Aerobiologia最新文献

In Europe, more than one quarter of the adult population and one third of the children suffer from pollinosis, but the geographical variability is large. In Belgium, at least ~ 10% of the people develop allergies due to birch pollen. These patients may benefit from a forecasting system that raises alerts when episodes with huge amount of airborne birch pollen grains are expected. Such a forecast system for birch pollen was established for the Belgian territory in 2023 based on the pollen emission and transport model System for Integrated modeLling of Atmospheric coMposition (SILAM). The question, however, is which uncertainty in modelling and forecasting airborne pollen levels can be expected? Here, we assess the uncertainty in modelling airborne birch pollen levels near the surface using SILAM in a Monte Carlo error approach summarized by the relative Coefficient of Variation (CV%) as descriptive statistic for the season of 2018 in Belgium. For the major inputs that drive the birch pollen model—the amount and location of birch trees (0.1° × 0.1° map), the start and end of the birch pollen season (1° × 1° map), and the ripening temperature of birch catkins—sets of 100 randomly sampled data layers were prepared for running SILAM 100 times. For each set of model input, 100 spatio-temporal maps of airborne birch pollen levels were produced and its spread was quantified by the CV%. We show that the spatial uncertainty of pollen emissions sources in SILAM is substantially high, but that the uncertainties of the parameters determining the start and end of the season are at least equally important. By accumulating the effects of all investigated model input uncertainties including the impact of the catkins-ripening temperature, CV% values of 50% and more are obtained when quantifying the variation of the modelled airborne birch pollen levels. These errors are in line with reported values from the current reference method for monitoring airborne birch pollen grains near the surface.

Biological particles known as bioaerosols are present in the atmosphere and have recently been implicated as influencing agriculture, cloud development, biogeography, and human health. The present study was conducted to characterize airborne bacterial heterogeneity at Jeju Island in Korea and at Saitama and Toyama in Japan, focusing on potential human pathogens. Air samples were collected during the winter, when the monsoon blows from the northwest. Samples were analyzed by high-throughput sequencing and denaturing gradient gel electrophoresis of PCR-amplified 16S rRNA genes to detect spatial differences in airborne bacteria and the possible spread of bacteria by transboundary transport. Compositions of the bacterial in samples collected on the same dates from the different sites were similar. Notably, bacteria from two genera that are potentially pathogenic for humans—Acinetobacter and Clostridium—were detected on the same day in both Korea and Japan. These results indicate the possibility of long-range transport of airborne bacteria and its potential impact on human health.

The viable bacterial assemblages in clouds at Réunion Island (Indian Ocean) were examined through culture-based approach. A total of 176 isolates were recovered from 15 independent cloud events collected during 3 field campaigns, and identified to the species level through full length 16S rRNA gene sequencing. As often in atmospheric samples, Alpha-, Beta- and Gamma-proteobacteria dominated, along with Actinobacteria, Firmicutes, and Bacteroidetes, depicting these as the backbone of the global aeromicrobiome. A comparative analysis with similar work from a cloud sampling site in Central France revealed site-specificities, and numerous common species. These latter included members of Pseudomonas, Sphingomonas, Bacillus, Staphylococcus, Rhodococcus and others, whose such widespread presence in clouds supports the existence of a pan-atmospheric microbiome. This also confirms that cultures remain powerful methods in the description of the viable microbial diversity by allowing deep taxonomic affiliation.

The advent of automatic pollen and fungal spore monitoring over the past few years has brought about a paradigm change. The provision of real-time information at high temporal resolution opens the door to a wide range of improvements in terms of the products and services made available to a widening range of end-users and stakeholders. As technology and methods mature, it is essential to properly quantify the impact automatic monitoring has on the different end-user domains to better understand the real long-term benefits to society. In this paper, we focus the main domains where such impacts are expected, using Europe as a basis to provide qualitative estimates and to describe research needs to better quantify impacts in future. This will, in part, also serve to justify further investment and help to expand monitoring networks.

In 2019, the world grappled with an unexpected and severe global health crisis—the Coronavirus disease (COVID-19) outbreak, which significantly impacted various aspects of human life. This case study, focusing on Bangladesh, aimed to uncover the complex spatial patterns and potential risk factors influencing the virus’s uneven spread across 64 districts. To analyze spatial patterns, two techniques, namely Moran I and Geary C, were employed to study spatial autocorrelation. Hotspots and coldspots were identified using local Moran I, while spatial hotspots were pinpointed using local Getis Ord G. Exploring spatial heterogeneity involved implementing two non-spatial models (Poisson–Gamma and Poisson-Lognormal) and three spatial models (Conditional Autoregressive model, Convolution model, and Leroux model) through Gibbs sampling. The Leroux model emerged as the optimal choice, meeting criteria based on the lowest values of deviance information criterion and Watanabe–Akaike information criterion. Regression analysis revealed that factors such as humidity, population density, and urbanization were associated with an increase in COVID-19 cases, while the aging index appeared to hinder the virus’s spread. The research outcomes provide a comprehensive framework adaptable to the evolving nature of COVID-19 in Bangladesh. It categorizes influential factors into distinct clusters, enabling government agencies, policymakers, and healthcare professionals to make informed decisions for controlling the pandemic and addressing future infectious diseases.

