Simultaneous enhancement of nitrate removal flux and methane utilization efficiency in MBfR for aerobic methane oxidation coupled to denitrification by using an innovative scalable double-layer membrane.

Water research(2021)

引用 13|浏览11
暂无评分
摘要
Endevours on the enhancement of nitrate removal efficiency during methane oxidation coupled with denitrification (AME-D) has always overlooked the role of membrane employed. It would be highly beneficial to enrich the biomass content and to manage biofilm on the membrane, in the utilization of methane and denitrification. In this study, an innovative and scalable double-layer membrane (DLM) was designed and prepared for a membrane biofilm reactor (MBfR), to simultaneously enhance nitrate removal flux and methane utilization efficiency during aerobic methane oxidation coupled with the denitrification (AME-D) process. The DLM allowed quick bacterial attachment and biomass accumulation for biofilm growth, which would be then self-regulated for well distribution of functional microbes on/within the DLM. Upon a high biofilm density of over 70 g-VSS m-2 achieved on the DLM, the methane utilization efficiency of the MBfR was enhanced significantly to over 1.3 times than the control MBfR with conventional polypropylene membrane. The MBfR employed DLM also demonstrated the maximum nitrate removal flux of 740 mg-NO3--N m-2 d-1 that was approximately 1.64 times of that in control MBfR at continuous-mode operation. This DLM indeed favored the enrichment of Type II aerobic methanotrophs of Methylocystaceae, and methanol-utilization denitrifiers of Rhodocyclaceae that preferentially utilize methanol as the cross-feeding intermediates to promote the methane utilization efficiency, and thus to enhance the nitrate removal flux. These results raised from new designed DLM confirmed the importance of membrane surface properties on the effectiveness of MBfR, and offered great potential to address challenging problems of MBfRs during engineering application.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要