Per- and polyfluoroalkyl substances (PFAS) persist in aquatic environments, creating an urgent need for effective and sustainable adsorbents for water treatment. This study compared activated carbons derived from spent coffee grounds (CGAC), bamboo (BAC), and waste coke (WCAC), prepared under identical carbonization and steam activation conditions, to clarify how precursor-dependent physicochemical properties control PFAS adsorption. Nine representative PFAS were evaluated through batch kinetic and isotherm experiments.WCAC showed the highest overall removal efficiency among the three activated carbons, achieving more than 98% removal of most long-chain PFAS within 10 min. Based on pseudo-second-order kinetic fitting, the adsorption capacities ranged from 358.8 to 628.4 μg g⁻¹ for CGAC, 336.7 to 455.7 μg g⁻¹ for BAC, and 397.5 to 1,064.4 μg g⁻¹ for WCAC. The highest fitted capacities were obtained for PFNA on WCAC (1,064.4 μg g⁻¹) and PFOA on WCAC (930.5 μg g⁻¹), indicating strong affinity toward long-chain perfluorocarboxylates, while kinetic parameters revealed PFAS- and adsorbent-specific adsorption behavior.Isotherm analysis further confirmed the strong adsorption performance of WCAC for selected PFAS, with experimental equilibrium adsorption capacities of 2,301.6 μg g⁻¹ for PFOS, 1,952.0 μg g⁻¹ for PFHpA, 1,670.0 μg g⁻¹ for PFNA, and 1,444.0 μg g⁻¹ for PFOA. The isotherm parameters indicated heterogeneous adsorption on energetically diverse carbon surfaces. Overall, PFAS adsorption depended on pore accessibility, graphitic character, hydrophobicity, and oxygen-containing functional groups rather than surface area alone, supporting the rational design of sustainable carbon adsorbents for water treatment.

Taste is a critical yet under-monitored parameter influencing consumer trust in drinking water. Despite its importance, conventional systems rarely quantify taste objectively for operational management. This study introduces a novel sensor-based Taste Index (TI), developed using a potentiometric electronic tongue (E-tongue) with seven ion-selective electrodes, to enable continuous, quantitative evaluation of taste stability across treatment and distribution systems. Multivariate analyses, including principal component analysis and partial least squares discriminant analysis, characterized treatment-dependent variations and spatial heterogeneity. The TI was defined as the normalized Euclidean distance from the final treated water reference (TI = 0.00). Results showed raw water at TI = 1.00, while a temporary increase to TI = 0.38 post-ozonation indicated the formation of taste-active byproducts. Notably, distribution samples with TI > 0.4 precisely corresponded to areas with documented aesthetic complaints. This research presents the first application of a sensor-derived TI for proactive taste monitoring. By enabling early anomaly detection and process tracking, the TI supports data-driven, consumer-centered water management. Its scalability and real-time applicability position it as a practical tool for smart water infrastructure and enhanced operational control.

The rapid expansion of lithium-ion battery (LIB) markets for electric vehicles and renewable energy storage has exponentially increased lithium demand, driving research into sustainable extraction methods. Traditional lithium recovery from brine using evaporation ponds is resource intensive, consuming vast amounts of water and causing severe environmental issues. In response, Direct Lithium Extraction (DLE) technologies have emerged as more efficient, eco-friendly alternatives. This review explores two promising electrochemical DLE methods: Electrodialysis (ED) and Capacitive Deionization (CDI). ED employs ion-exchange membranes (IEMs), such as cation exchange membranes, to selectively transport lithium ions from sources like brine and seawater and achieves high recovery rates. IEMs utilize chemical and structural properties to enhance the selectivity of Li+ over competing ions like Mg2+ and Na+. However, ED faces challenges such as high energy consumption, membrane fouling, and reduced efficiency in ion-rich solutions. CDI uses electrostatic forces to adsorb lithium ions onto electrodes, offering low energy consumption and adaptability to varying lithium concentrations. Advanced variants, such as Membrane Capacitive Deionization (MCDI) and Flow Capacitive Deionization (FCDI), enhance ion selectivity and enable continuous operation. MCDI incorporates IEMs to reduce co-ion interference effects, while FCDI utilizes liquid electrodes to enhance scalability and operational flexibility. Advancements in electrode materials remain crucial to enhance selectivity and efficiency. Validating these methods at the pilot scale is crucial for assessing performance, scalability, and economic feasibility under real-world conditions. Future research should focus on reducing operational costs, developing more durable and selective electrodes, and creating integrated systems to enhance overall efficiency. By addressing these challenges, DLE technologies can provide sustainable solutions for lithium resource management, minimize environmental impact, and support a low-carbon future.

The consistent quality control of ultrapure water (UPW) in semiconductor manufacturing depends on removing trace organonitrogen compounds such as urea. Due to its high solubility, chemical stability, and neutral polarity, urea is inadequately removed by conventional processes. Even at low concentrations, it elevates total organic carbon (TOC) and reduces electrical resistivity. The use of reclaimed water as a sustainable feed stream amplifies this challenge because its nitrogen content is variable and persistent. Conventional methods such as reverse osmosis, ultraviolet oxidation, and ion exchange remain limited in treating urea due to its uncharged, low-molecular-weight nature. This review examines the performance and limitations of these processes and explores electrochemical oxidation (EO) as an alternative. Advances in EO are analyzed with attention to degradation pathways, electrode design, reaction selectivity, and operational parameters. Integrated systems combining EO with membrane filtration, adsorption, or chemical oxidation are also reviewed. Although EO shows promise for selectively degrading urea, its application in UPW production is still in its early stages. Challenges such as low conductivity, byproduct formation, and energy efficiency must be addressed. The paper first discusses urea in reclaimed water and associated removal challenges, then examines both conventional and emerging treatment technologies. Subsequent sections delve into the mechanisms and optimization of EO, including electrode materials and operational parameters. The review concludes with a summary of main findings and a discussion of future research directions, aiming to provide a comprehensive foundation for validating EO as a viable technology for producing UPW from reclaimed water.

Achieving carbon neutrality is a priority in global environmental policies, and South Korea is committed to its 2050 carbon neutrality goal. This study explores methods to reduce carbon emissions in urban water cycle (UWC) systems, which are essential urban infrastructures that consume considerable energy. Focusing on Incheon Metropolitan City (IMC), the research identifies UWC components, estimates energy consumption, and calculates carbon emissions across eight administrative districts. The analysis comprises four water abstraction plants (WAPs), four water treatment plants (WTPs), and eleven wastewater treatment plants (WWTPs). Strategies for carbon reduction involve decreasing water and energy consumption and minimizing emissions from wastewater treatment. This study categorizes management targets as water, energy, and carbon, developing different carbon emissions reduction scenarios. A carbon emission calculation model for WTPs and WWTPs was developed to evaluate energy consumption and carbon emissions across scenarios. Notably, the scenario focusing on renewable energy development and energy efficiency improvements yielded the highest carbon emissions reductions, confirming that the government’s renewable energy initiatives are vital for achieving net-zero emissions in IMC’s UWC systems. Conversely, the scenario prioritizing water use reduction proved less effective, but excelled regarding investment costs. These findings can serve as a model for other cities managing UWC systems while striving for sustainability.

With the rising demand for lithium-ion batteries, the development of sustainable and selective lithium recovery technologies has become increasingly important. In this study, we fabricated cost-effective carbon electrode materials from spent coffee grounds through a two-step process involving pyrolytic carbonization to produce biochar (CGB) and high-temperature activation to obtain activated carbon (CGAC). These materials were applied as electrodes in a membrane capacitive deionization (MCDI) system to evaluate their performance in lithium recovery from synthetic wastewater simulating spent lithium-ion battery (LIB) wastewater. Material characterization revealed that CGAC possessed a well-developed microporous structure with a high surface area of 1332.4 m2 g- 1 and abundant oxygen-containing functional groups. MCDI experiments demonstrated that CGACs achieved the highest salt adsorption capacity (22.8 mg g- 1), a lithium recovery capacity (41.6 mg g- 1), and superior lithium selectivity with separation factors of alpha Li/Na = 1.4 and alpha Li/Mg = 1.0. While CGB exhibited rapid ion removal and favorable regeneration behavior, CGAC showed enhanced cycling stability and overall performance. These results highlight the potential of upcycled coffee waste as a sustainable carbon source for highperformance MCDI electrodes, offering a promising approach for efficient and selective lithium recovery in water treatment applications.

Urban water systems are essential infrastructure but significantly contribute to greenhouse gas emissions through their operation. This study analyzed the greenhouse gas emissions of Incheon’s water system and proposed effective reduction strategies. In 2021, total greenhouse gas emissions from Incheon’s water system are 410,407 tCO2eq, with the sanitation sector accounting for 82.1% and water supply for 17.9%. N2O from wastewater treatment contributes 59.2% of total emissions, followed by CO2 (36.6%) and CH4 (4.2%). Sensitivity analysis using system dynamics identified per capita water consumption (LPCD) reduction as the most impactful mitigation strategy, surpassing widely adopted strategies such as renewable energy adoption. Scenario analysis showed that an aggressive policy could reduce emissions by 28.8% by 2050 compared to the baseline scenario. These findings provide a decision-making policy for carbon-neutral urban water management, emphasizing the need for integrated approaches to water management, emphasizing water demand reduction, energy efficiency, and sludge management.

Pharmaceuticals and personal care products (PPCPs) are recognized as emerging contaminants of concern, even at ultra-trace concentrations. However, the current detection systems are prohibitively expensive and typically rely on labor-intensive, lab-based workflows that lack automation in sample pretreatment. In this study, we developed a robotic and on-flow solid-phase extraction (ROF-SPE) system, fully integrated with online liquid chromatography-tandem mass spectrometry (LC-MS/MS), for the on-site and real-time monitoring of 16 PPCPs in wastewater effluent. The system automates the entire pretreatment workflow—including sample collection, filtration, pH adjustment, solid-phase extraction, and injection—prior to seamless coupling with LC–MS/MS analysis. The optimized pretreatment parameters (pH 7 and 10, 12 mL wash volume, 9 mL elution volume) were selected for analytical efficiency and cost-effectiveness. Compared with conventional offline SPE methods (~370 min), the total analysis time was reduced to 80 min (78.4% reduction), and parallel automation significantly enhanced the throughput. The system was capable of quantifying target analytes at concentrations as low as 0.1 ng/L. Among the 16 PPCPs monitored at a municipal wastewater treatment plant in South Korea, only sulfamethazine and ranitidine were not detected. Compounds such as iopromide, caffeine, and paraxanthine were detected at high concentrations, and seasonal variation patterns were also observed This study demonstrates the feasibility of a fully automated and on-site SPE pretreatment system for ultra-trace environmental analysis and presents a practical solution for the real-time monitoring of contaminants in remote areas.

Aquifer storage and recovery (ASR) is a promising water management technique in terms of quantity and quality. During ASR, iron (Fe) (hydr)oxides contained in the aquifer play a crucial role as electron acceptors in attenuating dissolved organic carbon (DOC) in recharging water through dissimilatory iron reduction (DIR). Considering the preference of electron acceptors, nitrate (NO3-), possibly coexisting with DOC as the prior electron acceptor to Fe (hydr)oxides, might influence DIR by interrupting electron transfer. However, this phenomenon is yet to be clarified. In this study, we systematically investigated the potential effect of NO3- on DOC attenuation during ASR using a series of sediment columns representing typical aquifer conditions. The results suggest that DOC attenuation could be enhanced by the presence of NO3-. Specifically, total DOC attenuation was notably higher than that from the stoichiometric calculation simply employing NO3- as the additional electron acceptor to Fe (hydr)oxides, implying a synergetic effect of NO3- in the overall reactions. Xray photoelectron spectroscopy analyzes revealed that the Fe(II) ions released from DIR transformed the Fe (hydr)oxides into a less bioavailable form, inhibiting further DIR. In the presence of NO3-, however, no aqueous Fe(II) was detected, and another form of Fe (hydr)oxide appeared on the sediment surface. This may be attributed to nitrate-dependent Fe(II) oxidation (NDFO), in which Fe(II) is (re)oxidized into Fe (hydr)oxide, which is available for the subsequent DOC attenuation. These mechanisms were supported by the dominance of DIR-relevant bacteria and the growth of NDFO-related bacteria in the presence of NO3-.

