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 atmosphere of Tetouan (NW Morocco): effect of meteorological parameters and forecast of daily pollen concentration

The Poaceae pollen season has been characterized in Tetouan during a 7-year period, and the effect of weather conditions on daily concentrations was examined. The forecast models were produced using a stepwise multiple regression analyses. Firstly, three models were constructed to predict daily Poaceae pollen concentrations during the main pollen season, as well as the pre-peak and post-peak periods with data from 2008 to 2012 and tested on data from 2013 and 2014. Secondly, the regression models using leave-one-out cross-validation were produced with data obtained during 2008–2014 taking into account meteorological parameters and mean pollen concentrations of the same day in other years. The duration of the season ranged from 70 days in 2009 to 158 days in 2012. The highest amount of Poaceae pollen was detected in spring and the first fortnight of July. The annual sum of airborne Poaceae pollen concentrations varied between 2100 and 6251. The peak of anthesis was recorded in May in six of the other years studied. The regression models accounted for 36.3–85.7% of variance in daily Poaceae pollen concentrations. The models fitted best when the mean pollen concentration of the same day in other years was added to meteorological variables, and explained 78.4–85.7% of variance of the daily pollen changes. When the year 2014 was used for validating the models, the lowest root-mean-square errors values were found between the observed and estimated data (around 13). The reasonable predictor variables were the mean pollen concentration of the same day in other years, mean temperature, precipitations, and maximum relative humidity.     

Quantitative forecasting of olive yield in Northern Portugal using a bioclimatic model

In this work the objective was to develop a bioclimatic model to forecast olive yield based on airborne pollen, soil water content, and favourable conditions for phytopathological attacks. Olive airborne pollen was sampled from 1998 to 2006 using Cour traps installed in the Trás-os-Montes e Alto Douro region, in the provinces of Valença do Douro and Vila Nova de Foz-Côa. Meteorological data from a meteorological station located in Pinhão, near the pollen samplers, was used to calculate other independent variables. According to the bioclimatic model, at the flowering stage 63% of regional olive production can be predicted from the regional pollen index, with an average deviation between observed and predicted production of 10%. The variable soil water content enabled an increase in forecasting accuracy of about 30%, and a reduction in the average deviation between observed and predicted production of 6%. The final regression with all three variables tested showed that the bioclimatic model was able to predict the annual variability of regional olive fruit production with an accuracy of 97%, the average deviation between observed and predicted production being 3% for internal validation and 6% for external validation.     

Differences in atmospheric emissions of Poaceae pollen and Lol p 1 allergen

The allergens of different grass species share similar physicochemical and immunological features that account for the high incidence of allergenic cross-reactivity. We aimed to gain more information on the correlation between Poaceae airborne pollen and allergen concentration and hence make a reliable assessment of true pollen exposure in different bioclimatic areas. The release of Lol p 1 allergen from grass pollen differs between years and areas depending on variables like meteorological factors, biological sources, and cross-reactions with homologous allergens. This study monitored airborne pollen concentrations of grasses and Lol p 1 aeroallergen in León and Ourense, two cities with different climatic conditions located in northwestern Spain. Lol p 1 content in aerosol samples was quantified using specific ELISA antibody plates. Some our results show that Lol p 1 concentration increases when the atmospheric relative humidity is below 70%. This could explain the appearance of protein peaks at times when little or no grass pollen is present, especially after a short and heavy storm.     

The combination of airborne pollen and allergen quantification to reliably assess the real pollinosis risk in different bioclimatic areas

