摘要
启动周期长是单级全程自养脱氮工艺(CANON)的主要制约因素之一.本文研究了基于淹没式生物滤池(SBAF)的CANON工艺的快速启动方法.首先,以城镇污水处理厂二沉池中普通活性污泥为种泥,在(30±2)℃、不添加有机碳源,控制DO(阶段Ⅰ:0.3~0.5 mg·L^(-1),阶段Ⅱ~Ⅳ:0.1~0.2 mg·L^(-1))的实验条件下,经过48 d对污泥微生物的驯化,成功启动了CANON工艺,氨氮(NH+4-N)和总氮(TN)最大去除率分别达到99.9%和86.5%.其次,采用16S r DNA宏基因组高通量测序技术研究了体系内微生物种群结构特性.测序结果显示体系内两个优势微生物菌门是Proteobacteria(变形菌门)和Planctomycetes(浮霉菌门),平均分别占比26.6%和17.8%,主要脱氮微生物是β-Proteobacteria中的Nitrosomonas和Brocadiae中的Candidatus brocadia.通过以上实验分析得出:采用SBAF启动CANON技术,具有可实现体系快速启动、生物高效脱氮、过程稳定运行等特性.
Long period start-up is one of the main restraining factors of the single-stage completely autotrophic nitrogen removal over nitrite（ CANON） process. This study investigated the fast start-up of the CANON process initiated by a submerged biological aerated filter（ SBAF） method. With conventional activated sludge from the secondary sedimentation tank of municipal waste water treatment plants as the seed sludge,the CANON process was successfully started up after the acclimation of sludge microorganisms for 48 days under the experimental conditions of（ 30 ± 2） ℃,organic carbon free and controlled dissolved oxygen（ stage Ⅰ： 0. 3-0. 5 mg·L^-1;stage Ⅱ-Ⅳ： 0. 1-0. 2 mg·L^-1）,with the maximum removal rates of ammonia nitrogen and total nitrogen achieved at 99. 9% and86. 5%,respectively. The population structure characteristics of microorganisms in the system were studied using high-throughput sequencing of 16 S r DNA amplicon. The results demonstrated that the two dominant microbial strains in the system were Proteobacteria and Planctomycetes,accounting for 26. 6% and 17. 8%,respectively. The major contributors of nitrogen removal were Nitrosomonas inβ-Proteobacteria and Candidatus brocadia in Brocadiae. Through the above experiments,it was revealed that the investigated SBAF based CANON possesses had the advantages of fast start-up,efficient biological nitrogen removal and stable operation process.
作者
刘竹寒
岳秀
于广平
金腊华
唐嘉丽
吉世明
LIU Zhu-han YUE Xiu YU Guang-ping JIN La-hua TANG Jia-li JI Shi-ming(School of Environment, Jinan University, Guangzhou 510632,China Shenyang Institute of Automation in Guangzhou, Chinese Academy of Sciences, Guangzhou 5114581 China)
出处
《环境科学》
EI
CAS
CSCD
北大核心
2017年第1期253-259,共7页
Environmental Science
基金
广州市科技计划项目(201510010199)
