泥浆
结垢
膜污染
剥离(纤维)
化学
氨
膜
沼气
制浆造纸工业
化学工程
废物管理
环境工程
环境科学
材料科学
有机化学
生物化学
工程类
复合材料
作者
Cong Chen,Zhinan Dai,Yifan Li,Qin Zeng,Yang Yu,Xin Wang,Changyong Zhang,Le Han
出处
期刊:Water Research
[Elsevier]
日期:2023-02-01
卷期号:229: 119453-119453
被引量:17
标识
DOI:10.1016/j.watres.2022.119453
摘要
Hydrophobic gas permeable membranes (GPMs) exhibit great potential in stripping or recovering ammonia from wastewater, but they also suffer from severe fouling issues due to the complex water matrix, since the related process is often operated under highly alkaline conditions (pH > 11). In this study, we proposed a novel membrane stripping process by integrating a cation exchange membrane (CEM) in alkali-driven Donnan dialysis prior to GPM for efficient and robust ammonia recovery from real biogas slurry. During the conventional stripping for diluted biogas slurry, the ammonia removal across GPM finally decreased by 15% over 6 consecutive batches, likely due to the obvious deposition of inorganic species and penetration of organic compounds (rejection of 90% only). In contrast, a constant ammonia removal of 80% and organic matter rejection of more than 99%, as well as negligible fouling of both membranes, were found for the proposed novel stripping process operated over 120 h. Our results demonstrated that additional divalent cations clearly aggravated the fouling of GPM in conventional stripping, where only weak competition across CEM was found in the CEM-GPM hybrid mode. Then, for raw biogas slurry, the new stripping achieved a stable ammonia removal up to 65%, and no fouling occurrence was found, superior to that in the control (declined removal from 87% to 55%). The antifouling mechanism by integrating CEM prior to GPM involves size exclusion and charge repulsion towards varying foulants. This work highlighted that the novel membrane stripping process of hybrid CEM-GPM significantly mitigated membrane fouling and can be regarded as a potential alternative for ammonia recovery from high-strength complex streams.
科研通智能强力驱动
Strongly Powered by AbleSci AI