厌氧氨氧化菌
反硝化
移动床生物膜反应器
化学
硝酸盐
反硝化细菌
流出物
生物量(生态学)
生物膜
环境化学
环境工程
制浆造纸工业
氮气
环境科学
细菌
农学
生物
遗传学
工程类
有机化学
作者
Yu Li,Yi‐Ting Wang,Xin Tian,Fan Ye,Yexing Liu,Jing Yang,Long Li
标识
DOI:10.1016/j.cej.2023.141890
摘要
Partial denitrification (PD) and anaerobic ammonia oxidation (anammox) are modern treatment processes that can be combined to provide energy- and resource-efficient nitrogen removal methods; however, these processes are challenging to implement as a one-stage hybrid system. The coupling forms to achieve steady long-term PD/anammox operation need to be investigated. In this study, two reactors were operated for 300 days at 25 ± 1℃, in which one was inoculated with PD biofilms and anammox biofilms in a moving bed biofilm reactor (MBBR), and the other was inoculated with PD flocs and anammox biofilms in an integrated fixed-film activated sludge (IFAS) reactor. The results showed that the IFAS reactor had suprerior nitrogen removal performance, with the effluent total nitrogen (TN) concentration in the MBBR and IFAS of 5.17 ± 0.94 mg∙L−1 and 1.52 ± 0.75 mg∙L−1, respectively. Illumina MiSeq sequencing showed that Thauera and OLB8 were the dominant nitrate-reducing denitrifiers in PD biofilms in MBBR and flocs in IFAS, respectively. Since Thauera tended to selectively immigrate to the anammox biofilms, nitrate-reducing denitrifiers and anammox bacteria (AnAOB) coexisted in the anammox biofilms in MBBR. This decreased the PD activity (486.14 ± 23.04 mg∙(L∙d)−1 to 249.66 ± 26.90 mg∙(L∙d)−1) in the PD biofilms. On the contrary, nitrate-reducing denitrifiers and AnAOB were separately allocated in flocs and anammox biofilms in the IFAS reactor. The retention of PD biomass and superior mass transfer performance of the activated sludge flocs maintained a higher PD activity (2193.20 ± 26.62 mg∙(L∙d)−1), which provided sufficient NO2−-N for AnAOB and was beneficial to the growth of AnAOB. Hence, IFAS may be a potentially superior coupling mode for the PD/anammox process for engineering applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI