Pollen Levels Research Articles

The Effect of Bee Pollen on SGOT, SGPT Levels and Liver Histopathological Images of Male Rats Wistar Induced by High Fat Diet

Dyslipidemia is a risk factor for Non Alcoholic Fatty Liver Disease causing hepatocyte damage. Bee pollen has hypolipodemic, anti-inflammatory effects. The purpose of the study was to analyze the effects of Bee Pollen on the levels of SGOT, SGPT, and its effects on the liver’s histopathologic. The experimental laboratory research method, 30 rats divided into 6 groups (n = 5). HFD was given for 28 days, Simvastatin and Bee Pollen were given from 15 until 28 days. SGOT, SGPT were examined at 0, 15, 29 days by spectrophotometry (340 nm). Histopathological liver examination at 29 days. Results: The levels of SGOT, SGPT between Bee pollen 1 (18 mg/kgBW/day), 2 (36 mg /kgBW/day), 3 (72 mg /kgBW/day) with HFD were very significant differences. The levels of SGOT Bee Pollen 1,2,3 compared to simvastatin were not significantly different. SGPT Bee Pollen 3 levels compared to simvastatin there were no significant differences. Measurement of the degree of cloudy swollen cells, portal inflammation, bridging fibrosis, periportal fibrosis between Bee Pollen 1, 2 with HFD there is a significant difference, Bee Pollen 3 and HFD differ very significantly. Conclusion: Bee Pollen can reduce levels of SGOT, SGPT, its potential effects is equivalent to simvastatin on reducing levels of SGOT, SGPT and improved the histopathological image of the liver on male rats wistar induced by high-fat diet. .
 
 Keywords : Dyslipidemia, SGOT, SGPT, Bee pollen, Histopatological Image 

The Inclusion of a Supercritical Fluid Extract, Obtained From Honey Bee Pollen, in the Diet of Gilthead Sea Bream (Sparus aurata), Improves Fish Immune Response by Enhancing Anti-oxidant, and Anti-bacterial Activities

In the present study, the immune-stimulatory effect of two levels of honey bee pollen (5 and 10%, P5 and P10 treatment, respectively) and its supercritical fluid extract (0. 5 and 1%, E0.5 and E1, respectively) included in the diet, was tested in gilthead seabream (Sparus aurata). The in vivo trial was preceded by the evaluation of antioxidant properties of three different bee pollen extracts obtained by water, ethanol 80%, and Supercritic Fluids Extraction (SFE). The preliminary evaluation attested that the SFE showed the lowest extraction yield (10.47%) compared to ethanol 80% (48.61%) and water (45.99%). SFE extract showed good antioxidant properties with high polyphenol content (13.06 mg GAE/g), radical scavenging activity (3.12 mg/ml), reducing power (38.68 mg/mL EC50). On the contrary, the water extract showed the significantly lowest polyphenol content (2 mg GAE/g; P < 0.05). The results of in vivo trial demonstrate that the diets supplemented with SFE bee pollen extract had a stimulatory effect on fish serum immunity, respect to the inclusion of raw pollen, this latter revealing some inhibitory effects in the immune response, such a decrease of serum peroxidase and lysozyme activities, particularly in P10 group significantly different (P < 0.05) from the control group. On the contrary, serum peroxidase, protease, antiprotease, were significantly increased in fish fed the diets supplemented with supercritical fluid extract, respect to the fish fed on control and on diets supplemented with 5 and 10% of raw pollen. For what concerns the bactericidal activity against Vibrio harveyii, all the treatments containing bee pollen regardless of the type showed their serum bactericidal activity significantly increased with respect to the control groups (p < 0.05). Given its high antioxidant properties, the absence of toxic solvents and the positive action carried out on improving the humoral response in gilthead seam bream, honey bee pollen SFE extract can be taken into account in the formulation of fish feeds.