Exposure to allergens represents a key factor among the environmental determinants of asthma. The most common information available for pollinosis patients is the concentration of pollen grains in the bioaerosol and their temporal distribution. However, in recent years, discordance between pollen concentrations and allergic symptoms has been detected. The purpose of this research is to evaluate the relationship between pollen counts and the atmospheric aeroallergen concentrations in different Spanish bioclimatic areas. For the monitoring of allergen content in the air, a quantitative antigen–antibody technique combined with the Cyclone sampling methodology was used. The study was conducted during 2007 by considering some of the most common allergens that induce pollinosis in each area: Platanus and Urticaceae in Ourense and Cartagena, and Poaceae in Ourense and León. In Ourense, pollen counts and aeroallergen concentrations coincided for the three pollen types studied, and the pollen and allergen data associated with the meteorological factors were highly significant for the pollen counts. In Cartagena (for Platanus and Urticaceae) and León (for Poaceae), the low correlations between pollen counts and allergen concentrations obtained could be due to the specific bioclimatic conditions. In contrast, the higher allergen concentrations found in the atmosphere in Cartagena and León compared to Ourense could be related to the existing pollutant levels there, inducing a higher expression of plant pathogenesis-related proteins in the plants of polluted cities. The combination of pollen counts and allergen quantification must be assessed to reliably estimate exposure of allergic people to allergens in different bioclimatic areas.     

Hay Fever in a Changing Climate: Linking an Internet-Based Diary with Environmental Data

Investigating the impact of climate change on human health requires the development of efficient tools that link patient symptoms with changing environmental variables. We developed an internet-based hay fever diary linked to simultaneously recorded pollen load and weather variables in Canberra, Australia over spring 2010. We recruited 42 hay fever sufferers to complete a simple online pollen diary daily over a period of 60 days. In conjunction, daily airborne pollen load was counted and meteorological data collected simultaneously. We focused on the relationships between temperature, rainfall, pollen count and rhinoconjunctivitis symptoms. Pollen load increased after a peak rainfall event until the end of the study. Compliance was high, averaging 79% of days per person. Nasal rhinoconjunctivitis symptoms increased in concert with increasing pollen load, and then remained high. Mucosal itching increased more gradually and strongly coincided with increased daily maximum temperature. Our study successfully demonstrated the feasibility of linking pollen load and climate variables to symptoms of rhinoconjunctivitis in the Australian community. However, a larger study would better explore the nature of associations between these variables. Similar online methods could be used to monitor a range of health responses to our changing environment.     

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.     

Biometeorological characterization of the winter in north‐west Spain based on Alnus pollen flowering

The timing of pollen appearance in the atmosphere provides a general idea of the flowering onset of plants over a wide area. Woody plants in temperate regions have evolved mechanisms to preserve cells from the risk of frost during adverse weather conditions in the period prior to flowering regulated mainly by temperature. A number of indices have been developed to quantify the rest and heat requirements of temperature, which will enable the plant to adapt to environmental conditions. However, flowering is a dynamic and complex phenomenon and it is difficult to separate individual effects of different meteorological parameters. The use of modified bioclimatic indices could be a major step forward. In this study the Alnus glutinosa flowering in four different areas in north‐western Spain in the period 1995–2003 is examined, and trends identified by means of information gathered by Hirst pollen traps. Temperature plays an important role in the maturation of reproductive organs and pollen production. Comparison with bioclimatic indices showed that temperature during the 25–55 days preceding pollen release was the main controlling factor, and that relationship between flowering time and bioclimatic indicator values differs according to local conditions. In colder areas, rest and heat temperature requirements are greater because the trees need protection over a longer period; in the Mediterranean region of north‐western Spain, the rest temperature requirement and the threshold temperature are both higher than in Eurosiberian areas. Ombrothermic, Continentality and Thermicity indices are thus useful tools for characterizing the various bioclimatic areas of north‐western Spain.     

Five ways to define a pollen season: exploring congruence and disparity in its attributes and their long-term trends

