Aerobiologia最新文献

Airborne pollen exposure is a major trigger of respiratory allergy, but long-term aerobiological series from the Southern Hemisphere remain scarce. We analyzed changes in the intensity, time and meteorological variables of major allergenic pollen types in Talca, a representative city of central Chile, over nearly two decades. Daily pollen counts from Hirst-type volumetric traps were obtained for three seasons (2007/2008, 2013/2014 and 2024/2025), and the annual pollen integral (APIn) and main pollen season (MPS) metrics were calculated for nine relevant taxa and for total pollen. The APIn increased by more than 240% between the first and last periods, with particularly marked rises for Olea, Cupressaceae, Poaceae, Corylus and several herbaceous plants. For many taxa, the MPS started earlier and/or ended later in 2024/2025, lengthening clinically relevant exposure windows, whereas Platanus and Populus maintained short but intense spring peaks. Cupressaceae showed an extended MPS of about six months, and Olea and Corylus exhibited sharp increases in seasonal totals consistent with recent expansion of nearby plantations. Temperature emerged as the main, though taxon-specific, driver of day-to-day variability, with Poaceae positively associated with temperature and solar radiation and negatively with relative humidity, while some arboreal taxa showed negative correlations coefficients with temperature. Our results indicate an intensification and extension of pollen seasons in the city of Talca. General implications for clinical and public‑health are discussed.

Indoor air is an important yet understudied reservoir of antibiotic-resistant bacteria (ARB), posing potential risks as people spend 90% of their time indoors. Bioaerosols containing multidrug-resistant organisms contribute to respiratory issue, but environmental sources such as air conditioner (AC) dust remain poorly characterized. This study examined the presence of bacteria (ESKAPEE) pathogens and antibiotic resistance genes (ARGs) in AC dust, indoor air and sputum samples from occupants of such indoor spaces within seven faculties at Redeemer’s University, Nigeria. A total of 105 samples were analysed using standard microbiological identification, antibiotic susceptibility testing and PCR screening for ARGs and resistance-related genes (intl1, blaTEM, gyrA, tetA, tetG, mphA). Overall, 59% of isolates were ESKAPEE pathogens, dominated by Staphylococcus aureus (51.1%) and Enterococcus faecium (33.3%). Multidrug resistance was observed in 83.3% (150/180) of ESKAPEE isolates, while tetracycline and ampicillin are the most resisted antibiotics. Three ARGs—intl1, tetA and gyrA—were detected in both dust and sputum isolates. The Multiple Antibiotic Resistance Index (MARI) exceeded 70%, indicating high-risk contamination, although non-carcinogenic risk assessment suggested low immediate health risk. The findings highlight AC filters as valuable surveillance points for tracking indoor AMR dissemination and monitoring multidrug-resistant pathogens in indoor environments.

This study aimed to predict daily concentrations of Alternaria and Cladosporium spores in Tétouan (2009–2017) and revealed their near-continuous presence with clear seasonal patterns. Monthly spore integrals (MSIn) were highest from spring to autumn. Alternaria reached its highest values mainly in May–June, with a maximum in June 2010 (5,652 spores*day/m³). Cladosporium showed its highest MSIn values mostly in October, reaching its maximum in 2014 (109,218 spores*day/m³). Since both taxa exhibited two seasonal increases each year, we delineated pre-maximum 1 from the season onset to the first maximum value, and pre-maximum 2 from the subsequent rise to the later seasonal maximum. Pre-maximum 1 showed higher mean concentrations for Alternaria, whereas Cladosporium was higher in pre-maximum 2. During pre-maximum 1, maximum (T_max), mean and minimum temperatures showed significant positive correlations with daily concentrations of both spores. In Pre-maximum 2, temperature exhibited a significant negative correlation for Cladosporium. Correlations with other meteorological parameters were also significant in some cases. For Alternaria, the pre-maximum 1 regression model was the most accurate, explaining 47% of the variability, with T_max as the main predictor and validation in 2015 was satisfactory. For Cladosporium, the best model explained 33.66% of the variability and likewise included T_max as a key predictor. When validated with pre-maximum 2 data from 2016, no significant differences were found between predicted and observed values. Overall, the findings highlight the strong influence of climatic conditions on fungal spore dynamics and provide valuable insights into the ecology of airborne fungi and their potential public health implications.

