摘要
利用典型的活性污泥实验了辛基酚(octylphenol,OP)的生物降解性能。研究了水力停留时间、OP浓度和碳氮比对OP处理效率的影响,通过实时PCR和PCR-DGGE方法分别分析了微生物群落的总体密度和多样性变化。通过30d的启动,OP在序批式活性污泥典型好氧条件下出现有效生物降解。在OP浓度50~150μg/L整个实验过程中,OP去除率(84%~99%)基本保持稳定。在实验范围内,较长的水力停留时间(12 h)和碳氮比(2∶1)有利于OP生物降解。通过实时PCR方法测定得到系统微生物平均密度约为1.22 g/L,但富碳状态下生物密度增长上升。通过DGGE分离到17种优势基因型,包括了α-proteobacteria(6种)、β-proteobacteria(5种)、γ-proteobacteria(2种)、Actinobacteria(2种)和δ-proteobacteria(1种)群落。α-proteobacteria和δ-proteobacteria菌群密度呈现增长,β-proteobacteria和Actinobacteria菌群中的部分种类密度出现减少,OP在活性污泥中的好氧生物降解可能与α-proteobacteria中的特定类别相关。
Traditional activated sludge process was employed to investigate the influence of HRT, initial OV concentration and C/N on aerobic OP biodegradation. Real-time PCR and PCR-DGGE methods were applied re- spectively to analyze the variety in population concentration and bio-diversity of the bacterial community. After 30 days start-up, an effective OP biodegradation appeared in the lab-scale sequencing batch reactor (SBR) un- der aerobic conditions. With influent OP concentrations of 50 -150 p.g/L throughout the entire experiment, OP removal rate remained relatively stable, ranging from 94% to 99% ~ It was demonstrated that a long HRT ( 12 h) and low C/N (2:1 ) was beneficial for OP biodegradation. The mean population concentration of the bacterial was about 1.22 g/L, however it seemed to increase under carbon-riched condition. 17 dominant bacterial strains were separated from DGGE gel, which were divided into vt-proteobacter^a (6 strains), f3-proteobacteria (5 strains) , T-proteobacteria (2 strains) , Actinobacteria (2 strains) and ^-proteobacteria ( 1 strain) , respectively. According to DGGE profiles, a-proteobacteria and Actinobacteria population showed gradually growth, while some strains of fl-proteobacteria and Actinobacteria population appeared to reduce over operation time. The effective aerobic degradation of OP in the activated sludge may be related to specific strains of a-proteobacteria.
出处
《环境工程学报》
CAS
CSCD
北大核心
2012年第8期2903-2908,共6页
Chinese Journal of Environmental Engineering
基金
国家科技支撑计划课题(2009BAC57B01)