Atmospheric Pollen Concentrations Research Articles

Flowering seasonality and airborne pollen recent trends in Sierra de las Nieves, the southernmost National Park in continental Spain

Sierra de las Nieves is the southernmost National Park in continental Spain and, in a global warming scenario, it is important to determine the impacts of climatic variations on the vegetation, with special relevance to their reproductive cycles. The flowering seasonality and intensity of the dominant anemophilous species usually reflect the response of the vegetation to climate variations, which can be monitored through the atmospheric pollen concentrations. In this study, airborne pollen was analysed for 6 years (2018–2023). A pollen calendar was elaborated to show the flowering seasonality and intensity of the dominant anemophilous taxa. Spring was the season with the highest airborne pollen diversity and intensity, Quercus being the pollen type with the highest concentrations. We observed that weather conditions influenced the presence of airborne pollen. Precipitation and relative humidity reduce pollen concentrations, while temperature rises increase them during the pre-peak period and reduce them during the post-peak. Wind dynamics play different roles depending on the pollen type considered given the heterogeneous distribution of the pollen emission sources. Significant advances were detected in the start date of the main pollen season of Quercus and Olea, as well as in the peak date of Quercus. On the contrary, other taxa such as Pinus or Poaceae did not show any trend. This brings to the fore that the responses to climatic variations may differ from one taxon to another, a continuous study in natural areas being required for detecting possible changes in the observed trends.

Influence of spatiotemporal and meteorological variation on Norwegian atmospheric pollen seasonality

Climate change is and will continue to alter plant responses to their environment. This is especially prominent concerning the adaptive tracking in reproductive phenology. For wind pollinated plants, this will substantially influence their pollen seasonality, yet there are gaps in knowledge about how environmental variation influences pollen seasonality. To investigate this, we monitored daily atmospheric pollen concentrations of seven pollen types from ecologically, economically and allergenically important plants (alder, hazel, willow, birch, pine, grass and mugwort) in twelve Norwegian locations spanning the entire country for up to 28 years. Six daily meteorological variables (maximum temperature, precipitation, wind speed, relative humidity, solar radiation and atmospheric pressure) was obtained from the MET Nordic dataset with full data cover. The pollen seasonality was then modelled using four spatial, three temporal and the six meteorological variables in a generalized linear model approach with a negative binomial distribution to investigate how each variable group thematically and individually contribute to variation in pollen seasonality. We found that the full models explained the most variation, ranging from R2 = 20.3 % to 59.5 %. The models were also highly accurate, being able to predict 54.5 % to 99.1 % of daily pollen concentrations to within 20.1 pollen grains/m3. Overall, the temporal variables were able to explain more variation than spatial and meteorological variables for most pollen types. Month, altitude and maximum temperature were the most important single variables for each category. The importance of each variable could be traced back to their individual effects of reproductive phenology, plant metabolism, species distributions and pollen release processes. We further emphasise the importance of source maps and atmospheric regional transport models in further model improvements. By understanding the relevance of environmental variation to pollen seasonality we can make better predictions regarding the consequences of climate change on plant populations.

Atmospheric pollen concentrations and chronic obstructive pulmonary disease (COPD) patients visits in Beijing: time series analysis using a generalized additive model

To investigate the correlation between the daily visits of chronic obstructive pulmonary disease (COPD) patients in hospital clinic and pollen concentrations in Beijing. We collected daily visits of COPD patients of Beijing Shijitan Hospital from April 1st, 2019 to September 30th, 2019. The relationship between pollen concentrations and COPD patient number was analyzed with meteorological factors, time trend, day of the week effect and holiday effect being controlled by the generalized additive model of time series analysis. R4.1.2 software was applied to generate Spearman correlation coefficient, specific and incremental cumulative effect curves of relative risks as well as the response and three-dimensional diagrams for the exposure lag effect prediction. The fitting models were used to predict the lag relative risk and 95% confidence intervals for specific and incremental cumulative effects of specific pollen concentrations. The number of COPD patients was positively correlated with pollen concentration. When pollen concentration increased by 10 grains/1000 mm2, the peak value of the specific cumulative effect appeared on day0, with the effect gone on day4 and a lag time of 4 days observed, whereas the incremental cumulative effect’s peak value was shown on day17, and the effect disappeared on day18, with a lag time of 18 days. The results showed that pollen concentration was not only positively correlated with the number of COPD patients, but also had a bimodal lag effect on COPD visits in the hospital at Beijing.

