Dataset Information

Comparison of bacterial community structure in PM_2.5 during hazy and non-hazy periods in Guilin, South China.

ABSTRACT: 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.

SUBMITTER: Long T

PROVIDER: S-EPMC9762634 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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

Long Tengfa T Ye Ziwei Z Tang Yanchun Y Shi Jiaxin J Wen Jianhui J Chen Chunqiang C Huo Qiang Q

Aerobiologia 20221219 1

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 PM2.5 was analysed under different environmental conditions during hazy and non-hazy periods in Guilin. A total of 32 PM2.5 samples were collected in December 2020 and July 2021, and the microbial community struct ...[more]

PMID: 36568442

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Project description:IntroductionDespite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM2.5 found in this subway system are not well understood.MethodsSpatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM2.5 across the LU network, including diurnal and day-to-day variability and spatial distribution (above ground, depth below ground and subway line). Population-weighted station PM2.5 rankings were produced to understand the relative importance of concentrations at different stations and on different lines.ResultsThe PM2.5 mass in the LU (mean 88 μg m-3, median 28 μg m-3) was greater than at ambient background locations (mean 19 μg m-3, median 14 μg m-3) and roadside environments in central London (mean 22 μg m-3, median 14 μg m-3). Concentrations varied between lines and locations, with the deepest and shallowest submerged lines being the District (median 4 μg m-3) and Victoria (median 361 μg m-3 but up to 885 μg m-3). Broadly in agreement with other subway systems around the world, sampled LU PM2.5 comprised 47% iron oxide, 7% elemental carbon, 11% organic carbon, and 14% metallic and mineral oxides. Although a relationship between line depth and air quality inside the tube trains was evident, there were clear influences relating to the distance from cleaner outside air and the exchange with cabin air when the doors open. The passenger population-weighted exposure analysis demonstrated a method to identify stations that should be prioritised for remediation to improve air quality.ConclusionPM2.5 concentrations in the LU are many times higher than in other London transport Environments. Failure to include this environment in epidemiological studies of the relationship between PM2.5 and health in London is therefore likely to lead to a large exposure misclassification error. Given the significant contribution of underground PM2.5 to daily exposure, and the differences in composition compared to urban PM2.5, there is a clear need for well-designed studies to better understand the health effects of underground exposure.

Dataset Information

Comparison of bacterial community structure in PM_2.5 during hazy and non-hazy periods in Guilin, South China.

Supplementary information

Publications

Comparison of bacterial community structure in PM<sub>2.5</sub> during hazy and non-hazy periods in Guilin, South China.

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