With the continuous expansion of industrial enterprises, a large amount of high-salt wastewater with complex components is produced. Direct discharge will cause great harm to the ecosystem and waste a large amount of potential salt resources. This paper summarizes the source, water quality characteristics, and environmental impact of high-salinity wastewater, and introduces the desalination and treatment technologies of high-salinity wastewater. The desalination technology of high-salinity wastewater mainly includes two processes: concentration and crystallization, obtaining concentrated solution through membrane concentration or thermal concentration and then carrying out crystallization treatment on the concentrated solution, thereby realizing the recovery of salt. The advanced treatment technologies of high-salinity wastewater were analyzed, including physicochemical treatment, biological treatment, and coupling treatment. Catalytic ozonation is one of the most widely used physicochemical technologies for the advanced treatment of high-salinity wastewater. Biological treatment processes operating in the presence of halotolerant bacteria show excellent performance at high salinity. High salinity has a negative impact on the performance of various physicochemical processes and biological treatment technologies. However, high salinity has little effect on the performance of a coupled system designed to treat high-salinity wastewater. In this review, the effect of salinity on the scaling and corrosion of equipment is also illustrated. It is suggested that the research direction of high-salinity wastewater should be to develop new membrane materials and catalysts, develop salt-tolerant microorganisms, explore high-efficiency and energy-saving physico–chemical–biochemical combination processes, improve the treatment efficiency of high-salinity organic wastewater, and reduce treatment costs.

Carboxymethyl chitosan (CMCS), acrylamide, and methacryloxyethyltrimethyl ammonium chloride were used as co-monomers to produce a sludge dewatering agent carboxymethyl chitosan-graft-poly(acrylamide-methacryloxyethyltrimethyl ammonium chloride) (CCPAD) by UV-induced graft polymerization. Single-factor experiments and response surface methodology were employed to investigate and optimize the grafting rate, grafting efficiency, and intrinsic viscosity influenced by the total monomer concentration, CMCS concentration, cationic degree, pH value, and illumination time. The structure, surface morphology, and thermal stability of CCPAD were characterized by infrared spectroscopy, hydrogen nuclear magnetic resonance, X-ray diffraction, scanning electron microscopy, and differential thermal-thermogravimetry. The raw sludge with 97.9% water content was sourced from the concentrated tank of a sewage treatment plant and used in the sludge condition experiments. In addition, CCPAD was applied as the sludge conditioner to investigate the effects of cationic degree, intrinsic viscosity, and pH on the supernatant turbidity, moisture content, specific resistance to filtration, and sludge settling ratio. Moreover, the mechanism of sludge conditioning by CCPAD was discussed by examining the zeta potential and extracellular polymeric substance (EPS) content of the supernatant. The sludge dewatering results confirmed that CCPAD had excellent performance for improving sludge dewaterability.

Municipal sludge is characterized by high organic matter content, high viscosity, and fine particles, resulting in poor dewatering performance. This article analyzes the composition and properties of municipal sludge, examines the factors affecting the dewatering performance of sludge and the mechanisms corresponding to each influencing factor, and introduces chemical conditioning in detail. Chemical conditioning includes flocculation conditioning, oxidation conditioning, acid-base conditioning, and aggregate conditioning. The principles and applications of existing sludge conditioning technologies are systematically analyzed. By comparing the advantages and disadvantages of different technologies, it is pointed out that the key to developing sludge conditioning technology lies in developing a more appropriate combination of the sludge conditioning and dewatering process according to the sludge quality of different municipal wastewater treatment plants, taking into account their local environment, input costs, subsequent sludge disposal methods, and other factors, and further optimizing the sludge dewatering process by developing new efficient and environmentally friendly sludge conditioning agents.

As a rapidly developing and potent instrument for resolving practical issues, artificial intelligence (AI) has garnered considerable interest and has been widely used in many different domains. Diverse AI models have also been used in wastewater treatment (WWT) to optimize processes, forecast efficiency, and assess performance in order to explore high-efficiency and cost-effective solutions because of their remarkable learning and predictive capabilities. This review gathers the latest developments and applications of AI technologies in wastewater treatment plants and carefully examines the application and outcomes of various AI models, including artificial neural networks (ANN), support vector machines (SVM), decision trees (DT), and deep learning (DL), in domains such as water quality monitoring, process optimization, fault diagnosis, membrane fouling prediction and control, and resource recovery. This study examines the benefits of these models in real-world engineering applications through a comparison with traditional approaches, as well as current issues like data collection and model generalization. Additionally, it looks to the future, where AI will be used in conjunction with emerging technologies like cloud computing, big data, and the Internet of Things (IoT) to drive the automated and intelligent advancement of wastewater treatment.