Integration of flowering dates in phenology and pollen counts in aerobiology: analysis of their spatial and temporal coherence in Germany (1992–1999)

We studied the possibility of integrating flowering dates in phenology and pollen counts in aerobiology in Germany. Data were analyzed for three pollen types (Betula, Poaceae, Artemisia) at 51 stations with pollen traps, and corresponding phenological flowering dates for 400 adjacent stations (< 25 km) for the years 1992–1993 and 1997–1999. The spatial and temporal coherence of these data sets was investigated by comparing start and peak of the pollen season with local minima and means of plant flowering. Our study revealed that start of birch pollen season occurred on average 5.7 days earlier than local birch flowering. For mugwort and grass, the pollen season started on average after local flowering was observed; mugwort pollen was found 4.8 days later and grass pollen season started almost on the same day (0.6 days later) as local flowering. Whereas the peak of the birch pollen season coincided with the mean flowering dates (0.4 days later), the pollen peaks of the other two species took place much later. On average, the peak of mugwort pollen occurred 15.4 days later than mean local flowering, the peak of grass pollen catches followed 22.6 days after local flowering. The study revealed a great temporal divergence between pollen and flowering dates with an irregular spatial pattern across Germany. Not all pollen catches could be explained by local vegetation flowering. Possible reasons include long-distance transport, pollen contributions of other than phenologically observed species and methodological constraints. The results suggest that further research is needed before using flowering dates in phenology to extrapolate pollen counts.     

Long-term and short-term forecast models for Poaceae (grass) pollen in Poznań, Poland,constructed using regression analysis

Airborne concentrations of Poaceae pollen have been monitored in Poznań for more than 10 years and the length of the dataset is now considered sufficient for statistical analysis. The objective of this paper is to produce long-range forecasts that predict certain characteristics of the grass pollen season (such as the start, peak and end dates of the grass pollen season) as well as short-term forecasts that predict daily variations in grass pollen counts for the next day or next few days throughout the main grass pollen season. The method of forecasting was regression analysis. Correlation analysis was used to examine the relationship between grass pollen counts and the factors that affect its production, release and dispersal. The models were constructed with data from 1994 to 2004 and tested on data from 2005 and 2006. The forecast models predicted the start of the grass pollen season to within two days and achieved 61% and 70% accuracy on a scale of 1–4 when forecasting variations in daily average grass pollen counts in 2005 and 2006, respectively. This study has emphasised how important the weather during the few weeks or months preceding pollination is to grass pollen production, and draws attention to the importance of considering large-scale patterns of climate variability (indices of the North Atlantic Oscillation) when constructing forecast models for allergenic pollen.     

Influence of the North Atlantic Oscillation on grass pollen counts in Europe

Relationships between temporal variations in the North Atlantic Oscillation (NAO) and grass pollen counts at 13 sites in Europe, ranging from Córdoba in the south-west and Turku in the north-east, were studied in order to determine spatial differences in the amount of influence exerted by the NAO on the timing and magnitude of grass pollen seasons. There were a number of significant (P < 0.05) relationships between the NAO and start dates of the grass pollen season at the 13 pollen-monitoring sites. The strongest associations were generally recorded near to the Atlantic coast. Several significant correlations also existed between winter averages of the NAO and grass pollen season severity. Traditional methods for predicting the start or magnitude of grass pollen seasons have centred on the use of local meteorological observations, but this study has shown the importance of considering large-scale patterns of climate variability like the NAO.     

Airborne grass pollen in Leiden, The Netherlands: annual variations and trends in quantities and season starts over 26 years

The long-term, 26 years’ data set of observations on daily concentrations of airborne grass pollen in Leiden is analyzed to present the variations and trends in quantities, and season starting dates. Monitoring of airborne pollen has been done continuously at one location, with a volumetric pollen trap. Annual totals of daily average grass-pollen concentrations are within a normal range of an urban site between 3690 and 9277, averagely 5510. The annual totals are irregularly fluctuating from year to year, and show no increasing or decreasing trend. Each year’s seasonal fluctuation is different, probably under the influence of changing weather conditions. The typical grass-pollen month is June. Using the Σ 75 criterium, the average starting date is on 16 May, whereas with the 1% threshold criterium the start of the grass-pollen season averagely is on 3 June. The mean air temperature in the preceding period is taken as the main factor for the timing of the season start. Analyzing the relationships of the two different criteria for the season starts with a number of temperature observation periods, the best relations were found between the mean air temperature in the period 11 April to 20 May and the Σ 75 criterium season start on 16 May (r=−0.78); and between the mean air temperature in May and the 1% threshold criterium season start on 3 June (r=−0.76). Forecasts of the season start which are significantly better than the average starting date are only possible with the mean air temperature up to a few days before the actual start. This limits the practical usefulness of the forecasting system.     

