Airborne pollen concentrations strongly correlate with flowering intensity of wind-pollinated species growing at and around monitoring sites. The pollen spectrum, and the variations in its ...composition and concentrations, is influenced by climatic features and by available nutritional resources but it is also determined by land use and its changes. The first factor influence is well known on aerobiological researches but the impact of land cover changes has been scarcely studied until now.
This paper reports on a study carried out in Southern Spain (Córdoba city) examining airborne pollen trends over a 15-year period and it explores the possible links both to changes in land use and to climate variations. The Seasonal-Trend Decomposition procedure based on Loess (STL) which decomposes long-term data series into smaller seasonal component patterns was applied. Trends were compared with recorded changes in land use at varying distances from the city in order to determine their possible influence on pollen-count variations. The influence of climate-related factors was determined by means of non-parametric correlation analysis.
The STL method proved highly effective for extracting trend components from pollen time series, because their features vary widely and can change quickly in a short term. Results revealed mixed trends depending on the taxa and reflecting fluctuations in land cover and/or climate. A significant rising trend in Olea pollen counts was observed, attributable both to the increasing olive-growing area but also to changes in temperature and rainfall. Poaceae pollen concentrations also increased, due largely to an expansion of heterogeneous agricultural areas and to an increase in pollen season length positively influenced by rainfall and temperature. By contrast, the significant declining trend observed for pollen from ruderal taxa, such as Amaranthaceae, Rumex, Plantago and Urticaceae, may be linked to changes in urban planning strategies with a higher building pressure.
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•Usually airborne pollen changes are attributed only to climate and land cover changes are not taking into account.•Pollen trends extracted by STL were compared with main changes on land use and climate.•Changes in land uses and land cover may explain pollen spectrum variations through the years.•Different increasing or decreasing trends depending on pollen taxa reflecting land cover and/or climate fluctuations
Cumulative data indicate that pollen grains and air pollution reciprocally interact. Climate changes seem also to influence pollen allergenicity. Depending on the plant species and on the pollutant ...type and concentration, this interaction may modify the features and metabolism of the pollen grain. Previous results revealed a significant positive correlation between pollen and aeroallergen, even using two different samplers. However, some discrepancy days have been also detected with low pollen but high aeroallergen concentrations. The main aim of the present paper is to find how the environmental factors, and specially pollutants, could affect the amount of allergens from olive and grass airborne pollen. Pollen grains were collected by a Hirst-type volumetric spore trap. Aeroallergen was simultaneously sampled by a low-volume Cyclone Burkard sampler. Phl p 5 and Ole e 1 aeroallergen were quantified by double-sandwich ELISA test. The data related to air pollutants, pollen grains, and aeroallergens were analyzed with descriptive statistic. Spearman’s correlation test was used to identify potential correlations between these variables. There is a significant positive correlation between aeroallergens and airborne pollen concentrations, in both studied pollen types, so allergen concentrations could be explained with the pollen concentration. The days with unlinked events coincide between olive and grass allergens. Nevertheless, concerning to our results, pollutants do not affect the amount of allergens per pollen. Even if diverse pollutants show an unclear relationship with the allergen concentration, this association seems to be a casual effect of the leading role of some meteorological parameters.
Artemisia pollen is the main vector for airborne endotoxin Oteros, Jose; Bartusel, Elke; Alessandrini, Francesca ...
Journal of allergy and clinical immunology,
January 2019, 2019-Jan, 2019-01-00, 20190101, Letnik:
143, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Endotoxin (LPS) released from gram-negative bacteria causes strong immunologic and inflammatory effects and, when airborne, can contribute to respiratory conditions, such as allergic asthma.
We ...sought to identify the source of airborne endotoxin and the effect of this endotoxin on allergic sensitization.
We determined LPS levels in outdoor air on a daily basis for 4 consecutive years in Munich (Germany) and Davos (Switzerland). Air was sampled as particulate matter (PM) greater than 10 μm (PM > 10) and PM between 2.5 and 10 μm. LPS levels were determined by using the recombinant Factor C assay.
More than 60% of the annual endotoxin exposure was detected in the PM > 10 fraction, showing that bacteria do not aerosolize as independent units or aggregates but adhered to large particles. In Munich 70% of annual exposure was detected between June 12th and August 28th. Multivariate modeling showed that endotoxin levels could be explained by phenological parameters (ie, plant growth). Indeed, days with high airborne endotoxin levels correlated well with the amount of Artemisia pollen in the air. Pollen collected from plants across Europe (100 locations) showed that the highest levels of endotoxin were detected on Artemisia vulgaris (mugwort) pollen, with little on other pollen. Microbiome analysis showed that LPS concentrations on mugwort pollen were related to the presence of Pseudomonas species and Pantoea species communities. In a mouse model of allergic disease, the presence of LPS on mugwort pollen was needed for allergic sensitization.
The majority of airborne endotoxin stems from bacteria dispersed with pollen of only one plant: mugwort. This LPS was essential for inducing inflammation of the lung and allergic sensitization.
