Effect of meteorological parameters on Poaceae pollen in the atmosphere of Tetouan (NW Morocco)

Poaceae pollen is one of the most prevalent aeroallergens causing allergenic reactions. The aim of this study was to characterise the grass pollen season in Tetouan during the years 2008–2010, to analyse the effect of some meteorological parameters on the incidence of the airborne Poaceae pollen, and to establish forecasting variables for daily pollen concentrations. Aerobiological sampling was undertaken over three seasons using the volumetric method. The pollen season started in April and showed the highest pollen index in May and June, when the maximum temperature ranged from 23 to 27 °C, respectively. The annual pollen score recorded varied from year to year between 2,588 and 5,404. The main pollen season lasted 114–173 days, with peak days occurring mainly in May; the highest concentration reached 308 pollen grains/m³. Air temperature was the most important meteorological parameter and correlated positively to daily pollen concentration increase. An increase in relative humidity and precipitation was usually related to a decrease in airborne pollen content. External validation of the models performed using data from 2011 showed that Poaceae pollen concentration can be highly predicted (64.2–78.6 %) from the maximum temperature, its mean concentration for the same day in other years, and its concentration recorded on the previous day. Sensitive patients suffering allergy to Poaceae pollen are at moderate to highest risk of manifesting allergic symptoms to grass pollen over 33–42 days. The results obtained provide new information on the quantitative contribution of the Poaceae pollen to the airborne pollen of Tetouan and on its temporal distribution. Airborne pollen can be surveyed and forecast in order to warn the atopic population.     

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.     

Threat of allergenic airborne grass pollen in Szczecin,NW Poland: the dynamics of pollen seasons,effect of meteorological variables and air pollution

The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004–2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM₁₀ and SO₂ was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy.     

Bioclimatic indices as a tool in pollen forecasting

The use of bioclimatic indices could be a major step forward in the methodology of pollen forecasting. The basis for this proposal is that simple meteorological parameters do not reflect the global status of the atmosphere, but merely some static measurements. However, pollen dispersal is, above all, a dynamic phenomenon, and this fact should be reflected in the variables we used to explain it. Here, we test the two methodologies for routine pollen forecasting by comparing correlation coefficients using the same daily Poaceae airborne pollen data base from León (6 years, from 1994 to 1999) as the dependent variable and either simple daily meteorological variables or compound daily bioclimatic indices as independent variables. Both simple and compound indices reproduced the same profile of evolution of plant eco-physiological requirements, as the length of the study period during the pollen season increased. However, for time frames larger than the main pollen period, bioclimatic indices gave superior coefficients, which seems to indicate that these could be more valuable for pre-season pollen forecasting. The continentality index produced the highest mean coefficient, higher than those generated by any meteorological variable. Furthermore, at least for a Mediterranean climate, site location and evapotranspiration in relation to precipitation seem to be the most promising factors for increasing success when forecasting Poaceae airborne pollen concentration.     

Seasonal distribution of airborne pollen in Manila,Philippines, and the effect of meteorological factors to its daily concentrations

Pollen-related allergic diseases are a growing health problem. Thus, information on prevalence of airborne pollen may serve as guide for clinicians to accurately manage allergic diseases. In this study, an aeropalynological survey was conducted from November 2013 to October 2014 in Manila, Philippines, to determine the seasonal distribution of the most prevalent airborne pollen and correlate the influence of meteorological factors on their daily concentrations. A volumetric pollen trap was placed on a rooftop, 21 m above ground level. A total of 5677 pollen grains from 18 pollen types were identified, of which Urticaceae, Cannabaceae, Poaceae and Moraceae were the most prevalent. Other pollen types observed that represented 1 % of the total pollen concentration, in descending order, were Terminalia catappa, Myrtaceae, Muntingia calabura, Verbenaceae, Amaranthaceae, Cyperaceae, Caricaceae and Mimosa sp. Of the total airborne pollen, 87 % were obtained during the dry season (November–May). Pollen concentrations peaked (55 %) during the summer months (March–May), indicating a positive correlation (p < 0.01) between pollen concentration and temperature (maximum and mean). Alternatively, only 13 % of the pollen concentrations were obtained during the wet season (June–October). It was observed that pollen concentrations were negatively correlated (p < 0.01) with rainfall and humidity. As the pollen collection was done for one sampling year, only an approximation of the daily concentration of the pollen types was identified and correlated with meteorological factors. Further data collection is required to generate an accurate pollen calendar for use in allergy studies.     