A long-term study of winter and early spring tree pollen in the Tulsa, Oklahoma atmosphere

Since 1986 the atmosphere in Tulsa, Oklahoma has been monitored for airborne pollen and spores with a Burkard 7-day spore trap situated on the roof of a building at The University of Tulsa. The present study specifically examined the early spring tree pollen season for several local taxa and the occurrence of pre-season pollen during December and January. Knowledge of the local pollen season will help identify the presence of out-of-season pollen and possible long distance transport (LDT) events. Average daily concentrations of airborne pollen for species ofBetula, Quercus, Ulmus, and Cupressaceae were determined for each year from 1987 to 1996. The data showed that during the early spring the precise pollination periods for these allergenic tree species are highly variable. There were considerable variations in start date, season length, peak concentration, date of peak, and cumulative season total. The start dates forUlmus, Betula, andQuercus varied by 30 days or more, while the early spring Cupressaceae pollen showed the least variation in start date (only 23 days). More research is needed to understand the mechanisms which govern the onset and magnitude of pollen release. Although several reports have documented episodes of long distance transport (LDT) of pollen, the actual contribution of out-of-season or out-of-region pollen to local air spora is poorly known. The current study also re-examined the LDT ofJuniperus ashei pollen in Oklahoma.Juniperus pollen appeared in the Tulsa atmosphere on 40% of the days in December and January with concentrations as high as 2400 pollen grains/m³ of air; however, no local populations ofJuniperus pollinate at this time of the year. High concentrations occurred on days with southerly winds suggesting thatJuniperus ashei populations in southern Oklahoma and Texas were the pollen source. Since no local pollen is present in the Tulsa atmosphere in December and January, this example of LDT has been easy to document.     

On the causes of variability in amounts of airborne grass pollen in Melbourne,Australia

In Melbourne, Australia, airborne grass pollen is the predominant cause of hay fever (seasonal rhinitis) during late spring and early summer, with levels of airborne grass pollen also influencing hospital admissions for asthma. In order to improve predictions of conditions that are potentially hazardous to susceptible individuals, we have sought to better understand the causes of diurnal, intra-seasonal and inter-seasonal variability of atmospheric grass pollen concentrations (APC) by analysing grass pollen count data for Melbourne for 16 grass pollen seasons from 1991 to 2008 (except 1994 and 1995). Some of notable features identified in this analysis were that on days when either extreme (>100 pollen grains m⁻³) or high (50–100 pollen grains m⁻³) levels of grass pollen were recorded the winds were of continental origin. In contrast, on days with a low (<20 pollen grains m^-3) concentration of grass pollen, winds were of maritime origin. On extreme and high grass pollen days, a peak in APC occurred on average around 1730 hours, probably due to a reduction in surface boundary layer turbulence. The sum of daily APC for each grass pollen season was highly correlated (r = 0.79) with spring rainfall in Melbourne for that year, with about 60% of a declining linear trend across the study period being attributable to a reduction of meat cattle and sheep (and hence grazing land) in rural areas around Melbourne. Finally, all of the ten extreme pollen events (3 days or more with APC > 100 pollen grains m⁻³) during the study period were characterised by an average downward vertical wind anomaly in the surface boundary layer over Melbourne. Together these findings form a basis for a fine resolution atmospheric general circulation model for grass pollen in Melbourne’s air that can be used to predict daily (and hourly) APC. This information will be useful to those sectors of Melbourne’s population that suffer from allergic problems.     

10. Na Bahně (Czech Republic): Vegetation development over the last 2.5 millennia in the Eastern Bohemian lowland

To determine the best date for patients in the southern part of the Netherlands to begin treatment for pollinosis, an attempt was made to predict the start of the grass pollen season at Helmond as accurately as possible, as was previously done at Leiden. The start of the grass pollen season was defined as the date when at a given location the accumulated total (from 1 Jan.) of 24 h average grass pollen concentrations (No./m³) reaches 100 (the so-called Σ100-method). Using the phenological method over the years 1981 through 1985, with the birch (Σ125=x) as the indicator plant, the start of the grass pollen period (Σ100=z) could be predicted much more accurately than would have been possible solely on the basis of the mean starting dates in the preceding years. The predicted starting date (z) can be calculated with the equation z=0.44x+95.46 (x and z as day-of-year numbers), SD=3.6 days, r=0.83, n=5). The SD of the Σ100-method of grasses being 5.6 days, the effectivity of the prediction is 35.7%. The difference in results between Helmond and Leiden is discussed.     