Exposure to airborne fungi has been linked with infections and the exacerbation of existing chronic conditions. Specific factors, such as seasonal variations and weather, can significantly influence fungal concentration. The environmental conditions in Las Vegas, Nevada play, a role in the distribution and concentration of airborne fungal spores. The objective of this study was to provide a comprehensive assessment of the estimated total fungal DNA concentration of airborne fungi in Las Vegas using polymerase chain reaction (PCR) across different seasons, weather patterns, and meteorologic factors. Environmental air samples collected for one year from 13 sites across Las Vegas were analyzed with a universal fungal PCR assay. Standards of known concentration were used to determine DNA copies in the samples. The estimated total fungal DNA concentration ranged from 346 to 4967 copies/m³. The mean estimated total fungal DNA concentration was 2276 copies/m³. There was a significant difference in the mean estimated total fungal DNA concentration between seasons (p = 0.026). There were no significant correlations between estimated total fungal DNA concentration and meteorologic factors. This study utilized a molecular detection method to measure outdoor fungal DNA concentrations. The methodology developed in this study can enhance indoor and outdoor air quality surveillance for public health assessment by providing rapid and quantitative results.

Grass pollen is the major outdoor allergen source, inducing allergic rhinitis in susceptible people. In Australia, the considerable prevalence of allergic rhinitis (23.8%) and asthma (11%) is creating a major health and economic burden. Subtropical grass species exhibit distinct ecological and phylogenetic differences compared with temperate grasses, including variations in pollen allergen composition and immune response. Traditional light microscopy, however, cannot differentiate between airborne grass pollen of various subfamilies. This study hypothesizes that automated holography and fluorometry sensing can discern grass pollen beyond family level (Poaceae). This project applied automatic sensing to five aerosolized dried grass pollen samples from Panicoideae; Paspalum notatum (Bahia grass) and Sorghum halepense (Johnson grass), Chloridoideae; Cynodon dactylon (Bermuda grass), and Pooideae; Lolium perenne (Ryegrass) and Phleum pratense (Timothy grass). Datasets were examined for differences in distributions of holography-derived particle features and emitted fluorescence spectra. In three repeated measurement campaigns of the same dry L. perenne pollen sample, distributions of particle features, and relative fluorescence intensity values suggested that reliability and reproducibility of automatic sensors remain a challenge. Data from five grass pollen types, even within the same subfamily, showed distinct morphological and fluorescence profiles, particularly at excitation 280 nm with 357 nm emission. The automated monitoring was also capable of distinguishing dried and freshly collected local P. notatum pollen. To translate these new insights for improved respiratory disease management, further research with broader data collection and validation with key locally relevant pollen taxa will be required for more precise real-time monitoring of grass pollen exposure.

The instruments used for routine pollen monitoring are gradually changing from traditional impactors with manual data processing to automated pollen monitors using deterministic and/or machine-learning algorithms for data analysis. This manuscript compares pollen number concentration of Alnus sp., Betula sp., Corylus sp., and Poaceae measured by Hirst-type bioaerosol samplers and the SwisensPoleno automated bioaerosol monitor in Switzerland and Norway. Due to physical particle losses and the classification rate of the algorithms being well below unity, scaling factors had to be applied to the measurements of the SwisensPoleno to match those of the Hirst impactor. These scaling factors depended on the geographic location, i.e. differed significantly between Switzerland and Norway. The importance of adjusting the scaling factors according to the location of the monitoring network and the need for reporting the numerical values of these scaling factors in future scientific publications is emphasized.

Older buildings often face challenges related to physical deterioration and material decay, which can lead to fungal contamination and the development of sick building syndrome (SBS). In Malaysia, there have been limited studies on the occurrence of fungal identification in indoor air, particularly in old buildings. This study focused on determining the fungal diversity and total fungal load (expressed in colony-forming units, CFU/m³) in selected old buildings in Peninsular Malaysia. Samples were collected from indoor air, building materials (painted walls and ceilings) and swabs at 18 sites within two selected old buildings (A and B) known to have fungal issues. A total of 182 indoor air, 76 scraped and 75 swabbed samples were collected from June to November 2021. Molecular identification was performed by extracting DNA from fungal isolates and amplifying the internal transcribed spacer (ITS) region using polymerase chain reaction (PCR). The fungal load, measured as ranging from 215 to 5235 CFU/m³, with five sites exceeding the Industry Code of Practice on Indoor Air Quality (ICOP IAQ) guidelines: two in building A and three in building B. Higher loads of fungi were identified in the indoor air samples. The most frequently identified genera in both buildings were Aspergillus spp., Penicillium spp. and Cladosporium spp. Dominant species were A. niger, P. citrinum, A. tamarii, C. haloterans and C. cladosporoides. These findings demonstrate the considerable diversity and extent of fungal contamination present in older buildings, underscoring the potential health risks associated with exposure to indoor fungi.