We applied five sets of criteria for pollen season (PS) definition, which are associated with the ‘clinical’, ‘grains’, ‘logistic’, ‘moving average’ and ‘percentage’ methods, on a 30-year time series of daily airborne pollen concentration values of Cupressaceae (cypress family), Oleaceae (olive family) and Poaceae (grass family), from Thessaloniki, Greece. These methods could identify a pollen season for more than 90% of the study period for all three taxa, except for the clinical that identified less than 40% for Oleaceae. The estimated values of the PS start, end, and duration varied largely, in a method-specific way. Even significant reverse patterns of change were recorded for the same attribute and taxon, as for the Poaceae PS end date that shows a significant advance earlier in the year with the moving average method and delay with the percentage. As the season peak date is method-independent and, hence, directly comparable, we recommend this attribute to be examined in airborne pollen studies. Results taken with the percentage method could be compared with those of the past for Thessaloniki, with a more than 10-year shorter time series. No climate-related change was detected for Cupressaceae PS attributes, but an earlier peak was now detected for Oleaceae and Poaceae, and a later end and a longer duration for Poaceae, suggesting an increased allergy risk for this taxon. The different criteria concurrently applied for PS definition that led to even greatly diverging results for the same PS attribute is an issue for the science and calls for efforts at standardization.

     

Forecasting the start of <Emphasis Type="Italic">Quercus</Emphasis> pollen season using several methods – the evaluation of their efficiency

Forecasting the time when the atmospheric pollen season of allergenic plants begins is particularly important for doctors and their patients. The aim of this paper is to determine whether it is possible to forecast the start of the oak (Quercus) pollen season in Rzeszów, Poland. In the elaboration of the most effective model, various forecasting techniques were tested: growth degree days (GDD°C); meteorological factors; bioclimatic factors; and indicator taxon. The aerobiological monitoring was carried out in 1997–2005 and 2007 in Rzeszów (SE Poland). In the presented investigation, three methods defining the start of the Quercus pollen season were selected on the basis of accumulated sums of pollen or the constant occurrence of pollen grains in air. Despite the application of different combinations of GDD°C methods and threshold temperatures, the correlation coefficients between the expected and obtained values were low. In some cases, however, they proved highly effective for the test years (2005, 2007) with the accuracy of a few days. For GDD°C methods, the best threshold temperatures range between 5 and 6°C. Models based on bioclimatic indices and meteorological variables were not satisfactory. On the basic of the 10 years of results, the method of indicator species were good for forecast the start of oak pollen season. Birch was the best indicator taxa.     

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.     

Annual pollen spectrum variations in the air of Bratislava (Slovakia): years 2002–2009

Pollen grains in the atmosphere of Bratislava were quantitatively and qualitatively analysed during an 8-year period (2002–2009) using a Burkard volumetric pollen trap. The mean annual total pollen grain count recorded during this period was 36,608, belonging to 34 higher plant taxa (22 trees and/or shrubs and 12 herbaceous species). The maximum annual total pollen grain count (50,563) was recorded in 2003 and the minimum (14,172) in 2009. The taxa contributing the highest concentration of pollen grains were Betula, Urticaceae, Cupressaceae-Taxaceae, Populus, Pinus, Poaceae and Ambrosia. During the study period, there was a remarkable increase in the number of pollen grains from February to April, with the highest daily mean pollen counts recorded in April. Total pollen concentration began to decrease markedly in May, but there was a second increase between July and August, followed by a decrease in September. The timing and length of the pollen seasons varied. Betula and Poaceae showed a rather constant 2-year fluctuating rhythm. The relationships between airborne pollen concentration and meteorological variables were assessed. Based on these results, the first pollen calendar in Slovakia has been constructed for the area of Bratislava, which provides a great deal of useful and important information.     

The effects of large-scale atmospheric fields on the cypress pollen season in Tuscany (Central Italy)

This research was performed for the purpose of analysing the relationships between large-scale meteorological information, in particular the North Atlantic Oscillation (NAO) index and the Sea Surface Temperature (SST), and the timing and magnitude of the Cupressaceae pollen season in the Pistoia district of Central Italy. The results demonstrated that in specific periods of the year, the NAO index, by partially determining the distribution of the main meteorological variables over the study area, is negatively correlated with the start and the end, as well as the peak day of pollen concentration. Pollen data were also correlated with the SST of the North Atlantic Ocean east of the Azores for the September–December period of the previous year, which is significant for exploring possibilities in terms of predicting the timing and magnitude of the cypress pollen season. The analysis of such meteorological variables and indices could be used to improve the existing forecasting systems of the phenology of the cypress pollen season. Moreover, the possibility of using meteorological information freely available on internet could cut costs and reduce spatial and temporal representativeness limitations relating to weather monitoring in loco.     