Effect of atmospheric pollen concentration on daily visits of allergic rhinitis in Beijing: a distributed lag nonlinear model analysis.

To investigate the influence and lag effect of atmospheric pollen concentration on daily visits of patients with allergic rhinitis (AR), we collected the AR data during the pollen seasons from 2018 to 2019 from the outpatient and emergency department of Beijing Shijitan Hospital. The distributed lag non-linear model (DLNM) was used to analyze the correlation and the lag effect between pollen concentration and the incidence of AR. R4.1.2 was used to generate the Spearman correlation coefficients and plot the lag response curves of relative risk specific and incremental cumulative effects. In 2018 and 2019, the number of AR visits was moderately positively correlated with pollen concentration. The peak value of the overall specific cumulative effect for every 10 grains/1000 mm2 increase in atmospheric pollen concentration occurred on day 0 (2018, 2019), and the lag disappearance time was day 6 (2018) and day 7 (2019), and the specific cumulative effect duration was respectively 6 days (2018) and 7 days (2019), with the curve showing a downward trend with time increase. In 2018, the peak value of the overall incremental cumulative effect was on day 7, the lag disappearance time was day 13, and the duration of the incremental cumulative effect was 13 days, forming a curve pattern of rising first and then falling. In 2019, the peak value time of the overall incremental cumulative effect was on day 8, and the curve went down afterwards until it showed the trend of ascending again after day26.

Experimental soiling assessment, characterization and modelling of a highly-compact heliostat field in an urban environment

The soiling effect is presently assessed on heliostats of the very-high concentration solar tower facility located in Móstoles on the outskirts of Madrid, Spain, covering the lack of studies concerning Concentrated Solar Power, but also of key importance for solar-to-heat industrial applications, namely in urban areas. Specular reflectance loss was monitored with a Condor reflectometer on fifteen heliostats spaced throughout the solar field. The objectives were to evaluate the soiling effect in an urban environment during different seasons, including the measurement methodology, soiling ratio characterization, tilt angle to reduce the soiling effect and assessment of soiling intra-heliostat dynamics. Soiling rates ranging from 0.13%/day to 0.58%/day were found for this location, associated with wet and dry seasons, respectively. Special focus is given to assess long-range transports of Saharan desert dust, with soiling ratio losses of up-to 30%, and spring period due to higher atmospheric pollen concentration. Lastly, a detailed evaluation of the intra-heliostat soiling effect was performed leading to the development of soiling models to reduce reflectance loss assessment time by binding localized intra-heliostat measurements and the average soiling ratio between different heliostats with distinct tilt angles.

Comparative aerobiological study between two stations located at different points in a coastal city in Southern Spain

Due to the increase in allergies, aerobiological studies carried out in cities are essential to keep the population informed about the pollen atmospheric concentrations detected. However, the high cost and complexity of aerobiological studies often mean that the information is generated from a single sampling point that may not be representative of the entire city. In this study, the data obtained by two volumetric pollen traps, located in the coastal city of Malaga (Spain) were analyzed. One of the pollen traps was situated in the city center while the other was located on the city outskirts, 5 km away from the first. This was complemented with a meteorological and land use analysis to determine their influence on the pollen concentrations. Despite being located within the same city, the data obtained from both collectors showed significant differences in the relative abundance and annual integrals of the main pollen types, as well as in the periods in which elapse their main pollen seasons. These differences were more notable in the case of Amaranthaceae, Casuarina, Parietaria and Plantago pollen types due to the asymmetric distribution of green areas, agro-forestry areas and urban surfaces within the city, as well as the influence of local wind dynamics on the airborne pollen detected. Despite that, some differences were also observed in the other pollen types. For all the above, we consider that it is important to keep operational several sampling points in cities of a certain magnitude to provide more detailed information about atmospheric pollen concentrations.

