Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain)

PM2.5 exceedances and source appointment as inputs for an early warning system

Between June 2018 and April 2019, a sampling campaign was carried out to collect PM_2.5, monitoring meteorological parameters and anthropogenic events in the Sartenejas Valley, Venezuela. We develop a logistic model for PM_2.5 exceedances (≥ 12.5 µg m^-3). Source appointment was done using elemental composition and morphology of PM by scanning electron microscopy coupled with energy dispersive spectroscopy (SEM-EDS). A proposal of an early warning system (EWS) for PM pollution episodes is presented. The logistic model has a holistic success rate of 94%, with forest fires and motor vehicle flows as significant variables. Source appointment analysis by occurrence of events showed that samples with higher concentrations of PM had carbon-rich particles and traces of K associated with biomass burning, as well as aluminosilicates and metallic elements associated with resuspension of soil dust by motor-vehicles. Quantitative source appointment analysis showed that soil dust, garbage burning/marine aerosols and wildfires are three majority sources of PM. An EWS for PM pollution episodes around the Sartenejas Valley is proposed considering the variables and elements mentioned.

A Modified Spectroscopic Approach for the Real-Time Detection of Pollen and Fungal Spores at a Semi-Urban Site Using the WIBS-4+, Part I

The real-time monitoring of primary biological aerosol particles (PBAP) such as pollen and fungal spores has received much attention in recent years as a result of their health and climatic effects. In this study, the Wideband Integrated Bioaerosol Sensor (WIBS) 4+ model was evaluated for its ability to sample and detect ambient fungal spore and pollen concentrations, compared to the traditional Hirst volumetric method. Although the determination of total pollen and fungal spore ambient concentrations are of interest, the selective detection of individual pollen/fungal spore types are often of greater allergenic/agricultural concern. To aid in this endeavour, modifications were made to the WIBS-4 instrument to target chlorophyll fluorescence. Two additional fluorescence channels (FL4 and FL5 channels) were combined with the standard WIBS channels (FL1, FL2, FL3). The purpose of this modification is to help discriminate between grass and herb pollen from other pollen. The WIBS-4+ was able to successfully detect and differentiate between different bioaerosol classes. The addition of the FL4 and FL5 channels also allowed for the improved differentiation between tree (R² = 0.8), herbaceous (R² = 0.6) and grass (R² = 0.4) pollen and fungal spores (R² = 0.8). Both grass and herbaceous pollen types showed a high correlation with D type particles, showing strong fluorescence in the FL4 channel. The additional fluorescent data that were introduced also improved clustering attempts, making k-means clustering a comparable solution for this high-resolution data.

Importance of Meteorological Parameters and Airborne Conidia to Predict Risk of Alternaria on a Potato Crop Ambient Using Machine Learning Algorithms

Secondary infections of early blight during potato crop season are conditioned by aerial inoculum. However, although aerobiological studies have focused on understanding the key factors that influence the spore concentration in the air, less work has been carried out to predict when critical concentrations of conidia occur. Therefore, the goals of this study were to understand the key weather variables that affect the hourly and daily conidia dispersal of Alternaria solani and A. alternata in a potato field, and to use these weather factors in different machine learning (ML) algorithms to predict the daily conidia levels. This study showed that conidia per hour in a day is influenced by the weather conditions that characterize the hour, but not the hour of the day. Specifically, the relative humidity and solar radiation were the most relevant weather parameters influencing the conidia concentration in the air and both in a linear model explained 98% of the variation of this concentration per hour. Moreover, the dew point temperature three days before was the weather variable with the strongest effect on conidia per day. An improved prediction of Alternaria conidia level was achieved via ML algorithms when the conidia of previous days is considered in the analysis. Among the ML algorithms applied, the CART model with an accuracy of 86% were the best to predict daily conidia level.

A study on correlations between precipitation ETCCDI and airborne pollen/fungal spore parameters in the NE Iberian Peninsula

Precipitation is one of the meteorological variables usually involved in the aerobiological studies, which presents a complex relationship with atmospheric levels of pollen and fungal spores and the temporal characteristics of their seasons. This complexity is due in a large part to rainfall's twofold impact of having, prior to pollination, a positive influence on subsequent pollen production and of contributing, during pollination, to pollen removal from the air through a wash-out effect. To better explore this impact, we place particular emphasis on extreme rainfall by calculating the correlation between airborne pollen and fungal spore parameters and the precipitation indices that the Expert Team on Climate Change Detection and Indices (ETCCDI) proposed for characterising climate extremes. Parameters for twenty-seven pollen and fungal spore taxa measured in six aerobiological stations in the NE Iberian Peninsula have been considered. We have distinguished between annual and winter ETCCDI in order to compare the correlations between extreme rainfall and airborne pollen concentrations and to avoid the wash-out effect as far as possible. Results show a positive influence from an increase in moderately extreme winter rainfall, specifically on subsequent pollen/fungal spore production: the percentage of all possible significant correlations is higher for winter than for annual rainfall. Furthermore, while annual rainfall in this region has nearly the same number of positive as negative correlations, the positive correlations for winter rainfall are more than twice that of the negative ones. The seasonal consideration on rainfall ETCCDI made with the aim to avoid the confounding overlapping of different rainfall impacts has led to more sharpened observations of its positive and negative effects on airborne pollen and fungal spore concentrations.

