Study on cultivation of aerobic granular sludge and its application in degrading lignin models in the sequencing batch biofilter granular reactor

Abstract

In this study, three sequencing batch biofilter granular reactors (SBBGRs) were employed to treat model lignin wastewater containing different lignin models (2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin). After 40 days of cultivation, uniform-shaped aerobic granular sludge (AGS) was successfully developed through nutrient supplementation with synthetic wastewater. During the acclimation stage, the chemical oxygen demand (COD) reduction efficiencies of the three reactors showed a trend of initial decreasing (5–20%) and then recovering to a high reduction efficiency (exceeding 90%) in a short period of time. During the stable operation stage, all three reactors achieved COD reduction efficiencies exceeding 90%. These findings indicated the cultivated AGS's robust resistance to changes in lignin models in water. UV–Vis spectra analysis confirmed the effective degradation of the three lignin models. Microbiological analysis showed that Proteobacteria and Bacteroidetes were always the dominant phyla. At the genus level, while Acinetobacter (15.46%) dominated in the inoculation sludge, Kapabacteriales (7.93%), SBR1031 (11.77%), and Chlorobium (25.37%) were dominant in the three reactors (for 2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin) after degradation, respectively. These findings demonstrate that AGS cultured with SBBGR effectively degrades lignin models, with different dominant strains observed for various lignin models. HIGHLIGHTS The aerobic granular sludge cultivated in SBBGR was applied to treat lignin models and demonstrated excellent impact resistance.; The high sludge concentration and diverse microbial community enable effective lignin model degradation.; Different strains dominated the cultured AGS in three reactors that degraded 2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin, respectively.;

Keywords

• aerobic granular sludge
• lignin models
• microorganism
• sbbgr