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Paper mulberry pollen, declared a pest in several countries including Pakistan, can trigger severe allergies and cause asthma attacks. We aimed to develop an algorithm that could accurately predict ...high pollen days to underpin an alert system that would allow patients to take timely precautionary measures. We developed and validated two prediction models that take historical pollen and weather data as their input to predict the start date and peak date of the pollen season in Islamabad, the capital city of Pakistan. The first model is based on linear regression and the second one is based on phenological modelling. We tested our models on an original and comprehensive dataset from Islamabad. The mean absolute errors (MAEs) for the start day are 2.3 and 3.7 days for the linear and phenological models, respectively, while for the peak day, the MAEs are 3.3 and 4.0 days, respectively. These encouraging results could be used in a website or app to notify patients and healthcare providers to start preparing for the paper mulberry pollen season. Timely action could reduce the burden of symptoms, mitigate the risk of acute attacks and potentially prevent deaths due to acute pollen-induced allergy.
Automatic and Online Pollen Monitoring Oteros, Jose; Pusch, Gudrun; Weichenmeier, Ingrid ...
International archives of allergy and immunology,
01/2015, Letnik:
167, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Pollen are monitored in Europe by a network of about 400 pollen traps, all operated manually. To date, automated pollen monitoring has only been feasible in areas with limited variability in pollen ...species. There is a need for rapid reporting of airborne pollen as well as for alleviating the workload of manual operation. We report our experience with a fully automated, image recognition-based pollen monitoring system, BAA500.
The BAA500 sampled ambient air intermittently with a 3-stage virtual impactor at 60 m3/h in Munich, Germany. Pollen is deposited on a sticky surface that was regularly moved to a microscope equipped with a CCD camera. Images of the pollen were constructed and compared with a library of known samples. A Hirst-type pollen trap was operated simultaneously.
Over 480,000 particles sampled with the BAA500 were both manually and automatically identified, of which about 46,000 were pollen. Of the automatically reported pollen, 93.3% were correctly recognized. However, compared with manual identification, 27.8% of the captured pollen were missing in the automatic report, with most reported as unknown pollen. Salix pollen grains were not identified satisfactorily. The daily pollen concentrations reported by a Hirst-type pollen trap and the BAA500 were highly correlated (r = 0.98).
The BAA500 is a functional automated pollen counter. Its software can be upgraded, and so we expected its performance to improve upon training. Automated pollen counting has great potential for workload reduction and rapid online pollen reporting.
Bioinformatics clustering application for mining of a large set of olive pollen aerobiological data to describe the daily distribution of Olea pollen concentration. The study was performed with ...hourly pollen concentrations measured during 8 years (2011–2018) in Extremadura (Spain). Olea pollen season by quartiles of the pollen integral in preseason (Q1: 0%–25%), in-season (Q2 and Q3: 25%–75%) and postseason (Q4: 75%–100%). Days with pollen concentrations above 100 grains/m3 were clustered according to the daily distribution of the concentrations. The factors affecting the prevalence of the different clusters were analyzed: distance to olive groves and the moment during the pollen season and the meteorology. During the season, the highest hourly concentrations during the day where between 12:00 and 14:00, while during the preseason the highest hourly concentrations were detected in the afternoon and evening hours. In the postseason the pollen concentrations were more homogeneously distributed during 9-16 h. The representation shows a well-defined hourly pattern during the season, but a more heterogeneous distribution during the preseason and postseason. The cluster dendrogram shows that all the days could be clustered in 6 groups: most of the clusters shows the daily peaks between 11:00 and 15:00 with a smooth curve (Cluster 1 and 3) or with a strong peak (2 and 5). Days included in cluster 9 shows an earlier peak in the morning (before 9:00). On the other hand, cluster 6 shows a peak in the afternoon, after 15:00. Hourly concentrations show a sharper pattern during the season, with the peak during the hours close to the emission. Out of the season, when pollen is expected to come from farther distances, the hourly peak is located later from the emission time of the trees. Significant factors for predicting the hourly pattern were wind speed and direction and the distance to the olive groves.
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•Bioinformatics clustering application for mining of a large set of olive pollen data.•Olea hourly pollen concentrations measured during 8 years in Extremadura (Spain).•New methodological approach in allergy prevention and cultivation of olives groves.•Cluster dendrogram shows that all the days could be clustered in 6 groups.•Significant factors for predicting the hourly pattern were wind speed and direction.
Airborne pollen concentration varies depending on several factors, such as local plant biodiversity, geography and climatology. These particles are involved in triggering pollinosis in a share of ...worldwide human population, and adequate monitoring is, therefore, important. However, the pollen traps in aerobiological monitoring networks are usually installed in cities, and the features of the whole territory are not taken into account. The aim of this study was to analyze what environmental parameters are more suitable as regards setting up monitoring stations throughout a territory in order to obtain an aerobiological network that can represent environmental diversity. The analysis was carried out in 13 locations in Castilla y León over an 8 year period. This is a favorable territory in which to conduct this type of study owing to its climatic features, orography and biodiversity. The ten most abundant pollen types in the region were analyzed, and a clustering analysis was calculated with different distances so as to obtain homogeneous groups of stations. Moreover, the clusters obtained were analyzed in combination with altitudinal and different bioclimatic parameters, which derived from temperature and precipitation.