Global warming and the earlier start of the Japanese-cedar (Cryptomeria japonica) pollen season in Toyama, Japan

Atmospheric pollen surveys were conducted in Toyama City, Japan over a 21-year period (1983–2003). Airborne pollen was collected by two methods, the gravimetric method and the volumetric method. The gravimetric method indicated that the start of the Cryptomeria japonica pollen season, as indicated by pollen dispersion, has advanced from day 73 (from January 1) in 1983 to day 47 in 2003. Measurements taken using the volumetric method confirmed this trend. There was a significant correlation between the start dates obtained by both methods. Meteorological data indicated that the most noticeable elevation in temperature during the experimental period occurred in February – an increase of 2.1°C. Significant correlations existed between the mean temperatures and the start dates of the pollen season. These results support the steadily increasing number of reports indicating a global warming trend. The temperature change in February in affecting the start dates of the C. japonica pollen season is particularly relevant in the context of human health. Further studies will be needed to clarify the effects of the global warming trend on the pollen season and human health in more detail.     

Predicting the grass pollen count from meteorological data with regard to estimating the severity of hayfever symptoms in Melbourne (Australia)

In Melbourne, Australia, grass pollen is the predominant cause of hayfever in late spring and summer. The grass pollen season has been monitored in Melbourne, using a Burkard spore trap, for 13 years (1975–1981, 1985 and 1991–1997). Total counts for grass pollen were highly variable from one season to the next (approximately 1000 to >8000 grains/m³). The daily grass pollen counts also showed a high variability (0 to approximately 400 grains/m³). In this study, the grass pollen counts of the 13 years (12 grass pollen seasons, extending from October to January) have been compared with meteorological data in order to identify the conditions that can determine the daily amounts of grass pollen in the air. It was found that the seasonal total of grass pollen was directly correlated with the rainfall sum of the preceding 12 months (1 September–31 August): seasonal total of grass pollen (counts/m³)=18.161 × rainfall sum of the preceding 12 months (mm) −8541.5 (r _s=0.74,P<0.005,n=12). The daily amounts of grass pollen in the air were positively correlated with the corresponding daily average ambient temperatures (P<0.001). The daily amount of grass pollen which was to be expected with a certain daily average temperature was linked to the seasonal total of grass pollen: in years with high total grass pollen counts, a lower daily average temperature was required for a high daily pollen count than in years with low total grass pollen counts. As the concentration of airborne grass pollen determines the severity of hayfever in sensitive patients, an estimation of daily grass pollen counts can provide an indication of potential pollinosis symptoms. We compared daily grass pollen counts with the reported symptomatic responses of hayfever sufferers in November 1985 and found that hayfever symptoms were significantly correlated to the grass pollen counts (P<0.001 for nasal,P<0.005 for eye symptoms). Thus, a combination of meteorological information (i.e. rainfall and temperature) allows for an estimation of the potential daily pollinosis symptoms during the grass pollen season. Here we propose a symptom estimation chart, allowing a quick prediction of eye and nasal symptoms that are likely to occur as a result of variations in meteorological conditions, thus enabling both physicians and patients to take appropriate avoidance measures or therapy.     

<Emphasis Type="BoldItalic">Betula</Emphasis> spp. pollen in the atmosphere of Novi Sad (2000–2002)

Pollen of Betula spp. is one of the main European aeroallergens. The aim of this study was to determine characteristics and occurrence of the Betula pollen in Novi Sad atmosphere, based on 3-year observations (2000–2002), and to compare pollen season start dates calculated by different methods. Pollen samples have been collected by Hirst volumetric method with a 7-day Burkard spore trap. Four methods (Sum 75, 2.5%, 30 and 1 pg/m ³) have been used for determination of the start dates of the Betula pollen season and the results have been compared. The total annual pollen sum increased during the observed period. In 2000, 2001 and 2002, the highest daily pollen concentrations were 97, 137 and 1034 pg/m ³, respectively. The earliest Betula pollen season start has been calculated by the 1 pg/m ³ method.     