On-site single pollen metabolomics reveals varietal differences in phosphatidylinositol synthesis under heat stress conditions in rice

Although a loss of healthy pollen grains induced by metabolic heat responses has been indicated to be a major cause of heat-induced spikelet sterility under global climate change, to date detailed information at pollen level has been lacking due to the technical limitations. In this study, we used picolitre pressure-probe-electrospray-ionization mass spectrometry (picoPPESI-MS) to directly determine the metabolites in heat-treated single mature pollen grains in two cultivars, heat-tolerant cultivar, N22 and heat-sensitive cultivar, Koshihikari. Heat-induced spikelet fertility in N22 and Koshihikari was 90.0% and 46.8%, respectively. While no treatment difference in in vitro pollen viability was observed in each cultivar, contrasting varietal differences in phosphatidylinositol (PI)(34:3) have been detected in mature pollen, together with other 106 metabolites. Greater PI content was detected in N22 pollen regardless of the treatment, but not for Koshihikari pollen. In contrast, there was little detection for phosphoinositide in the single mature pollen grains in both cultivars. Our findings indicate that picoPPESI-MS analysis can efficiently identify the metabolites in intact single pollen. Since PI is a precursor of phosphoinositide that induces multiple signaling for pollen germination and tube growth, the active synthesis of PI(34:3) prior to germination may be closely associated with sustaining spikelet fertility even at high temperatures.

Land-Use and Height of Pollen Sampling Affect Pollen Exposure in Munich, Germany

Airborne pollen concentrations vary depending on the location of the pollen trap with respect to the pollen sources. Two Hirst-type pollen traps were analyzed within the city of Munich (Germany): one trap was located 2 m above ground level (AGL) and the other one at rooftop (35 m AGL), 4.2 km apart. In general, 1.4 ± 0.5 times higher pollen amounts were measured by the trap located at ground level, but this effect was less than expected considering the height difference between the traps. Pollen from woody trees such as Alnus, Betula, Corylus, Fraxinus, Picea, Pinus and Quercus showed a good agreement between the traps in terms of timing and intensity. Similar amounts of pollen were recorded in the two traps when pollen sources were more abundant outside of the city. In contrast, pollen concentrations from Cupressaceae/Taxaceae, Carpinus and Tilia were influenced by nearby pollen sources. The representativeness of both traps for herbaceous pollen depended on the dispersal capacity of the pollen grains, and in the case of Poaceae pollen, nearby pollen sources may influence the pollen content in the air. The timing of the pollen season was similar for both sites; however, the season for some pollen types ended later at ground level probably due to resuspension processes that would favor recirculation of pollen closer to ground level. We believe measurements from the higher station provides a picture of background pollen levels representative of a large area, to which local sources add additional and more variable pollen amounts.

Identifying patterns of airborne pollen distribution using a synoptic climatology approach

Understanding the mechanisms of pollen release and dispersion in the atmosphere is of high importance, not only for getting an insight on the patterns of movement of these biological particles that are necessary for plants' reproduction, but also because exposure to airborne pollen is a major concern for respiratory allergies worldwide. In this work, a synoptic circulation-to-environment classification method was adopted to elucidate the relationship between distinct atmospheric patterns and pollen levels for the 11 most abundant but also allergenic taxa in Thessaloniki, Greece, for the 15-year period 1987–2001. It was found that the NW1 depressional weather type is associated with the “low winter pollen season” and high levels of pollen from Carpinus spp., Corylus spp., Cupressaceae, Platanus spp., Pinaceae, Quercus spp. and Urticaceae. In contrast, the SW1 cyclonic type is linked to the “high spring-summer pollen season” and high levels of pollen from Oleaceae and Urticaceae. On the other hand, anticyclonic weather is associated with the “summer-autumn pollen season” and high levels of Poaceae and Chenopodiaceae pollen in the atmosphere. Regional transport of Alnus pollen is linked to a strong high-pressure system centered over Italy, giving light NE winds over northern Greece. These findings shed light to the synoptic climatology of airborne pollen in Thessaloniki and could feed early-warning systems for alerting vulnerable groups of the allergic population.

Retained metabolic activity in honey bee collected pollen has implications for pollen digestion and effects on honey bee health

The mechanisms by which pollen is digested by honey bees are incompletely understood. Potential methods are thought to include pseudogermination, mechanical disruption, enzymatic breakdown, or osmotic shock. Understanding the role of pseudogermination in this process has been hampered by a lack of tools demonstrating retention of metabolic activity in pollen collected by honey bees. Here, we show that pollen collected by honey bees produces reactive oxygen species (ROS) at robust levels upon germination, suggesting that ROS is a suitable marker of this process in pollen. ROS can be readily found in the digestive tract of honey bees and is localized to pollen grains within the lumen. Finally, manipulating pollen levels in the midgut can change ROS levels in the digestive tract. These data provide evidence of retained metabolic activity in bee-collected pollen that lends support to pseudogermination as a mechanism for pollen digestion in honey bees, and points to novel approaches for better understanding of pollen digestion in this species and beyond.

Profilin is a marker of severity in allergic respiratory diseases.

The capacity of profilin to induce allergic symptoms in patients with respiratory allergy has been questioned. In this sense, the aim of this study was to investigate the correlation between profilin exposure and induction of symptoms in a prospective case-control study. The concentration of profilin as well as pollen levels in the air was measured. A diary score of symptoms was collected from allergic patients. Seventy-nine individuals were included in the study; fifty cases and 28 controls were positive or negative to profilin, respectively. Conjunctival and bronchial provocation tests were performed with purified profilin (Pho d 2) in a subgroup of cases and controls. Profilin was detected in the environment on 133days (maximum peak of 0.56ng/m3 ). A positive correlation between profilin and pollen count of Olea and Poaceae was observed (ρ=0.24; P<.001). Intensity of total, nasal and ocular symptoms was statistically higher in cases than in controls (P<.001). The risk of suffering symptoms, measured by the percentage of patients who presented any of the symptoms each day, was also higher in cases than in controls. The provocation test was positive in 95% of bronchial and 90% of conjunctival challenges in cases, and negative in all controls. Profilin was detected in the environment and had the ability to induce a specific allergen response. Patients sensitized to this panallergen showed more symptoms and were more likely to have symptoms. Therefore, sensitization to profilin seems to be a marker of severity in patients with rhinoconjunctivitis and asthma mediated by pollen.

Crowd-sourced allergic rhinitis symptom data: The influence of environmental and demographic factors

Allergic Rhinitis (AR) affects over half a billion people worldwide with an estimated prevalence of 1 in 5 individuals in developed countries. Although ambient pollen exposure is a causal factor in AR, the symptom-exposure relationship is typically not studied in the broader community but in small, well-characterised cohorts drawn from clinical populations. To identify relationships between AR symptoms in the community and a range of environmental factors, we used a database containing over 96,000 symptom score reports collected over a 3-year period (2014–2016) through freely available smartphone apps released in two Australian cities, Melbourne and Canberra. Ambient pollen levels and symptom scores were strongly related, with grass pollen explaining most of the symptom variation. Other factors correlated with higher symptom scores included temperature (R > 0.73) and wind speed (R > 0.75). In general, worse symptom scores were reported by younger participants, women, and those who had taken medication for AR in the preceding 24 h. The strength of this relationship varied between the two cities. Smartphone-based symptom surveys offer a cost-effective means of studying real-world risk factors for AR in a broader ‘extra-clinical’ population.

The application of a neural network-based ragweed pollen forecast by the Ragweed Pollen Alarm System in the Pannonian biogeographical region

Ragweed Pollen Alarm System (R-PAS) has been running since 2014 to provide pollen information for countries in the Pannonian biogeographical region (PBR). The aim of this study was to develop forecast models of the representative aerobiological monitoring stations, identified by analysis based on a neural network computation. Monitoring stations with 7-day Hirst-type pollen trap having 10-year long validated data set of ragweed pollen were selected for the study from the PBR. Variables including forecasted meteorological data, pollen data of the previous days and nearby monitoring stations were used as input of the model. We used the multilayer perceptron model to forecast the pollen concentration. The multilayer perceptron (MLP) is a feedforward artificial neural network. MLP is a data-driven method to forecast the behaviour of complex systems. In our case, it has three layers, one of which is hidden. MLP utilizes a supervised learning technique called backpropagation for training to get better performance. By testing the neural network, we selected different sets of variables to predict pollen levels for the next 3 days in each of the monitoring stations. The predicted pollen level categories (low–medium–high–very high) are shown on isarithmic map. We used the mean square error, mean absolute error and correlation coefficient metrics to show the forecasting system’s performance. The average of the Pearson correlations is around 0.6 but shows big variability (0.13–0.88) among different locations. Model uncertainty is mainly caused by the limitation of the available input data and the variability in ragweed season patterns. Visualization of the results of the neural network forecast on isarithmic maps is a good tool to communicate pollen information to general public in the PBR.

