Meteorological factors had more impact on airborne bacterial communities than air pollutants

Airborne fungal communities are more susceptible to anthropogenic activities than bacteria

Airborne microorganisms (AM) have significant environmental and health implications. Extensive studies have been conducted to investigate the factors influencing the composition and diversity of AM. However, the knowledge of AM with anthropogenic activities has not reach a consensus. In this study, we took advantage of the dramatic decline of outdoor anthropogenic activities resulting from COVID-19 lockdown to reveal their associations. We collected airborne particulate matter before and during the lockdown period in two cities. The results showed that it was fungal diversity and communities but not bacteria obviously different between pre-lockdown and lockdown samples, suggesting that airborne fungi were more susceptible to anthropogenic activities than bacteria. However, after the implementation of lockdown, the co-occurrence networks of both bacterial and fungal community became more complex, which might be due to the variation of microbial sources. Furthermore, Mantel test and correlation analysis showed that air pollutants also partly contributed to microbial alterations. Airborne fungal community was more affected by air pollutants than bacterial community. Notably, some human pathogens like Nigrospora and Arthrinium were negatively correlated with air pollutants. Overall, our study highlighted the more impacts of anthropogenic activities on airborne fungal community than bacterial community and advanced the understanding of associations between anthropogenic activities and AM.

A super sandstorm altered the abundance and composition of airborne bacteria in Beijing

Sandstorm, which injects generous newly emerging microbes into the atmosphere covering cities, adversely affects the air quality in built environments. However, few studies have examined the change of airborne bacteria during severe sandstorm events. In this work, we analyzed the airborne bacteria during one of the strongest sandstorms in East Asia on March 15th, 2021, which affected large areas of China and Mongolia. The characteristics of the sandstorm were compared with those of the subsequent clean and haze days. The composition of the bacterial community of air samples was investigated using quantitative polymerase chain reaction (qPCR) and high-throughput sequencing technology. During the sandstorm, the particulate matter (PM) concentration and bacterial richness were extremely high (PM2.5: 207 µg/m3; PM10: 1630 µg/m3; 5700 amplicon sequence variants/m3). In addition, the sandstorm brought 10 pathogenic bacterial genera to the atmosphere, posing a grave hazard to human health. As the sandstorm subsided, small bioaerosols (0.65-1.1 µm) with a similar bacterial community remained suspended in the atmosphere, bringing possible long-lasting health risks.

Influence of rainfall on size-resolved bioaerosols around a livestock farm

Bioaerosols, capable of transporting microorganisms, can impact human health and agriculture by spreading to nearby communities. Their transmissions are influenced by various factors, including weather conditions and human activities. However, the scarcity of detailed, taxon-specific data on bioaerosols' sizes limits our ability to assess risks associated with bioaerosols' generation and spread. This study examined the composition and size of bioaerosols at a livestock farm and a non-agricultural site, focusing on how bioaerosols evolve at different locations and meteorological conditions. The location had an impact on bioaerosol samples. We conducted 16S rRNA gene amplicon sequencing to identify bacteria genera in bioaerosols. We observed consistently higher concentrations of bioaerosols across all sizes at the livestock farm, and samples from the livestock farm exhibited greater bacterial diversity, where we identified Staphylococcus and Corynebacterium as the most abundant species. The effects of rainfall on bioaerosol diversity are complex, suggesting a dynamic interplay between bioaerosol removal and generation. After rainfall, the bioaerosol fraction of particles larger than 2.5 μm increased by nearly 400% compared to post-rain levels. Conversely, for bioaerosols below 1 μm size, the fraction decreased by 50%. Furthermore, the sequencing results showed that precipitation differentially responded to the abundance of various genera in the bioaerosols. Moreover, even for the same genus, the response to precipitation varied depending on the size of the bioaerosols. Our research reveals how size, location, and environmental conditions influence bioaerosol dynamics, enhancing our understanding of bioaerosol formation and transmission.

Characteristics of bioaerosol emissions from a municipal wastewater treatment plant: Health risk assessment and microbial composition

Bioaerosols released from municipal wastewater treatment plants (MWWTPs) contain pathogenic microorganisms, if dispersed into the atmosphere, which pose potential health risks to humans. In this study, the concentrations and size distribution of bioaerosol, factors on the bioaerosol emission, exposure risk, and microbial composition in different treatment units of a MWWTP were investigated. The results showed that bioaerosol was released to different degrees in each treatment unit, with the concentrations of bioaerosol varied widely, ranging from 978 to 3710 CFU/m3. FG and PST were primary bioaerosol emission sources in MWWTP. COD concentration, wind speed (WS) and relative humidity (RH) significantly influenced bioaerosol concentrations. The proportion of inhalable particles (< 4.7 μm) ranged from 51.35 % to 83.33 %, and bioaerosol emitted from WWTP caused a non-carcinogenic risk to children by the exposure risk assessment (HI > 1), which need to be paid more attention. Bacterial, fungal and actinomycete aerosols were detected in each treatment unit of MWWTP. Among these bioaerosols, bacterial aerosol was dominant. Importantly, several pathogenic bacteria including Sphingobium, Brevundimonas, Romboutsia, Arcobacter, Acinetobacter, and Mycobacterium were identified within the airborne bacteria population, most of which originated from wastewater or sludge, particularly in the ambient air of AeT. Pathogenic bacteria from MWWTP should be studied further to determine their long-term behavior and possible health risks.

The abundance and pathogenicity of microbes in automobile air conditioning filters across the typical cities of China and Europe

Bioaerosols are widely distributed in urban air and can be transmitted across the atmosphere, biosphere, and anthroposphere, resulting in infectious diseases. Automobile air conditioning (AAC) filters can trap airborne microbes. In this study, AAC filters were used to investigate the abundance and pathogenicity of airborne microorganisms in typical Chinese and European cities. Culturable bacteria and fungi concentrations were determined using microbial culturing. High-throughput sequencing was employed to analyze microbial community structures. The levels of culturable bioaerosols in Chinese and European cities exhibited disparities (Analysis of Variance, P < 0.01). The most dominant pathogenic bacteria and fungi were similar in Chinese (Mycobacterium: 18.2-18.9 %; Cladosporium: 23.0-30.2 %) and European cities (Mycobacterium: 15.4-37.7 %; Cladosporium: 18.1-29.3 %). Bartonella, Bordetella, Alternaria, and Aspergillus were also widely identified. BugBase analysis showed that microbiomes in China exhibited higher abundances of mobile genetic elements (MGEs) and biofilm formation capacity than those in Europe, indicating higher health risks. Through co-occurrence network analysis, heavy metals such as zinc were found to correlate with microorganism abundance; most bacteria were inversely associated, while fungi exhibited greater tolerance, indicating that heavy metals affect the growth and reproduction of bioaerosol microorganisms. This study elucidates the influence of social and environmental factors on shaping microbial community structures, offering practical insights for preventing and controlling regional bioaerosol pollution.

Seasonal distribution of human-to-human pathogens in airborne PM2.5 and their potential high-risk ARGs

Airborne microorganisms, an emerging global health threat, have attracted extensive studies. However, few attentions have been paid to the seasonal distribution of airborne pathogens, in particular their associations with antibiotic resistance genes (ARGs). To this end, two-week daily PM2.5 samples were consecutively collected from Nanchang in four seasons, and the human-to-human pathogens were screened based on high-throughput sequencing. The results showed that there were 20 pathogenic taxa in PM2.5 in Nanchang, and the highest relative abundance of pathogens was observed in winter (5.84%), followed by summer (3.51%), autumn (2.66%), and spring (1.80%). Although more than half of pathogenic taxa were shared by the four seasons, the analysis of similarities showed that pathogenic community was shaped by season (r = 0.16, p < 0.01). Co-occurrence network analysis disclosed significant interactions among pathogens in each season. Moreover, some dominant pathogens such as Plesiomonas shigelloides, Bacteroides fragilis, and Escherichia-Shigella were hub pathogens. In addition, PICRUSt2 predicted that there were 35 high-risk ARG subtypes in PM2.5, and the pathogens had strongly positive correlations with these ARGs. Even some pathogens like Plesiomonas shigelloides, Bacteroides fragilis, Aeromonas, Citrobacter, may be multi-drug resistant pathogens, including beta-lactam, aminoglycosides, chloramphenicol and multi-drug resistances, etc. Both air pollutants and meteorological conditions contributed to the seasonal variation of airborne pathogenic bacteria (r = 0.15, p < 0.01), especially CO, O3, PM2.5, temperature and relative humidity. This study furthers our understanding of airborne pathogens and highlights their associations with ARGs.

Comprehensive analysis of metal(loid)s and associated metal(loid) resistance genes in atmospheric particulate matter

Despite global concerns about metal(loid)s in atmospheric particulate matter (PM), the presence of metal(loid) resistance genes (MRGs) in PM remains unknown. Therefore, we conducted a comprehensive investigation of the metal(loid)s and associated MRGs in PMs in two seasons (summer and winter) in Xiamen, China. According to the geoaccumulation index (Igeo), most metal(loid)s, except for V and Mn, exhibited enrichment in PM, suggesting potential anthropogenic sources. By employing Positive Matrix Factorization (PMF) model, utilizing a dataset encompassing both total and bioaccessible metal(loid)s, along with backward trajectory simulations, traffic emissions were determined to be the primary potential contributor of metal(loid)s in summer, whereas coal combustion was observed to have a dominant contribution in winter. The major contributor to the carcinogenic risk of metal(loid)s in both summer and winter was predominantly attributed to coal combustion, which serves as the main source of bioaccessible Cr. Bacterial communities within PMs showed lower diversity and network complexity in summer than in winter, with Pseudomonadales being the dominant order. Abundant MRGs, including the As(III) S-adenosylmethionine methyltransferase gene (arsM), Cu(I)-translocating P-type ATPase gene (copA), Zn(II)/Cd(II)/Pb(II)-translocating P-type ATPase gene (zntA), and Zn(II)-translocating P-type ATPase gene (ziaA), were detected within the PMs. Seasonal variations were observed for the metal(loid) concentration, bacterial community structure, and MRG abundance. The bacterial community composition and MRG abundance within PMs were primarily influenced by temperature, rather than metal(loid)s. This research offers novel perspectives on the occurrence of metal(loid)s and MRGs in PMs, thereby contributing to the control of air pollution.

Ambient particle composition and toxicity in 31 major cities in China

Current assessment of air quality or control effectiveness is solely based on particulate matter (PM) mass levels, without considering their toxicity differences in terms of health benefits. Here, we collected a total of 465 automobile air conditioning filters from 31 major Chinese cities to study the composition and toxicity of PM at a national scale. Dithiothreitol assay showed that normalized PM toxicity (NIOG) in different Chinese cities varied greatly from the highest 4.99 × 10-3 for Changsha to the lowest 7.72 × 10-4 for Yinchuan. NIOG values were observed to have significant correlations with annual PM10 concentration (r = -0.416, p = 0.020) and some PM components (total fungi, SO4 2- and calcium element). The concentrations of different elements and water-soluble ions in PM also varied by several orders of magnitude for 31 cities in China. Endotoxin concentrations in PM analyzed using limulus amebocyte lysate assay ranged from 2.88 EU/mg PM (Hangzhou) to 62.82 EU/mg PM (Shijiazhuang) among 31 Chinese cities. Besides, real-time qPCR revealed 10∼100-fold differences in total bacterial and fungal levels among 31 Chinese cities. The concentrations of chemical (water soluble ions and trace elements) and biological (fungi, bacteria and endotoxin) components in PM were found to be significantly correlated with some meteorological factors and gaseous pollutants such as SO2. Our results have demonstrated that PM toxicity from 31 major cities varied greatly up to 6.5 times difference; and components such as fungi and SO4 2- in PM could play important roles in the observed PM toxicity. The city-specific air pollution control strategy that integrates toxicity factors should be enacted in order to maximize health and economic co-benefits. This work also provides a comprehensive view on the overall PM pollution situation in China.

Implications of PM2.5 chemical composition in modulating microbial community dynamics during spring in Seoul

Particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) harbors a diverse microbial community. To assess the ecological dynamics and potential health risks associated with airborne microorganisms, it is crucial to understand the factors influencing microbial communities within PM2.5. This study investigated the influence of abiotic parameters, including air pollutants, PM2.5 chemical composition (water-soluble ions and organics), and meteorological variables, on microbial communities in PM2.5 samples collected in Seoul during the spring season. Results revealed a significant correlation between air pollutants and water-soluble ions of PM2.5 with microbial α-diversity indices. Additionally, air pollutants exerted a dominant effect on the microbial community structure, with stronger correlations observed for fungi than bacteria, whereas meteorological variables including temperature, pressure, wind speed, and humidity exerted a limited influence on fungal α-diversity. Furthermore, the results revealed specific water-soluble ions, such as SO42-, NO3-, and NH4+, as important factors influencing fungal α-diversity, whereas K+ negatively correlated with both microbial α-diversity. Moreover, PM2.5 microbial diversity was affected by organic compounds within PM2.5, with fatty acids exhibited a positive correlation with fungal diversity, while dicarboxylic acids exhibited a negative correlation with it. Furthermore, network analysis revealed direct links between air pollutants and dominant bacterial and fungal genera. The air pollutants exhibited a strong correlation with bacterial genera, such as Arthrospira and Clostridium, and fungal genera, including Aureobasidium and Cladosporium. These results will contribute to our understanding of the ecological dynamics of airborne microorganisms and provide insights into the potential risks associated with PM2.5 exposure.

Study on the concentration, composition, and recovery rate of bacterial bioaerosols after rainfall in Ho Chi Minh City

Aerosolized microorganisms have become an important factor in assessing air quality. To determine the characteristics of bacterial bioaerosols in air and rainwater, as well as calculate the recovery rate of bacteria after rains in Ho Chi Minh City, our study was performed using the SKC Biostage sampler for airborne bacteria and Plate Count Agar (PCA) medium for bacterial concentration. Subsequently, the study determined the bacterial community composition at the phylum and order levels using the 16S rRNA (16S metabarcoding) method. Before the rain, bacterial concentrations in the air ranged from 263.39 ± 21.00 to 277.39 ± 78.99 CFU/m3, and in rainwater 264.89 ± 51.17 to 285.72 ± 28.00 CFU/m3. Following rains, the bacterial concentrations decreased to their lowest levels within the first 1-2 h and gradually increased thereafter, reaching their peak after 9 h for heavy rain and after 12 h for light and moderate rains. The bacterial bioaerosols recovery rate was determined to be 100% for light and moderate rains and 94.6% for heavy rain. The change in bacterial concentration after rainfall showed a positive correlation with temperature (r = 0.85) and CO2 concentration (r = 0.70) and a negative correlation with relative humidity (r =  - 0.79). Bacterial composition analysis revealed that the Actinobacteria, Firmicutes, and Proteobacteria phyla were dominant and characteristic of the humid tropical climate in Vietnam. Notably, Firmicutes were the most prevalent phylum both before and after rains. The increased prevalence of certain bacterial orders, particularly Staphylococcus, could contribute to the spread of pathogens, particularly foodborne pathogens. In addition to rain, relative humidity contributed to reducing bacterial bioaerosols concentration and their recovery rate after the rain.

Bioaerosols in the atmosphere: A comprehensive review on detection methods, concentration and influencing factors

In the past few decades, especially since the outbreak of the coronavirus disease (COVID-19), the effects of atmospheric bioaerosols on human health, the environment, and climate have received great attention. To evaluate the impacts of bioaerosols quantitatively, it is crucial to determine the types of bioaerosols in the atmosphere and their spatial-temporal distribution. We provide a concise summary of the online and offline observation strategies employed by the global research community to sample and analyze atmospheric bioaerosols. In addition, the quantitative distribution of bioaerosols is described by considering the atmospheric bioaerosols concentrations at various time scales (daily and seasonal changes, for example), under various weather, and different underlying surfaces. Finally, a comprehensive summary of the reasons for the spatiotemporal distribution of bioaerosols is discussed, including differences in emission sources, the impact process of meteorological factors and environmental factors. This review of information on the latest research progress contributes to the emergence of further observation strategies that determine the quantitative dynamics of public health and ecological effects of bioaerosols.

Grid computing method for atmospheric environmental capacity coupled with ventilation coefficient using CALPUFF simulation and GIS spatial analysis technology

Atmospheric environmental issues have evolved from point source pollution to regional pollution, leading to controlling specific air pollutant emissions. A-value method has been found suitable for estimating large-scale atmospheric environmental capacity rather than small-scale, resulting in the inaccuracy of developing air pollution control strategy. This study proposed a grid computing method based on the CALPUFF modelling system and GIS spatial analysis tool. The meteorological data from the MM5 model were used to simulate the spatial distribution of air pollutants. The meteorological flow field data was used to simulate the ventilation coefficient. The A value was revised with the simulated to achieve accurate results of atmospheric environment capacity. The credibility was verified by applying this method to Fengtai District, Beijing, China. The research area was divided into small partitions via the ArcGIS spatial analysis tool. The simulation results agreed well with the observation data from actual monitoring stations, even for the PM10 concentration with the most significant error (MRE: 7.05%-13.28%, RMSE: 11.62-17.89, R2: 0.84-0.90). The GIS spatial analysis tools were applied to match the underlying surface types and overcome the restrictions of administrative boundary management. The study proposed four schemes to achieve differentiated air pollutant emission reduction and develop suitable control strategies. Furthermore, this method can be applied on different scales of natural geographic boundaries and realize the precise spatial management of atmospheric environmental capacity.

Dynamic human exposure to airborne bacteria-associated antibiotic resistomes revealed by longitudinal personal monitoring data

Airborne antibiotic-resistant bacteria (ARB) can critically impact human health. We performed resistome profiling of 283 personal airborne exposure samples from 15 participants spanning 890 days and 66 locations. We found a greater diversity and abundance of airborne bacteria community and antibiotic resistomes in spring than in winter, and temperature contributed largely to the difference. A total of 1123 bacterial genera were detected, with 16 genera dominating. Of which, 7/16 were annotated as major antibiotic resistance gene (ARG) hosts. The participants were exposed to a highly dynamic collection of ARGs, including 322 subtypes conferring resistance to 18 antibiotic classes dominated by multidrug, macrolide-lincosamide-streptogramin, β-lactam, and fosfomycin. Unlike the overall community-level bacteria exposure, an extremely high abundance of specific ARG subtypes, including lunA and qacG, were found in some samples. Staphylococcus was the predominant genus in the bacterial community, serving as a primary bacterial host for the ARGs. The annotation of ARG-carrying contigs indicated that humans and companion animals were major reservoirs for ARG-carrying Staphylococcus. This study contextualized airborne antibiotic resistomes in the precision medicine framework through longitudinal personal monitoring, which can have broad implications for human health.

Environmental determinants and demographic influences on global urban microbiomes, antimicrobial resistance and pathogenicity

Urban microbiome plays crucial roles in human health and are related to various diseases. The MetaSUB Consortium has conducted the most comprehensive global survey of urban microbiomes to date, profiling microbial taxa/functional genes across 60 cities worldwide. However, the influence of environmental/demographic factors on urban microbiome remains to be elucidated. We collected 35 environmental and demographic characteristics to examine their effects on global urban microbiome diversity/composition by PERMANOVA and regression models. PM10 concentration was the primary determinant factor positively associated with microbial α-diversity (observed species: p = 0.004, β = 1.66, R2 = 0.46; Fisher's alpha: p = 0.005, β = 0.68, R2 = 0.43), whereas GDP per capita was negatively associated (observed species: p = 0.046, β = -0.70, R2 = 0.10; Fisher's alpha: p = 0.004, β = -0.34, R2 = 0.22). The β-diversity of urban microbiome was shaped by seven environmental characteristics, including Köppen climate type, vegetation type, greenness fraction, soil type, PM2.5 concentration, annual average precipitation and temperature (PERMANOVA, p < 0.001, R2 = 0.01-0.06), cumulatively accounted for 20.3% of the microbial community variance. Canonical correspondence analysis (CCA) identified microbial species most strongly associated with environmental characteristic variation. Cities in East Asia with higher precipitation showed an increased abundance of Corynebacterium metruchotii, and cities in America with a higher greenness fraction exhibited a higher abundance of Corynebacterium casei. The prevalence of antimicrobial resistance (AMR) genes were negatively associated with GDP per capita and positively associated with solar radiation (p < 0.005). Total pathogens prevalence was positively associated with urban population and negatively associated with average temperature in June (p < 0.05). Our study presents the first comprehensive analysis of the influence of environmental/demographic characteristics on global urban microbiome. Our findings indicate that managing air quality and urban greenness is essential for regulating urban microbial diversity and composition. Meanwhile, socio-economic considerations, particularly reducing antibiotic usage in regions with lower GDP, are paramount in curbing the spread of antimicrobial resistance in urban environments.

Machine Learning in Environmental Research: Common Pitfalls and Best Practices

Machine learning (ML) is increasingly used in environmental research to process large data sets and decipher complex relationships between system variables. However, due to the lack of familiarity and methodological rigor, inadequate ML studies may lead to spurious conclusions. In this study, we synthesized literature analysis with our own experience and provided a tutorial-like compilation of common pitfalls along with best practice guidelines for environmental ML research. We identified more than 30 key items and provided evidence-based data analysis based on 148 highly cited research articles to exhibit the misconceptions of terminologies, proper sample size and feature size, data enrichment and feature selection, randomness assessment, data leakage management, data splitting, method selection and comparison, model optimization and evaluation, and model explainability and causality. By analyzing good examples on supervised learning and reference modeling paradigms, we hope to help researchers adopt more rigorous data preprocessing and model development standards for more accurate, robust, and practicable model uses in environmental research and applications.

How dominant the load of bioaerosols in PM2.5 and PM10: a comprehensive study in the IGP during winter

The winter period is most ideal for studying near-surface aerosols in the Indo-Gangetic plains (IGP) of India, since this period is inundated with significantly higher concentrations of aerosols across the unique geographical domain because of shallow atmospheric boundary layer. This study focuses on analysing the concentration of the biotic component of aerosols (bioaerosols) in a central location of the IGP and estimating their dominance in ambient particulate matter (PM) from 2021 to 2023. Observations showed that bioaerosol concentrations also increased significantly with the increasing concentrations of PM2.5 and PM10, suggesting that bioaerosols are a dominant component of the total aerosol load in the atmosphere. The total microbe's concentration (collectively fungi and bacteria) was found to be 94 to 226 cfu m-3 in PM2.5 and 167 to 375 cfu m-3 in PM10 where bacteria contributed 81.12 and 79.99%, respectively. The contribution of fungal spores in PM2.5 and PM10 remained as 18.88 and 20.01%, respectively, in the total microbes in the respective particulate matter. In the bioaerosols, fungi, namely Aspergillus, Cladosporium, and Penicillium, were dominant, and bacteria, namely E. coli, Mammaliicoccus and Enterobacter, were prevalent in both the PM size regimes. The most prominent microbial presence was observed when the temperature ranged between 16 and 20°C and relative humidity between 80 and 85%. The outcomes of the present study will be useful for further research on the health effect of the bioaerosols in the IGP.

Distinct responses of airborne abundant and rare microbial communities to atmospheric changes associated with Chinese New Year

Airborne microorganisms, including pathogens, would change with surrounding environments and become issues of global concern due to their threats to human health. Microbial communities typically contain a few abundant but many rare species. However, how the airborne abundant and rare microbial communities respond to environmental changes is still unclear, especially at hour scale. Here, we used a sequencing approach based on bacterial 16S rRNA genes and fungal ITS2 regions to investigate the high time-resolved dynamics of airborne bacteria and fungi and to explore the responses of abundant and rare microbes to the atmospheric changes. Our results showed that air pollutants and microbial communities were significantly affected by human activities related to the Chinese New Year (CNY). Before CNY, significant hour-scale changes in both abundant and rare subcommunities were observed, while only abundant bacterial subcommunity changed with hour time series during CNY. Air pollutants and meteorological parameters explained 61.5%-74.2% variations of abundant community but only 13.3%-21.6% variations of rare communities. These results suggested that abundant species were more sensitive to environmental changes than rare taxa. Stochastic processes predominated in the assembly of abundant communities, but deterministic processes determined the assembly of rare communities. Potential bacterial pathogens during CNY were the highest, suggesting an increased health risk of airborne microbes during CNY. Overall, our findings highlighted the "holiday effect" of CNY on airborne microbes and expanded the current understanding of the ecological mechanisms and health risks of microbes in a changing atmosphere.

Comprehensive insights into advances in ambient bioaerosols sampling, analysis and factors influencing bioaerosols composition

While the study of bioaerosols has a long history, it has garnered heightened interest in the past few years, focusing on both culture-dependent and independent sampling and analysis approaches. Observations have been made regarding the seasonal fluctuations in microbial communities and their connection to particular ambient atmospheric factors. The study of airborne microbial communities is important in public health and atmospheric processes. Nevertheless, the establishment of standardized protocols for evaluating airborne microbial communities and utilizing microbial taxonomy as a means to identify distinct bioaerosols sources and seasonal patterns remains relatively unexplored. This article discusses the challenges and limitations of ambient bioaerosols sampling and analysis, including the lack of standardized methods and the heterogeneity of sources. Future prospects in the field of bioaerosols, including the use of high-throughput sequencing technologies, omics studies, spectroscopy and fluorescence-based monitoring to provide comprehensive incite on metabolic capacity, and activity are also presented. Furthermore, the review highlights the factors that affect bioaerosols composition, including seasonality, atmospheric conditions, and pollution levels. Overall, this review provides a valuable resource for researchers, policymakers, and stakeholders interested in understanding and managing bioaerosols in various environments.

Abundant Cyanobacteria in Autumn Adhering to the Heating, Ventilation, and Air-Conditioning (HVAC) in Shanghai

Cyanobacteria are ever-present, mainly flourishing in aquatic environments and surviving virtually in other habitats. The microbiota of indoor dust on the pre-filter of heating, ventilation, and air-conditioning (HVAC) systems, which reflect indoor microbial contamination and affect human health, has attracted attention. Contemporary studies on cyanobacteria deposited on the pre-filter of HVAC remain scant. By the culture-independent approach of qPCR and high throughput sequencing technologies, our results documented that the cyanobacterial concentrations were highest in autumn, occurred recurrently, and were about 2.60 and 10.57-fold higher than those in winter and summer. We proposed that aquatic and terrestrial cyanobacteria contributed to the pre-filter of HVAC by airborne transportation produced by wave breaks, bubble bursts, and soil surface by wind force, owing to the evidence that cyanobacteria were commonly detected in airborne particulate matters. The cyanobacteria community structure was characterized in Shanghai, where Chroococcidiopsaceae, norank_cyanobacteriales, Nostocaceae, Paraspirulinaceae, and others dominated the dust on the pre-filter of HVAC. Some detected genera, including Nodularia sp., Pseudanabaena sp., and Leptolyngbya sp., potentially produced cyanobacterial toxins, which need further studying to determine their potential threat to human health. The present work shed new insight into cyanobacteria distribution in the specific environment besides aquatic habitats.

Greener residential environment is associated with increased bacterial diversity in outdoor ambient air

In urban areas, exposure to greenspace has been found to be beneficial to human health. The biodiversity hypothesis proposed that exposure to diverse ambient microbes in greener areas may be one pathway leading to health benefits such as improved immune system functioning, reduced systemic inflammation, and ultimately reduced morbidity and mortality. Previous studies observed differences in ambient outdoor bacterial diversity between areas of high and low vegetated land cover but didn't focus on residential environments which are important to human health. This research examined the relationship between vegetated land and tree cover near residence and outdoor ambient air bacterial diversity and composition. We used a filter and pump system to collect ambient bacteria samples outside residences in the Raleigh-Durham-Chapel Hill metropolitan area and identified bacteria by 16S rRNA amplicon sequencing. Geospatial quantification of total vegetated land or tree cover was conducted within 500 m of each residence. Shannon's diversity index and weighted UniFrac distances were calculated to measure α (within-sample) and β (between-sample) diversity, respectively. Linear regression for α-diversity and permutational analysis of variance (PERMANOVA) for β-diversity were used to model relationships between vegetated land and tree cover and bacterial diversity. Data analysis included 73 ambient air samples collected near 69 residences. Analysis of β-diversity demonstrated differences in ambient air microbiome composition between areas of high and low vegetated land (p = 0.03) and tree cover (p = 0.07). These relationships remained consistent among quintiles of vegetated land (p = 0.03) and tree cover (p = 0.008) and continuous measures of vegetated land (p = 0.03) and tree cover (p = 0.03). Increased vegetated land and tree cover were also associated with increased ambient microbiome α-diversity (p = 0.06 and p = 0.03, respectively). To our knowledge, this is the first study to demonstrate associations between vegetated land and tree cover and the ambient air microbiome's diversity and composition in the residential ecosystem.

East Asian monsoon manipulates the richness and taxonomic composition of airborne bacteria over China coastal area

Airborne bacteria may have significant impacts on aerosol properties, public health and ecosystem depending on their taxonomic composition and transport. This study investigated the seasonal and spatial variations of bacterial composition and richness over the east coast of China and the roles of East Asian monsoon played through synchronous sampling and 16S rRNA sequencing analysis of airborne bacteria at Huaniao island of the East China Sea (ECS) and the urban and rural sites of Shanghai. Airborne bacteria showed higher richness over the land sites than Huaniao island with the highest values found in the urban and rural springs associated with the growing plants. For the island, the maximal richness occurred in winter as the result of prevailing terrestrial winds controlled by East Asian winter monsoon. Proteobacteria, Actinobacteria and Cyanobacteria were found to be top three phyla, together accounting for 75 % of total airborne bacteria. Radiation-resistant Deinococcus, Methylobacterium belonging to Rhizobiales (related to vegetation) and Mastigocladopsis_PCC_10914 originating from marine ecosystem were indicator genera for urban, rural and island sites, respectively. The Bray-Curits dissimilarity of taxonomic composition between the island and two land sites was the lowest in winter with the representative genera over island also typically from the soil. Our results reveal that seasonal change of monsoon wind directions evidently affects the richness and taxonomic composition of airborne bacteria in China coastal area. Particularly, prevailing terrestrial winds lead to the dominance of land-derived bacteria over the coastal ECS which may have a potential impact on marine ecosystem.

Antibiotic Resistance Genes in Aerosols: Baseline from Kuwait

Antimicrobial resistance (AMR) is one of the biggest threats to human health worldwide. The World Health Organization (WHO, Geneva, Switzerland) has launched the "One-Health" approach, which encourages assessment of antibiotic-resistant genes (ARGs) within environments shared by human-animals-plants-microbes to constrain and alleviate the development of AMR. Aerosols as a medium to disseminate ARGs, have received minimal attention. In the present study, we investigated the distribution and abundance of ARGs in indoor and outdoor aerosols collected from an urban location in Kuwait and the interior of three hospitals. The high throughput quantitative polymerase chain reaction (HT-qPCR) approach was used for this purpose. The results demonstrate the presence of aminoglycoside, beta-lactam, fluoroquinolone, tetracycline, macrolide-lincosamide-streptogramin B (MLSB), multidrug-resistant (MDR) and vancomycin-resistant genes in the aerosols. The most dominant drug class was beta-lactam and the genes were IMP-2-group (0.85), Per-2 group (0.65), OXA-54 (0.57), QnrS (0.50) and OXA-55 (0.55) in the urban non-clinical settings. The indoor aerosols possessed a richer diversity (Observed, Chao1, Shannon's and Pielou's evenness) of ARGs compared to the outdoors. Seasonal variations (autumn vs. winter) in relative abundances and types of ARGs were also recorded (R² of 0.132 at p < 0.08). The presence of ARGs was found in both the inhalable (2.1 µm, 1.1 µm, 0.7 µm and < 0.3 µm) and respirable (>9.0 µm, 5.8 µm, 4.7 µm and 3.3 µm) size fractions within hospital aerosols. All the ARGs are of pathogenic bacterial origin and are hosted by pathogenic forms. The findings present baseline data and underpin the need for detailed investigations looking at aerosol as a vehicle for ARG dissemination among human and non-human terrestrial biota.

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

Characterized by their high spatiotemporal variability, rainfalls are difficult to predict, especially under climate change. This study proposes a multilayer perceptron (MLP) network optimized by Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), and Teleconnection Pattern Indices - such as North Atlantic Oscillation (NAO), Southern Oscillations (SOI), Western Mediterranean Oscillation (WeMO), and Mediterranean Oscillation (MO) - to model monthly rainfalls at the Sebaou River basin (Northern Algeria). Afterward, we compared the best-optimized MLP to the application of the Extreme Learning Machine optimized by the Bat algorithm (Bat-ELM). Assessment of the various input combinations revealed that the NAO index was the most influential parameter in improving the modeling accuracy. The results indicated that the MLP-FFA model was superior to MLP-GA and MLP-PSO for the testing phase, presenting RMSE values equal to 33.36, 30.50, and 29.92 mm, respectively. The comparison between the best MLP model and Bat-ELM revealed the high performance of Bat-ELM for rainfall modeling at the Sebaou River basin, with RMSE reducing from 29.92 to 11.89 mm and NSE value from 0.902 to 0.985 during the testing phase. This study shows that incorporating the North Atlantic Oscillation (NAO) as a predictor improved the accuracy of artificial intelligence systems optimized by metaheuristic algorithms, specifically Bat-ELM, for rainfall modeling tasks such as filling in missing data of rainfall time series.

Full-length 16S rRNA gene sequencing and machine learning reveal the bacterial composition of inhalable particles from two different breeding stages in a piggery

Bacterial loading aggravates the harm of particulate matter (PM) to public health and ecological systems, especially in operations of concentrated animal production. This study aimed to explore the characteristics and influencing factors of bacterial components of inhalable particles at a piggery. The morphology and elemental composition of coarse particles (PM₁₀, aerodynamic diameter ≤ 10 µm) and fine particles (PM_2.5, aerodynamic diameter ≤ 2.5 µm) were analyzed. Full-length 16 S rRNA sequencing technology was used to identify bacterial components according to breeding stage, particle size, and diurnal rhythm. Machine learning (ML) algorithms were used to further explore the relationship between bacteria and the environment. The results showed that the morphology of particles in the piggery differed, and the morphologies of the suspected bacterial components were elliptical deposited particles. Full-length 16 S rRNA indicated that most of the airborne bacteria in the fattening and gestation houses were bacilli. The analysis of beta diversity and difference between samples showed that the relative abundance of some bacteria in PM_2.5 was significantly higher than that in PM₁₀ at the same pig house (P < 0.01). There were significant differences in the bacterial composition of inhalable particles between the fattening and gestation houses (P < 0.01). The aggregated boosted tree (ABT) model showed that PM_2.5 had a great influence on airborne bacteria among air pollutants. Fast expectation-maximization microbial source tracking (FEAST) showed that feces was a major potential source of airborne bacteria in pig houses (contribution 52.64-80.58 %). These results will provide a scientific basis for exploring the potential risks of airborne bacteria in a piggery to human and animal health.

Seasonal variation characteristics of inhalable bacteria in bioaerosols and antibiotic resistance genes in Harbin

Bioaerosols have received extensive attention due to their impact on climate, ecological environment, and human health. This study aimed to reveal the driving factors that structure bacterial community composition and the transmission route of antibiotic resistance genes (ARGs) in PM_2.5. The results showed that the bacterial concentration in spring (8.76 × 10⁵ copies/m³) was significantly higher than that in summer (1.03 × 10⁵ copies/m³) and winter (4.74 × 10⁴ copies/m³). Low temperatures and air pollution in winter negatively affected bacterial concentrations. Keystone taxa were identified by network analysis. Although about 50 % of the keystone taxa had low relative abundances, the strong impact of complex interactions between keystone taxa and other taxa on bacterial community structure deserved attention. The bacterial community assembly was dominated by stochastic processes (79.3 %). Interactions between bacteria and environmental filtering together affected bacterial community composition. Vertical gene transfer played an important role in the transmission of airborne ARGs. Given the potential integration and expression of ARGs in recipients, the human exposure risk due to high concentrations of ARGs and mobile genetic elements cannot be ignored. This study highlights human exposure to inhalable bacterial pathogens and ARGs in urban areas.

Low to Zero Concentrations of Airborne Bacterial Pathogens and Indicator E. coli in Proximity to Beef Cattle Feedlots in Imperial Valley, California

This study characterized the effect of distance from beef cattle feedlots, environmental factors, and climate on the occurrence of airborne bacterial indicators and pathogens. Three hundred air samples were collected over 6 months from five feedlots, with each air sample comprising 6000 L of air. Air samples were processed onto TSB-enriched air filters, qPCR-screened, and then qPCR-confirmed for suspect positive colonies of E. coli O157, non-O157-Shiga-toxin-producing E. coli (STEC), Salmonella, and E. coli. Direct enumeration of E. coli was also collected. Although no bacterial pathogens were qPCR-confirmed for the 300 samples, E. coli was detected in 16.7% (50/300) of samples, with an overall mean concentration of 0.17 CFU/6000 L air. Logistic regression analyses revealed a higher odds of E. coli for samples in close proximity compared to >610 m (2000 ft) distance from feedlots, along with significant associations with meteorological factors, sampling hour of day, and the presence of a dust-generating activity such as plowing a field or nearby vehicular traffic. The lack of bacterial pathogen detection suggests airborne deposition from nearby feedlots may not be a significant mechanism of leafy green bacterial pathogen contamination; the result of our study provides data to inform future revisions of produce-safety guidance.

Fog-Induced Alteration in Airborne Microbial Community: a Study over Central Indo-Gangetic Plain in India

Fog supports an increase in airborne microbial loading by providing water with nutrients and protecting it from harmful incoming solar radiation. To improve our present understanding of fog-induced alteration in an atmospheric microbial community, a study was conducted during 1 to 14 January 2021 for continuous investigation of airborne bacteria over a rural site, Arthauli (25.95°N, 85.10°E), in central Indo-Gangetic Plain (IGP) in India. An increase of 36% ± 0.4% in airborne bacterial loading was noticed under fog versus prefog conditions, and a decrease of 48% ± 0.4% was noticed under the postfog condition. Airborne bacterial loading had a strong correlation with RH (R2 = 0.56; P < 0.05), temperature (R2 = -0.55, P < 0.05), and wind speed (R2 = -0.52, P < 0.05). Unique types of bacteria, representing about 29% of the whole community, were detected only under foggy conditions, likely by a continuous supply of nutrients and water from a cold, calm, and humid atmosphere. As a result, no significant diurnal variation of bacterial loading was noticed on a foggy day, with a higher daily mean concentration of about (8.4 ± 1.7) × 105 cells · m-3 than that on a typical winter day [(6.3 ± 3.8) × 105 cells · m-3]. A typical winter day experienced about a 60% decrease in bacterial loading in the afternoon in comparison to that in the morning. A 3-day back-trajectory analysis suggests a slow movement of airmass along with the wind blowing from west to central IGP. Fog pauses wind movement, which reduces continuous transportation of urban sources while increasing airborne bacteria from local sources. The abundances of Gp6 (14.8% ± 8.6%), Anaeromyxobacter (7.1% ± 2.8%), and Gp7 (6.8 ± 2.6%) have been observed to increase due to occurrences of fog over central IGP. IMPORTANCE Fog was investigated in the present study as a cause of alteration in the airborne microbial community. Occurrences of fog were responsible for an increase in airborne microbial loading (36%) over central IGP in India due to the easy availability of nutrients and water in the air and dimming of harmful solar radiation. More than 90% of unique bacteria were detected under fog (64%) and postfog (28%) conditions. A few bacteria, like Gp18 (0.5% ± 0.3%), Alicyclobacillus (0.5% ± 0.1%), Sinomonas (0.4% ± 0.2%), and Phenylobacterium (0.4% ± 0.2%), were detected only under foggy conditions. A strong correlation between meteorological parameters and bacterial loading was found in the current research work. The present study provides additional support toward a new direction in interdisciplinary science for the detailed investigations of the effects of meteorological conditions on airborne bacteria and their implications for society.

Comparison of bacterial community structure in PM2.5 during hazy and non-hazy periods in Guilin, South China

In recent years, significant efforts have been made to study changes in the levels of air pollutants at regional and urban scales, and changes in bioaerosols during air pollution events have attracted increasing attention. In this study, the bacterial structure of PM_2.5 was analysed under different environmental conditions during hazy and non-hazy periods in Guilin. A total of 32 PM_2.5 samples were collected in December 2020 and July 2021, and the microbial community structures were analysed using high-throughput sequencing methods. The results show that air pollution and climate change alter the species distribution and community diversity of bacteria in PM_2.5, particularly Sphingomonas and Pseudomonas. The structure of the bacterial community composition is related to diurnal variation, vertical height, and urban area and their interactions with various environmental factors. This is a comprehensive study that characterises the variability of bacteria associated with PM_2.5 in a variety of environments, highlighting the impacts of environmental effects on the atmospheric microbial community. The results will contribute to our understanding of haze trends in China, particularly the relationship between bioaerosol communities and the urban environment.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10453-022-09777-0.

The Relationship Between Dust Sources and Airborne Bacteria in the Southwest of Iran

The biological agents are carried from deserts and dried lands to long distances by high dust volumes. Their adverse effects can be reduced by specifying and controlling dust sources and their related biological agents. Thus, the current work examined the relationship between the bacteria in air and soil samples by taking samples from the soil surface of two dust sources, as well as from air samples during spring from Khorramshahr and Abadan cities. The dust event is the most influential factor on airborne bacteria. There is an insignificant negative (-0.06), insignificant positive (0.14), and weak positive (0.24) correlation between airborne bacteria and UV radiation, relative humidity, and temperature, respectively. After preparing a 16S ribosomal DNA (rDNA) clone library from the soil and air samples, operational taxonomic unit picking and taxonomic assignment were conducted using QIIME Virtual Box. In the present work, Bacillus was the dominant species. The relationship between dust sources and air samples was determined by principal component analysis. Bacteria in the Hoor-Al-Azim dust source and airborne bacteria on dusty and non-dusty days showed a more significant correlation compared to bacteria in the Shadegan dust source. Source Tracker software was used to estimate the contribution of dust sources. The primary source of dust was associated with the dried areas of Hoor-Al-Azim on the non-dusty and dusty days. Finally, the long transport of airborne bacteria was assessed by moderate resolution imaging spectroradiometer (MODIS) and the back trajectory model of Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) data. The research findings can help decision-makers prioritize dust sources to control the adverse effects of dust.

Size distribution, community composition, and influencing factors of bioaerosols on haze and non-haze days in a megacity in Northwest China

Bioaerosols have become a major environmental concern in recent years. In this study, the diurnal variations and size distributions of bioaerosols, as well as airborne bacterial community compositions and their influencing factors on haze and non-haze days in Xi'an, China, were compared. The results indicated that the mean bacteria and fungi concentrations on non-haze days were 1.7 and 1.4 times of those on haze days, respectively, whereas the mean total airborne microbe (TAM) concentration was higher on haze days. Bacteria concentrations were the lowest in the afternoon, and the TAM concentration exhibited a bimodal distribution with two peaks coinciding with traffic rush hours. On haze days airborne fungi was mainly attached to PM_2.5, whereas bacteria and TAM were mainly distributed in coarse PM. The relative abundance of Chao1, Shannon and Simpson indices of bacterial communities were higher in the non-haze day samples, for the reason that high PM_2.5 levels with a large specific surface area may absorb more toxic and harmful substances on haze days, which should affect microbial growth. At the generic level, the relative abundance of Rhodococcus, Paracoccus, Acinetobacter, and Kocuria on haze days was higher than that on non-haze days, indicating a higher risk of contracting pathogenic pneumonia. The results of the redundancy analysis revealed that PM_2.5 and water-soluble inorganic ions (WSIIs, NO₃^-, SO₄²⁺, and NH₄⁺) strongly affected the bacterial communities on non-haze days, especially Acinetobacter. The atmospheric oxidation capacity (O_x) had a significant effect on bacterial communities during haze episodes, which were positively correlated with Paracoccus, Deinococcus, Sphingomonas, and Rubellimicrobium and were negatively correlated with Rhodococcus. These results provide valuable data to elucidate the formation and evolution of bioaerosol between haze and non-haze events and its potential threats to human health.

A systematic review of enteric pathogens and antibiotic resistance genes in outdoor urban aerosols

Aerosol transport of enteric microbiota including fecal pathogens and antimicrobial resistance genes (ARGs) has been documented in a range of settings but remains poorly understood outside indoor environments. We conducted a systematic review of the peer-reviewed literature to summarize evidence on specific enteric microbiota including enteric pathogens and ARGs that have been measured in aerosol samples in urban settings where the risks of outdoor exposure and antibiotic resistance (AR) spread may be highest. Following PRISMA guidelines, we conducted a key word search for articles published within the years 1990-2020 using relevant data sources. Two authors independently conducted the keyword searches of databases and conducted primary and secondary screenings before merging results. To be included, studies contained extractable data on enteric microbes and AR in outdoor aerosols regardless of source confirmation and reported on qualitative, quantitative, or viability data on enteric microbes or AR. Qualitative analyses and metric summaries revealed that enteric microbes and AR have been consistently reported in outdoor aerosols, generally via relative abundance measures, though gaps remain preventing full understanding of the role of the aeromicrobiological pathway in the fate and transport of enteric associated outdoor aerosols. We identified remaining gaps in the evidence base including a need for broad characterization of enteric pathogens in bioaerosols beyond bacterial genera, a need for greater sampling in locations of high enteric disease risk, and a need for quantitative estimation of microbial and nucleic acid densities that may be applied to fate and transport models and in quantitative microbial risk assessment.

Airborne microbial community structure and potential pathogen identification across the PM size fractions and seasons in the urban atmosphere

As a vital component of airborne bioaerosols, bacteria and fungi seriously endanger human health as pathogens and allergens. However, comprehensive effects of environmental variables on airborne microbial community structures remain poorly understood across the PM sizes and seasons. We collected atmospheric PM_1.0, PM_2.5, and PM₁₀ samples in Hefei, a typical rapidly-developing city in East China, across three seasons, and performed a comprehensive analysis of airborne microbial community structures using qPCR and high-throughput sequencing. Overall the bacterial and fungal abundances in PM_1.0 were one to two orders of magnitude higher than those in PM_2.5 and PM₁₀ across seasons, but their α-diversity tended to increase from PM_1.0 to PM₁₀. The bacterial gene abundances showed a strong positive correlation (P < 0.05) with atmospheric SO₂ and NO₂ concentrations and air quality index. The bacterial gene abundances were significantly higher (P = 0.001) than fungi, and the bacterial diversity showed stronger seasonality. The PM sizes influenced distribution patterns for airborne microbial communities within the same season. Source-tracking analysis indicated that soils, plants, human and animal feces represented important sources of airborne bacteria with a total relative abundance of more than 60% in summer, but total abundance from the unidentified sources surpassed in fall and winter. Total 10 potential bacterial and 12 potential fungal pathogens were identified at the species level with the highest relative abundances in summer, and their abundances increased with the PM sizes. Together, our results indicated that a complex set of environmental factors, including water-soluble ions in PM, changes in air pollutant levels and meteorological conditions, and shifts in the relative importance of available microbial sources, acted to control the seasonal compositions of microbial communities in the urban atmosphere.

Bioaerosol Seasonal Variation and Contribution to Airborne Particulate Matter in Huangshi City of Central China

Ambient bioaerosols affect ecosystems and public health, but their seasonal variations and their contributions to aerosol particles are limitedly understood. Ambient bioaerosols in PM2.5 and PM10 samples were measured in Huangshi City, Hubei Province of China from April 2018 to December 2018. Bioaerosols were measured using a fluorescence microscope after staining with 4′, 6-diamino-2-phenylindole dihydrochloride (DAPI) following a direct staining technique. The bioaerosol number concentrations ranged from 0.12 to 15.69 # cm−3 for PM2.5 and 0.22 to 18.20 # cm−3 for PM10, with averages of 2.79 # cm−3 and 4.66 # cm−3, respectively. The bioaerosol concentrations of PM2.5 and PM10 varied significantly by seasons and were arranged in the following descending order: spring > fall > winter > summer. Bioaerosol numbers were dominated by fine particles of 0.37–2.5 μm diameter, while the spring bioaerosol particles were detected at the peak concentration of 0.56–1 μm diameter. Bioaerosol fractions accounted for 18.3 ± 10.6% PM10 mass and 13.7 ± 12.5% PM2.5 mass. Bioaerosol concentrations were increased during the haze event, but the increased amounts were not as large as those of the dust event, and higher bioaerosol contributions to PM were observed in the dust event than in the haze event. As enhanced emission controls have reduced PM concentrations in China, bioaerosols can be important contributors to PM mass.

Development of a Novel Bioaerosol Chamber to Determine Survival Rates of Airborne Staphylococci

Large amounts of microorganisms are emitted from animal houses into the environment via exhaust air. To assess the potential risks, the spread of microorganisms can be simulated with computer models. Such modeling usually does not take into account die-off rates, since there are hardly any reliable data so far on how long microorganisms can survive in outdoor air. Previous studies were conducted almost exclusively in closed chambers and usually only took into account the influence of individual environmental factors such as temperature or humidity. Therefore, a novel bioaerosol chamber was developed to quantify the survival rates of Staphylococci specific to livestock under outdoor air conditions. For evaluation, the survival rates of Staphylococcus xylosus were determined as a function of temperature, relative humidity, ozone concentration, and global radiation. Survival rates decreased with increasing temperature, decreasing relative humidity, increasing global radiation intensity, and increasing ozone concentration. At 12 min in the airborne state, die-off rates of more than 90% were observed, especially at high global radiation levels > 400 W/m2. The novel bioaerosol chamber enabled the investigation of the survival rates of airborne microorganisms over a certain period of time in a quasi-closed system and yet under real outdoor air conditions.

Effects of Yellow Light on Airborne Microbial Composition and on the Transcriptome of Typical Marker Strain in Ward

Airborne diseases are transmitted by pathogens in the air. The complex microbial environment in wards is usually considered a major cause of nosocomial infection of various diseases which greatly influences the health of patients with chronic diseases, whereas the illuminant of wards impacts on the microbe especially the disease marker strain is seldom studied. In the present study, high-throughput sequencing was used to study the effect of yellow light on airborne microbial composition, and changes of transcriptome of marker strains Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa, which were isolated from wards, were further studied after the irradiation by yellow light. High-throughput sequencing results indicated that yellow light significantly decreased α-diversity. The relative abundance of Firmicutes at the phylum level, and Clostridium sensu stricto 1, Paraclostridium at the genus level were significantly reduced. RNA sequencing results declared that yellow light significantly downregulated the genes associated with flagella, heme transport system and carbohydrate, amino acid metabolism in E. coli, and the genes related to arginine biosynthesis and the biosynthesis of isoleucine, leucine, and valine in S. aureus. Meanwhile, yellow light significantly upregulated the genes relating to porphyrin metabolism in P. aeruginosa. In conclusion, our work reveals the impacts of yellow light on the microbe in wards, pointing out the application value of yellow light in the prevention of infectious diseases in clinical practice.

Microbial Activity and Community Structure in PM2 .5 at Different Heights in Ground Boundary Layer of Beijing Atmosphere under Various Air Quality Levels

The outbreak of the COVID-19 epidemic is a reminder that aerosols have important health effects as a potential route for disease transmission. Biological components in aerosols (especially PM_2.5 ) may pose potential threats to humans as pathogens and allergens. Research on PM_2.5 and biological components currently focuses mainly on polluted conditions, with less emphasis on clean environments. Sampling has also been primarily based on a single point with a lack of data at different positions. In this study, a modified fluorescein diacetate hydrolysis method was used to measure microbial activity in PM_2.5 at different altitudes over a year in Beijing, China. A high-throughput sequencing method was used to study the microbial community. Results showed that microbial activity 1.5 m (0.0465 ng m^-3 ) above the ground was higher than 31.5 m (0.0348 ng m^-3 ). There was higher microbial activity at both heights during spring. Furthermore, a positive correlation was observed between microbial activity and relative abundance of dominant species. Microbial activity increased during autumn and winter increased alongside the pollution level, but in spring higher levels of microbial activity were observed in excellent or good weather conditions. The results from this study are valuable for further research regarding the biological components of atmospheric PM, the prevention of biological pollution, and establishing a comprehensive air quality evaluation system. This article is protected by copyright. All rights reserved.

Seasonal and vegetational variations of culturable bacteria concentrations in air from urban forest parks: a case study in Hunan, China

It is important to investigate the airborne bacterial air quality in urban forest parks as tree bacteriostasis practices are being increasingly advocated as measures to improve the air quality and public health in urban green spaces around the world. The aim of the study was to quantitatively investigate airborne culturable bacteria (ACB) concentration levels based on field measurements in every season in five selected forest communities and the uncovered space in an urban forest park, as well as the effects of several factors on the culturability of airborne bacteria. Results suggested that the airborne bacterial levels of all the forest communities reached the clean air quality standard with regard to the airborne bacteria content, with the highest concentration of ACB showing in the uncovered space (1658 ± 1298 CFU/m³) and the lowest showing in the mixed community (907 ± 567 CFU/m³). The temporal distribution analysis showed that the airborne bacteria were mostly concentrated in summer, as well as in the morning and afternoon. The bacteriostatic rates of the mixed community were significantly different with seasonal variation (p < 0.05). Spearman's correlations revealed that the concentration of ACB was significantly positively correlated with the season, wind speed (WS), temperature (T), ultraviolet light (UV), negative air ion (NAI), and total suspended particles (TSP) (p<0.05) but significantly negatively correlated with the forest community type (p < 0.05). Overall, the selection of tree species plays a key role in shaping the forest structure and improving air quality, and the urban forest highlights key priorities for future efforts toward a cleaner, healthier, and more diverse regional forest environment.