Airborne pollen in Nuuk, Greenland, and the importance of meteorological parameters

To describe the season of airborne pollen ofbirch and grass in the city of Nuuk, Greenland,pollen concentrations were measured dailythroughout the pollen seasons in 1997 to 1999.The study was part of a large epidemiologicalcross-sectional study of allergy and riskfactors for allergy in Greenlander Inuit livingin Greenland and Denmark.For the three years the mean birch pollenseason started around 8 June, lasted in average16 days and the mean annual total pollen countwas 46. The highest daily concentration of 23birch pollen pr. m³ was measured in 1999.The mean grass pollen season began around 22July, it lasted 53 days and the mean annualtotal pollen count was 81. The highest grasspollen number registered for one day reached 12in 1998. Several other types of pollen werealso measured, generally in smallconcentrations, but for Cyperaceae and Alderthe mean annual total pollen count were 43 and19 respectively. Though the measuredconcentrations are small, it is concluded thatairborne pollen occur in the arctic climate ofNuuk in potentially clinically relevantamounts.For the three years large variations wereobserved for the start, duration and amountsfor both birch and grass. Models forestimation of the starting date based onGrowing Degree Hours (GDHs) predicted the startof the birch and grass pollen with greataccuracy – within one day. Analysis of themeteorological conditions show that themeasured pollen in general originated from thearea around Nuuk, but there are indicationsthat pollen might have been long-transportedfrom Canada.     

Temporal and geographical variations in grass pollen seasons in areas of west0ern Europe: an analysis of season dates at sites of the European pollen information system

Geographical and temporal variations in the start dates of grass pollen seasons are described for selected sites of the European Pollen Information Service. Daily average grass pollen counts are derived from Network sites in Finland, the Netherlands, Denmark, United Kingdom, Austria, Italy and Spain, giving a broad longitudinal transect over Western Europe. The study is part of a larger project that also examines annual and regional variations in the severity, timing of the peak and duration of the grass pollen seasons. For several sites, data are available for over twenty years enabling long term trends to be discerned. The analyses show notable contrasts in the progression of the seasons annually with differing lag times occurring between southern and northern sites in various years depending on the weather conditions. The patterns identified provide some insight into geographical differences and temporal trends in the incidence of pollinosis. The paper discusses the main difficulties involved in this type of analysis and notes possibilities for using data from the European Pollen Information service to construct pan European predictive models for pollen seasons. This revised version was published online in June 2006 with corrections to the Cover Date.     

The effect of the meteorological factors on the Alnus pollen season in Lublin (Poland)

Alder pollen seasons and the effect of meteorological conditions on daily average pollen counts in the air of Lublin (Poland) were analysed. Alnus pollen grains reach very high concentrations in the atmosphere of this city during the early spring period and the parameters of pollen seasons were very different in the particular years studied. The pollen season lasted on average one month. The highest variation was observed for the peak value and the Seasonal Pollen Index (SPI). The pollen seasons, which started later, had shorter duration. Peak daily average pollen counts and SPI value were higher during the shorter seasons. Similarities in the stages of pollen seasons designated by the percentage method depended on the start date of the pollen season. Season parameters were mainly correlated with thermal conditions at the beginning of the year. Regression analysis was used to predict certain characteristics of the alder pollen season. The highest level of explanation of the variation in Alnus pollen season start and peak dates was obtained in the model using mean temperature in February. The obtained regression models may predict 82% of the variation in the pollen season start date, 73% of the variation in the duration, and 62% in the peak date.     

Regional and seasonal variation in airborne grass pollen levels between cities of Australia and New Zealand

Although grass pollen is widely regarded as the major outdoor aeroallergen source in Australia and New Zealand (NZ), no assemblage of airborne pollen data for the region has been previously compiled. Grass pollen count data collected at 14 urban sites in Australia and NZ over periods ranging from 1 to 17 years were acquired, assembled and compared, revealing considerable spatiotemporal variability. Although direct comparison between these data is problematic due to methodological differences between monitoring sites, the following patterns are apparent. Grass pollen seasons tended to have more than one peak from tropics to latitudes of 37°S and single peaks at sites south of this latitude. A longer grass pollen season was therefore found at sites below 37°S, driven by later seasonal end dates for grass growth and flowering. Daily pollen counts increased with latitude; subtropical regions had seasons of both high intensity and long duration. At higher latitude sites, the single springtime grass pollen peak is potentially due to a cooler growing season and a predominance of pollen from C₃ grasses. The multiple peaks at lower latitude sites may be due to a warmer season and the predominance of pollen from C₄ grasses. Prevalence and duration of seasonal allergies may reflect the differing pollen seasons across Australia and NZ. It must be emphasized that these findings are tentative due to limitations in the available data, reinforcing the need to implement standardized pollen-monitoring methods across Australasia. Furthermore, spatiotemporal differences in grass pollen counts indicate that local, current, standardized pollen monitoring would assist with the management of pollen allergen exposure for patients at risk of allergic rhinitis and asthma.     