Water and energy are essential resources for human life, and carbon emissions (CEs) occur in tandem with their use. Thus, water, energy, and carbon are closely inter-related. Approximately 4% of the global energy is used in urban water sectors (UWSs), which encompass various processes such as water intake, treatment, and distribution and wastewater collection and treatment, all of which consume significant energy and emit CO2. Several countries are actively working toward achieving carbon neutrality by 2050–2060. Therefore, increasing energy efficiency and reducing CEs through comprehensive evaluations of UWSs is essential. This study aimed to quantify energy consumption and CEs in UWSs and proposed a methodology for analyzing water–energy–carbon (WEC) links at the city level. By applying it to Incheon Metropolitan City (IMC), we first identified the UWSs and established a WEC database. Based on this database, the WEC consumption and emissions were analyzed by process or administrative district, and visualizations using Sankey diagrams and Geographic Information System Mapping were created to enhance their understandability. In 2021, the UWSs in IMC consumed 308,496,107 kWh of energy, representing 32.7% of the public electricity consumption of IMC, with an average energy intensity of 0.46 and 0.38 kWh/m³ for water supply systems (WSSs) and sewerage systems (SSs), respectively. Their carbon emissions totaled 315,765,358 kg CO2, accounting for 2.7% of IMC’s total carbon emissions, with an average carbon intensity of 0.21 and 0.58 kg CO2/m³ for WSSs and SSs, respectively. The proposed methodology was used to comprehensively evaluate WEC consumption and emissions in IMC. It is expected to enable relevant stakeholders to develop measures, such as water reuse and increasing renewable energy usage in water treatment and wastewater treatment plants, to build sustainable UWSs.

Water and wastewater treatment plants (WWTPs) receive various types of microplastics (MPs), with fibers and fragments being dominant shapes. Here we investigated the removal behavior and transformation of MPs (polypropylene and polyethylene terephthalate fibers and fragments) in simulated water and wastewater treatment units, including activated sludge process, coagulation, sand filtration, and advanced oxidation/disinfection. Sand filtration demonstrated the highest average efficiency in removing MPs (98 %), followed by activated sludge process (61 %) and coagulation (55 %), which was associated with their physicochemical properties (shape, size, density, surface functional groups, etc). In activated sludge process and coagulation, the polymer type had a greater impact on the removal of MPs than the particle shape, while in sand filtration, the particle shape played a more important role. When subjected to the long-term operation and backwashing of sand filters, approximately 15 % of the initially filtered fragments broke through the sand media, with nearly no fibers escaping. UV-based advanced oxidation and chlorination induced the leaching of dissolved organic matters with different molecular characteristics from fragment MPs, resulting in varying levels of cytotoxicity and bacterial toxicity. Our study provides important information for predicting the fate of MPs and mitigating their impacts in WWTPs.

The effectiveness of ozonation, one of the techniques known for destroying organic contaminants from wastewater, depends on the composition of the wastewater matrix. The required ozone (O3) dose is determined based on the target compounds during ozonation. Hydroxyl radicals are quantified using a probe compound. The para-chlorobenzoic acid (pCBA) is typically used as a probe compound to measure hydroxyl radicals. However, real-time measurement is impossible, as the analysis process consumes time and resources. This study aimed to evaluate the spectroscopic characteristics of various organic substances in wastewater ozonation through fluorescence excitation-emission matrix and parallel factor analysis. The study also demonstrated that real-time analyzable tryptophan-like fluorescence (TLF) can be used as a hydroxyl radical index. Importantly, the correlation between para-chlorobenzoic acid and TLF was derived, and the results showed a high correlation (R2 = 0.91), confirming the reliability of our findings. Seven trace organic compounds, classified based on their reactivity with O3 and hydroxyl radicals, were selected as target compounds and treated with O3. The TLF index was used as a model factor for the removal rate of the target compounds. The experimental and model values matched when the O3 dose was below 1.0 g O3 /g DOC (RMSE: 0.0445∼0.0895).

Trace organic contaminants (TrOCs), including pharmaceutically active compounds (PhACs), present significant challenges for conventional water treatment processes and pose potential risks to environmental and human health. To address these issues, nanofiltration (NF) and reverse osmosis (RO) membrane technologies have gained attention. This study aims to evaluate the performance of NF and RO membranes in removing TrOCs from wastewater and develop a predictive model using the Solution Diffusion Model. Experiments were conducted using a stirred cell setup at various target concentrations, stirring speeds, and operating pressures, with acetaminophen and caffeine selected as representative pharmaceutical compounds. The results demonstrated that most of the pharmaceutical compounds were effectively removed, showing excellent performance. NF membranes exhibited high permeate flux with somewhat lower removal efficiency (average 84.17%), while RO membranes demonstrated high removal efficiency (average 99.21%), highlighting their importance in trace pharmaceutical treatment. The predictive model based on the solution diffusion model correlated well with the experimental data, suggesting its potential utility for large-scale system applications. This study confirms that NF and RO membranes are effective technologies for the removal of TrOCs from wastewater, offering a promising solution to the challenges posed by trace pharmaceutical contaminants.