Suspended particles of biological origin comprising of virus, fragments of plants and animals dander, pollen grains, fungal spores and bacteria known as bioaerosols have become a major concern in the past decades. In the present study reports, the concentration and size distribution of fungal bioaerosol in and around a sugar mill situated in the Muzaffarnagar region of Uttar Pradesh, India, are presented. The sampling was performed in the winter when the mill used to be in the operational mode. The highest mean fungal concentration was observed at the cutter site (4022 ± 321 cfu/m³) and lowest at storage site (832 ± 85 cfu/m³). The maximum and minimum concentration of fungal bioaerosol was observed during January (3090 ± 174 cfu/m³⁾ and March (629 ± 69 cfu/m³) respectively. During the entire sampling period, the fine fraction of fungal bioaerosol was observed to be significantly higher at all the sites, whereas coarse fraction was lower. The association between fine and coarse fractions of bioaerosols showed a very strong positive relationship. The levels of fungal bioaerosol and their association with the meteorological parameters in sugar mill were also conducted. A positive association with the relative humidity and wind speed was observed at significance level of p < 0.05, whereas a negative relation was observed with temperature at p < 0.05. The lifetime average daily dose was calculated for both inhalation and dermal; among them LADD_inhalation is ~ 5 times over LADD_dermal. The health risk index was observed as < 1 for both inhalation and dermal routes, whereas HI_inhalation value was 10⁵ times higher than the HI_dermal value. The dominant fungi genera found in the air of examined dwellings were Penicillium spp., Aspergillus spp., Cladosporium spp., and Alternaria spp., which occurred predominantly at all of the studied sites during the sampling period.

Dengue fever is a virus-borne disease spread by mosquitos, and its global prevalence has risen significantly in recent years. The aim of this study was to analyze the impact and association of climatic factors on the spread of dengue incidence in Bangladesh. From January 2011 to December 2021, the study used secondary data on monthly dengue cases and the monthly average of climatic factors. In addition to the descriptive statistics, bivariate analyses of Kendall’s tau-b and Spearman’s rho have been performed for measuring the association of climatic factors on dengue infection. The generalized linear negative binomial regression model with and without lag was applied to evaluate the impacts of climatic factors on dengue transmission. Results of goodness of fit statistics ((AIC, BIC, and deviance)) showed that NBR model with one month lag best fitted to our data. The model findings revealed that temperature ((IRR:1.223, 95% CI:1.089-1.374)), humidity ((IRR:1.131, 95% CI:1.103-1.159)), precipitation ((IRR:1.158, 95% CI:1.072-1.253)), and air pressure ((IRR:5.279, 95% CI:1.411-19.046)) were significantly positively influenced the spread of dengue incidence in Bangladesh. Additionally, dengue fever cases are anticipated to rise by 1.223, 1.131, 1.158, and 5.279 times, respectively, for the everyone-unit increase in the monthly average mean temperature, humidity, precipitation, and air pressure range. The findings on the epidemiological trends of the dengue epidemic and weather changes may interest policymakers and health officials.

Deposited dust represents a nutritional niche for microflora. Inhibiting microflora-associated deposited dust is a critical approach to manage cultural heritage buildings. Knowledge on the effectiveness of commercial disinfection on microflora in a real field environment is limited. The present study aims to: (1) characterize deposited dust composition, and (2) assess the effectiveness of several commercial biocides/and an air ionizer on microflora-associated floor surface and air before and after treatment. Deposited dust was collected using a dust collector and microbial air sampling was conducted via a volumetric impactor sampler. Susceptibility of microorganisms to biocide/ionizer was performed in a naturally ventilated unoccupied room with a floor area of 18 m². One-treatment protocol, a daily disinfection mode, was applied to each biocide/ionizer. The surface floor was adjacently sprayed by a biocide, and the ionizer was turned on for 30 min. Indoor deposited dust rates varied between 0.75 and 8.7 mg/m²/day with indoor/outdoor ratio of ~ 1:100. Ion concentrations of NH₄⁺, Cl⁻, SO₄²⁻ and NO₃⁻ were higher indoor than outdoor. The concentration of microorganisms-associated deposited dust averaged 10⁶ CFU/g; 10⁵ CFU/g and 10⁴ CFU/g for bacteria, fungi and actinomycetes, respectively. A total of 23 fungal taxa were identified, with Aspergillus flavus, Asp. fumigatus and Asp. niger were the predominant taxa. Biocides quickly reduced floor surface and airborne microbial loads. The biocidal effect was time limited, as microflora loads increased again after ~ 4 days of the treatment protocol. Benzalkonium chloride (BAC) out-performed other biocides, showed a relatively permanent microbial inhibiting effect. The air ionizer reduced airborne microorganisms and increased surface floor ones. Characterizing of deposited dust (rate and composition) and choice an appropriate biocide may effectively reduce biodeterioration. Further real field treatment trials under various microenvironmental conditions are needed to determine the effectiveness of disinfection treatment.

This scientific article presents a comprehensive exploration of the intriguing ecological phenomenon known as "red rain", observed in the coastal town located at latitude N 11°.61108 and longitude E 75°.57383 in Kerala, India. The study aims to elucidate the origins, characteristics, and potential environmental implications associated with this phenomenon. Through a meticulous descriptive analysis, incorporating microscopic evaluation, DNA-sequencing, Fourier-transform infrared spectroscopy (FTIR), Gas Chromatography-Mass Spectrometry (GC–MS) analysis, and phylogenetic analysis, we deciphered the underlying factors responsible for the distinct red coloration observed in the rain. Our research findings highlight the presence of specific organic compounds, namely psi-psi Carotene 3,4 didehydro-1,2,7′8'-tetrahydro-1-methoxy-2-oxo and psi-psi and- Carotene 3,3',4,4'-tetradehydro1′2' dihydro 1-hydroxy-1'-methoxy in the algae, Trentepohlia abietina, as the primary contributors to the red color observed in the red rain. The research findings contribute to a deeper understanding of this distinctive occurrence and its implications for the local ecosystem in Kerala.