A time-series analysis on generalized additive model for atmospheric pollen concentration and the number of visits of allergic conjunctivitis, Beijing, China.

The objective of this study is to investigate the correlation between atmospheric pollen concentration and daily visits for allergic conjunctivitis. Daily counts of outpatient visits for allergic conjunctivitis, atmospheric pollen concentration, and meteorological data during pollen season of 2018 and 2019 were collected from Beijing Shijitan Hospital, China. A time-series analysis on generalized additive model with Poisson distribution was used to estimate the relationship between pollen concentration and visits for allergic conjunctivitis, after controlling for the time trend, weather variables, day of the week, and holiday effect. The RStudio was used to generate Spearman correlation coefficients and then to plot the lag-response curves for specific and incremental cumulative effects of relative risk (RR). There was a moderate positive correlation between pollen concentration and visits for allergic conjunctivitis, and Spearman's correlation coefficient was 0.521 in 2018 and 0.515 in 2019 (P<0.01). The specific cumulative effect peak associated with per 10 grains/kmm2 increases of atmospheric pollen concentration was within 0 day, and the lag time was 8 days(2018, 2019). The incremental cumulative effect peak associated with per 10 grains/kmm2 increases of atmospheric pollen concentration occurred on lag day 10 (2018) and lag day 8 (2019), and the lag time was 14 days (2018) and 20 days (2019). Elevated concentrations of pollen increase the risk of allergic conjunctivitis with a time lag effect.

Do we need aerobiological air monitoring in desert climates? The Qatar experience.

Knowledge about diurnal, seasonal, and annual fluctuations in airborne pollen and fungal spores in any geographical area is essential for effective diagnosis and treatment of allergies. Aerobiological analysis enables the detection of airborne pollen and spores, thus providing information on plant phenology, plant distribution, related diseases, and the risks for some species in terms of allergies. Although pollen and fungal spores have been widely studied as aeroallergens throughout the world, not much is known about the biological aerosols in countries with a desert environment; and these could be present in much higher concentrations than expected. Arid desert regions (including the region surrounding the Arab Gulf), characterized by hot weather, poor soils, and low biological productivity, have typically been neglected when building ambitious biomonitoring networks for the large-scale monitoring of biological particles; however, few studies in Kuwait, Saudi Arabia, and recently Qatar have aimed to delineate the various botanical families that contribute to inhalant allergens in this region.Understanding the aerobiological features of countries with hot and desert climates may better prepare healthcare providers to assist patients with allergic rhinitis. It may be argued that one of the reasons why aerobiologists have only recently turned their attention to the state of Qatar investigating how pollen and fungal spore records could contribute to evaluating the correlation between different pollen conditions and allergy symptoms.The first aerobiological network of Qatar was monitoring (2017–2020) the atmospheric pollen concentrations of Doha and Al Khor to determine the association between the possible risk of respiratory allergies and the distribution of certain species throughout the region. In the Qatari database, more than 25 native taxa have been recorded, up to 50% of which can be considered allergenic. This includes Amaranthaceae and Poaceae pollen among the major aeroallergens causing allergy symptoms in Qatar. Our study has confirmed a statistically significant association between Amaranthaceae and asthma and allergic rhinitis. To summarize, it is worth considering aerobiological monitoring in desert climate regions when assessing the effectiveness of pollen allergy therapy and planning prevention methods for patients.

