Direct treatment of high-strength soft drink wastewater using a down-flow hanging sponge reactor: performance and microbial community dynamics

Abstract

A stand-alone down-flow hanging sponge (DHS) system with a two-stage configuration was operated for 700 days to treat synthetic soft drink wastewater at 3000 mg/L chemical oxygen demand (COD). Throughout the operation, >90% COD and total organic carbon (TOC) removal efficiency was obtained by the first stage, and a final effluent of COD <60 mg/L (TOC <20 mg/L) was consistently maintained with the second stage. Lower organic removal efficiency was observed to closely correlate with lower pH, higher volatile fatty acid (VFA) concentration, and higher suspended solid (SS) in the effluent. Occasionally, biomass sloughing was observed as a cause to unstable reactor performance in the first stage. The microbial community of the retained biomass on the sponges differed significantly based on spatial locations of sponges, sampling time points, and loading shocks. In general, Proteobacteria were found to be more abundant in the reactor at an organic removal efficiency >80% than that at <50%. Specifically, operational taxonomic units closely related to Tolumonas auensis and Rivicola pingtungensis were identified as important populations that were responsible for degrading the major substrate in the soft drink wastewater toward to the end of the reactor operation. In addition, high abundance of Bacteroidetes in the reactor was speculated to be responsible for the VFA accumulation in the effluent. This study demonstrated that stand-alone DHS reactor could be used in treating high-strength wastewater efficiently.

Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process

“…Abundant populations in the upstream process can play active or inactive roles in the downstream. This could not be effectively addressed by many previous studies [4, 5, 11, 13–17]. Coupling a mass balance model with amplicon sequencing data allows the calculation of the net growth rate of individual community members, enabling the differentiation between actively growing populations and non-growing ones.…”

“…However, this method assumes that all the observed microbial populations in the downstream community come from upstream environments and ignores the fact that some active microorganisms will undergo rapid reproduction independent from immigration. Other studies simply count shared species between upstream and downstream communities, which is usually visualized with a Venn diagram [11, 17]. This approach could only provide a numerical summary of potential immigrants and ignores their different fates in the downstream environment.…”