Aerobiology of Urticaceae pollen in Trieste (NE Italy)

The aerobiological behaviour of Urticaceae in Trieste and the correlations with the meteorological parameters were examined. Airborne pollen was collected from 1990 to 1999 using a Hirst type spore trap (Burkard) and the data interpretation was performed according to the standard method adopted by the Italian Aeroallergen Network. The main pollen season of Urticaceae in Trieste goes from mid-April to mid-September. The highest values occur in May and June. Although different seasonal patterns are found every year, the main peak occurs on average at the beginning of May, followed by other decreasing peaks until September. Thecumulative counts vary greatly over the years, with a mean value of 18.315 p/m³. The maximum annual total pollen grains was registered in 1996 and the minimum in 1991. Spearman's correlation was used to establish the relationship between the daily pollen counts and the daily meteorological data both considering their original quantitative values and transformed values according to their day by day changes. Daily pollen concentrations present usually positive correlation with temperature, negative with rainfall and wind speed and no correlation with humidity. Better results were obtained with transformed values.     

The diurnal variation of Poaceae pollen concentrations in a rural area

Records of Poaceae pollen concentration from three years of sampling in a rural area of West Wales have revealed distinctive circadian patterns of variation. Maximum pollen concentrations are typically recorded between 14.00 and 16.00 hours, on days both above and below an average daily Poaceae pollen count of 50 grains m^-3, although later peaks in concentration may be recorded during periods with no precipitation. Variations in the periodicity of Poaceae pollen are analysed in relation to meteorological conditions, phenological patterns of pollen release, pollen source area, and the magnitude of the average daily pollen count. The time of peak pollen concentration in West Wales is generally earlier than in other studies and this is explained by this study being conducted closer to Poaceae pollen source areas than most urban-based studies.     

Multivariate statistical forecasting modeling to predict Poaceae pollen critical concentrations by meteoclimatic data

Forecasting pollen concentrations in the short term is a topic of major importance in aerobiology. Forecasting models proposed in the literature are numerous and increasingly complex, but they fail in at least 25 % of cases and are not available for all botanical species. This work makes it possible to build a forecast model from meteorological data for estimating pollen concentration over a certain threshold of Poaceae, an allergenic family. In Italy, about 25 % of the population suffer from allergies, these in 80 % of cases being caused by airborne allergens, including taxa of agricultural interest such as Poaceae. The pollen dispersion in air is determined by both the phenological stage of plants and the meteorological conditions; the pollen presence varies according to the year, month and even the time of the day. There is a correlation between environmental factors, pollen concentrations and pollinosis. A partial least squares discriminant analysis approach was used in order to predict the presence of Poaceae pollen in the atmosphere with a time lag of 3, 5, 7 days, on the basis of a data set of 14 meteorological and pollen variables over a period of 14 years (1997–2010). The results show a high accuracy in predicting pollen critical concentrations, with values ranging from 85.4 to 88.0 %. This study is hopefully a positive first step in the use of a statistical approach that in the next future could have clinical applications.     

The use of discriminant analysis and neural networks to forecast the severity of the Poaceae pollen season in a region with a typical Mediterranean climate

Biological particles in the air such as pollen grains can cause environmental problems in the allergic population. Medical studies report that a prior knowledge of pollen season severity can be useful in the management of pollen-related diseases. The aim of this work was to forecast the severity of the Poaceae pollen season by using weather parameters prior to the pollen season. To carry out the study a historical database of 21 years of pollen and meteorological data was used. First, the years were grouped into classes by using cluster analysis. As a result of the grouping, the 21 years were divided into 3 classes according to their potential allergenic load. Pre-season meteorological variables were used, as well as a series of characteristics related to the pollen season. When considering pre-season meteorological variables, winter variables were separated from early spring variables due to the nature of the Mediterranean climate. Second, a neural network model as well as a discriminant linear analysis were built to forecast Poaceae pollen season severity, according to the three classes previously defined. The neural network yielded better results than linear models. In conclusion, neural network models could have a high applicability in the area of prevention, as the allergenic potential of a year can be determined with a high degree of reliability, based on a series of meteorological values accumulated prior to the pollen season.     

A 2-year aeropalynological survey of allergenic pollen in the atmosphere of Kastamonu, Turkey

Knowledge of airborne pollen concentrations and the weather conditions influencing them is important for air quality forecasters, allergists and allergy sufferers. For this reason, a 7-day recording volumetric spore trap of the Hirst design was used for pollen monitoring between January 2006 and December 2007 in Kastamonu, Turkey. A total of 293,427 pollen grains belonging to 51 taxa were recorded during the study period. In the 2?years of study, the period March–August was identified as the main pollination season for Kastamonu. The highest monthly pollen counts were observed in May in both years. Six taxa made up 86.5% of the total amount of pollen recorded in the atmosphere of Kastamonu. These were as follows: Pinaceae (42.9%), Cupressaceae (20.6%), Poaceae (9.7%), Quercus (5.5%) Betula (5.3%) and Carpinus (2.6%). Four of these are considered to be highly allergenic (Betula, Carpinus, Cupressaceae and Poaceae). There were also a greater percentage of highly allergenic taxa found within the city, including Betula pendula that is not part of the local flora. This shows that through urban planting, the public and municipalities can unconsciously create a high risk for allergy sufferers. Daily average pollen counts from the six most frequently recorded pollen types were entered into Spearman’s correlation analysis with meteorological data. Mean daily temperature, relative humidity, daily rainfall and wind speed were found to significantly (p?<?0.05) affect atmospheric pollen concentrations, but the relationships between pollen concentrations and meteorological variables can vary and so there is a need for more local studies of this nature.     