Phenological and seismological impacts on airborne pollen types: A case study of Olea pollen in the Region of Murcia, Mediterranean Spanish climate

The rationale of this paper was to investigate whether earthquakes impact airborne pollen concentrations, considering some meteorological parameters. Atmospheric pollen concentrations in the Region of Murcia Aerobiological Network (Spain) were studied in relation to the occurrence of earthquakes of moment magnitude (up to Mw = 5.1) and intensity (intensity up to grade VII on the European Macroseismic Scale). In this study, a decade (2010–2019) was considered across the cities of the network. Earthquakes were detected in 12 out of 1535 days in the Olea Main Pollen Season in Cartagena, 49 out of 1481 days in the Olea Main Pollen Season in Lorca, and 39 out of 1441 days in the Olea Main Pollen Season in Murcia. The Olea pollen grains in this network were attributed to the species Olea europaea, i.e., the olive tree, a taxon that appears widely in the Mediterranean basin, in both cultivated and wild subspecies. Differences between the Olea concentration on days with and without earthquakes were only found in Lorca (Kruskal-Wallis: p-value = 0.026). The low frequency and intensity of the earthquakes explained these results. The most catastrophic earthquake felt in Lorca on May 11th, 2011 (IVII, Mw = 5.1, 9 casualties) did not result in clear variations in pollen concentrations, while meteorology (e.g., African Dust Outbreak) might have conditioned these pollen concentrations. The research should be broadened to other active seismological areas to reinforce the hypothesis of seismological impact on airborne pollen concentrations.

Characterising non-linear associations between airborne pollen counts and respiratory symptoms from the AirRater smartphone app in Tasmania, Australia: A case time series approach

Pollen is a well-established trigger of asthma and allergic rhinitis, yet concentration-response relationships, lagged effects, and interactions with other environmental factors remain poorly understood. Smartphone technology offers an opportunity to address these challenges using large, multi-year datasets that capture individual symptoms and exposures in real time. We aimed to characterise associations between six pollen types and respiratory symptoms logged by users of the AirRater smartphone app in Tasmania, Australia. We analyzed 44,820 symptom reports logged by 2272 AirRater app users in Tasmania over four years (2015–2019). With these data we evaluated associations between daily respiratory symptoms and atmospheric pollen concentrations. We implemented Poisson regression models, using the case time series approach designed for app-sourced data. We assessed potentially non-linear and lagged associations with (a) total pollen and (b) six individual pollen taxa. We adjusted for seasonality and meteorology and tested for interactions with particulate air pollution (PM2.5). We found evidence of non-linear associations between total pollen and respiratory symptoms for up to three days following exposure. For total pollen, the same-day relative risk (RR) increased to 1.31 (95% CI: 1.26–1.37) at a concentration of 50 grains/m3 before plateauing. Associations with individual pollen taxa were also non-linear with some diversity in shapes. For all pollen taxa the same-day RR was highest. The interaction between total pollen and PM2.5 was positive, with risks associated with pollen significantly higher in the presence of high concentrations of PM2.5. Our results support a non-linear response between airborne pollen and respiratory symptoms. The association was strongest on the day of exposure and synergistic with particulate air pollution. The associations found with Dodonaea and Myrtaceae highlight the need to further investigate the role of Australian native pollen types in allergic respiratory disease.

The Impact of Climate Change on the Pollen Allergy and Sporulation of Allergic Fungi