First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

Ambient fungal spores within the atmosphere can contribute to a range of negative human, animal and plant health conditions and diseases. However, trends in fungal spore seasonality, species prevalence, and geographical origin have been significantly understudied in Ireland. Previously unpublished data from the late 1970s have recently been collected and analysed to establish historical fungal spore trends/characteristics for Dublin. Historical spore concentrations were largely dominated by Alternaria, Ascospores, Basidiospores, Botrytis, Cladosporium, Erysiphe and Rusts. The main fungal spore season for Dublin commenced in April with the fructification of Scopulariopsis and Ganoderma. However, the vast majority of other spore types did not reach peak spore release until late summer. The correlation between ambient spore concentration, and meteorological parameters was examined using Multivariable Regression Tree (MRT) analysis. The notable correlations found for fungal spore concentrations tended to involve temperature-based parameters. The use of a non-parametric wind regression was also employed to determine the potential geographical origin of ambient fungal spores. The impact of wind direction, and high windspeed on fungal spores was established, ultimately highlighting the importance of studying and monitoring fungal spores within Ireland, rather than attempting to rely on data from other regions, as most fungal spores collected in Dublin appeared to originate from within the island.

Airborne Fungal Spore Review, New Advances and Automatisation

Fungal spores make up a significant portion of Primary Biological Aerosol Particles (PBAPs) with large quantities of such particles noted in the air. Fungal particles are of interest because of their potential to affect the health of both plants and humans. They are omnipresent in the atmosphere year-round, with concentrations varying due to meteorological parameters and location. Equally, differences between indoor and outdoor fungal spore concentrations and dispersal play an important role in occupational health. This review attempts to summarise the different spore sampling methods, identify the most important spore types in terms of negative effects on crops and the public, the factors affecting their growth/dispersal, and different methods of predicting fungal spore concentrations currently in use.

Airborne Alt a 1 Dynamic and Its Relationship with the Airborne Dynamics of Alternaria Conidia and Pleosporales Spores

Fungal spores are universal atmospheric components associated to allergic reactions. Alternaria (Ascomycota) is considered the most allergenic spore taxa. Alt a 1 is the major allergen of Alternaria and is present also in other Pleosporales. In this study, standard Hirst-based sampling and analyzing methods for measuring spore daily concentrations of Alternaria, Curvularia, Drechslera-Helminthosporium, Epicoccum, Leptosphaeria, Pithomyces, Pleospora and Stemphylium (all included in the taxon Pleosporales) have been used as well as two high-volume samplers, Burkard Cyclone (2017) and MCV CAV-A/mb (2019–2020), and ELISA kits for measuring the allergen. The detection and quantification of Alt a 1 was only possible in the samples from the MCV sampler. Although Alt a 1 was better correlated with Alternaria spores than with Pleosporales spores, the three of them showed high correlations. It is shown that there is a high and significant correlation of Alt a 1 with temperature, a negative correlation with relative humidity and no correlation with precipitation. The aerobiological monitoring of these three elements ensures the best information for understanding the affectation to allergy sufferers, but, if this is not possible, as a minimum public health service aimed at the detection, treatment and prevention of allergies, the study of the airborne Alternaria spores should be ensured.

Alternaria as an Inducer of Allergic Sensitization

Alternaria alternata is a saprophytic mold whose spores are disseminated in warm dry air, the typical weather of the Mediterranean climate region (from 30° to 45°), with a peak during the late summer and early autumn. Alternaria spores are known to be biological contaminants and a potent source of aeroallergens. One consequence of human exposure to Alternaria is an increased risk of developing asthma, with Alt a 1 as its main elicitor and a marker of primary sensitization. Although the action mechanism needs further investigation, a key role of the epithelium in cytokine production, TLR-activated alveolar macrophages and innate lymphoid cells in the adaptive response was demonstrated. Furthermore, sensitization to A. alternata seems to be a trigger for the development of co-sensitization to other allergen sources and may act as an exacerbator of symptoms and an elicitor of food allergies. The prevalence of A. alternata allergy is increasing and has led to expanding research on the role of this fungal species in the induction of IgE-mediated respiratory diseases. Indeed, recent research has allowed new perspectives to be considered in the assessment of exposure and diagnosis of fungi-induced allergies, although more studies are needed for the standardization of immunotherapy formulations.