Prediction of climate change and airborne pollen concentrations is essential for understanding allergenic risks from aeroallergens. Temperature and rainfall influence the main pollen season (MPS) both before and during the season. Temperature influences the MPS start (MPSS), while rainfall affects the seasonal pollen integral (SPIn). Improving understanding of these relationships enables accurate pollen forecasts for allergy prevention, public health preparedness, and environmental health policies. The study investigates the impact of rainfall before pollen release using the Dry Days Since the Last Rain (DDSLR) method and defines the role of temperature, chilling, and forcing requirements in predicting the MPSS for Quercus and Cupressaceae in Córdoba (Spain) and Tulsa (Oklahoma, USA). Three approaches combining chilling and forcing heat thresholds were applied. All used Growing Degree Days (GDD°) to calculate forcing but differed in chilling calculation: chilling units based on defined thresholds, accumulative chilling temperature, and omitted chilling calculations altogether. The results show that Quercus MPSS occurred in mid-to-late March at both sites. Cupressaceae exhibited greater regional variation. DDSLR effectively predicted the main pollen season end (MPSE) in Córdoba and the SPIn of Cupressaceae in Tulsa (Oklahoma, USA), indicating regional differences in rainfall influence. The chilling threshold was 0 °C in both sites, while forcing thresholds varied by region and species. Methods excluding chilling showed better MPSS prediction. These findings highlight the value of rainfall and temperature in pollen forecasts. Improved models support the development of targeted allergy forecasts and risk management and public health planning in a changing climate.

Passenger air transport is a significant vector for the global dissemination of pathogenic microorganisms. Therefore, evaluating indoor air quality (IAQ) in aircraft cabins is critical for ensuring a safe environment for passengers and crew. This study retrospectively assessed IAQ in commercial aircraft operating at Maceió International Airport, focusing on the microbiological characterization of cabin air through quantifying and identifying airborne bacteria and fungi. Air samples were collected while aircraft were grounded, specifically from the cockpit and the central cabin aisle. Domestic and international flights were included, and analyses adhered to the Brazilian standard NBR 17037. Bioaerosols were sampled using a portable bioaerosol sampler. Fungi were identified via macroscopic and microscopic traits, while bacteria were identified using genetic markers. A diverse fungal population was detected, predominantly Aspergillus and Penicillium spp. Mycotoxin screening yielded positive results in three fungal isolates. Potentially pathogenic bacteria were identified, including Acinetobacter spp., Stutzerimonas stutzeri, Pseudomonas oryzihabitans, and Pantoea dispersa. Results suggest that indoor sources predominantly influence bacterial concentrations, whereas outdoor air significantly contributes to airborne fungal presence. Temperature and relative humidity had a greater effect on fungal bioaerosols than bacterial ones, although further investigation is needed to clarify these relationships. This is the first Brazilian study to assess IAQ in commercial aviation, highlighting the need to continuously monitor microbial contamination in aircraft cabins to mitigate potential health risks.

Indoor air quality is significantly compromised by the biodeterioration of building materials, such as oil-based paints, which facilitates the release of fungal bioaerosols posing health risks to occupants. This study examines the role of Cladosporium sphaerospermum as a key airborne contaminant in paint degradation and evaluates metal nanoparticles as antimicrobial additives to mitigate associated bioaerosol emissions. Cladosporium sphaerospermum was isolated from deteriorated oil-based paint samples and identified via phenotypic and genotypic analyses. Microscopic evaluations, including stereomicroscopy, light microscopy, and scanning electron microscopy (SEM), confirmed its primary involvement in paint degradation through surface invasion and colonization. The fungus displayed robust lipase and urease activities, with specific activities of 43.2 and 824 units per milligram protein, respectively, indicating enzymatic breakdown of paint components. Indoor air quality assessments identified C. sphaerospermum as the predominant bioaerosol in environments with degraded paint, accounting for 69.8% of the total fungal count (128 CFU/m³), followed by Aspergillus niger at 11.7%. Incorporation of silver nanoparticles (Ag-NPs; 3–60 nm particle size) and zinc oxide nanoparticles (ZnO-NPs; 18.2 nm particle size) into oil-based paints markedly improved resistance to fungal deterioration in vivo, relative to controls. These results underscore Ag-NPs and ZnO-NPs as effective additives for enhancing paint longevity and reducing fungal bioaerosol contamination in indoor settings, particularly from C. sphaerospermum and related dematiaceous fungi.