The purpose of this chapter is to review allergic disease and how it is potentially impacted by climate change. It is difficult to measure the direct impact climate change has on allergic disease. This is difficult because there are many variables impacting human health as well as what capacity humans have to adapt to these changes. Asthma is tightly associated with allergies and environmental factors, especially in children. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy and associated respiratory disease. Furthermore, this paper is to review the impact of climate change on allergy to atmospheric fungi which are known to cause a common allergic response. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy. The climate has been measurably changing for the past 100 years and has been described as the most significant health threat of the twenty-first century. How climate change impacts human health is varied and coming more into focus. While direct effects, such as heatwaves, severe weather, drought, and flooding, are well reported, effects that are indirect or secondary impacts involving changes in ecosystems are less obvious, though the body of data is growing and becoming more robust. It is these changes in ecosystems that may have the greatest impact on allergic and respiratory diseases. Otherwise, the airborne pollens and spores have also been linked with upper and lower respiratory conditions. Atmospheric pollen and spore concentrations are influenced by a wide array of environmental, meteorological, and biological factors and various interspecies interactions. Pollen and spores underlie seasonal variations. Especially climatic factors and circadian patterns influence the spectrum of their species and their concentrations in the environment. It may have the greatest impact on respiratory allergic diseases. This review will explore some of the impacts our changing climate, current and predicted, has which influences upper and lower respiratory allergic diseases. The discussion will focus on changing pollination with altered pollen patterns, as well as alteration of the composition and transformation of atmospheric allergic fungi with increased CO2 air pollution and heat stress. The sporulation of fungi is likely to be amplified as CO2 concentration increases with climate change, potentially contributing to the increasing prevalence and severity of asthma and other respiratory allergies.

Standardising pollen monitoring: quantifying confidence intervals for measurements of airborne pollen concentration

Measurement of atmospheric pollen concentrations is inexact, yet pollen concentrations are universally reported without estimate of accuracy. These imprecise values are nevertheless used for modelling, forecasting and public health decision-making. Estimation of the variability in reported pollen concentrations would help resolve associations between weather and pollen aerobiology as well as associations between pollen exposure and health. For any given daily atmospheric pollen level, a statistical variability would be expected in the set of possible measures. This variability is introduced and compounded by many factors including human error, classification error or instrument variability, as well as variability derived from strategies used to count and scale the airborne pollen sample. Here, we performed numeric simulations of pollen deposition and modelled the variability in contemporary pollen density estimates. Statistical distribution of the mean and variance of these simulated counts was compared with an existing pollen count dataset. Both simulations and actual pollen data showed that a significant range of atmospheric pollen concentrations could be inferred from the same daily pollen collection. The range of possible concentrations varied both with the atmospheric pollen density and with the portion of the daily pollen sample that is counted. Furthermore, pollen concentration data were shown to be non-normal and heteroscedastic, which has implications for a variety of tests (e.g. ANOVA), for regression analysis, and for pollen forecasting and forecast verification. These results reinforce the importance of counting as much of the collected pollen impaction surface as feasible to minimise the uncertainty in reported pollen levels. The outcomes of this study suggest that confidence intervals for daily pollen concentrations should be reported.

The impact of rainfall on the diurnal patterns of atmospheric pollen concentrations

Atmospheric precipitation removes the majority of biological and chemical pollutants from the lower parts of the troposphere. However, some studies infer increasing atmospheric pollen concentrations during precipitation events and/or thunderstorms, which are known to trigger allergic reactions (referred to as thunderstorm-triggered asthma). The aim of this study was to determine the impacts of precipitation on the diurnal variability of airborne pollen concentrations, with particular focus on the timing and intensity of precipitation events. We also considered the impacts of other meteorological elements on atmospheric pollen concentrations. The research was conducted in Rzeszów (SE Poland) from 2016 to 2018. We used two aerobiological and two meteorological stations in this study to determine potential spatial variability in the pollen response to rainfall, the diurnal precipitation changes, and the precipitation intensity in the city area. We determined the pollen response of four pollen types: Betula, Pinus, Poaceae, and Urtica, and we only included data from days that fulfilled restrictive criteria throughout all pollen seasons. We analysed a total of 81 days, which were divided into five groups according to precipitation intensity, the time of day of a precipitation event, and the type of pollen response to precipitation. Our results suggest that precipitation intensity was the dominant control on pollen concentrations; concentrations only decreased clearly under rainfall intensities of at least 5 mm•h−1 and this value we recommended as threshold value for long lasting decrease of pollen concentrations in our region. Lower intensity rainfall events resulted in no change in atmospheric pollen concentrations throughout the day. We noted the occurrence of increased pollen concentration immediately before and during rainfall events. Further, other parameters were also found to influence pollen concentrations in the atmosphere, including relative humidity, the time of day, and biological factors such as the plant phenophase or the phase of a pollen season.