Efficacy of Desloratadine and Levocetirizine in Patients with Cedar Pollen-Induced Allergic Rhinitis: A Randomized, Double-Blind Study

Background: No comparative study of antihistamines that differ in structural system has been conducted in allergic rhinitis. Objective: This was a randomized, double-blind, crossover comparative study to verify the efficacy of antihistamines that differ in structural system. Methods: A total of 50 patients with moderate or more severe Japanese cedar pollen-induced allergic rhinitis were randomized to receive either placebo, desloratadine 5 mg (a tricyclic), or levocetirizine 5 mg (a piperazine). One dose of the study drug was orally administered at 9 pm on the day before a pollen exposure test, which was performed for 3 h (9 a.m. to 12 p.m.) to assess symptoms in an environmental challenge chamber (ECC). Nasal and ocular symptoms were compared at an airborne pollen level of 8,000 grains/m³. The primary endpoint was mean total nasal symptom score (TNSS) from 120 to 180 min in the ECC. Subjects with a difference of ≥1 in TNSS between 2 drugs were extracted to the relevant drug-responsive group. Results: The difference in TNSS from placebo was –2.42 (p < 0.0001) with levocetirizine and –1.66 (p < 0.01) with desloratadine, showing that both drugs were significantly more effective than placebo in controlling symptoms, but with no statistically significant difference between the 2 drugs. There were 12 subjects in the desloratadine-responsive group and 24 subjects in the levocetirizine-responsive group, with no contributor to response was detected. Conclusion: Levocetirizine tended to control nasal symptoms more effectively than desloratadine. However, the response to each antihistamine varied among individuals and the predictors to the response are unknown. Clinical Trial Registration number: UMIN ID: UMIN000029653.

Airborne pollen calendar of Portugal: a 15-year survey (2002–2017)

IntroductionData about the occurrence of airborne pollen enables the creation of pollen calendars with an approximation of flowering periods for the most common allergenic plant species in a specific area. The aim of this work is to provide pollen calendar for each of the seven monitoring regions of Portugal based on 15 years of airborne sampling, in order to chart the seasonal behaviour of the main allergenic pollen types. Material and methodsAirborne pollen monitoring (2002–2017) was carried out by the Portuguese Aerobiology Network (RPA), using Hirst-type volumetric spore traps, following well-established guidelines. ResultsA total of 14 airborne pollen types were recorded at RPA monitoring stations, of which 64.2% belong to trees, 28.5% to herbs and 7.1% to weeds. The airborne pollen spectrum is dominated by important allergenic pollen types such as Poaceae, Quercus spp., Urticaceae and Cupressaceae. The average pollen index was 42.557 in mainland Portugal and 3.818 in the Islands. There was an increased trend in the airborne pollen levels over the years, namely in Coimbra, Évora and Porto, compared to the remaining regions. ConclusionThis report provides accessible information about the main allergenic airborne pollen types occurring in the course of the year. The pollen calendars charted for each Portuguese region showed that the occurrence of most allergenic taxa was centred from March to July. Pollen peak concentrations were detected earlier in the Centre and Lisbon and Tagus Valley regions, and later in the remaining regions.

Effects of air temperature, humidity and air pollution on fertility of birch pollen in urban environments

We studied effects of environmental factors on pollen fertility of Betula pendula Roth.) in 15 sites of the city of Barnaul (Russia, Altai Territory), differing in traffic intensity. We found that low temperature was more stressful for the development of birch pollen compared to high one. When the temperature drops below +8°C, the amount of sterile pollen in all locations significantly increased regardless of the anthropogenic load, on average exceeding 8%. With an increase in temperature of more than +10 °C, the proportion of sterile pollen also increased, but the jump was not as sharp as in cold weather. The optimum temperature for the formation of fertile pollen grains was in the range of 8–10 °С. The optimal humidity for the development of fertile pollen of B. pendula was 40–45%. The increase in air dryness led to a significant decrease in the quality of pollen grains, the proportion of sterile ones exceeded 8%. According to the transmission coefficient (Keff = 0.1514), the dominant factor in the development of sterile pollen grains of birch was the level of air pollution (concentration of carbon monoxide). Air temperature (Keff = 0.1427) and humidity (Keff = 0.1427) affected equally the quality of pollen. The proposed model makes it possible to predict the level of sterile birch pollen in the conditions of Barnaul depending on the weather conditions of vegetation and on the level of pollutants in the atmosphere.

