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The present study integrates experimental and intelligent models in the modeling and optimization of the iron electrode-based electrocoagulation-flocculation (EC-FLC) process for the treatment of aquafarm effluent (AFE). The modeling was done using Response Surface Methodology (RSM), Artificial Neural Networks (ANN), and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), while the optimization was performed with Particle Swarm Optimization (PSO). The physicochemical properties of AFE were determined before and post-treatment to assess the effectiveness of the process. Central composite design (CCD) embedded in RSM was employed for experimental design. ANFIS model utilized the grid partition and ANN employed a multi-layer perceptron-based feed-forward architecture. The statistical analysis revealed superior prediction accuracy in the decreasing order ANFIS (R2: 0.9968, AAD: 0.0009, RMSE: 0.2373), ANN (R²: 0.9896, AAD: 0.0023, RMSE: 0.4388), and RSM (R²: 0.9655, AAD: 0.0067, RMSE: 0.7764), demonstrating the superiority of ANFIS model. Models’ reliability were validated by the strong correlation between the actual/predicted values of turbidity removal. The experimentally validated optimization solutions for turbidity were RSM numerical (96.71 %), RSM-PSO (97.46 %), ANN-PSO (98.83 %), and ANFIS-PSO (99.01 %). Post-treatment analysis revealed significant reductions in turbidity, nutrient content, and organic matter. These findings demonstrated the effectiveness of the intelligent tools in the modeling/optimization of EC-FLC recovery of AFE.

Landfill leachate, a complex and hazardous liquid waste, poses significant environmental and public health challenges due to its diverse composition and potential for contamination. This review examines the difficulties in landfill leachate management (LLM), focusing on its impact on water, soil, and air quality. Advanced leachate treatment technologies were evaluated for their effectiveness in mitigating leachate's effects. Sustainable development and circular economy principles are critical in addressing these challenges. Effective waste reduction and recycling can significantly decrease landfill volume and leachate production, with potential savings of up to 57.7% in maintenance costs. Composting not only converts organic waste into valuable compost but also generates methane for energy, enhancing waste management efficiency. Energy recovery technologies, including gasification/pyrolysis, effectively convert waste into usable energy, reducing reliance on landfills and minimizing environmental impact. Advanced treatment technologies, including integrated advanced oxidation processes (AOPs) with biological processes and adsorbent-enhanced constructed wetlands, demonstrated promising cost-effectiveness and high treatment efficiency, with savings of up to 32% in treatment costs. Future research should focus on emerging technologies like nanotechnology and artificial intelligence for process optimization, and the impact of municipal leachate on air quality. Continued innovation in leachate treatment and sustainable practices are essential for effective waste management.