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.     

Poaceae pollen in Galicia (N.W. Spain): characterisation and recent trends in atmospheric pollen season

Airborne Poaceae pollen counts are greatly influenced by weather-related parameters, but may also be governed by other factors. Poaceae pollen is responsible for most allergic reactions in the pollen-sensitive population of Galicia (Spain), and it is therefore essential to determine the risk posed by airborne pollen counts. The global climate change recorded over recent years may prompt changes in the atmospheric pollen season (APS). This survey used airborne Poaceae pollen data recorded for four Galician cities since 1993, in order to characterise the APS and note any trends in its onset, length and severity. Pollen sampling was performed using Hirst-type volumetric traps; data were subjected to Spearman’s correlation test and regression models, in order to detect possible correlations between different parameters and trends. The APS was calculated using ten different methods, in order to assess the influence of each on survey results. Finally, trends detected for the major weather-related parameters influencing pollen counts over the study period were compared with those recorded over the last 30 years. All four cities displayed a trend towards lower annual total Poaceae pollen counts, lower peak values and a smaller number of days on which counts exceeded 30, 50 and 100 pollen grains/m³. Moreover, the survey noted a trend towards delayed onset and shorter duration of the APS, although differences were observed depending on the criteria used to define the first and the last day of the APS.     

Comparative study of seasonal and intradiurnal variation of airborne herbaceous pollen in urban and rural areas

The content of herbaceous pollen in the atmosphere depends on the vegetal cover, climate and the weather and geographical conditions. The aim of the study reported here was to compare aerobiological data obtained from pollen monitoring stations located at sites differing with respect to their flora and microclimate – i.e. a town and a rural area. A volumetric method was used for sampling. In each microscopic preparation 12 vertical strips corresponding with 2-h intervals were analysed. A 90% method was used to determine the pollen season. The results were statistically verified using the u test and the Kolmogorov-Smirnov, Spearman and Wilcoxon tests. Higher values of the Seasonal Pollen Index (SPI), higher daily average concentrations and higher peak values were recorded in the rural area. An analysis of intradiurnal variations of airborne pollen showed that apart from the Poaceae the number of pollen grains in the air began to increase earlier in the day in the rural area; in the case of Rumex and Ambrosia, the maximum values also appeared a few hours earlier. For all the taxa investigated, the analysis of correlation showed a significant association between the daily average concentrations at both sites. The weakest association occurred for Plantago lanceolata; for all other taxa, the determination coefficients (R ²) were high. The results of the Wilcoxon test showed that, despite the strong positive association between daily concentrations of the pollen types investigated, there were differences in mean pollen concentrations in the overlapping pollen season. Mean concentrations of Poaceae and Rumex airborne pollen were significantly higher in the rural area in both years, and those of Urtica and P. lanceolata were significantly higher only in 2002.     

A 10-year survey of allergenic airborne pollen in the city of Porto (Portugal)

Airborne pollen calendars are useful to estimate the flowering season of the different plants as well as to indicate the allergenic potential present in the atmosphere at a given time. In this study, it is presented a 10-year survey of the atmospheric concentration of allergenic pollen types. Airborne pollen was performed, from 2003 to 2012, using a 7-day Hirst-type volumetric trap. The interannual variation of the daily mean concentration of the number of pollen grains and the main pollen season was determined as well as the hourly variations and correlation with meteorological parameters. During the study period, 18 different allergenic pollen types were considered based on its representativeness on the total annual airborne pollen concentration. The lowest annual concentrations were sampled in 2006 and the highest in 2007. The highest airborne pollen concentration was found during early spring and early summer. On the contrary, December was the month with the lowest pollen concentration. The major pollen sampled belongs to trees followed by weeds and grasses, being the most representative pollen types in the atmosphere: Urticaceae, Platanus, Poaceae, Pinaceae, Cupressaceae, Acer, Quercus, Castanea, Plantago, Alnus, Olea europaea, Betula, Myrtaceae and Populus. Intradiurnal distribution patterns of the pollen types studied presented differences with some taxa being predominantly sampled in the morning (9–11 a.m.) while others in first night hours (between 9 and 12 p.m.). Significantly correlations were found between the airborne pollen concentration and meteorological parameters.     

