Study on Enhancement of Denitrification Performance of Alcaligenes faecalis

IF 2.5 4区 工程技术 Q3 CHEMISTRY, ANALYTICAL
Zicheng Luo, Shugen Hu, Yameng Zhang, Guanlong Yu, Yunhe Yang, Qing Li, Peng Duan
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Abstract

Nitrogen pollution in water bodies presents a serious threat to ecosystems due to its role in eutrophication. In this study, the aerobic denitrifying bacterium Alcaligenes faecalis was used as a model microorganism to investigate the optimal operating conditions for nitrogen removal from nitrogen-containing wastewater by Alcaligenes faecalis under different aeration modes, microbial dosages and C/N ratios. The results showed that the optimal aeration mode for efficient bacterial denitrification was 10 min of aeration with a 30 min interval, and the total nitrogen removal reached 87.82%. At different bacterial doses, NO3−–N was completely denitrified and NO2−–N accumulation levels were reduced, all of which resulted in significant denitrification, and the final total nitrogen removal efficiencies reached 86.39–98.50%. With an increase in the C/N ratio, the pollutant removal performance of denitrifying bacteria increased. When the C/N ratio was 17, the final rates of NO3−–N, TN and COD removal were 100%, 98.50% and 96.13%, respectively. At lower C/N ratios, the growth and metabolism of microorganisms were inhibited and fewer electron acceptors were available during the denitrification process, which seriously affected denitrification performance. In this study, the denitrification performance of aerobic denitrifying bacterium Alcaligenes faecalis was explored in experiments using changes in aeration mode, microbial dosage and C/N ratio, and the optimal operating conditions of Alcaligenes faecalis for treating nitrogenous wastewater were indicated. This provides technical support for Alcaligenes faecalis in improving the remediation effect of nitrogenous wastewater and provides a theoretical basis for further in-depth research on the performance of Alcaligenes faecalis in the future.
关于提高粪阿卡菌反硝化性能的研究
水体氮污染对水体富营养化具有重要影响,对生态系统构成严重威胁。本研究以好氧反硝化菌粪碱性碱性菌(Alcaligenes faecalis)为模型微生物,考察了不同曝气方式、微生物投加量和C/N比下粪碱性碱性碱性菌对含氮废水脱氮的最佳操作条件。结果表明,细菌反硝化的最佳曝气方式为曝气10 min,曝气间隔30 min,总氮去除率达87.82%。在不同细菌剂量下,NO3−-N被完全反硝化,NO2−-N积累水平降低,反硝化效果显著,最终总氮去除率达到86.39 ~ 98.50%。随着C/N比的增加,反硝化细菌对污染物的去除性能提高。当C/N为17时,NO3−-N、TN和COD的最终去除率分别为100%、98.50%和96.13%。C/N较低时,微生物的生长和代谢受到抑制,反硝化过程中可用电子受体较少,严重影响反硝化性能。本研究通过改变曝气方式、微生物投加量和C/N比,探讨好氧反硝化菌粪碱性碱性菌(Alcaligenes faecalis)的反硝化性能,指出粪碱性碱性菌(Alcaligenes faecalis)处理含氮废水的最佳操作条件。这为粪藻藻提高含氮废水的修复效果提供了技术支持,也为今后进一步深入研究粪藻藻的性能提供了理论基础。
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来源期刊
Separations
Separations Chemistry-Analytical Chemistry
CiteScore
3.00
自引率
15.40%
发文量
342
审稿时长
12 weeks
期刊介绍: Separations (formerly Chromatography, ISSN 2227-9075, CODEN: CHROBV) provides an advanced forum for separation and purification science and technology in all areas of chemical, biological and physical science. It publishes reviews, regular research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, unique features of this journal: Manuscripts regarding research proposals and research ideas will be particularly welcomed. Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. Manuscripts concerning summaries and surveys on research cooperation and projects (that are funded by national governments) to give information for a broad field of users. The scope of the journal includes but is not limited to: Theory and methodology (theory of separation methods, sample preparation, instrumental and column developments, new separation methodologies, etc.) Equipment and techniques, novel hyphenated analytical solutions (significantly extended by their combination with spectroscopic methods and in particular, mass spectrometry) Novel analysis approaches and applications to solve analytical challenges which utilize chromatographic separations as a key step in the overall solution Computational modelling of separations for the purpose of fundamental understanding and/or chromatographic optimization
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