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.     

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.     

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.     

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.     

A 30-day-ahead forecast model for grass pollen in north London, United Kingdom

A 30-day-ahead forecast method has been developed for grass pollen in north London. The total period of the grass pollen season is covered by eight multiple regression models, each covering a 10-day period running consecutively from 21 May to 8 August. This means that three models were used for each 30-day forecast. The forecast models were produced using grass pollen and environmental data from 1961 to 1999 and tested on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times the forecast model was able to successfully predict the severity (relative to the 1961–1999 dataset as a whole) of grass pollen counts in each of the eight forecast periods on a scale of 1 to 4; the number of times the forecast model was able to predict whether grass pollen counts were higher or lower than the mean. The models achieved 62.5% accuracy in both assessment years when predicting the relative severity of grass pollen counts on a scale of 1 to 4, which equates to six of the eight 10-day periods being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and 2002, respectively, when predicting whether grass pollen counts would be higher or lower than the mean. Attempting to predict pollen counts during distinct 10-day periods throughout the grass pollen season is a novel approach. The models also employed original methodology in the use of winter averages of the North Atlantic Oscillation to forecast 10-day means of allergenic pollen counts.     

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.     

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.     

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.     

A predictive study of cupressaceae pollen season onset, severity, maximum value and maximum value date

In this paper Cupressaceae pollen season onset, severity, maximum value and maximum value date, have been studied for 15 consecutive years (1982–1996). The data set was obtained using a Hirst spore-trap (Burkard Manufacturing). In order to determine the influence of the previous months’ meteorological variables on Cupressaceae season’s parameters, the sums of maximum, average and minimum temperatures, and total rainfall for the months of October, November and December were used as independent variables in predictive formulae built by multiple regression analyses. The variance explained percentage by regression analyses varied between 60 and 87%. Total rainfall in the months prior to anthesis and temperature (particularly minimum temperature) are important factors to consider in forecasting models of Cupressaceae pollen season parameters, but meteorological conditions at the time of pollen production are also important and can modify the pre-established potential of pollination.     

Interannual variability of pollen productivity and transport in mid-North America from 1997 to 2009

Understanding the causes of interannual variability in atmospheric pollen concentration is an important but elusive goal for public health and environmental change. We analyzed long-term daily records of pollen counts from urban Kansas City, Missouri, USA collected from 1997 to 2009 for three pollen groups: Ambrosia, Poaceae, and a third group which is mostly composed of arboreal pollen types. The annual pollen index varied from 8,368 to 80,822 over the thirteen-year period. Although Ambrosia pollen is often thought to be associated with droughts and disturbance, years with high Ambrosia pollen were associated with high summer precipitation to the south of Kansas City. Years with high Poaceae pollen were associated with high spring precipitation to the south of the city. In support of the southern influence to Kansas City pollen, Ambrosia and Poaceae pollen mostly arrived on southern winds. In contrast to the other two pollen groups, the arboreal pollen was most associated with growing season precipitation to the east of Kansas City, although it was still highest on days with southern winds. Based on the correlations with climate, the severity of an upcoming allergy season may be predicted with early-season precipitation data, while short-term severity can be forecast from local weather patterns.     

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.     

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.     

First aerobiological study in Mediterranean part of Croatia (Dalmatia): pollen spectrum and seasonal dynamics in the air of Split

The aim of this study was to investigate aerobiological dynamics of pollen in the Mediterranean part of Croatia in the air of the city of Split. Pollen monitoring during the period from 2005 to 2013 was performed using a Hirst volumetric trap. Among the identified pollen of 50 taxa, 21 were allergenic. The average annual pollen index was 33,513. Three pollination seasons were established: early winter season dominated by tree pollen, spring–summer season dominated by herbaceous plants and summer–autumn season with lower amounts of Parietaria and Cupressaceae pollen. According to the abundance, the main taxa were: Cupressaceae, Parietaria/Urtica, Pinus, Quercus, Olea, Carpinus/Ostrya, Poaceae, Platanus and Ambrosia. The annual pollen index together with the daily maximum concentrations showed an upward trend for selected taxa during the study period. The highest monthly pollen index and the highest biodiversity were recorded in April and the lowest during the late autumn and winter months. The pollen calendar created for the city of Split confirmed Mediterranean features of the pollen spectrum. The longest pollen seasons were recorded for Cupressaceae, Parietaria/Urtica and Poaceae pollen types. The correlations between pollen concentrations and meteorological parameters were analyzed. The correlations between pollen concentrations and temperature were positive, while the humidity and the precipitation mostly showed negative influence.     