Indoor microbiome, air pollutants and asthma, rhinitis and eczema in preschool children - A repeated cross-sectional study

BACKGROUND

Indoor microbiome exposure is associated with asthma, rhinitis and eczema. However, no studies report the interactions between environmental characteristics, indoor microbiome and health effects in a repeated cross-sectional framework.

METHODS

1,279 and 1,121 preschool children in an industrial city (Taiyuan) of China were assessed for asthma, rhinitis and eczema symptoms in 2012 and 2019 by self-administered questionnaires, respectively. Bacteria and fungi in classroom vacuum dust were characterized by culture-independent amplicon sequencing. Multi-level logistic/linear regression was performed in two cross-sectional and two combined models to assess the associations.

RESULTS

The number of observed species in bacterial and fungal communities in classrooms increased significantly from 2012 to 2019, and the compositions of the microbial communities were drastically changed (p < 0.001). The temporal microbiome variation was significantly larger than the spatial variation within the city (p < 0.001). Annual average outdoor SO₂ concentration decreased by 60.7%, whereas NO₂ and PM₁₀ concentrations increased by 63.3% and 40.0% from 2012 to 2019, which were both associated with indoor microbiome variation (PERMANOVA p < 0.001). The prevalence of asthma (2.0% to 3.3%, p = 0.06) and rhinitis (28.0% to 25.3%, p = 0.13) were not significantly changed, but the prevalence of eczema was increased (3.6% to 7.0%; p < 0.001). Aspergillus subversicolor, Collinsella and Cutibacterium were positively associated with asthma, rhinitis and eczema, respectively (p < 0.01). Prevotella, Lactobacillus iners and Dolosigranulum were protectively (negatively) associated with rhinitis (p < 0.01), consistent with previous studies in the human respiratory tract. NO₂ and PM₁₀ concentrations were negatively associated with rhinitis in a bivariate model, but a multivariate mediation analysis revealed that Prevotella fully mediated the health effects.

CONCLUSIONS

This is the first study to report the interactions between environmental characteristics, indoor microbiome and health in a repeated cross-sectional framework. The mediating effects of indoor microorganisms suggest incorporating biological with chemical exposure for a comprehensive exposure assessment.

Characteristics of airborne bacterial communities and antibiotic resistance genes under different air quality levels

Pathogenic bacteria and antibiotic resistance genes (ARGs) in bioaerosols are major threats to human health. In this study, the microbial community structure and ARG distribution characteristics of airborne bacteria in total suspended particulates (TSP) and PM_2.5 were investigated under different air quality levels in Xinxiang, Central China. The results revealed that with the deterioration of air quality, the concentrations of airborne bacteria in both TSP and PM_2.5 decreased; however, the relative amounts of pathogenic bacteria increased. The predominant genera in pathogenic bacteria of Bacillus, Sphingomonas, Corynebacterium, Rhodococcus, and Staphylococcus were identified in both TSP and PM_2.5. Although the airborne bacteria concentrations and absolute abundances of ARGs in TSP were higher than those in PM_2.5 under identical air quality conditions, the bacterial community structure and relative amounts of pathogenic bacteria were similar. In addition, the relationship between environmental factors of ions, metal elements, and meteorological parameters and the community structures of airborne bacteria and pathogenic bacteria were also analyzed. The effects of soluble ions and metal elements on several dominant genera of total bacteria and pathogenic bacteria differed, probably due to the strong tolerance of pathogenic bacteria to harsh atmospheric environments Different subtypes of ARGs showed various distribution characteristics with variations in air quality. The deterioration of air quality can inhibit the dissemination of ARGs, as the minimum values of all ARGs and class 1 integrase intI1 were observed under Severely Polluted conditions. This study provides a comprehensive understanding of the effect of air pollution levels on the airborne bacteria community composition and ARG distribution.

Assessing the relationship between airborne fungi and potential dust sources using a combined approach

Dust events impose negative socio-economic, health, and environmental impacts on vulnerable areas and reflect their sources' physiochemical and biological characteristics. This study aimed to assess the impact of two dust sources on the concentration and diversity of airborne fungi in one of the dustiest areas in the world. This study is the first attempt to investigate the relationship between dust sources fungal community and those in airborne dust. Also, the contribution of dust sources to airborne fungi was estimated. Air masses arriving at the study area were assessed using local wind rose and the HYSPLIT model. Sampling was carried out from airborne dust at the Arvand Free Zone as target areas and soil in the dried parts of the Hor al-Azim and Shadegan wetlands as source areas to explore the relationship between fungi in the dust sources and the downwind area. The samples were analyzed in the lab to extract DNA. The internal transcribed spacer (ITS) regions of the rDNA gene were amplified using the primers ITS1F and ITS4, and then PCR products were sent to the lab for sequencing. The raw DNA data were processed using the QIIME virtual box to pick operational taxonomic units and taxonomy assignments. The most common fungi at the genus level were in the order of Penicillium > Aspergillus > Alternaria > Fusarium > Paradendryphiella > Talaromyces. The similarity between air and soil fungal genera was investigated using richness and diversity indices, the phylogenetic tree, and principal component analysis. The results showed that the community structures of ambient fungi in the Hor al-Azim and Shadegan dust sources were more similar to those on dusty days than non-dusty days. The source tracker model was used to quantify the contributions of known dust sources to airborne fungi. The results showed that the main source of airborne fungi was Hor al-Azim on dusty and non-dusty days. This study's results can help managers identify and prioritize dust sources regarding fungal species.

Culturable Filamentous Fungi in the Air of Recreational Areas and Their Relationship with Bacteria and Air Pollutants during Winter

One of the greatest environmental health problems to arise in recent years is air pollution. Inorganic and organic particles are important components of air aerosol. The potential of air microbiota as an indicator of air quality is gaining increasing research interest. The aim of the present study was to determine the relationship between the level of fungal contamination and the levels of bacteria and smog particles in outdoor air in recreational areas during the heating season. A quantitative and qualitative mycological evaluation and quantitative bacteriological evaluation of air quality in 10 selected parks were performed. The numbers of microorganisms in the air were correlated with smog levels. The mean prevalence of fungi was 18.96 ± 15.43–23.30 ± 26.70 CFU/m3 of air and the mean bacterial count was 74.06 ± 130.89–268.04 ± 126.10 CFU/m3. Among the isolated fungi, clinically significant species were identified: four species belonged to Risk Group 2, and 17 to Risk Group 1. The predominant genera were Aspergillus, Penicillium and Alternaria. The total number of bacteria demonstrated a positive correlation with the size of the park, air temperature and ozone level during sampling, and a negative correlation with humidity, pressure and smog parameters (CO, NO, NO2 and NOx). The qualitative and quantitative composition of bioaerosols can be used as a bioindicator for environmental monitoring. There is a need for more efficient monitoring of airborne pollutants and microorganisms to learn about the structure of the air biota, the mechanisms regulating their occurrence, and to identify potential threats to human health.

Abundance and diversity of antibiotic resistance genes possibly released to ambient air by experiments in biology laboratories

Antibiotic resistance genes (ARG) have been considered as a global emerging threat to public health systems. As special locations where both antibiotics and ARGs are directly used, biology laboratories are poorly studied but potential important emission sources where not only the environmental stress is strong but also obtaining resistance is much easier comparing to other well studied hot spots including farms, hospitals, wastewater treatment plants and landfills where antibiotics but not ARGs are used or discharged. Therefore, in this study, 11 Swiss biology laboratories working on different fields and located in the city center, suburb and rural area were studied to reveal the abundance and diversity of airborne ARGs in them and their surrounding areas with Colony-forming units (CFU) cultivation and quantitative Polymerase Chain Reaction (qPCR). Most biology laboratories did not discharge significant amounts or varieties of ARGs and cultivable bacteria via air. No correlation was found between the number of CFUs and the abundance of 16S rRNA, but two clusters of correlated airborne ARGs, the animal husbandry related cluster, and city and hospital related cluster were identified in this study. Although most biology laboratories may not be the emission sources of a wide variety of airborne ARGs, the ARGs in the animal husbandry related cluster which are abundant in the animal laboratories and aadA1 which is abundant in the laboratories working on other eukaryocytes need to be furtherly studied to make sure if they are potential health risks for the researchers.

