污水处理系统中N<sub>2</sub>O的生产利用及数据驱动模拟研究进展

徐润泽; 操家顺; 方芳

doi:10.13205/j.hjgc.202206014

污水处理系统中N₂O的生产利用及数据驱动模拟研究进展

doi: 10.13205/j.hjgc.202206014

河海大学环境学院浅水湖泊综合治理与资源开发教育部重点实验室, 南京 210024

基金项目:

国家自然科学基金面上项目"胞内存储物介导下硫自养/异养协同反硝化系统中不同微生物间相互作用机制研究"(52170032)

国家自然科学基金面上项目"温室气体N₂O为电子受体条件下活性污泥胞内PHA的合成机制研究"(51878244)

详细信息

作者简介:
徐润泽(1995-),男,在读博士研究生,主要研究方向为污水资源化。runzexu@hhu.edu.cn

通讯作者:
方芳(1982-),女,副教授,主要研究方向为污水处理及资源化。ffang65@hhu.edu.cn

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出版历程
- 收稿日期: 2022-01-01
- 网络出版日期: 2022-09-01
- 刊出日期: 2022-09-01

RESEARCH PROGRESS ON N₂O RECYCLING AND DATA-DRIVEN MODELING IN WASTEWATER TREATMENT PROCESSES

Key Laboratory of Integrates Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing 210024, China

摘要

摘要: 氧化亚氮(N₂O)是一种温室气体,同时也是具有能源回收潜力的强氧化性物质。综述了促进N₂O产生的新兴污水脱氮过程及提高N₂O产生的方法,比较了不同方法的运行条件及N₂O转化率,并指出了各种方法的不足之处。从识别N₂O产生的关键影响因素和预测N₂O产量2个方面综述了污水处理过程中N₂O数据驱动模型的研究进展。目前N₂O的增产方法主要包括耦合好氧-缺氧氮分解过程、单反应器生产过程及基因工程菌和半导体修饰菌增产过程。收集污水处理厂中的大数据可以建立N₂O数据驱动模型,但是现有的数据驱动模型仅仅关注N₂O减排。开发N₂O的新型增产过程,优化控制增产过程的功能菌种,建立N₂O数据驱动模型与N₂O增产方法之间的关联性是未来N₂O生产利用技术的发展方向。
- 氧化亚氮 /
- 污水处理 /
- 机器学习 /
- 能源回收 /
- 脱氮
Abstract: Nitrous oxide (N₂O) is a greenhouse gas and a strong oxidizing substance with the potential of energy recovery.This paper critically reviewed the novel nitrogen removal bioprocesses and methods for increasing N₂O production from wastewater.The operating conditions and N₂O conversion efficiencies in these bioprocesses were compared.Then,the shortages of these methods were pointed out.Moreover,this paper comprehensively reviewed the research progress on data-driven modeling of N₂O emission in wastewater treatment processes from two perspectives:1) identifying key factors related to N₂O,and 2) predicting N₂O production.Currently,the main methods for recovering N₂O include coupled aerobic-anoxic nitrous decomposition operation (CANDO),single reactor process,applications of recombinant strains or semiconductor modification strains.Big data of wastewater treatment plants could be utilized to establish the data-driven models for N₂O emissions,whereas the existing N₂O models mainly focus on reducing N₂O emission.The future trends of N₂O recovery include:1) developing new methods for recovering N₂O;2) optimizing functional microbes in N₂O recovering processes;3) establishing the relationships between data-driven modeling of N₂O and N₂O recovering processes.
- nitrous oxide /
- wastewater treatment /
- machine learning /
- energy recovery /
- nitrogen removal

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