Recently, environmental pollution from microplastics (MPs) has become a significant reason for increasing the number of studies to develop analysis methods. The Nile red staining method (NR-S), which is staining polymer particles with Nile red (NR) dye, has been widely used for the analysis of MPs in environmental samples. However, this method has several limitations, as it is difficult to stain MPs covered with organic matter residues. In this study, we modified the NR-S method into an NR plate method (NR-P), where the plate is coated with NR instead of staining MPs directly. The optimum concentration of NR solution was obtained (1000 mg/L), and the effectiveness of the NR-P method for the analysis of MPs was assessed using different types (polypropylene, polyethylene, polyethylene terephthalate, and polystyrene), sizes (100–1000 µm), and shapes (sphere, fiber, film, and flake) of plastic materials. The NR-P method demonstrated improved resolution in the overall types, shapes, and sizes of MPs and was better than the control (without NR plate method) and NR-S method. In particular, the NR-P method can effectively observe MPs covered with organic matter, which was a major limitation of the NR-S method. Finally, MPs in sewage field samples were analyzed by the NR-P method with an accuracy of 78% confirmed by FT-IR. We demonstrated that this method is a convenient and efficient alternative for identifying MPs, even for field samples.

Microplastics (MPs) are plastic particles < 5 mm in diameter, which are detected in air, soil, and water, causing various environmental problems. In total, 37.3% of MPs are generated from point pollution sources and 62.7% from non-point sources; most of the non-point-source MPs are from vehicles tires, road-marking paint, and bitumen used in road pavements. In this study, the concentrations of MPs generated from roads in Goyang city, South Korea, were examined in terms of the drying period (0, 1, 2, or 3 d). Road dust sampling was performed at the kerb and quantitative and qualitative analyses were conducted for each sample. The MP concentrations were 552 (±39) MPs g⁻¹ for a 0 d drying period and 1530 (±602) MPs g⁻¹ for a 3 d drying period, confirming that the MP concentration in road dust increased with the increase in drying period. Among the detected substances, black particles accounted for the highest proportion (72%) and were found to be bitumen and tyre particles. This study also confirmed that the MPs accumulated on roads were washed away when rainfall exceeded a certain amount.

Sewage treatment can remove more than 90% of microplastics, yet large amounts of microplastics are discharged into the ocean. Because microfibers (MFs), primarily generated from the washing of synthetic clothes, are the most abundant type of microplastics among various microplastics detected in the sewage treatment, reducing the amount of MFs entering these treatment plants is necessary. This study aimed to test whether the amount of MFs released from the washing process can be reduced by applying a chitosan pretreatment to the garments before washing. Before the chitosan pretreatment, the polyester clothes released 148 MFs/L, whereas 95% of MFs were reduced after the chitosan pretreatment with 0.7% of chitosan solution. The chitosan pretreatment was applied to other types of garments, such as polyamide and acrylic garments, by treating them with 0.7% of chitosan solution; subsequently, MFs reduced by 48% and 49%, respectively. A morphology analysis conducted after washing revealed that chitosan coating on the polyamide and acrylic were more damaged than on polyester, suggesting that the binding strength of polyamide and acrylic with chitosan was weaker than that of polyester garment. Thus, the results suggested that the chitosan pretreatment might be a promising solution for reducing the amount of MFs generated in the laundering process.

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.

The abundant growth in cyanobacterial blooms poses severe ecological threats with a high risk to aquatic organisms and global public health. Control of cyanobacterial blooms involves spraying cyanobacteria removal materials, including coagulants. However, little is known about the fate of the coagulated-cyanobacteria-laden water. Here, we examined long-term changes in water quality following treatment with various coagulants and minerals for cyanobacterial removal when the coagulated cyanobacterial cells were not removed from the water. An experiment in a controlled water system tested the effects of six different compounds, one conventional coagulant, two natural inorganic coagulants, and three minerals. All tested coagulants and minerals exhibited >75% of cyanobacterial removal efficiency. However, compared to the control, higher concentrations of nitrogen were observed from some samples treated during the experimental period. After 20 months, the final total phosphorus concentration of the raw water increased 20-fold compared to the initial concentration to 11.82 mg/L, indicating significant nutrient release over time. Moreover, we observed that the decomposition of sedimented cyanobacterial cells caused the release of intracellular contents into the supernatant, increasing phosphorous concentration over time. Therefore, cyanobacterial cells should be removed from water after treatment to prevent eutrophication and maintain water quality.