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The world faces growing water scarcity and the need for efficient wastewater treatment. The application of advanced artificial intelligence (AI) techniques holds great promise in optimizing processes, enhancing predictive capabilities, and supporting informed decision-making in this critical domain. This study, which focuses on research trends and developments in the use of AI for wastewater treatment, provides a thorough bibliometric analysis of 368 documents from the Scopus database between 2015 and 2024. The analysis reveals a significant increase in research output, peaking at 93 publications in 2023. This suggests growing interest and focus in leveraging AI techniques to address wastewater management challenges. According to the data, the most important journals in this field are Chemosphere, Water Science and Technology, and the Journal of Environmental Management. Significant contributors to the study were China, India, and the US, with the University of Johannesburg emerging as the most influential institution. The main research direction in this field is properly indicated by the frequently used keywords ''artificial intelligence,'' ''wastewater treatment,'' and ''machine learning,'' according to the analysis of keywords indicating the technological approaches being explored. Adsorption, microalgae, and anaerobic digestion are common methods that are gaining popularity. The most frequently studied wastewater contaminants in recent years have included heavy metals and nutrients. The findings of this analysis provide valuable insights that can guide future research priorities, inform the development of effective AI-driven solutions, and contribute to more sustainable water management practices.

This study aimed to investigate the effectiveness of combining electrocoagulation with adsorption on natural zeolite (ECA) for the treatment of industrial dairy wastewater. The response surface methodology (RSM) was employed to analyze the process. Several operating parameters were investigated, including the initial pH (5–9), electrolysis time (15–45 min), current density (12–48 A/m2), and the zeolite dosage (0.083–0.15 g/ml). The experimental design consisted of 30 runs, which were determined using the Central Composite Design (CCD). The key parameters measured were the removal efficiencies of chemical oxygen demand (COD), turbidity, and energy consumption. The obtained data were analyzed using Minitab 21.2 software, and regression models were constructed. The models demonstrated a strong coefficient of determination (R2), indicating a strong correlation between the experimental and predicted values. The optimal conditions for achieving 92 % COD removal and 97 % turbidity removal were found to be pH 7, a current density of 38 A/m2, an electrolysis time of 20 min, and a zeolite dosage of 0.183 g/ml. To evaluate the impact of natural zeolite on the treatment process, the results obtained from this experimental design were compared with those from a second design involving electrocoagulation (EC) alone (based on 20 runs). The comparison revealed that the addition of natural zeolite did not enhance the treatment efficiency in terms of COD and turbidity removal in dairy wastewater.

The rapid urbanization, economic growth, and improved living standards in developing countries are causing a significant increase in the amount of solid waste generated. To ensure a healthy environment for city residents and effectively manage waste resources, it is crucial to employ scientific methods as decision-making tools. However, the lack of competent institutions, financial and technical capabilities, and irresponsible social behavior hinder the implementation of an integrated and sustainable solid waste management (SWM) system. To address these challenges, researchers have proposed an optimized solution using mathematical modeling and GIS. This solution aims to enhance collection efficiency, optimize transportation, and maximize resource recovery and waste processing. By using linear mathematical modeling and the Arc-GIS Network Analyst tool, the study achieved a 13% route optimization in Phase 7 Hayatabad, indicating the potential for a more sustainable and cost-effective municipal solid waste (MSW) collection system in urban Peshawar. The study also explored different scenarios, such as increasing waste collection efficiency and implementing waste-to-energy technologies, which resulted in improved economic viability and reduced payback periods. Overall, the research highlights the need for adaptive strategies and policy reforms to establish sustainable and efficient waste management systems in rapidly growing cities, fostering a cleaner and more environmentally responsible urban future.

One of the major environmental problems caused by the agro-food industry is the treatment of olive mill wastewater (OMW). OMW is a byproduct of olive oil production and is characterized by high concentrations of various organic compounds, including organic acids, pectin, and polyphenols, as well as inorganic compounds like sulfate, chlorides, and phosphoric salts of potassium and sodium, and trace amounts of other elements. These compounds make OMW complex and toxic to plants, inhibiting bacterial activity. Therefore, these compounds must be removed from wastewater before it is discharged into the environment. Many conventional treatment processes for OMW have been used, relying on physical, biological, and chemical methods. However, they have limitations and low efficiency in removing pollutants, as they only transfer pollutants from one stage to another. The ultimate goal of any treatment process is to achieve complete mineralization of pollutants, which can be achieved through the integration of appropriate processes. Over the years, many researchers have evaluated various combined treatment methods to enhance treatment efficiency and comply with environmental regulations regarding wastewater discharge. This review focuses on combined treatment methods for treated OMW. We analyzed preliminary results in the literature and discussed many parameters used to improve the process. Additionally, this review summarizes the combined processes according to their respective types, along with their benefits, drawbacks, and future prospects. It also summarizes the environmental impacts of treating OMW. In general, the results extracted from the literature review show that combined treatment processes have proven effective in treating OMW and should remain a focal point for the development of enhanced processes that can remove more pollutants in a single process.