A novel technology with precise oxygen-input control: application of the partial nitritation-anammox process

2020 
Abstract Reliable and accurate oxygen-input control, which is critical to maintaining efficient nitrogen removal performance for partial nitritation-anammox (PN-A) process, remains one of the main operational difficulties. In this study, a novel, yet simple system (a simple process for autotrophic nitrogen-removal, SPAN) with precise oxygen-input control was developed to treat ammonium-rich wastewater via PN-A process. SPAN brings oxygen to biomass by circulating water and creating water spray (shower) at the water-air interface, and effectively balances the activities of core functional microorganisms through precise oxygen-input control. The oxygen-input rate is decided by the water circulation rate and shower rate and is measurable and predictable. Therefore, the required amount of oxygen for ammonium oxidation can be precisely delivered to the biomass by adjusting the circulation rate and shower rate. The results of two parallel SPAN reactors demonstrated that during long-term operation, the required oxygen input was precisely and reliably controlled. More than 99% of NH4+-N and 81% - 85% of total nitrogen were stably removed, with anammox bacteria contributing to more than 96% of total nitrogen removal. Anammox bacteria were efficiently enriched to the highest level among the key nitrogen-converting microbial groups, both in terms of abundance (8.17%) and nitrogen-conversion capacity, while ammonium oxidizing bacteria were well controlled to provide sufficient ammonium-oxidizing capacity. Nitrite oxidizing bacteria were maintained stable (relative abundance of 1.08%-1.88%) and their activity was effectively suppressed. This study provided a novel technology, SPAN, to precisely control oxygen input in PN-A system, and proved that SPAN was effective and reliable in achieving long-term high-efficiency nitrogen removal.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    43
    References
    9
    Citations
    NaN
    KQI
    []