厌氧氨氧化工艺处理氧化铁红废水的工程研究

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Abstract In this study, a full-scale CANON system was constructed to treat high ammonia nitrogen iron oxide wastewater following physicochemical pretreatment. Over the course of 165days of continuous operation, the CANON system demonstrated excellent stability and shock resistance, achieving ammonia and total nitrogen removal efficiencies (TNRE) of 90% and 80%, respectively. Spearman correlation analysis and SHAP feature importance analysis were employed to elucidate the impact of water quality and environmental parameters on TNRE. Microbial community profiling unveiled substantial shifts in microbial population structures within the system, marked by the transition of the dominant anammox bacteria from Candidatus Anammoxoglobus to Candidatus Kuenenia, accounting for a relative abundance of 13.22%. Nitrosomonas was identified as the predominant ammonium-oxidizing bacteria with a relative abundance of 1.27%. Additionally, a machine learning model based on XGBoost was developed, which achieved a predictive accuracy of over 99.9% for TNRE, with a prediction precision of 98% for new data points in practical applications. This research provides valuable empirical insights into the engineering application and intelligent development of anammox processes.

Key words： anammox iron oxide red wastewater microbial community machine learning model

Received: 28 June 2024

PACS:

X703.1

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	Articles by authors
	YANG Jun-feng
	CHEN Zhen-guo
	ZHENG Xu-wen
	ZHANG yu
	LI Jia-yi
	ZHOU Song-wei
	WANG Xiao-jun

Cite this article:

YANG Jun-feng,CHEN Zhen-guo,ZHENG Xu-wen等. Research on the engineering of anammox process for treating iron oxide red wastewater[J]. CHINA ENVIRONMENTAL SCIENCECE, 2025, 45(1): 158-166.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2025/V45/I1/158

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