反硝化
流出物
厌氧氨氧化菌
化学
化学需氧量
移动床生物膜反应器
碳纤维
环境工程
环境化学
氮气
废水
环境科学
反硝化细菌
生物膜
材料科学
有机化学
复合数
复合材料
生物
细菌
遗传学
作者
Justin Macmanus,Chenghua Long,Stephanie Klaus,Michael Parsons,Kartik Chandran,Haydée De Clippeleir,Charles Bott
摘要
A pilot study was conducted to investigate the carbon demand requirements and nitrogen removal capabilities of two mainstream partial denitrification/anammox (PdNA) processes: a two-zone, moving bed biofilm reactor (MBBR) process and an integrated fixed-film activated sludge (IFAS) process. The first MBBR zone conducted PdNA, while the second operated as an anammox zone. Operation of the IFAS process was conducted in two phases. The first phase of the operation involved minor external carbon addition, while the second phase of the operation involved controlled external carbon addition. The MBBR process produced an average effluent TIN concentration and chemical oxygen demand (COD)/TIN ratio of 2.81 ± 1.21 mg/L and 2.42 ± 0.77 g/g. The average effluent TIN concentrations and COD/TIN ratios for the IFAS process were 4.07 ± 1.66 mg/L and 1.08 ± 0.38 g/g during phase 1 and 3.30 ± 0.96 mg/L and 2.18 ± 0.99 g/g during phase 2. Despite having relatively low and unstable partial denitrification (PdN) efficiencies, both mainstream PdNA processes exhibited low effluent TIN concentrations and carbon requirements compared to nitrification/denitrification. Successful operation of the PdNA IFAS process indicates that mainstream PdNA can be implemented with minimal capital costs in a water resource recovery facility's second anoxic zone. PRACTITIONER POINTS: Low effluent TIN concentrations can be maintained in mainstream PdNA MBBR and IFAS processes with low external carbon demand. MBBR and IFAS PdNA processes do not require consistent or high PdN efficiencies to maintain low effluent TIN concentrations. IFAS and MBBR PdNA processes exhibit similar TIN and NH3 removal efficiencies. PdNA can be implemented in a second anoxic zone, using IFAS technology for anammox retention, with minimal capital costs.
科研通智能强力驱动
Strongly Powered by AbleSci AI