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基于多阶段氨氧化的部分硝化/厌氧氨氧化/部分硝化/厌氧氨氧化(PN/A/PN/A)工艺的建立与优化:以响应面法为工具。

Establishment and optimization of partial nitrification/anammox/partial nitrification/anammox (PN/A/PN/A) process based on multi-stage ammonia oxidation: Using response surface method as a tool.

机构信息

Key Laboratory of Water Science and Water Environment Recovery Engineering, Beijing University of Technology, Beijing 100123, China.

Key Laboratory of Water Science and Water Environment Recovery Engineering, Beijing University of Technology, Beijing 100123, China.

出版信息

Bioresour Technol. 2022 Oct;361:127722. doi: 10.1016/j.biortech.2022.127722. Epub 2022 Jul 30.

Abstract

The presence of nitrite-oxidizing bacteria (NOB) when treating low-strength ammonia wastewater was a challenge in the application of the PN/A process. The partial nitrification/ANAMMOX/partial nitrification/ANAMMOX (PN/A/PN/A) process based on multiple oxidations of ammonia was proposed to solve this problem. The influence of independent variables such as nitrite concentration was analyzed based on the response surface method (RSM). The model showed that nitrite concentration has an adverse impact on ammonia removal efficiency and nitrite accumulation rate. The model provided optimal parameters for the PN/A/PN/A process: the dissolved oxygen concentration was 0.60 mg/L, and the cycle duration was 90 min. Advanced nitrogen removal was achieved by maintaining the nitrite concentration below 10.0 mg/L. The nitrogen removal efficiency was 81.44 ± 4.15 %, and the nitrogen removal rate was 0.18 ± 0.02 kg N/(m⋅d). Potential functions of microorganisms were analyzed by functional annotation of prokaryotic taxa (FAPROTAX) and the correlation network analysis was performed.

摘要

在处理低浓度氨废水时,存在亚硝酸盐氧化菌 (NOB) 是 PN/A 工艺应用中的一个挑战。基于氨的多次氧化,提出了部分硝化/厌氧氨氧化/部分硝化/厌氧氨氧化 (PN/A/PN/A) 工艺来解决这个问题。基于响应面法 (RSM) 分析了亚硝酸盐浓度等自变量的影响。该模型表明,亚硝酸盐浓度对氨去除效率和亚硝酸盐积累率有不利影响。该模型为 PN/A/PN/A 工艺提供了最佳参数:溶解氧浓度为 0.60mg/L,周期持续时间为 90min。通过将亚硝酸盐浓度保持在 10.0mg/L 以下,实现了先进的脱氮。氮去除效率为 81.44±4.15%,氮去除速率为 0.18±0.02kgN/(m⋅d)。通过对原核分类群的功能注释 (FAPROTAX) 分析微生物的功能潜力,并进行相关网络分析。

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