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Updated: Mar 1, 2026

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
Meteorological factors had more impact on airborne bacterial communities than air pollutants
Quan Zhen1, Ye Deng2, Yaqing Wang1
1State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Abstract:
Airborne bacteria have gained increasing attention because they affect ecological balance and pose potential risks on human health. Recently, some studies have focused on the abundance and composition of airborne bacteria under heavy, hazy polluted weather in China, but they reached different conclusions about the comparisons with non-polluted days. In this study, we tested the hypothesis that meteorological factors could have a higher impact on shaping airborne bacterial communities than air pollutants by systematically monitoring the communities for 1year. Total suspended particles in Beijing were sampled for 20 consecutive days in each season of 2015. Bacterial abundance varied from 8.71×103 to 2.14×107 ribosomal operons per cubic meter according to the quantitative PCR analysis. There were relatively higher bacterial counts in spring and in autumn than in winter and summer. Airborne bacterial communities displayed a strong seasonality, according to the hierarchical cluster analysis. Only two exceptions overtook the seasonal trend, and both occurred in or after violent meteorological changes (sandstorm or rain). Aggregated boosted tree analysis performed on bacterial abundance showed that the dominant factors shaping bacterial communities were meteorological. They were air pressure in winter, air temperature and relative humidity in spring, RH in summer, and vapor pressure in autumn. Variation partition analysis on community structure showed that meteorological factors explained more variations than air pollutants. Therefore, both of the two models verified our hypothesis that the differences in airborne bacterial communities in polluted days or non-polluted days were mainly driven by the discrepancies of meteorological factors rather than by the presence of air pollutants.
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