No abstract

No abstract

No abstract

The study of spatio-temporal variability of airborne bacterial communities has recently gained importance due to the evidence that airborne bacteria are involved in atmospheric processes and can affect human health. In this work, we described the structure of airborne microbial communities in two urban areas (Milan and Venice, Northern Italy) through the sequencing, by the Illumina platform, of libraries containing the V5-V6 hypervariable regions of the 16S rRNA gene and estimated the abundance of airborne bacteria with quantitative PCR (qPCR). Airborne microbial communities were dominated by few taxa, particularly Burkholderiales and Actinomycetales, more abundant in colder seasons, and Chloroplasts, more abundant in warmer seasons. By partitioning the variation in bacterial community structure, we could assess that environmental and meteorological conditions, including variability between cities and seasons, were the major determinants of the observed variation in bacterial community structure, while chemical composition of atmospheric particulate matter (PM) had a minor contribution. Particularly, Ba, SO4 (2-) and Mg(2+) concentrations were significantly correlated with microbial community structure, but it was not possible to assess whether they simply co-varied with seasonal shifts of bacterial inputs to the atmosphere, or their variation favoured specific taxa. Both local sources of bacteria and atmospheric dispersal were involved in the assembling of airborne microbial communities, as suggested, to the one side by the large abundance of bacteria typical of lagoon environments (Rhodobacterales) observed in spring air samples from Venice and to the other by the significant effect of wind speed in shaping airborne bacterial communities at all sites.

Urban air quality represents a major public health burden and is a long-standing concern to European citizens. Combustion processes and traffic-related emissions represent the main primary particulate matter (PM) sources in urban areas. Other sources can also affect air quality (e.g., secondary aerosol, industrial) depending on the characteristics of the study area. Thus, the identification and the apportionment of all sources is of crucial importance to make effective corrective decisions within environmental policies. The aim of this study is to evaluate the impacts of different emissions sources on PM2.5 concentrations and compositions in a mid-size city in the Po Valley (Treviso, Italy). Data have been analyzed to highlight compositional differences (elements and major inorganic ions), to determine PM2.5 sources and their contributions, and to evaluate the influence of air mass movements. Non-parametric tests, positive matrix factorization (PMF), conditional bivariate probability function (CBPF), and concentration weighted trajectory (CWT) have been used in a multi-chemometrics approach to understand the areal-scale (proximate, local, long-range) where different sources act on PM2.5 levels and composition. Results identified three levels of scale from which the pollution arose: (i) a proximate local scale (close to the sampling site) for traffic non-exhaust and resuspended dust sources; (ii) a local urban scale (including both sampling site and areas close to them) for combustion and industrial; and (iii) a regional scale characterized by ammonium nitrate and ammonium sulfate. This approach and results can help to develop and adopt better air quality policy action