The effects of transmembrane pressure (TMP) and ozonation on the reduction of ceramic membrane fouling were investigated to reclaim and reuse secondary treated wastewater. A tubular ZnO₃/TiO₂ ceramic membrane with a molecular weight cutoff of 300 kD was used for filtration tests at different TMPs of 1, 2, and 3 bar. Pre-ozonation at 3, 6, and 9 mg/L O₃ followed by membrane filtration at 1 bar were also conducted to assess the effect of ozonation on the reduction of membrane fouling and the improvements of water qualities. Ceramic membrane filtration removed large size of molecules, which were mostly aromatic and hydrophobic compounds. However, hydrophobic fractions of organics caused the irreversible fouling of the ceramic membrane; the irreversible fouling increased as TMP increased. Molecular weight distribution and fluorescence excitation emission matrix verified the results. Ozonation improved water quality and membrane permeability, regardless of the doses, but it could not decrease the relative ratio of irreversible fouling to reversible fouling of the ceramic membrane filtration system.

Coagulation is a critical unit process in drinking water treatment plants (DWTPs), where accurate dosing of coagulants such as polyaluminum chloride (PAC) and polyaluminum hydroxide chloride silicate (PACS) directly determines turbidity removal and operational stability. However, nonlinear interactions among water-quality variables complicate dosage prediction, and jar tests or operator heuristics cannot support real-time control. This study presents a scientifically interpretable and operationally transferable framework based on polynomial multiple linear regression (PMLR) with Lasso regularization, which was specifically developed for full-scale DWTP environments. While conventional PMLR rapidly overfits beyond polynomial degrees of 4–5, the Lasso-regularized model maintained stable generalization even at a degree of 10 by automatically pruning redundant terms and suppressing multicollinearity, thereby minimizing the need for manual hyperparameter tuning. Using 8303 hourly operational records from a full-scale DWTP in Korea, the Lasso-PMLR achieved R² = 0.951, RMSE = 0.120, and MAPE = 7.02%, outperforming traditional linear regression (R² = 0.896; MAPE = 8.64%). This proportional stability across increasing polynomial degrees, demonstrated directly using long-term real-world data, is particularly valuable for practical deployment because it ensures robustness without complex model-selection procedures. The transparent coefficient structure enables operators—who typically rely on jar tests—to understand and adjust dosing behavior, offering a field-ready and interpretable alternative to black-box models and supporting more efficient coagulant use, reduced sludge production, and sustainable automation in DWTP operation.

In this study, we developed a pilot-scale membrane capacitive deionization (MCDI) system for treating mildly brackish water and examined various operational parameters, including module arrangements, adsorption/desorption times, and flow rates. As we aimed to optimize these parameters to increase total dissolved solids (TDS) removal efficiency, the results revealed that the dual-series mode module arrangement and an adsorption time of 120 s with a flow rate of 10 L/min achieved the highest TDS removal efficiency of 99%. Energy consumption analysis showed that lower flow rates were associated with higher TDS removal efficiencies, highlighting the balance between energy consumption and water quality. This study provides insights into optimizing a pilot-scale MCDI for efficient water supply solutions, offering promise for sustainable and eco-friendly water treatment.