Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29721
Title: Treatment of high-strength saline bilge wastewater by four pilot-scale aerobic moving bed biofilm reactors and comparison of the microbial communities
Authors: Mazioti, Aikaterini A 
Vyrides, Ioannis 
Major Field of Science: Engineering and Technology
Field Category: Chemical Engineering
Keywords: aerobic biological treatment;biofilm;Industrial saline wastewater;microbial community;suspended biomass
Issue Date: 31-Oct-2022
Source: Environmental Technology (United Kingdom), 2022
Abstract: Four Pilot-scale Moving Bed Biofilm Reactors (MBBRs) were operated for the treatment of real, saline, bilge wastewater. The MBBRs were connected in pairs to create two system configurations with different filling ratios (20%, 40%) and were operated in parallel. The inflow organic loading rate (OLR) varied from 3.6 ± 0.2 to 7.8 ± 0.6 g COD L-1 d-1, salinity was >15 ppt and three hydraulic residence times (HRTs) were tested 48, 30 and 24 h. In both systems, the first-stage bioreactors (R1 and R3) eliminated the higher part of the organic load (57%-65%). The second-stage bioreactors (R2 and R4) removed an additional fraction (18%-31%) of the organic load received by the effluent of R1 and R3, respectively. The microbial communities of the influent wastewater, suspended, and attached biomass were determined using 16S rRNA gene amplicon sequencing analysis. The evolution of the microbial communities was investigated and compared over the different operational phases. The microbial communities of the biofilm presented higher diversity and greater stability in composition over time, while the suspended biomass exhibited intense and rapid changes in the dominance of genera. Proteobacteria, Bacteroidetes and Firmicutes were highly present in the biofilm. The genera Celeribacter, Novispirillum, Roseovarius (class: Alphaproteobacteria) and Formosa (class: Flavobacteriia) were highly present during all operational phases. Principal Component Analysis (PCA) was used to identify similarities between samples, exhibiting high relation of samples according to the series of the bioreactor (1st, 2nd).
URI: https://hdl.handle.net/20.500.14279/29721
ISSN: 09593330
DOI: 10.1080/09593330.2022.2137436
Rights: © Informa UK Limited, trading as Taylor & Francis Group
Type: Article
Affiliation : Cyprus University of Technology 
University of the Aegean 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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