期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 637, 期 -, 页码 507-516出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2018.04.203
关键词
Atmospheric particulate matter; Airborne microorganisms; Community structure; Chemical composition; Pathogens
资金
- National Natural Science Foundation of China [51178048, 51378064, 51678054]
In this study, particulate matter (PM) with aerodynamic diameters of <= 2.5 and <= 10 mu m (PM2.5 and PM10, respectively), which was found at different concentrations in spring, was collected in Beijing. The chemical composition and bacterial community diversity of PM were determined, and the relationship between them was studied by 16S rRNA sequencing and mathematical statistics. Chemical composition analysis revealed greater relative percentages of total organic compounds (TOC) and secondary ions (NO3-, SO42-, and NH4+). The concentrations of Ca2+, Na+, Mg2+, K+ and SO42+ increased in high-concentration PM, which was associated with the contribution of soil, dust and soot. Microbiological analysis revealed 1191 operational taxonomic units. Microbial community structure was stable at the phylum level. The most abundant phyla were Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes and Cyanobacteria. Community clustering analysis at the genus level showed that the difference in bacterial community structure between different PM concentrations (clean air vs. smog) was greater than that between different particle sizes. The dominant genera varied in different concentrations of PM. An unclassified genus of Cyanobacteria and Comamonadaceae were most abundant in low-and high-concentration PM, respectively. The microbial community structure was dynamic at the genus level due to different environmental factors. The dominant bacteria in high-concentration PM were widely distributed in soils, indicating that the soil contributed more to the increase in the PM. The individual microbes that were detected did not increase significantly as the PM concentration increased. The bacterial community structure was strongly correlated with K+, Ca2+, Na+, Mg2+, SO42- and TOC in high-concentration PM and had a good correlation with NO3-, Cl-, NH4+ and TIC in low-concentration PM. Soil and dust contributed to the increase in the concentration of the particles, and the relevant chemical components also produced differences in the bacterial community structure in different concentrations of PM. (C) 2018 Published by Elsevier B.V.
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