Spatio-temporal monitoring and modelling of birch pollen levels in Belgium

In Belgium, ~ 10% of the people is estimated to suffer from allergies due to pollen emitted by the birch family trees. Timely information on forthcoming pollen exposure episodes using a forecasting system can allow patients to take preventive measures. To date, the only available information on pollen concentrations in Belgium comes from five stations that monitor daily airborne birch pollen concentrations, but real-time and detailed spatial information is lacking. Pollen transport models can both quantify and forecast the spatial and temporal distribution of airborne birch pollen concentrations if accurate and updated maps of birch pollen emission sources are available and if the large inter-seasonal variability of birch pollen is considered. Here we show that the SILAM model driven by ECMWF ERA5 meteorological data is able to determine airborne birch pollen levels using updated maps of areal fractions of birch trees, as compared to the pollen observations of the monitoring stations in Belgium. Forest inventory data of the Flemish and Walloon regions were used to update the default MACCIII birch map. Spaceborne MODIS vegetation activity combined with an updated birch fraction map and updated start and end dates of the birch pollen season were integrated into SILAM. The correlation (R2) between SILAM modelled and observed time series of daily birch pollen levels of 50 birch pollen seasons increased up to ~ 50%. The slopes of the linear correlation increased on average with ~ 60%. Finally, SILAM is able to capture the threshold of 80 pollen grains m−3 exposure from the observations.

Forecasting the seasonal pollen index by using a hidden Markov model combining meteorological and biological factors

The seasonal pollen index (SPI) is a continuing concern within the fields of aerobiology, ecology, botany, and epidemiology. The SPI of anemophilous trees, which varies substantially from year to year, reflects the flowering intensity. This intensity is regulated by two factors: weather conditions during flower formation and the inner resource for assimilation. A deterministic approach has to date been employed for predicting SPI, in which the forecast is made entirely by parameters. However, given the complexity of the masting mechanism (which has intrinsic stochastic properties), few attempts have been made to apply a stochastic model that considers the inter-annual SPI variation as a stochastic process. We propose a hidden Markov model that can integrate the stochastic process of mast flowering and the meteorological conditions influencing flower formation to predict the annual birch pollen concentration. In experiments conducted, the model was trained and validated by using data in Hokkaido, Japan covering 22 years. In the model, the hidden Markov sequence was assigned to represent the recurrence of mast years via a transition matrix, and the observation sequences were designated as meteorological conditions in the previous summer, which are governed by hidden states with emission distribution. The proposed model achieved accuracies of 83.3% in the training period and 75.0% in the test period. Thus, the proposed model can provide an alternative perspective toward the SPI forecast and probabilistic information of pollen levels as a useful reference for allergy stakeholders.

Allergenic pollen production across a large city for common ragweed (Ambrosia artemisiifolia)

Predictions of airborne allergenic pollen concentrations at fine spatial scales require information on source plant location and pollen production. Such data are lacking at the urban scale, largely because manually mapping allergenic pollen producing plants across large areas is infeasible. However, modest-sized field surveys paired with allometric equations, remote sensing, and habitat distribution models can predict where these plants occur and how much pollen they produce. In this study, common ragweed (Ambrosia artemisiifolia) was mapped in a field survey in Detroit, MI, USA. The relationship between ragweed presence and habitat-related variables derived from aerial imagery, LiDAR, and municipal data were used to create a habitat distribution model, which was then used to predict ragweed presence across the study area (392 km2). The relationship between inflorescence length and pollen production was used to predict pollen production in the city. Ragweed occurs in 1.7% of Detroit and total pollen production is 312 × 1012 pollen grains annually, but ragweed presence was highly heterogeneous across the city. Ragweed was predominantly found in in vacant lots (75%) and near demolished structures (48%), and had varying associations with land cover types (e.g., sparse vegetation, trees, pavement) detected by remote sensing. These findings also suggest several management strategies that could help reduce levels of allergenic pollen, including appropriate post-demolition management practices. Spatially-resolved predictions for pollen production will allow mechanistic modeling of airborne allergenic pollen and improved exposure estimates for use in epidemiological and other applications.