A method to forecast the start of theBetula, Platanus andQuercus pollen seasons in North London

This paper attempts the prediction of the start of theBetula, Quercus andPlatanus pollen seasons in London, UK based on pollen sampling conducted over a 5-year period, 1987–1991. The times at which eight different thresholds of accumulated daily pollen counts (M⁻³) were passed were correlated against heat sums, chill units, accumulated sunshine hours, monthly meteorological parameters and the start dates of earlier pollen seasons to identify significant associations. Few meteorological parameters were significantly correlated with the start dates of the three pollen seasons, the exceptions being significant negative correlations between the average monthly air temperature in the months immediately preceding theBetula andPlatanus pollen season. However, significant relationships were identified between the start dates of theBetula, Quercus andPlatanus pollen seasons and the start of theCorylus, Taxus andPopulus pollen seasons with coefficients of determination as high as 98%. These indicator species were then used as predictors to forecast the start of theBetula, Quercus andPlatanus pollen seasons, both individually and in combination with one another, providing levels of explanation of up to 99%.     

Monitoring biogeographical response to climate change: The potential role of aeropalynology

To test models predicting biological reponse to future climate change, it is essential to find climatically-sensitive, easily monitored biological indicators that respond to climate change. Routine monitoring of airborne pollen, now undertaken on a near-global basis, could be adapted for this purpose. Analysis of spatial and seasonal variations in pollen levels in New Zealand suggests that the timing of onset and peak abundance of certain pollen taxa should be explored as possible bio-indicators of climate change. The onset of the airborne grass pollen season during the summer of 1988/89 varied consistently with latitude, and hence temperature, with the season in Southland commencing 8--9 days after Northland. However, these patterns were only apparent after sampling sites were separated into two groups reflecting predominantly urban or rural pollen sources. A less consistent north to south trend was apparent in the frequency of high (30 grains/m³) grass pollen levels, with high levels frequent in North Island localities in November, December and January and in southern localities during December and January. The successive onset of pollen seasons for the principal tree species during the spring-to-early summer warming interval may also be a useful bio-indicator of climate change. As well as assisting forecasts of the onset of the pollinosis season, these biogeographical patterns, reflecting climatic variation with latitude, suggest that routine aeropalynological monitoring might provide early signals of vegetation response to climate change. These conclusions are supported by recent investigations of long-term aeropalynological datasets in Europe that indicate earlier onset of pollen seasons in response to recent global warming.     

Poaceae pollen in the air depending on the thermal conditions

The relationship between the meteorological elements, especially the thermal conditions and the Poaceae pollen appearance in the air, were analysed as a basis to construct a useful model predicting the grass season start. Poaceae pollen concentrations were monitored in 1991–2012 in Kraków using the volumetric method. Cumulative temperature and effective cumulative temperature significantly influenced the season start in this period. The strongest correlation was seen as the sum of mean daily temperature amplitudes from April 1 to April 14, with mean daily temperature >15 °C and effective cumulative temperature >3 °C during that period. The proposed model, based on multiple regression, explained 57 % of variation of the Poaceae season starts in 1991–2010. When cumulative mean daily temperature increased by 10 °C, the season start was accelerated by 1 day. The input of the interaction between these two independent variables into the factor regression model caused the increase in goodness of model fitting. In 2011 the season started 5 days earlier in comparison with the predicted value, while in 2012 the season start was observed 2 days later compared to the predicted day. Depending on the value of mean daily temperature from March 18th to the 31st and the sum of mean daily temperature amplitudes from April 1st to the 14th, the grass pollen seasons were divided into five groups referring to the time of season start occurrence, whereby the early and moderate season starts were the most frequent in the studied period and they were especially related to mean daily temperature in the second half of March.     

Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom

Constructing accurate predictive models for grass and birch pollen in the air, the two most important aeroallergens, for areas with variable climate conditions such as the United Kingdom, require better understanding of the relationships between pollen count in the air and meteorological variables. Variations in daily birch and grass pollen counts and their relationship with daily meteorological variables were investigated for nine pollen monitoring sites for the period 2000–2010 in the United Kingdom. An active pollen count sampling method was employed at each of the monitoring stations to sample pollen from the atmosphere. The mechanism of this method is based on the volumetric spore traps of Hirst design (Hirst in Ann Appl Biol 39(2):257–265, 1952). The pollen season (start date, finish date) for grass and birch were determined using a first derivative method. Meteorological variables such as daily rainfall; maximum, minimum and average temperatures; cumulative sum of Sunshine duration; wind speed; and relative humidity were related to the grass and birch pollen counts for the pre-peak, post peak and the entire pollen season. The meteorological variables were correlated with the pollen count data for the following temporal supports: same-day, 1-day prior, 1-day mean prior, 3-day mean prior, 7-day mean prior. The direction of influence (positive/negative) of meteorological variables on pollen count varied for birch and grass, and also varied when the pollen season was treated as a whole season, or was segmented into the pre-peak and post-peak seasons. Maximum temperature, sunshine duration and rainfall were the most important variables influencing the count of grass pollen in the atmosphere. Both maximum temperature (pre-peak) and sunshine produced a strong positive correlation, and rain produced a strong negative correlation with grass pollen count in the air. Similarly, average temperature, wind speed and rainfall were the most important variables influencing the count of birch pollen in the air. Both wind speed and rain produced a negative correlation with birch pollen count in the air and average temperature produced a positive correlation.     

An aeropalynological study of metropolitan Toronto

This study uses 6 years of atmospheric pollen data to examine temporal variability of airborne pollen concentrations at various scales. Airborne pollen was collected from 1985 to 1990 with a Burkard trap, located 18 m above ground at Scarborough College, Toronto, Canada. Pollen season parameters are defined and summarized for all taxa in preparation for developing forecasting models. Annual totals of pollen concentration show great interannual variability. The highest coefficient of variation occurs inTsuga, Fraxinus, Betula andFagus, while the lowest inQuercus andAmbrosia. Some taxa show periodic cycles consistent with mast reproductive behaviour. In many studies, the start of the pollen season is defined as an arbitrary percentage of the annual sum. As a result, the start of the season cannot be identified until the season has passed. As well, due to large fluctuations in annual sum, start dates are more variable. This is not practical for the purposes of forecasting. In this study, the start of the pollen season is defined by a critical concentration threshold which signals the onset of the main pollen season in all years. These critical levels ranged from 2 to 60 grains/m³ for the abundant taxa. Interannual variation in the start of the season is approximately 20 days for tree taxa, 5 days for Poaceae, and 2 days forAmbrosia. For many plants, dehiscence is triggered at a critical level of accumulated degree-days. Since annual rates of temperature increase show great variation, there is also interannual variability in the onset of pollen release. Multi-year average pollen curves incorporate these differences in onset and may give an inaccurate representation of the pollen season in a typical year. This paper presents a method of aligning yearly pollen curves to reduce seasonal variation and more accurately represent both the average timing and magnitude of the pollen season. For some types, such asBetula and Poaceae, the resulting curves are positively skewed. Tree taxa, in general, exhibit a more symmetric pollen concentration curve. Aligned average pollen concentration curves are presented for Toronto in the form of a pollen calendar. In addition, phenological data for all common taxa are summarized.     

Thirty-four years of pollen monitoring: an evaluation of the temporal variation of pollen seasons in Belgium

For the first time in Belgium, fluctuations in airborne pollen quantities over a 34 years period have been analyzed. Seven pollen types have been selected comprising the most clinically relevant in Belgium nowadays (birch, alder, hazel and grasses) and others that are known to be allergenic in other European countries and frequently found in Belgium (plane, ash and mugwort). Pollen monitoring was performed with a seven-day recording volumetric spore trap placed in Brussels. We measured increasing airborne pollen for four trees, namely alder, hazel, ash and plane. Although the total pollen index for birch has not increased significantly, an increasing trend in the annual amount of days above the concentration threshold of 80 pollen grains/m³ was clearly observed. Concerning temporal variations, the pollen season has tended to end earlier for birch, ash and plane and the peak concentration of the pollen of plane has been appearing earlier in the year. In the investigated period, the pollen seasons of grasses and mugwort have tended to become less severe. Furthermore, we reported a temporal shift of the grass pollen season, beginning and ending earlier, together with an advance of the annual peak date.