数字农科院2.0

Artificial Intelligence in Chemical Dosing for Wastewater Purification and Treatment: Current Trends and Future Perspectives

文献类型： 外文期刊

作者： Jie Jin;Ming Liu;Boyu Chen;Xuanbei Wu;Ling Yao;Yan Wang;Xia Xiong;Luoyu Wei;Jiang Li;Qifeng Tan;Dingrui Fan;Yibo Du;Yunhui Lei;Nuan Yang

作者机构：

关键词： artificial intelligence;chemical dosing system;operating parameters;wastewater purification and treatment

期刊名称： Separations

ISSN： 2297-8739

年卷期： 2025 年 12 卷 9 期

页码：

收录情况： SCIE（2025版）

摘要： Recent concerns regarding artificial intelligent (AI) technologies have spurred studies into improving wastewater treatment efficiency and identifying low-carbon processes. Treating one cubic meter of wastewater necessarily consumes a certain amount of chemicals and energy. Approximately 20% of the total chemical consumption is attributed to phosphorus and nitrogen removal, with the exact proportion varying based on treatment quality and facility size. To promote sustainability in wastewater treatment plants (WWTPs), there has been a shift from traditional control systems to AI-based strategies. Research in this area has demonstrated notable improvements in wastewater treatment efficiency. This review provides an extensive overview of the literature published over the past decades, aiming to advance the ongoing discourse on enhancing both the efficiency and sustainability of chemical dosing systems in WWTPs. It focuses on AI-based approaches utilizing algorithms such as neural networks and fuzzy logic. The review encompasses AI-based wastewater treatment processes: parameter analysis/forecasting, model development, and process optimization. Moreover, it summarizes six promising areas of AI-based chemical dosing, including acid–base regents, coagulants/flocculants, disinfectants/disinfection by-products (DBPs) management, external carbon sources, phosphorus removal regents, and adsorbents. Finally, the study concludes that significant challenges remain in deploying AI models beyond simulated environments to real-world applications.

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