Sludge floc characteristics and microbial community in high-rate activated sludge and high-rate membrane bioreactor for organic recovery

Abstract

High-rate activated sludge (HRAS) and high-rate membrane bioreactor (HRMBR) are considered as potential processes for organic recovery through bioflocculation and biosorption of particulate COD and colloidal COD with sludge flocs. In this study, bioflocculation and biosorption, in terms of sludge floc characteristics and microbial community, in HRAS and HRMBR was investigated in relation to organic recovery performance for low strength wastewater treatment. HRAS and HRMBR were operated at two different solids retention times (SRTs) of 2 and 0.8 days. Reducing the SRT of HRAS from 2.0 to 0.8 days resulted in failure in total COD (tCOD) removal efficiency (from 79 ± 2 to 34 ± 13 %) and lowering organic recovery (from 40.8 to 15.7 %). This contrasted with HRMBR, which showed high tCOD removal efficiency (84 ± 2 and 84 ± 1 %) and organic recovery (43.4 and 46.3 %) at both SRTs of 2.0 and 0.8 days. Analysis of sludge floc characteristics showed that the lower organic recovery of the HRAS operated at an SRT of 0.8 days could be associated with poor bioflocculation and biosorption, as evidenced by relatively larger floc size, higher extracellular polymeric substance, higher protein/polysaccharide ratio, and higher zeta potential value of the sludge. These characteristics were in contrast to the HRMBR operated at an SRT of 0.8 days, that exhibited the highest organic recovery among the reactors studied. The microbial taxa Bdellovibrio, Clostridium sensu stricto 9, Hyphomicrobium, and Ideonella could play a role in the poor bioflocculation and biosorption in HRAS. Rhodanobacter, Enterobacter, Terrimonas, Nakamurella, and Mizugakiibacter may be associated with bioflocculation and biosorption and organic recovery in HRMBR. The results of this study enhanced our understanding on the relationships between the microbial community, sludge floc characteristics, and organic recovery performance of HRAS and HRMBR for future optimization of the systems.