State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment , Tsinghua University , Beijing , China , 100084.
Advanced Water Management Centre , The University of Queensland , St. Lucia , QLD 4072 , Australia.
Environ Sci Technol. 2018 Jun 5;52(11):6457-6465. doi: 10.1021/acs.est.8b00202. Epub 2018 May 22.
Ammonium partial oxidation to nitrite (i.e., partial nitritation) is required in a two-stage autotrophic nitrogen removal system, to provide effluent suitable for the anammox reaction. This study aims to establish influent (ammonium and bicarbonate concentrations) and operational (dissolved oxygen (DO) concentration and solids retention time (SRT)) conditions that favor partial nitritation. This is achieved through extending the nitritation and nitratation models to predict pH variation as well as the effects of pH, free ammonia (NH), and free nitrous acid (HNO) on the two reactions. Experiments were performed on a lab-scale sequencing batch reactor (SBR) operated for over 500 days to provide dynamic data for the calibration of model parameters, particularly those related to the NH and HNO inhibition on nitrite-oxidizing bacteria (NOB). The influent ammonium (19-84 mM) and bicarbonate (23-72 mM) were varied, which led to dynamic ammonium, nitrite, and nitrate data suitable for model calibration and validation. The model was able to well-describe pH dynamics as well as the inhibitory effects of NH and HNO on NOB. Model-based scenario analysis was then undertaken to establish the joint regions of influent ammonium and bicarbonate concentrations and the operational DO, temperature, and SRT conditions that favor partial nitritation. The results provide support to the design and optimization of partial nitritation reactors.
亚硝酸盐的氨部分氧化（即部分硝化）是两段式自养脱氮系统所必需的，以提供适合厌氧氨氧化反应的出水。本研究旨在确定进水（氨和碳酸氢盐浓度）和操作（溶解氧（DO）浓度和固体停留时间（SRT））条件，以有利于部分硝化。这是通过扩展硝化和反硝化模型来预测 pH 值变化以及 pH 值、游离氨（NH）和游离亚硝酸（HNO）对两种反应的影响来实现的。实验在实验室规模的序批式反应器（SBR）上进行了超过 500 天，以提供动态数据用于模型参数的校准，特别是与 NH 和 HNO 对亚硝酸氧化菌（NOB）的抑制有关的参数。进水氨（19-84mM）和碳酸氢盐（23-72mM）变化，导致了适合模型校准和验证的动态氨、亚硝酸盐和硝酸盐数据。该模型能够很好地描述 pH 动力学以及 NH 和 HNO 对 NOB 的抑制作用。然后进行了基于模型的情景分析，以确定有利于部分硝化的进水氨和碳酸氢盐浓度以及操作 DO、温度和 SRT 条件的联合区域。结果为部分硝化反应器的设计和优化提供了支持。