The influence of temperature,relative humidity and rainfall on the occurrence of pollen allergens (Betula,Poaceae, Ambrosia artemisiifolia) in the atmosphere of Bratislava (Slovakia)

The occurrence of pollen grains in the atmosphere markedly relates to meteorological factors. In the study we have evaluated a correlation between the concentration of pollen grains in the atmosphere of Bratislava and temperature, relative humidity and rainfall during the vegetation period of 1995 and 1997. For our analysis we have selected one representative of each phytoallergen group (trees, grasses, weeds). We have chosen the Betula genus of trees, the whole Poaceae family of grasses and ragweed Ambrosia artemisiifolia L. to represent weeds. The taxons mentioned represent the most significant allergens in Slovakia. The concentration of pollen grains has been monitored by a Lanzoni volumetric pollen trap. The data obtained, the average daily concentration in 1 m(3), have been included in the statistical analysis together with values for the average daily temperature, relative humidity and total rainfall in 24 h. The correlation between the concentration of pollen grains in the atmosphere and selected meteorological variables from daily monitoring has been studied with the help of linear regression and correlation coefficients. We have found the average daily temperature and relative humidity (less than temperature) to be significant factors influencing the occurrence of pollen grains in the atmosphere of Bratislava. The total daily rainfall does not seem to be significant from the statistical point of view.     

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.     

An aerobiological study of Urticaceae pollen in the city of Granada (S. Spain): Correlation with meteorological parameters

An aerobiological study was made of Urticaceae pollen in the city of Granada, relating the mean values of the daily counts to meteorological parameters. Sampling was carried out with a Burkard seven‐day‐recording spore trap from October 1992 to September 1997. This pollen type has an extremely long main pollen season (MPS), with maximum counts in (January) February, March and April, causing numerous cases of human pollinosis throughout the entire Mediterranean region, including Granada. A highly constant intradiurnal variation pattern was obtained showing that the maximum peaks usually occur between 12.00 and 20.00. According to Spearman's correlation coefficient, during the pre‐peak period the parameters which have the greatest effect on the levels of this type of pollen are daily and accumulated temperature and sunshine, accumulated rainfall, and wind direction from the third quadrant; during the post‐peak period these same variables presented significantly negative coefficients. Daily rainfall and relative humidity presented negative coefficients during the entire MPS. The maximum daily temperature was the variable which provided the closest match with the theoretical predictive pattern presented here.     

Influence of meteorological parameters on olea pollen concentrations in Córdoba (South-western Spain)

The influence of meteorological parameters on the dispersion of airborne pollen has been studied by several authors. Olive pollen is the major cause of allergy in southern Spain, where a large part of the arable surface area is given over to olive cultivation. Daily pollen forecasts provide important information both for pollen-allergy sufferers and for agronomists trying to achieve a better biological understanding of variations in airborne olive pollen levels. The main purpose of this paper is to study, by means of short-term statistical analysis, the effect of meteorological parameters on airborne olive pollen concentrations in the city of Cordoba (south-western Spain). Twenty-one-year (1982–2002) aerobiological and meteorological databases were used. Correlation and multiple regression analyses were used to study the relationships between olive pollen levels and several meteorological parameters. Statistical analysis was applied both to the whole pollen season and to the pre-peak period. Daily meteorological parameters, such as accumulated mean temperature, accumulated sunlight hours, and accumulated rainfall were used as independent variables in both statistical analyses. Accumulated meteorological variables were of the greatest value in most regression analysis equations, heat-related variables being the most important.     

