Distribution of Total Microbes in Atmospheric Bioaerosols in the Coastal Region of Qingdao

Abstract

In order to determine the concentrations and size distributions of total airborne microbes in atmospheric bioaerosols, bioaerosol samples were collected in the coastal region of Qingdao, China, from Sep. 2016 to Jul. 2017 using size-fractionated bioaerosol samplers. The concentrations of total airborne microbes were then measured using an epifluorescence microscope after staining with DAPI (4', 6-diamidino-2-phenylindole). The results showed that the concentrations of total airborne microbes were in the range of 1.86×105-2.54×106 cells·m-3 in Qingdao during the sampling period, with an average of (6.84±4.83)×105 cells·m-3. The concentrations of total airborne microbes showed seasonal variation, with the highest values occurring in spring and winter, and the lowest values in summer and fall. Statistical analysis showed that the concentrations of total airborne microbes in autumn had a significant seasonal difference with spring and summer (P<0.05). The monthly averaged concentrations of total airborne microbes ranged from 2.65×105 cells·m-3 to 1.12×106 cells·m-3, with the highest values in Feb. 2017 and the lowest in Sep. 2016. Total microbe concentrations also varied greatly over a diurnal timescale in fall and winter during the period of 2015 to 2017, but this variation was not statistically significant (P>0.05). Overall, the size distribution of total airborne microbes was skewed, with the highest ratio occurring at >7.0 μm with a ratio of 20.5%-27.3%. The monthly averaged size distribution of total airborne microbes varied between months, showing two main distribution types, specifically bimodal and skewed patterns, respectively. Spearman's rank correlation analysis showed that the AQI and the concentrations of CO, PM2.5, and PM10 had a significant positive correlation with the concentrations of total airborne microbes (P<0.05), while air temperature, wind speed and direction, NO2, SO2, and O3 were not significantly correlated with the airborne microbe concentration during the sampling period (P>0.05). Multiple linear regression showed that 20.6% of the variation in the total microbe concentrations in bioaerosols correlated with relative humidity and PM2.5.