Stepwise selection of functional covariates in forecasting peak levels of olive pollen

High levels of airborne olive pollen represent a problem for a large proportion of the population because of the many allergies it causes. Many attempts have been made to forecast the concentration of airborne olive pollen, using methods such as time series, linear regression, neural networks, a combination of fuzzy systems and neural networks, and functional models. This paper presents a functional logistic regression model used to study the relationship between olive pollen concentration and different climatic factors, and on this basis to predict the probability of high (and possibly extreme) levels of airborne pollen, selecting the best subset of functional climatic variables by means of a stepwise method based on the conditional likelihood ratio test.Projects MTM2010-20502 from Dirección General de Investigación del MEC, Spain and FQM-307 from Consejería de Innovación, Ciencia y Empresa de la Junta de Andalucía Spai

Análisis exploratorio de las variaciones estacionales e intraestacionales de los principales tipos polínicos en la atmósfera de la ciudad de Sunchales, Argentina

Introducción y objetivos: El estudio de la variabilidad estacional e intraestacional de la concentración de polen en el aire es de suma importancia para comprender las relaciones con la vegetación emisora y los parámetros atmosféricos que modulan el transporte de polen. Esta investigación tiene como objetivo estudiar estas variabilidades en Sunchales, una ciudad ubicada en el centro-este de Argentina. M&M: El monitoreo atmosférico se realizó con una trampa Burkard durante dos temporadas en 2012 y 2013 en las afueras de la ciudad. Resultados & Conclusiones: Los períodos de polinización de los tipos de polen estudiados muestran un retraso en 2013 en comparación con el año anterior, presuntamente relacionado con una mayor cantidad de unidades de calor acumuladas en 2012. Sin embargo, la integral polínica para el período 2013 fue 1,4 veces mayor que 2012, hecho que no se explica por la precipitación acumulada sino por la hora del día en que ocurren los hidrometeoros. Las concentraciones de polen categorizadas en rangos muestran que los valores mayores coinciden con la ubicación urbana de las fuentes arbóreas mientras que las herbáceas muestran una asociación con un origen rural. En cuanto a la variabilidad intraestacional, la mayor proporción de la varianza del polen en el aire se acumula en la escala sinóptica (80 - 60%) con períodos entre 3 y 10 días. Durante 2012 predominaron las ondas largas (> 5,5 días) mientras que en 2013 predominaron las ondas medias (3,9 - 5,5 días).Background and aims: The study of the seasonal and intra-seasonal variability of the airborne pollen concentration is of paramount importance to understand the relationships with the emitting vegetation and the atmospheric parameters that modulate pollen transport. This research aims to study these variabilities in Sunchales, a city located in the center-east of Argentina. M&M: Atmospheric monitoring was carried out with a Burkard trap during two seasons in 2012 and 2013 on the outskirts of the city. Results & Conclusions: The pollination periods of the studied pollen types show a delay in 2013 compared to the previous year, presumably related to a greater amount of cumulative heat units in 2012. However, the integral pollen for the period 2013 was 1.4 times higher than 2012, a fact that is not explained by accumulated precipitation but by the time of day when the hydrometeors occur. Binned pollen concentrations show that the highest concentrations coincide with the urban location of the tree sources while the herbaceous ones show an association with a rural origin. Regarding the intra-seasonal variability, the highest proportion of the airborne pollen variance accumulates on the synoptic-scale (80 - 60%) with periods between 3 and 10 days. During 2012 long waves predominated (> 5.5 days) while in 2013 medium waves prevailed (3.9 - 5.5 days).Fil: Perez, Claudio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; ArgentinaFil: Covi, Mauro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gassmann, María Isabel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ulke, Ana Graciela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentin

A Comparison of Models for the Forecast of Daily Concentration Thresholds of Airborne Fungal Spores

Altres ajuts: Ministerio de Ciencia y Tecnología AMB97-0457-CO7-021, REN2001-10659-CO3-01, BOS2002-03474, CGL2004-21166-E, GGL2006-12648-CO3-02Unidad de excelencia María de Maeztu CEX2019-000940-MAerobiological predictive model development is of increasing interest, despite the distribution and variability of data and the limitations of statistical methods making it highly challenging. The use of concentration thresholds and models, where a binary response allows one to establish the occurrence or non-occurrence of the threshold, have been proposed to reduce difficulties. In this paper, we use logistic regression (logit) and regression trees to predict the daily concentration thresholds (low, medium, high, and very high) of six airborne fungal spore taxa (Alternaria, Cladosporium, Agaricus, Ganoderma, Leptosphaeria, and Pleospora) in eight localities in Catalonia (NE Spain) using data from 1995 to 2014. The predictive potential of these models was analyzed through sensitivity and specificity. The models showed similar results regarding the relationship and influence of the meteorological parameters and fungal spores. Ascospores showed a strong relationship with precipitation and basidiospores with minimum temperature, while conidiospores did not indicate any preferences. Sensitivity (true-positive) and specificity (false-positive) presented highly satisfactory validation results for both models in all thresholds, with an average of 73%. However, seeing as logit offers greater precision when attempting to establish the exceedance of a concentration threshold and is easier to apply, it is proposed as the best predictive model

Recent developments in monitoring and modelling airborne pollen, a review

Public awareness of the rising importance of allergies and other respiratory diseases has led to increased scientific effort to accurately and rapidly monitor and predict pollen, fungal spores and other bioaerosols in our atmosphere. An important driving force for the increased social and scientific concern is the realisation that climate change will increasingly have an impact on worldwide bioaerosol distributions and subsequent human health. In this review we examine new developments in monitoring of atmospheric pollen as well as observation and source-orientated modelling techniques. The results of a Scopus® search for scientific publications conducted with the terms ‘Pollen allergy’ and ‘Pollen forecast’ included in the title, abstract or keywords show that the number of such articles published has increased year on year. The 12 most important allergenic pollen taxa in Europe as defined by COST Action ES0603 were ranked in terms of the most ‘popular’ for model-based forecasting and for forecasting method used. Betula, Poaceae and Ambrosia are the most forecast taxa. Traditional regression and phenological models (including temperature sum and chilling models) are the most used modelling methods, but it is notable that there are a large number of new modelling techniques being explored. In particular, it appears that Machine Learning techniques have become more popular and led to better results than more traditional observation-orientated models such as regression and time-series analyses

Current Air Quality Issues

Air pollution is thus far one of the key environmental issues in urban areas. Comprehensive air quality plans are required to manage air pollution for a particular area. Consequently, air should be continuously sampled, monitored, and modeled to examine different action plans. Reviews and research papers describe air pollution in five main contexts: Monitoring, Modeling, Risk Assessment, Health, and Indoor Air Pollution. The book is recommended to experts interested in health and air pollution issues

Microscale pollen release and dispersal patterns in flowering grass populations

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites (<300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index (α-diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales