne pollen data in two sites in Trentino (Northern Italy): a comparison with meteorological data

In this paper airborne pollen concentration is compared to meteorological data of Trento and S. Michele all’Adige, two sites in the Adige Valley, in Trentino (North Italy). Pollen ofCorylus, Alnus, Betula andOstrya, four winter-spring flowering plants are considered. Pollen sampling was carried out in 1996 by volumetric Hirst-type samplers. For all pollen types considered, maximum pollen concentration coincided in both stations and there was a good overlap of the main pollen season length; the pollen curves of S. Michele a/A and Trento showed a highly positive correlation. The daily airborne pollen concentrations, defined as the number of pollen grains per cubic meter of air (P/m3), were compared to daily meteorological data: minimum and maximum air temperature (°C), average relative humidity (%), precipitation (mm), global incident radiation (cal/cm2), average wind direction (°) and wind speed (m/s). A highly positive correlation was found forCorylus and maximum temperature in both monitoring stations.Betula was positively, whereasOstrya was negatively correlated to relative humidity. With this first analytical approach sharp differences in the atmospheric pollen presence between the stations located at Trento and S. Michele all’Adige were not found.

Fluctuations and trends in airborne concentrations of some abundant pollen types, monitored at Vienna, Leiden, and Brussels

Abstract The annual sums of daily airborne pollen concentrations fluctuate from year to year. It has been suggested that for some taxa there is a regular or alternating pattern in these fluctuations. On the other hand, environmental changes may lead to decreasing or increasing trends in airborne pollen concentrations. These two phenomena can only be studied reliably on the basis of long-term volumetric observations of abundantly occurring pollen types. For this study two arboreal (Betula and Quercus) and two herbaceous (Poaceae and Urtica) types were chosen. For some of these pollen types a weak but significant trend is observed. For the arboreal types (Quercus and Betula) there appears to be a rather constant biennial fluctuating rhythm.