Aerobiologia最新文献

Urban green spaces are a vital element of sustainable cities. Nonetheless, there are associated disservices, one most important being pollen induced allergies. To examine how much vegetation analysis of urban green spaces can be an efficient indicator of the pollen-related qualitative and quantitative features of their atmospheric environment, we studied six such spaces, in Thessaloniki, Greece. We made a full analysis of their woody vegetation and collected aerobiological data, with sampling at breast height. Cupressaceae, Platanus, Quercus, Pinaceae and the herbaceous Urticaceae were the main pollen providers in almost all of them, when the main woody components of their vegetation were Cupressaceae, Rosaceae, Pinaceae and Fabaceae, with Quercus having only sporadic occurrence. The number of taxa represented in pollen and vegetation were not correlated, and pollen from external sources was detected even at high concentrations. Pollen similarity was higher than vegetation similarity, with taxa identity being more important than abundance in differentiating the green spaces. Pollen incidence was synchronized in many cases but, like concentration, duration of the pollen season also varied largely among green spaces, even when in proximity. Positive relationships between pollen concentration and vegetation abundance were detected for a few taxa, primarily Cupressaceae, and for green spaces that covered a large area (around 40 ha) or had an element of isolation. Vegetation analysis is not a reliable indicator of the pollen related atmospheric environment at the local scale. Aerobiological surveys are additionally needed locally to provide the necessary information regarding the prevailing conditions and the associated risks.

Proteins in atmospheric aerosols are the major components causing allergic reactions in the human respiratory tract and they are an increasing concern for public health. However, the deposition characteristics of proteins in the respiratory tract remain unclear, which hinders a comprehensive understanding of their threat to human health. In this study, size-segregated aerosol samples were collected in Xi 'an, and the protein concentration was then determined using the bicinchoninic acid (BCA) assay. Concurrently, the total and regional deposition doses of proteins in different age groups (infants, children, adolescents and adults) were estimated using a multi-path particle dosimetry (MPPD, v.3.04) model. The results showed that the total deposition dose varied seasonally, and it was significantly higher in autumn and winter than in spring and summer. Moreover, across all seasons, the highest deposition doses were recorded in adults (10.82 × 10^–3, 9.35 × 10^–3, 17.98 × 10^–3, and 20.33 × 10⁻³ μg/min), while infants (1.84 × 10^–3, 1.58 × 10^–3, 3.14 × 10^–3 and 3.68 × 10⁻³ μg/min) had the lowest doses. For different regions of the respiratory tract, the deposition dose in the extra-thoracic (ET) region consistently exceeded that in the tracheobronchial (TB) and pulmonary (PUL) regions, and it increased with age. Especially during summer, the deposition dose in the ET region of adults was 9.8 times higher than that of infants. Notably, the proteins deposited in the TB region are rapidly removed, while half of proteins deposited in the PUL region would persist for more than 1 year. The findings of this study contribute to a better understanding of the health risks associated with ambient proteins.

Graphical abstract

The Artemisia (mugwort) pollen season usually ranges from July until September, with one peak period around mid-August in Vienna (Austria). During the last decade, Artemisia pollen was also recorded later in September. This pattern was concluded by a significant peak pollen concentration day in autumn of 2023, which exceeded the usual summer peak pollen concentration day. The Artemisia pollen data from Vienna for the last ten years (2014–2023) were therefore analysed for a temporal trend. In addition, weather data from Vienna (temperature, precipitation, and relative humidity and sun hours) were retrieved and analysed to find a possible association with Artemisia pollen indices. No significant trend could be observed regarding the Artemisia pollen season parameters and no correlation was found between the weather data and the Artemisia pollen integrals during summertime. However, a significant positive correlation was found between higher temperatures during autumn and the occurrence of Artemisia pollen during this time. This suggests that a significant change in the Artemisia pollen season can be expected during years with a mild, summer-like autumn. Until now, it is not clear which species of Artemisia cause the pollination in autumn. A. annua and A. verlotiorum are two major suspects that could have established themselves in Vienna, but further evidence is needed. Considering the impact of global climate change, the shift in the pollen season for Artemisia described in this study could represent a point of no return.

Indoor air pollution directly affects mortality and also morbidity; it is also a vital issue of concern for the majority of nations that are in their developing phase. Coal and biomass (crop waste, wood, dung, and charcoal) are the main household energy sources for approximately around three billion people worldwide. Additionally, as most persons spend nearly 80–90% of their time in an indoor environment regularly, indoor air quality has a vital and direct effect on both general health and productivity of them. Although outdated, air pollution monitoring is nevertheless a very important idea in daily life. The monitoring of air quality has been done using both conventional methods and the most advanced computing techniques. However, as everyone needs access to clean air, many advanced wireless technologies have been used and some of them are quite helpful in giving information related to real-time data on air quality. The main purpose of this study is to describe some advanced techniques and devices used to monitor indoor air pollution and some of the significant advancements which have been done in this research field.

Air pollution, aeroallergens, and weather conditions can worsen health symptoms such as asthma. While studying the impact of these factors, the use of weather types (WTs) rather than individual meteorological variables (such as temperature, relative humidity, wind, cloudiness, or precipitation) is more appropriate since it is holistic and integrative. Moreover, several studies have shown that the human body responds to WTs, rather than to individual meteorological variables. In this study, the use of Sheridan’s WTs is adopted and compared with a so-called “In-House” WTs. The analysis presented here deals with the links between asthma hospitalization and the synergy among air pollution, birch tree pollen and WTs. Knowing the daily WT in a region can provide valuable information for health planning and management of asthma hospitalization, emergency visits and sub-clinical symptoms in the population. This is because air pollution and birch pollen both occur within only a few specific WTs, such as the TROWAL (trough of warm air aloft) or tropical airmasses. These specific WTs need to be more scrutinized since, in Montreal, these are often linked with higher daily mean hospitalization. The findings of this study emphasize the importance of specific WTs in determining the maximum daily concentrations of ozone, fine particles, Betula pollen concentrations and health effects such as asthma hospitalization. Moreover, the use of data filters in the analysis (for temperature and total count of hospitalization) also reveals new insights in the complex nature of asthma disease and its relationship with environmental factors.

Smog is a form of pollution composed of smoke and fog. It is one of the major environmental and public health problems in many urban areas around the world. Intriguingly, recent evidences have unveiled the potential link between smog and antimicrobial resistance (AMR). Smog can contribute to AMR through a complex and multifaceted set of mechanisms, including particulate matter (PM) which is found in smog, mediated transport of AMR microorganisms and genes, disruption of the respiratory microbiome, and modulation of host immune responses. Since the PM can lodge deeper in the lungs and harbors antibiotic resistance genes (ARGs), it should be considered that PM contributes to AMR toward the respiratory tract infections and other infections. PM can create conditions conducive to bacterial survival and growth in the respiratory system due to inflammation and immune suppression. PM2. 5 and PM10 have been associated with several respiratory system ailments due to their capability to penetrate inner areas. Moreover, PM can serve as a carrier for ARGs and other microbial components, aiding in their spread. This interaction may accelerate the development and spread of AMR. It is imperative to further unleash the mechanisms adopted by microbial extracellular DNA associated with the PM to envisage the potential health and environmental hazards. eDNA, for example, has been shown to contribute to the diversity and composition of microbiota associated with PM, such as bacteria, fungi, and viruses. This review focuses on PM, ARGs, and microbial eDNA as emerging environmental contaminants. A comprehensive analysis is conducted of the mechanisms and circumstances that contribute to its spread in diverse settings. Considering the current explosive increase in microbial resistance to the antibiotics, this also necessitates uncovering the underpinnings of the smog’s effect on AMR and developing effective strategies for mitigating these deleterious smog effects on health and environment.