Number of seasonal exposures to Japanese cedar pollen increases the risk of sensitization: Observational study in Korean adults

Sensitization to seasonal allergens usually requires repeated exposure to them. However, research on the extent of exposure that increases the risk of sensitization to specific allergens is lacking. Therefore, we investigated the levels of exposure to Japanese cedar pollen that increased the risk of sensitization to it. A cross-sectional study was conducted with 857 college students living in Jeju, South Korea, as it is the only province in Korea where Japanese cedar pollen levels are high. Questionnaires about demographic characteristics were distributed and skin prick tests for allergic sensitization were performed. Sensitization rates of groups divided by residence period were 3.8% (less than 1 year), 1.8% (1–2 years), 8.5% (2–3 years), 10.3% (3–4 years), 14.8% (4–10 years), and 19.1% (over 10 years). Residence period was an influencing factor of sensitization rate to Japanese cedar pollen, and the cut-off value of the residence period that increased the risk of sensitization to Japanese cedar pollen was found to be 25 months. Repeated exposure to seasonal allergens was related to an increased sensitization rate in young adults. Our results suggested that exposure to Japanese cedar pollen for over two seasons could increase the risk in Korean adults.

Use of Technology-Based Tools to Support Adolescents and Young Adults With Chronic Disease: Systematic Review and Meta-Analysis.

BackgroundWith the large amount of material that is readily available on the internet, there are endless opportunities for electronic health–literate patients to obtain and learn new information. Although novel, a Web- or mobile-based program can be a powerful way to engage adolescents and young adults (AYAs). The ongoing engagement of AYAs with chronic disease is vital not only to empower them but also to ensure a smooth transition from pediatric to adult health care.ObjectiveThis study aimed to evaluate the current evidence on Web- or mobile-based interventions designed for AYAs.MethodsThis review was registered with PROSPERO: CRD42018096487. A systematic search of MEDLINE Complete, EMBASE, and CINAHL Complete was conducted on April 10, 2019, for studies that examined the perspectives of transition-age patients about technology-based interventions, the process involved in intervention development, or the evaluation of intervention efficacy. For each study, the comprehensiveness of reporting was appraised. The Downs and Black checklist was used for intervention efficacy trials, the Standards for Reporting Qualitative Research checklist was used for qualitative work, and a 16-item tool developed by Tong et al was used for questionnaire research.ResultsThe search uncovered 29 relevant studies, which included qualitative studies (n=14), intervention efficacy studies (n=7), questionnaire studies (n=4), mixed qualitative and questionnaire studies (n=2), and a mixed qualitative and pilot randomized controlled trial study (n=1). The reporting comprehensiveness score of questionnaires was rated considerably lower (n=6, 13%-57% [2/16-8/14]) than the scores of intervention efficacy trials (n=8, 48%-85% [13/27-23/27]) and qualitative research (n=17, 40%-93% [8.5/21-19.5/21]). AYAs were receptive to obtaining information via a website or mobile app. An intervention was more likely to be perceived as useful by AYAs when there was a concerted effort to involve AYAs and subject matter experts in the process of intervention design, as opposed to relying solely on the AYAs or the experts alone. The preferred medium of intervention delivery varied greatly for AYAs, ranging from static text to audiovisual materials. However, AYAs considered being concise was the most important aspect. Across different conditions, AYAs were interested in receiving information on diverse topics, such as anxiety and stress management, dealing with insurance, and having social relationships. Patients also requested for disease-specific information, such as weather forecasts and pollen levels for patients with asthma and information related to the pretransplant period for organ transplant recipients. Meta-analyses showed no significant group differences across time on quality of life, self-efficacy, and self-management.ConclusionsOwing to the lack of intervention efficacy trials, no conclusion can be drawn if an intervention delivered via a mobile app is better than that delivered via a website. However, through this systematic review, it is confirmed that AYAs were receptive to receiving medical information electronically.

Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data.

Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming and the spread of highly invasive weeds. The production, release, and dispersal of pollen depend on the ambient weather conditions. The temperature, rainfall, humidity, cloud cover, and wind are known to affect the amount of pollen in the atmosphere. In the past, various regression techniques have been applied to estimate and forecast the daily pollen concentration in the atmosphere based on the weather conditions. In this research, machine learning methods were applied to the Next Generation Weather Radar (NEXRAD) data to estimate the daily Ambrosia pollen over a 300 km × 300 km region centered on a NEXRAD weather radar. The Neural Network and Random Forest machine learning methods have been employed to develop separate models to estimate Ambrosia pollen over the region. A feasible way of estimating the daily pollen concentration using only the NEXRAD radar data and machine learning methods would lay the foundation to forecast daily pollen at a fine spatial resolution nationally.

Applying a pollen forecast algorithm to the Swiss Alps clarifies the influence of topography on spatial representativeness of airborne pollen data

Pollen grains are carriers of allergens, causing severe symptoms to hay fever sufferers. Due to annual variability in pollen levels, there is a need to develop a precise forecasting model that can accurately predict levels of annual airborne pollen for use by patients and medical personnel. In a previous study, we developed and tested a new pollen prediction algorithm based on past meteorological conditions in a flat region. In this study, we analyzed pollen samples (spring 1997–2016) and meteorological data (summer 1991–2015) from nine Swiss cities, using the algorithm to test its applicability in a mountainous region. However, we found variations in model applicability (r2 and RMSE) among the nine observation sites. Based on considerations of topographical influence on the spatial representativeness of airborne pollen data, we then investigated the relationships between these indices and topographical features at varying spatial ranges. The results suggested that the applicability of the algorithm to annual total airborne pollen forecasts can indicate the spatial representativeness of observed airborne pollen concentrations: r2 and RMSE reflected deviations in airborne pollen concentration caused by dispersal conditions at local and meso-scales, respectively. At higher-altitude monitoring sites, the local spatial representativeness of airborne pollen declined due to the influence of local topography-driven climate. On the other hand, dispersal conditions in the atmospheric boundary layer may deteriorate the meso-scale representativeness of airborne pollen at monitoring sites with higher terrain complexity. This study provides a reference approach to determining the spatial representativeness of airborne pollen data by applying the pollen forecast algorithm.

Pollen forecasts in complex topography: two case studies from the Alps using the numerical pollen forecast model COSMO-ART

Pollen concentrations on Alpine mountain tops are poorly known due to few observations and few modeling studies. We present two case studies from the Alps that provide insights into the spatial and temporal distribution of birch pollen. The numerical pollen dispersion model COSMO-ART (COnsortium for Small-scale MOdelling-Aerosols and Reactive Trace gases) was used to simulate the birch pollen transport during the 2017 pollen season. The model configuration included 1.1-km horizontal grid spacing and 80 vertical levels. The simulations were compared with daily pollen concentrations from two mountain tops in the Alps (Weissfluhjoch near Davos, Switzerland, at 2692 m and Schneefernerhaus, Germany, at 2650 m a.s.l.). In addition, the Swiss pollen stations at Davos (1587 m a.s.l.) and Buchs (446 m a.s.l.) were used. COSMO-ART simulations agreed well with the observations at Davos and Weissfluhjoch. At the Environmental Research Station Schneefernerhaus, the pollen concentrations were generally overestimated. We analyzed the pollen transport episode of 9 April 2017 at Weissfluhjoch in more detail using vertical cross sections of the COSMO-ART simulations. The results suggest that pollen can be lifted up to 3000 m in the morning hours and are subsequently transported by large-scale winds leading to higher birch pollen concentrations at Weissfluhjoch than at Davos. This suggests that the actual situation regarding sources, topography and wind determines the pollen distribution and not only altitude. Still, pollen levels at Weissfluhjoch are more than one order of magnitude lower than typical pollen levels at lowland Swiss stations such as Buchs.