Application of artificial intelligence in (waste)water disinfection: Emphasizing the regulation of disinfection by-products formation and residues prediction

• Published in: Water research (Oxford) Vol. 253; p. 121267
• Main Authors: Ding, Yizhe, Sun, Qiya, Lin, Yuqian, Ping, Qian, Peng, Nuo, Wang, Lin, Li, Yongmei
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.04.2024
• Subjects: Artificial intelligence; Disinfection by-products; Disinfection residuals; Water/wastewater disinfection; LM; FT-ICR-MS; PS; GABPNNs; DL; GPR; BNMs; DHAAs; MLP; MLR; RBF; ANFIS; THMs; GANNs; ML; NAs; UV; DOM; HGA; AAD; WDS; ALs; AI; Water/wastewater disinfection; IML; HAAs; MX; NOM; PSO; RSM; OED; PCA; MAE; GEP; RF; GRA; ROS; FLC; TOX; DBPs; HANs; TCM; CFD; DCAA; LRVs; TCP; CNN; RCS; ARX; ARMAX; ANNs; ORP; SVMs; SVR; HKs; GA; HAMs; MSE; BPNNs; SSE; GRNNs; PMD; Disinfection residuals; Disinfection by-products; GP; PID; RMSE; HNMs; RBFNNs; NDMA; CT; PAA; DCAN; LS-SVMs; WWTP; QSAR; FRC; LRA; WOS; Artificial intelligence; CPK; DRL
• ISSN: 0043-1354; 1879-2448
• DOI: 10.1016/j.watres.2024.121267

•AI can capture complex variations and give an immediate response during disinfection.•Application of AI in novel disinfection processes was conducted.•A combination of AI techniques is needed to cope with unregulated DBPs control.•AI shows excellent performance for predicting disinfection residues including FRC.•Fuzzy logic-based neuro systems show superior control performance in disinfection. Water/wastewater ((waste)water) disinfection, as a critical process during drinking water or wastewater treatment, can simultaneously inactivate pathogens and remove emerging organic contaminants. Due to fluctuations of (waste)water quantity and quality during the disinfection process, conventional disinfection models cannot handle intricate nonlinear situations and provide immediate responses. Artificial intelligence (AI) techniques, which can capture complex variations and accurately predict/adjust outputs on time, exhibit excellent performance for (waste)water disinfection. In this review, AI application data within the disinfection domain were searched and analyzed using CiteSpace. Then, the application of AI in the (waste)water disinfection process was comprehensively reviewed, and in addition to conventional disinfection processes, novel disinfection processes were also examined. Then, the application of AI in disinfection by-products (DBPs) formation control and disinfection residues prediction was discussed, and unregulated DBPs were also examined. Current studies have suggested that among AI techniques, fuzzy logic-based neuro systems exhibit superior control performance in (waste)water disinfection, while single AI technology is insufficient to support their applications in full-scale (waste)water treatment plants. Thus, attention should be paid to the development of hybrid AI technologies, which can give full play to the characteristics of different AI technologies and achieve a more refined effectiveness. This review provides comprehensive information for an in-depth understanding of AI application in (waste)water disinfection and reducing undesirable risks caused by disinfection processes. [Display omitted]