In the last decade, a great deal of research has focused on the determination of potential toxic elements by total concentration and identification the microorganisms in dust. However, determining bio-relevant (e.g., inhalable) forms of elements instead of total contents in acids is necessary for human health. Moreover, examination of the behavior of microorganism under these bio-relevant conditions and revealing the interaction between elements and pathogens is vital and necessary for deeper understanding. However, previous studies have ignored these topics. Therefore, the present study aimed to (i) investigate elements in household dusts extracted in simulated lung fluids, (ii) examine the total concentration of culturable bacteria and their biochemical responses with exposure to bio-fractions of household dusts, and (iii) assess their relations and risks using the model approaches by inhalation. Here, settled dusts were collected in 25 houses, and extracted in four simulated body fluids to determine bio-fractions of elements. Moreover, total count of potentially pathogenic and heterotrophic bacteria, and four clinically important culturable pathogens were incubated in the presence of household-dusts extracted in simulated body fluids. The activity, biofilm, biochemical and oxidative responses of pathogens were measured following household-dust exposures. Afterward, the relationship between elements and pathogen responses were evaluated, and model and derived approaches were used for risk assessments of elements and pathogens. The higher daily intake of elements obtained in artificial lysosomal fluid fraction of household dust mimicking the inflammatory condition compared to other body fluids. Moreover, bacterial responses were mainly influenced from bio-fractions of household dusts and their elemental contents.

Airborne fungal spores of the genus Alternaria pose challenges for accurate airborne spore identification by automatic bioaerosol monitors, because of their significant implications for public health and agriculture due to their role as airborne allergen and plant pathogen. These systems require high-quality reference data for training algorithms by machine learning. Alternaria alternata was cultured on three different media, including exposure to UV light to favor sporulation. Spore morphology was evaluated both macroscopically and microscopically, and chemical analysis was conducted using micro-Raman spectroscopy to assess spore composition. Significant differences were observed in colony morphology and spore characteristics among culture media. While typical spores predominated, atypical forms were also identified, which may represent a potential bias for identification. Comparative analysis with air samples by the Hirst method also revealed overall differences in spore morphology pattern. Standardizing culture conditions and accounting for variability in spore properties are essential for improving the reliability of bioaerosol monitoring systems. Further research is needed to refine detection methods for A. alternata and other airborne fungal spores.

Accurate identification and quantification of pollens (e.g., pollen of a flower, airborne pollens) is essential to understand plant pollination and reproductive biology, pollen aerobiology, and plant–insect interactions. Currently, a couple of methods are available for pollen counting, such as manual counting, flow cytometry-based and image software-based counting. However, due to inconsistent results and experimental repeatability, a more accurate, consistent, and high-throughput quantification approach is required. This study evaluated and compared the performance between a proposed Swin-transformer-YOLOv5 (S-T-YOLOv5) and common YOLO models in pollen detection and quantification. The present study demonstrated that the S-T-YOLOv5 outperformed other YOLO models, including YOLOv3, YOLOv4, YOLOR, and YOLOv5 for alfalfa (Medicago sativa L.) pollen detection and quantification, with excellent precision (99.6%), recall (99.4%), F₁-score (0.995), mAP50 (99.4%), and mAP50-95 (76.2%) values. The mAP50-95 (mAP at an IoU of 0.5–0.95) of S-T-YOLOv5 was 9.9, 58.7, 25.3 and 8.2% higher than those of YOLOv3, YOLOv4, YOLOR, and YOLOv5, respectively. Additionally, the S-T-YOLOv5 showed a good transferability in quantifying pollen with varied sizes and shapes in different plant species, including annual fleabane, camelina, Canadian goldenrod, Indian lettuce, mustard, and oilseed rape. In summary, our results showed that the S-T-YOLOv5 is an accurate, robust, and widely adaptable pollen quantification approach, with minimizing errors and labor expense. We would like to highlight the potential application of S-T-YOLOv5 in quantifying samples of airborne pollens from a known pollen source or insect-dispersed pollens (e.g., alfalfa) in supporting the environmental risk assessment of genetically engineered (GE) plants.