颗粒(地质)
无氧运动
序批式反应器
化学
人口
化学工程
废水
制浆造纸工业
废物管理
环境工程
材料科学
环境科学
生物
复合材料
工程类
生理学
人口学
社会学
作者
Viktor A. Haaksman,M. Schouteren,Mark C.M. van Loosdrecht,Mario Pronk
出处
期刊:Water Research
[Elsevier BV]
日期:2023-02-27
卷期号:233: 119803-119803
被引量:26
标识
DOI:10.1016/j.watres.2023.119803
摘要
There is a growing interest to implement aerobic granular sludge (AGS) in existing conventional activated sludge (CAS) systems with a continuous flow-through configuration. The mode of anaerobic contact of raw sewage with the sludge is an important aspect in the adaptation of CAS systems to accommodate AGS. It remains unclear how the distribution of substrate over the sludge by a conventional anaerobic selector compares to the distribution via bottom-feeding applied in sequencing batch reactors (SBRs). This study investigated the effect of the anaerobic contact mode on the substrate (and storage) distribution by operating two lab-scale SBRs; one with the traditional bottom-feeding through a settled sludge bed similar to full-scale AGS systems, and one where the synthetic wastewater was fed as a pulse at the start of the anaerobic phase while the reactor was mixed through sparging of nitrogen gas (mimicking a plug-flow anaerobic selector in continuous flow-through systems). The distribution of the substrate over the sludge particle population was quantified via PHA analysis, combined with the obtained granule size distribution. Bottom-feeding was found to primarily direct substrate towards the large granular size classes (i.e. large volume and close to the bottom), while completely mixed pulse-feeding gives a more equal distribution of substrate over all granule sizes (i.e. surface area dependant). The anaerobic contact mode directly controls the substrate distribution over the different granule sizes, irrespective of the solids retention time of a granule as an entity. Preferential feeding of the larger granules will enhance and stabilise the granulation compared to pulse-feeding, certainly under less advantageous conditions imposed by real sewage.
科研通智能强力驱动
Strongly Powered by AbleSci AI