Seasonal variation of bacterial community structure in PM<sub>2.5</sub> in urban area of Beijing and its response to typical weather events

LIU Meijun; HUANG Yujia; SUN Yujiao; SUN Yujie; REN Xueqian; XUAN Yuanyan; YUN Ying; BAI Guomin; JIANG Fan

doi:10.13205/j.hjgc.202512021

Volume 43 Issue 12

Dec. 2025

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2025 > 43(12): 186-196

LIU Meijun, HUANG Yujia, SUN Yujiao, SUN Yujie, REN Xueqian, XUAN Yuanyan, YUN Ying, BAI Guomin, JIANG Fan. Seasonal variation of bacterial community structure in PM2.5 in urban area of Beijing and its response to typical weather events[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(12): 186-196. doi: 10.13205/j.hjgc.202512021

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LIU Meijun, HUANG Yujia, SUN Yujiao, SUN Yujie, REN Xueqian, XUAN Yuanyan, YUN Ying, BAI Guomin, JIANG Fan. Seasonal variation of bacterial community structure in PM_2.5 in urban area of Beijing and its response to typical weather events[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(12): 186-196. doi: 10.13205/j.hjgc.202512021

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Seasonal variation of bacterial community structure in PM_2.5 in urban area of Beijing and its response to typical weather events

doi: 10.13205/j.hjgc.202512021

College of Water Science, Beijing Normal University, Beijing 100875, China

Received Date: 2024-11-02
Accepted Date: 2024-12-15
Rev Recd Date: 2024-12-05

Available Online: 2026-01-09

Abstract

Abstract

Atmospheric PM_2.5 pollution is one of the typical environmental problems in Beijing， and the negative impact of bacterial communities of PM_2.5 on human health are attracting increasing public attention. In this study， a one-year sampling of atmospheric PM_2.5 was carried out at a typical atmospheric monitoring station in Beijing urban area， and samples were collected from four seasons of regular weather and haze， rainfall， snowfall， sandstorms， and dust storms， etc. Seasonal changes of the bacterial community structure in PM_2.5 were investigated by combining molecular biology and multivariate statistical methods. 43 phyla and 1344 genera were found in PM_2.5， and the dominant and characteristic genera varied in different seasons and typical weather， with norank_f__norank_o__Chloroplast and norank_f__Mitochondria in spring， Acidibacter and Paracoccus in summer， Ammoniphilus and unclassified_k__norank_d__Bacteria in autumn， and Sphingomonas and Pseudomonas in winter. The characteristic genus was Diaphorobacter in hazy weather， Delftia in rainy weather， Terrisporobacter in snowy weather， and norank_f__Cytophagaceae in dusty weather. The results of the non-metric multidimensional scaling （NMDS） analysis showed that the atmospheric bacterial community was more stable in summer and that typical weather such as rainfall， snowfall， haze， and dust storms in other seasons would cause greater perturbations to the bacterial community. Based on the functional prediction of BugBase， it was found that the atmospheric microorganisms are mainly aerobic and gram-negative bacteria. Acidibacter is the most abundant potential pathogenic bacterium in the four seasons， and the potential pathogenic risk of atmospheric microorganisms is greater in summer. This study are important for the development of air quality management strategies under different seasons and weather conditions.
- PM_2.5,
- bacterial community,
- seasonal variation,
- typical weather event,
- function prediction

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