Fifteen years' record of airborne allergenic pollen and meteorological parameters in Thessaloniki,Greece

A pollen calendar has been constructed for the area of Thessaloniki and relationships between pollen transport and meteorological parameters have been assessed. Daily airborne pollen records were collected over a 15-year period (1987-2001), using a Burkard continuous volumetric pollen trap, located in the centre of the city. Sixteen allergenic pollen types were identified. Simultaneously, daily records of five main meteorological parameters (mean air temperature, relative humidity, rainfall, sunshine, wind speed) were made, and then correlated with fluctuations of the airborne pollen concentrations. For the first time in Greece, a pollen calendar has been constructed for 16 pollen types, from which it appears that 24.9% of the total pollen recorded belong to Cupressaceae, 20.8% to Quercus spp., 13.6% to Urticaceae, 9.1% to Oleaceae, 8.9% to Pinaceae, 6.3% to Poaceae, 5.4% to Platanaceae, 3.0% to Corylus spp., 2.5% to Chenopodiaceae and 1.4% to Populus spp. The percentages of Betula spp., Asteraceae (Artemisia spp. and Ambrosia spp.), Salix spp., Ulmaceae and Alnus spp. were each lower than 1%. A positive correlation between pollen transport and both mean temperature and sunshine was observed, whereas usually no correlation was found between pollen and relative humidity or rainfall. Finally, wind speed was generally found to have a significant positive correlation with the concentrations of 8 pollen types. For the first time in the area of Thessaloniki, and more generally in Greece, 15-year allergenic pollen records have been collected and meteorological parameters have been recorded. The airborne pollen concentration is strongly influenced by mean air temperature and sunshine duration. The highest concentrations of pollen grains are observed during spring (May).     

How to prepare a pollen calendar for forecasting daily pollen concentrations of <Emphasis Type="Italic">Ambrosia,Betula</Emphasis> and Poaceae?

Forecasting daily airborne pollen concentrations is of great importance for management of seasonal allergies. This paper explores the performance of the pollen calendar as the most basic observation-oriented model for predicting daily concentrations of airborne Ambrosia, Betula and Poaceae pollen. Pollen calendars were calculated as the mean or median value of pollen concentrations on the same date in previous years of the available historic dataset, as well as the mean or median value of pollen concentrations of the smoothed dataset, pre-processed using moving mean and moving median. The performance of the models was evaluated by comparing forecasted to measured pollen concentrations at both daily and 10-day-average resolutions. This research demonstrates that the interpolation of missing data and pre-processing of the calibration dataset yields lower prediction errors. The increase in the number of calibration years corresponds to an improvement in the performance of the calendars in predicting daily pollen concentrations. However, the most significant improvement was obtained using four calibration years. The calendar models correspond well to the shape of the pollen curve. It was also found that daily resolution instead of 10-day averages adds to their value by emphasising variability in pollen exposure, which is important for personal assessment of dose-response for pollen-sensitive individuals.     

A systematic review of the effects of temperature and precipitation on pollen concentrations and season timing,and implications for human health

Climate and weather directly impact plant phenology, affecting airborne pollen. The objective of this systematic review is to examine the impacts of meteorological variables on airborne pollen concentrations and pollen season timing. Using PRISMA methodology, we reviewed literature that assessed whether there was a relationship between local temperature and precipitation and measured airborne pollen. The search strategy included terms related to pollen, trends or measurements, and season timing. For inclusion, studies must have conducted a correlation analysis of at least 5 years of airborne pollen data to local meteorological data and report quantitative results. Data from peer-reviewed articles were extracted on the correlations between seven pollen indicators (main pollen season start date, end date, peak date, and length, annual pollen integral, average daily pollen concentration, and peak pollen concentration), and two meteorological variables (temperature and precipitation). Ninety-three articles were included in the analysis out of 9,679 articles screened. Overall, warmer temperatures correlated with earlier and longer pollen seasons and higher pollen concentrations. Precipitation had varying effects on pollen concentration and pollen season timing indicators. Increased precipitation may have a short-term effect causing low pollen concentrations potentially due to “wash out” effect. Long-term effects of precipitation varied for trees and weeds and had a positive correlation with grass pollen levels. With increases in temperature due to climate change, pollen seasons for some taxa in some regions may start earlier, last longer, and be more intense, which may be associated with adverse health impacts, as pollen exposure has well-known health effects in sensitized individuals.