Climate change and allergy in Australia: an innovative, high-income country, at potential risk.

The impacts of climate change on allergens and allergic diseases are important and potentially serious in Australia. Australia is highly vulnerable to such impacts because of its very high prevalence of allergic diseases such as asthma and allergic rhinitis, and allergic sensitisation to environmental allergens such as certain pollens and fungal spores. This article aims to review published research on the impacts of climate change on allergens and allergic diseases from an Australian perspective. Research on climate change, allergens and allergy was reviewed. Recent global assessments of the topic were consulted, and supplemented with database searches to identify research published since the assessments were done, as well as research with an Australian focus. The databases used were Web of Science and Scopus. Only research published since the year 2000 was included. The impacts of climate change on allergens and allergic diseases are many and varied. Impacts on pollen include effects on pollen production and atmospheric pollen concentration, pollen seasonality, pollen allergenicity, and the dispersion and spatial distribution of pollen. Similarly, there is evidence for effects on fungal spore production, seasonality and allergenicity. There are also likely effects on indoor moisture and mould growth. Beyond these respiratory allergens, climate change may also affect food allergens, stinging insect allergens and contact allergens. All these changes could affect allergic diseases, in particular allergic respiratory diseases such as allergic asthma and allergic rhinitis. A large and sophisticated body of research exists from which to gauge both current and potential future impacts of climate change on allergens and allergic diseases. However, most, if not all, of this is from outside Australia. Australian-focused research is therefore urgently needed. Australia's vulnerability to the adverse effects of climate change on allergic diseases is compounded by the precarious nature of aeroallergen monitoring, reporting and forecasting in this country. But Australia has an impressive wealth of relevant experience and expertise, and has the potential to address the challenge of both current and future impacts of climate change on allergens and allergic diseases.

Using machine learning to estimate atmospheric pollen concentrations in Tulsa, OK

This article describes an example of using machine learning to estimate the abundance of airborne Ambrosia pollen for Tulsa, OK. Twenty-seven years of historical pollen observations were used. These pollen observations were combined with machine learning and a very complete meteorological and land surface context of 85 variables to estimate the daily Ambrosia abundance. The machine learning algorithms employed were Least Absolute Shrinkage and Selection Operator (LASSO), neural networks, and random forests. The best performance was obtained using random forests. The physical insights provided by the random forest are also discussed.

Relationships between airborne pollen grains, wind direction and land cover using GIS and circular statistics.

Airborne bio-aerosol content (mainly pollen and spores) depends on the surrounding vegetation and weather conditions, particularly wind direction. In order to understand this issue, maps of the main land cover in influence areas of 10km in radius surrounding pollen traps were created. Atmospheric content of the most abundant 14 pollen types was analysed in relation to the predominant wind directions measured in three localities of SW of Iberian Peninsula, from March 2011 to March 2014. Three Hirst type traps were used for aerobiological monitoring. The surface area for each land cover category was calculated and wind direction analysis was approached by using circular statistics. This method could be helpful for estimating the potential risk of exposure to various pollen types. Thus, the main land cover was different for each monitoring location, being irrigated crops, pastures and hardwood forests the main categories among 11 types described. Comparison of the pollen content with the predominant winds and land cover shows that the atmospheric pollen concentration is related to some source areas identified in the inventory. The study found that some pollen types (e.g. Plantago, Fraxinus-Phillyrea, Alnus) come from local sources but other pollen types (e.g. Quercus) are mostly coming from longer distances. As main conclusions, airborne particle concentrations can be effectively split by addressing wind with circular statistics. By combining circular statistics and GIS method with aerobiological data, we have created a useful tool for understanding pollen origin. Some pollen loads can be explained by immediate surrounding landscape and observed wind patterns for most of the time. However, other factors like medium or long-distance transport or even pollen trap location within a city, may occasionally affect the pollen load recorded using an air sampler.