Analysis of airborne allergenic pollen spectrum for 2009 in Timişoara, Romania

The objective of this investigation was to identify the overall pollen types and, more particularly, the allergenic pollen content in the investigated area and then to explore their seasonal variations. The measurement point was located in the Timi?oara city, Romania. A Lanzoni volumetric trap was used for sample collection. Duration of the pollen season of allergenic plants and respective variation in airborne pollen concentration are presented in the pollen calendar for the year 2009. Among the identified pollen of 23 types, 20 were allergenic: Taxaceae/Cupressaceae, Alnus sp., Fraxinus sp., Betula sp., Corylus sp., Carpinus sp., Salix sp., Populus sp., Ulmus sp., Juglans sp., Quercus sp., Pinaceae, Tilia, Poaceae, Urticaceae, Chenopodiaceae/Amaranthaceae, Rumex sp., Plantago sp., Artemisia sp., Ambrosia sp. These species prevail throughout almost the entire pollen season, from February–October, accounting for 87.03 % of the total pollen count. The greatest diversity of pollen types is detected in the months of spring. The summer months were characterized mostly by non-arboreal pollen types. In late summer and early autumn, Ambrosia airpollen was the most abundant in the atmosphere. The relationships between pollen concentrations and nine meteorological parameters are presented too. To analyze the correlation between pollen data and variables, the Spearman rank correlation coefficient was used. The correlation analysis of daily pollen counts and meteorological parameters showed that arboreal pollen and non-arboreal pollen counts were significantly correlated with temperature. The prevalence of pollen sensitization resulted to be very high in our patients with respiratory symptoms.     

Risk of pollen allergy in Nerja (southern Spain): a pollen calendar

An aeropalynological study was carried out in the atmosphere of the city of Nerja (southern Spain) during a period of 4 years (2000–2003), using a Hirst type volumetric pollen trap. An annual pollen index of 59,750 grains, on average, was obtained with 80–85% of the total pollen recorded from February to May, with Pinus, Olea, Urticaceae, Cupressaceae, Quercus and Poaceae being the principal pollen producers in abundance order. A total of 29 pollen types that reached a 10-day mean equal to or greater than 1 grain of pollen per m³ of air is reflected in a pollen calendar. The results were compared with those obtained for nearby localities and a correlation analysis was made between the daily fluctuations of the main pollen types and total pollen, and meteorological parameters (temperature, rainfall and hours of sun). The daily, monthly and annual values reached by the most important pollen types from an allergenic point of view (Olea, Urticaceae and Poaceae) confirms Nerja as a high-risk locality for the residents and the numerous tourists who visit the area.     

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.     

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.     

北京主要气传致敏花粉年浓度峰值日期预测

花粉是我国北方引发过敏性鼻炎最主要过敏原,花粉症发病期与花粉浓度高峰期吻合。基于北京地区2012至2020年花粉季多站、逐日分类花粉浓度观测数据分析,得出北京地区花粉浓度在3月上旬至5月中旬(可进一步划分为3月中旬至4月上旬和4月下旬至5月上旬两个高峰期)和8月中旬至9月中旬分别存在两个高峰期,第一个高峰期内优势致敏花粉种类为柏科、杨柳科和松科,第二个高峰期内优势致敏花粉种类为桑科、菊科蒿属和藜科。根据优势致敏花粉年浓度峰值日期观测数据,使用与花粉采样站点位置相匹配的逐日气象观测数据累积值,基于作物模型概念和模糊逻辑原理建立了北京地区主要气传致敏花粉年浓度峰值日期预测模型。经检验,柏科、杨柳科、松科、桑科、菊科蒿属和藜科花粉模型预测准确率分别为87.8%、80.0%、64.4%、86.7%、78.8%和81.8%。基于北京地区主要气传致敏花粉年浓度峰值日期预测模型可为本地花粉症防治提供理论参考。     

Effect of the meteorological parameters on the <Emphasis Type="Italic">Olea europaea</Emphasis> L. pollen season in Bahía Blanca (Argentina)

Olea europaea is one of the most prevalent aeroallergens causing allergenic reactions in the city of Bahía Blanca, Argentina. The aim of this study was to evaluate the influence of meteorological factors on the pollen season of Olea europaea L. The aerobiological analysis was performed over an 11-year period in the city. Sampling was carried out with a Rotorod model 40 volumetric impact sampler. The pollen season started in the middle of October and showed the highest values between 16 October and 24 November. A marked difference was noted over the years of this study, especially in 2005 and 2008, due to a significant decrease in the precipitation during the months prior flowering and high temperatures during the pollen season. A decreasing trend of pollen index during the study period coincided with a reduction in the precipitation from June to October (winter and spring). As expected, the air temperature prior to the onset of flowering is of great importance in determining the start of the pollen season.