Two statistical approaches to forecasting the start and duration of the pollen season of Ambrosia in the area of Lyon (France)

The aim of the present study was to forecast the start and duration of the pollen season of Ambrosia from meteorological data, in order to provide early information to allergists and allergic people. We used the airborne pollen data from Lyon (France), sampled using a Hirst trap from 1987 to 1999, and the meteorological data for the same period: air temperature (minimal, maximal, and average), rainfall, relative humidity, sunshine duration and soil temperature. Two forecasting models were used, one summing the temperatures and the other making use of a multiple regression on 10-day or monthly meteorological parameters. The start of the pollen season was predicted with both methods, results being more accurate with the regression (the errors between the predicted and the observed SDP ranging from 0 to 3 days). The duration of the pollen season was predicted by a regression model, errors ranging from 0 to 7 days. The models were later tested with satisfactory results from 2 additional years (2000 and 2001). Such forecasting models are helpful for allergic people, who have to begin their anti-allergic treatment before the start of the pollen season and not when the symptoms have appeared, since a preventive treatment is more efficient than a curative one. The regression allows predictions to be made 3-5 weeks in advance and so it is of particular interest. The forecasts will be broadcast on the Internet.     

Modelling the pollen season start in <Emphasis Type="Italic">Corylus avellana</Emphasis> and <Emphasis Type="Italic">Alnus glutinosa</Emphasis>

Hazel (Corylus avellana L.) and black alder (Alnus glutinosa (L.) Gaertn.) are important sources of airborne pollen and represent an allergen threat during the flowering period. Researches on airborne pollen concentrations in both species are useful in allergology, as well as for fruit production for hazel. The aims of the present study were: (1) to investigate the relationships between environmental conditions and the airborne pollen concentration of hazel and black alder during the flowering period by correlation and multiple regression analysis and (2) to predict the pollen season start (PSS) by using a sequential model, in order to obtain a helpful tool in allergology and hazel cultivation. In this study, the applied method defines the pollen season as the period in which 90 % of the total season’s catch occurred, using a data set of 18 years (1996–2014). The relationships between daily meteorological parameters (temperature, humidity, rainfall and wind speed) during the 14-day period that precedes the PSS and the PSS of hazel and black alder (day of the year) were investigated. The results showed that mean temperature and the number of rainy days before the PSS are the main factors influencing PSS for both taxa. Moreover, the chilling and heat needed to break dormancy were estimated in order to predict the PSS of both species. Different years and different thresholds of temperature and chill days were used to calibrate and validate the model.     

Predicting tree pollen season start dates using thermal conditions

Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data of Alnus, Corylus and Betula were obtained in 1991–2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (for Alnus and Corylus) and mean (for Betula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991–2010.     

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.     

Poaceae pollen concentrations in the atmosphere of three inland Croatian sites (2003-2004)

The aim of the study was to determine the length of Poaceae pollen season, intradiurnal, daily and monthly pollen variation, and the effect of some meteorological parameters on atmospheric pollen concentration, at three monitoring sites in inland Croatia during the 2003-2004 period. Seven-day Hirst volumetric pollen and spore traps were used for pollen sampling. At all three monitoring sites considerably higher precipitation and lower average temperature in 2004 led to a marked decrease in the grass pollen concentration in the air at all three monitoring sites. The highest grass pollen concentrations were recorded in Ivani? Grad (typical rural area), considerably lower in Samobor (effect of forest vegetation), and lowest in Zagreb (urban area). The highest atmospheric Poaceae pollen concentrations in inland Croatia were generally recorded in May and June. The highest intradiurnal concentrations were recorded between 8.00 and 12.00 a.m. Results of this aeropalynologic study are expected to help in preventing the symptoms of allergic reaction in individuals with Poaceae pollen hypersensitivity.     

The influence of ambient temperature on the abundance of Poaceae pollen

The sampling of pollen concentrations over six seasons in north London has revealed the importance of temperature in influencing the start, severity, daily and diurnal variation of Poaceae pollen seasons. Using accumulated degree days above 6°C and rainfall amount as predictors, models have been developed which account for 96% of the variation in the starting date and 91% of the variation in the severity of the Poaceae pollen season. Maximum daily temperature is an important influence on the daily pollen count although this relationship is not linear and maximum daily temperatures within the range 21.1–25°C are associated with the highest daily pollen concentrations. Likewise, when the two-hourly variation of pollen concentration is examined, temperatures within 2–4.9°C above the normal diurnal range, rather than in excess of 5.0°C, are found to be associated with the highest two-hourly concentrations. Occasional night-time maxima of pollen concentration have also been recorded and these are examined in relation to the possibility of temperature inversions, although few conclusive results have emerged.