The result here shows that the Castilla y León aerobiological network RACYL represents most of the environmental variability of the territory. Furthermore, it can be divided into two clusters and five sub-clusters for which the start of the main pollen season is different. This corresponds with the division of the territory as regards bioclimatic conditions. The most important bioclimatic parameters were the seasonality of the precipitation and the maximum temperature of the warmest month, although orography must also be taken into account. All of these help discover the optimal places in which to install traps and could reduce the number of monitoring stations. This study additionally provides data for unmonitored areas with similar bioclimatic conditions to those monitored.
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•RACYL monitoring network represents the environmental variability of the territory.•The territory is clustered in 2 areas and 5 subareas according to Main Pollen Season.•Seasonality of precipitation and max temperature defines pollen areas and subareas.•Orography is one of the most important features when installing samplers.•Traps in not urban areas are crucial for a better knowledge of flowering periods.
Climate change affects the reproductive life cycles of plants, including pollen production, which has consequences for allergic respiratory diseases. We examined climatic trends at eight locations in ...Bavaria, Southern Germany, with pollen time series of at least 10 years (up to 30 years in Munich). Climate change in Bavaria was characterized by a rise in temperature, but not during the winter. There is also a trend towards a more continental climate in Bavaria, which is significant in the Alps in the south of the territory. The influence of climate change depended on pollen type. Wind-pollinated arboreal species (e.g.
Alnus
,
Betula
and Cupressaceae/Taxaceae) showed advances in the start and end dates of pollen seasons and an increase in pollen load. These changes correlated negatively with late-winter (February) and spring temperatures (April). For herbaceous species, like Poaceae and Urticaceae, an earlier season was observed. Although precipitation is not a limiting factor in Southern Germany, water availability in the spring did influence the magnitude of grass pollen seasons. The effect of climatic change on the characteristics of pollen seasons was also more pronounced at higher altitudes, significant at > 800 m above sea level. Our results show that trends for start, end dates and intensity were similar at all locations, but only statistically significant at some. If we assume that earlier and more intense pollen seasons result in increases in prevalence and severity of allergic diseases, then the effect of climate change on public health in Bavaria may be significant.
The intensification of agriculture has significant environmental consequences. This intensification entails the simplification and homogenisation of the landscape, which leads to strong negative ...impacts at ecosystem level, including declines in animal biodiversity. The purpose of this study was to assess the effect of different land uses on reptilian and amphibian biodiversity patterns at a regional scale by analysing a large database on the presence of amphibians and reptiles in Andalusia (southern Spain). GIS techniques and the Ecological-Niche Factor Analysis (ENFA) were applied in order to assess whether the habitat was suitable for each reptilian and amphibian species, when the land use variables were excluded. The incongruence between the potential and the observed species richness was then correlated with the main types of land use in Andalusia. Our results showed that irrigated and unirrigated olive groves were associated with a biodiversity deficit of amphibians and reptiles respectively, whereas natural forests and pastures, along with more heterogeneous crops areas, were more suitable. A clustering analysis showed that generalist species were related to olive groves whereas rare and specialist species were related to land uses related to natural vegetation. In summary, our results indicate that large areas covered by olives groves harbour less amphibian and reptilian diversity, thus suggesting that agro-environmental schemes should be carried to promote the species richness in these crops.
•The species richness of amphibians and reptiles is reduced in olive groves.•Irrigated olive crops have a strong negative effect on amphibians but not on reptiles.•Generalist species are associated with olive groves whereas rare species are associated with other land uses.
The effects of climate change on agricultural systems raise important uncertainties about the future productivity and suitability of crops, especially in areas suffering from intense environmental ...changes. Olive groves occupy Mediterranean areas characterized by seasonal temporary droughts, which cause this cultivation to be highly dependent on local microclimatic conditions. Olive crop production can be reliably estimated using pollen intensity metrics together with post-pollination environmental conditions. In this study, we applied this kind of statistics-based models to identify the most relevant meteorological variables during the post-pollination periods for olive fruit production. Olive pollen time-series for the period of 1999–2012 was analyzed in 16 Italian provinces. Minimum and maximum temperature during spring and summer (March–August) showed a negative relationship with olive production, while precipitation always showed a positive correlation. The increase in aridity conditions observed in areas of Italy during the summer represents an important risk of decreasing olive crop production. The effect of climate change on the olive production trend is not clear because of the interactions between human and environmental factors, although some areas might show an increase in productivity in the near future under different climate change scenarios. However, as more drastic changes in temperature or precipitation take place, the risk to olive production will be considerably greater.
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