Distribution of bacterial concentration and viability in atmospheric aerosols under various weather conditions in the coastal region of China

Airborne bacteria have an important role in atmospheric processes and human health. However, there is still little information on the transmission and distribution of bacteria via the airborne route. To characterize the impact of foggy, haze, haze-fog (HF) and dust days on the concentration and viability of bacteria in atmospheric aerosols, size-segregated bioaerosol samples were collected in the Qingdao coastal region from March 2018 to February 2019. The total airborne microbes and viable/non-viable bacteria in the bioaerosol samples were measured using an epifluorescence microscope after staining with DAPI (4', 6-diamidino-2-phenylindole) and a LIVE/DEAD® BacLight Bacterial Viability Kit. The average concentrations of total airborne microbes on haze and dust days were 6.75 × 10⁵ and 1.03 × 10⁶ cells/m³, respectively, which increased by a factor of 1.3 and 2.5 (on average), respectively, relative to those on sunny days. The concentrations of non-viable bacteria on haze and dust days increased by a factor of 1.2 and 3.6 (on average), respectively, relative to those on sunny days. In contrast, the concentrations of viable bacteria on foggy and HF days were 7.13 × 10³ and 5.74 × 10³ cells/m³, decreases of 38% and 50%, respectively, compared with those on sunny days. Foggy, haze, dust and HF days had a significant effect on the trend of the seasonal variation in the total airborne microbes and non-viable bacteria. Bacterial viability was 20.8% on sunny days and significantly higher than the 14.1% on foggy days, 11.2% on haze days, 8.6% during the HF phenomenon and 6.1% on dust days, indicating that special weather is harmful to some bacterial species. Correlation analysis showed that the factors that influenced the bacterial concentration and viability depended on different weather conditions. The main influential factors were temperature, NO₂ and SO₂ concentrations on haze days, and temperature, particulate matter (PM_2.5) and NO₂ concentrations on foggy days. The median size of particles containing viable bacteria was 1.94 μm on sunny days and decreased to 1.88 μm and 1.74 μm on foggy and haze days, respectively, but increased to 2.18 μm and 2.37 μm on dust and HF days, respectively.

Airborne Bacterial Community Composition According to Their Origin in Tenerife, Canary Islands

Microorganisms are ubiquitous in the environment, and the atmosphere is no exception. However, airborne bacterial communities are some of the least studied. Increasing our knowledge about these communities and how environmental factors shape them is key to understanding disease outbreaks and transmission routes. We describe airborne bacterial communities at two different sites in Tenerife, La Laguna (urban, 600 m.a.s.l.) and Izaña (high mountain, 2,400 m.a.s.l.), and how they change throughout the year. Illumina MiSeq sequencing was used to target 16S rRNA genes in 293 samples. Results indicated a predominance of Proteobacteria at both sites (>65%), followed by Bacteroidetes, Actinobacteria, and Firmicutes. Gammaproteobacteria were the most frequent within the Proteobacteria phylum during spring and winter, while Alphaproteobacteria dominated in the fall and summer. Within the 519 genera identified, Cellvibrio was the most frequent during spring (35.75%) and winter (30.73%); Limnobacter (24.49%) and Blastomonas (19.88%) dominated in the summer; and Sediminibacterium represented 10.26 and 12.41% of fall and winter samples, respectively. Sphingomonas was also identified in 17.15% of the fall samples. These five genera were more abundant at the high mountain site, while other common airborne bacteria were more frequent at the urban site (Kocuria, Delftia, Mesorhizobium, and Methylobacterium). Diversity values showed different patterns for both sites, with higher values during the cooler seasons in Izaña, whereas the opposite was observed in La Laguna. Regarding wind back trajectories, Tropical air masses were significantly different from African ones at both sites, showing the highest diversity and characterized by genera regularly associated with humans (Pseudomonas, Sphingomonas, and Cloacibacterium), as well as others related to extreme conditions (Alicyclobacillus) or typically associated with animals (Lachnospiraceae). Marine and African air masses were consistent and very similar in their microbial composition. By contrast, European trajectories were dominated by Cellvibrio, Pseudomonas, Pseudoxanthomonas, and Sediminibacterium. These data contribute to our current state of knowledge in the field of atmospheric microbiology. However, future studies are needed to increase our understanding of the influence of different environmental factors on atmospheric microbial dispersion and the potential impact of airborne microorganisms on ecosystems and public health.

High time-resolved characterization of airborne microbial community during a typical haze pollution process

Variations of bioaerosol characteristics during the process of haze pollution have rarely been explored. In this study, high time-resolved variations of the community structures of bacteria, fungi, and ammonia-oxidizing microorganisms (AOMs) were assessed during a typical haze pollution process. The impacts of meteorological factors, water-soluble inorganic ions (WSII), and organic dicarboxylic acids (DCA) on the airborne microbial community were systematically evaluated. The results showed that the bacterial community varied greatly during the formation stages of haze pollution, and tended to stabilize with the further development of haze pollution. Nevertheless, variations of the fungal community lasted throughout the whole haze pollution process. Furthermore, Nitrososphaera absolutely dominated the ammonia-oxidizing archaea (AOA) and declined as PM_2.5 burst. Network analysis identified relatively weak interactions and co-occurrence patterns between dominant fungal genera. Importantly, dust source ions and PM_2.5 acidity exerted the most significant impacts on bacterial and fungal communities. These results identify the high time-resolved variations of airborne microbial communities during the formation and development of haze pollution process, and provide valuable data to better understand the interaction between bioaerosols and haze pollution.

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman's correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2, and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 μg/m3 increase during (Lag0-14) in PM2.5, PM10, and NO2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

Urban greenness and plant species are key factors in shaping air microbiomes and reducing airborne pathogens

Urban green space has been implicated in shaping airborne microbes, but there is an only rudimentary understanding of the key factors of urban green space affecting the composition and structures of airborne microbes. Here, we selected 40 urban sites based on stratified random sampling design and investigated the effects of multiple factors including landscapes, plant, soil, and anthropogenic factors on airborne microbial communities, especially bacterial and fungal pathogens. Bacterial and fungal communities in the control area with lower greenness were significantly (P < 0.05) different from those in other areas with a gradient of green space. The relative abundance of bacterial and fungal pathogens significantly (P < 0.05) decreased with increasing greenness. Other than soil thickness, soil type, slope position, and population density, plant species considerably contributed to the shift in the composition and abundance of potential bacterial and fungal pathogens. A significantly (P < 0.05) reduced abundance of bacterial and fungal pathogens was observed in areas with >30% masson pine. Together, these results provide insights into the importance of green space for providing health benefits for city dwellers by reducing pathogens in air, as well as providing support for the inclusion of plant species in the management of urban green space to reduce exposure risk of airborne pathogens.

Combining culturing and 16S rDNA sequencing to reveal seasonal and room variations of household airborne bacteria and correlative environmental factors in nanjing, southeast china

Exposure to bioaerosols poses important health effects on occupants. To elucidate seasonal and room variations of household airborne bacteria, this study investigated 30 residential homes during summer and winter throughout Nanjing, Southeast China, with a humid subtropical climate. Culturing and 16S rDNA sequencing methods were combined in this study. Results showed that the community structure and composition in the same season but different homes show similarity, however, they in the same home but in different seasons show a huge difference, with Sphingomonas (25.3%), Clostridium (14.8%), and Pseudomonas (7.6%) being the dominant bacteria in summer, and Pseudomonas (57.1%) was dominant bacteria in winter. Culturable concentrations of bacteria were also significantly higher in summer (854 ± 425 CFU/m³ ) than in winter (231 ± 175 CFU/m³ ), but difference by home or room was relatively minor. More than 80% of culturable bacteria (<4.7 μm) could penetrate into lower respiratory tract. The seasonal variations of bacterial community and concentrations were closely associated with seasonal variations of temperature, humidity, and PM_2.5 . Higher concentrations and larger sizes were observed in the bathroom and kitchen, typically with higher humidity than other rooms.

Seasonal Variation Characteristics of Bacteria and Fungi in PM2.5 in Typical Basin Cities of Xi’an and Linfen, China

Microorganisms existing in airborne fine particulate matter (PM2.5) have key implications in biogeochemical cycling and human health. In this study, PM2.5 samples, collected in the typical basin cities of Xi’an and Linfen, China, were analyzed through high-throughput sequencing to understand microbial seasonal variation characteristics and ecological functions. For bacteria, the highest richness and diversity were identified in autumn. The bacterial phyla were dominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. Metabolism was the most abundant pathway, with the highest relative abundance found in autumn. Pathogenic bacteria (Pseudomonas, Acinetobacter, Serratia, and Delftia) were positively correlated with most disease-related pathways. Besides, C cycling dominated in spring and summer, while N cycling dominated in autumn and winter. The relative abundance of S cycling was highest during winter in Linfen. For fungi, the highest richness was found in summer. Basidiomycota and Ascomycota mainly constituted the fungal phyla. Moreover, temperature (T) and sulfur dioxide (SO2) in Xi’an, and T, SO2, and nitrogen dioxide (NO2) in Linfen were the key factors affecting microbial community structures, which were associated with different pollution characteristics in Xi’an and Linfen. Overall, these results provide an important reference for the research into airborne microbial seasonal variations, along with their ecological functions and health impacts.