A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function.

Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2% and 92.5-98.5% for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

Correlation between airborne Olea europaea pollen concentrations and levels of the major allergen Ole e 1 in Córdoba, Spain, 2012-2014.

Olea europaea L. pollen is the second-largest cause of pollinosis in the southern Iberian Peninsula. Airborne-pollen monitoring networks provide essential data on pollen dynamics over a given study area. Recent research, however, has shown that airborne pollen levels alone do not always provide a clear indicator of actual exposure to aeroallergens. This study sought to evaluate correlations between airborne concentrations of olive pollen and Ole e 1 allergen levels in Córdoba (southern Spain), in order to determine whether atmospheric pollen concentrations alone are sufficient to chart changes in hay fever symptoms. The influence of major weather-related variables on local airborne pollen and allergen levels was also examined. Monitoring was carried out from 2012 to 2014. Pollen sampling was performed using a Hirst-type sampler, following the protocol recommended by the Spanish Aerobiology Network. A multi-vial cyclone sampler was used to collect aeroallergens, and allergenic particles were quantified by ELISA assay. Significant positive correlations were found between daily airborne allergen levels and atmospheric pollen concentrations, although there were occasions when allergen was detected before and after the pollen season and in the absence of airborne pollen. The correlation between the two was irregular, and pollen potency displayed year-on-year variations and did not necessarily match pollen-season-intensity.

Seasonal variation of airborne ragweed (Ambrosia artemisiifolia L.) pollen in Zagreb, Croatia

Previous research indicated that airborne ragweed pollen concentrations may be influenced by weather-related factors. Therefore, the object of this work was to examine the variation in daily pollen concentrations during four ragweed pollen seasons (2006–2009) in the highly urban area of Zagreb. Ragweed pollen grains were collected using a Burkard volumetric sampler (N45°49′55″, E15°58′54″). Meteorological data (maximum, minimum and mean temperatures, relative humidity, wind speed, precipitation, atmospheric pressure and irradiance) were related to daily pollen counts during the ragweed pollen season. The ragweed pollen season started around late July in 2007 and 2009, while it started on 15 August in 2006, the year characterized by a cold spring. However, the start dates of the pollen seasons were not related to the accumulation of thermal units. Maximum daily concentration of 363 grains m−3 was detected on 27 August 2008. Total airborne pollen concentrations ranged from 1188 grains m−3 in 2007 to 4384 grains m−3 in the following year, whereas the duration of ragweed pollen season varied from 50 days in 2008 to 72 days in 2007. The peak of the ragweed pollen season varied from 21 days in 2007 to 36 days in 2009 for airborne pollen concentrations ≥20 grains m−3 and from 1 day in 2007 to 20 days in 2008 for airborne pollen concentrations >80 grains m−3. Airborne pollen levels were affected by weather parameters such as temperature, sunshine, relative humidity, precipitation and wind speed in some ragweed pollen seasons in Zagreb, but these responses were inconsistent over the entire investigated period. Our study showed that large year-to-year variations in atmospheric pollen concentrations in Zagreb could not be consistently related to any of the analysed weather parameters.

Relationship between flowering phenology, pollen production and atmospheric pollen concentration of Plantago lanceolata (L.)

The present study sampled pollen grains in the atmosphere using a Burkard® 7-day-recording trap and periodically checked the flowering phases of Plantago lanceolata L. in the locality of Leon (NW of Spain) from late March to early August during 2007 and 2008. The results showed that the phenological phases considered for P. lanceolata coincided in most sampling points. The differences between them depended mainly on the characteristics of the land on which the plants developed and water availability. In addition, the differences between the start and duration of the different phenological phases over the 2 years were mainly due to climatic variations each year. Plantago pollen concentration in the atmosphere and phenological data were related during these 2 years of study. The differences in Plantago pollen production per anther were determined by environmental conditions such as humidity. Another important factor was human action.