In this study, we first comprehensively studied peroxymonosulfate (PMS) and peroxydisulfate (PDS) activation mechanisms using N, O codoped sludge biochar (NOSB) to degrade organics from water. Among the catalysts, NOSB with a higher content of graphitic N, optimal edge nitrogen (pyridinic N and pyrrolic N), CO groups, sp2-hybridized C, and rich defects were demonstrated to be a superior catalyst. Therefore, by activating PDS and PMS, NOSB exhibited the highest rate of BPA degradation, which was 22-fold and 13-fold that of pristine sludge biochar, respectively. However, owing to different oxidation potentials and molecular structures, PMS and PDS show different degradation performances due to various catalytic mechanisms occurring, even with the same biochar. Due to the asymmetrical structure of PMS, electrons passed from PMS to NOSB and further generated singlet oxygen (1O2), which governs the degradation of bisphenol A with an auxiliary contribution of single electron transfer. Meanwhile, PDS is reduced at the Lewis basic sites of NOSB, forming inner-surface-bound {PDS-NOSB}, which was oxidizing around neighboring carbon and decomposed targets through transferring single and double electrons. NOSB is promising for practical applications because of its adaptation to a wide pH range, anions, high total organic carbon removal, tunable active sites, and re-usability for degrading organics via PMS/PDS activation. This study unveils knowledge about N, O codoped sludge biochar catalysts for activating PMS/PDS and advocates a great approach for organics’ degradation in the environment.

In this study, a new method is proposed for the evaluation of taste and odor of drinking water quality in water distribution systems by means of objective and quantitative indices derived from electronic sensors and fluorescence spectroscopy analysis. This method can be analyzed easily, quickly, and instead of subjective sensory analysis. Taste index (T.I.) and odor index (O.I.) were derived using an electronic tongue and nose. This method is simpler, faster, and less expensive than human panel methods. The tryptophan-like fluorescence index (TLF-I) and pipe deterioration index (PDI) of the water distribution system, derived from fluorescence spectroscopy, were also calculated to determine if the T.I. and O.I. were high or what was causing the difference. The target of comparison was the final water (point 1) that supplies water, and T.I., O.I., TLF-I, and PDI were calculated for the seven sampled points. Points 5 (3.91), 3 (3.82), and 6 (3.66) observed high T.I. O.I. was highest in the order of points 6 (3.65), 3 (3.16), and 5 (2.51). High TLF-I was observed at points 5 (160), 3 (111), and 6 (89), indexing a solid correlation. Other influencing factors at points 5, 3, and 6 included the PDI and water supply of the reservoir type. Point 5 had the highest PDI of 0.47. These results suggest that TLF-I and PDI can serve as indicators for interpreting the causes of changes in T.I. and O.I., which are indicators of aesthetic water quality. This method can assist in managing taste and odor quality data in drinking water distribution networks.

Water-quality incidents in the water supply can occur because of errors in pressurization plant operations, leaks, and pollutant infiltration. They lead to citizen complaints about water quality. Identifying high-risk areas and contributing factors for accidents helps to prevent incidents. Here, a predictive analysis technique based on a geographic information system and complaint data was developed using SaTScan, a space–time statistical analysis program. High-risk clusters were identified using maximum log-likelihood ratios, relative risks, and Monte Carlo hypothesis testing. After a red water accident, high-risk clusters (C6–C9) were concentrated in one area. The relative risk of C7 before the accident was 4.58, double that of C2 (2.21). Using ArcGIS, a utility network dataset was created for the water-supply infrastructure in the high-risk cluster area. A utility network model enables flow simulation of the target water supply and tracing of the scope of influence. Downstream analysis of the trace showed that C8 had the greatest expected range of damage following an accident. To address this issue, four valves requiring controls were identified. C6 was predicted to suffer the most significant damage in an accident because it was closest to the water purification plant and had the largest pipe diameter.

Tryptophan-like fluorescence (TLF) is a key indicator of water contamination, particularly of microbial origin and biodegradable organic compounds. This study introduces an Internet of Things (IoT)-enabled portable device (IoT-TLF-PD) for real-time monitoring of microbial quality and biochemical oxygen demand (BOD5). The device was tested using surface water (S1), secondary wastewater (S2), and final wastewater effluents (S3). Results showed significant correlations between TLF intensity, Escherichia coli (E. coli) counts, and BOD5, with R2 values of 0.77 (S1), 0.61 (S2), and 0.76 (S3) for BOD5, and 0.60 (S2) to 0.68 (S3) for E. coli. Considering various water samples, a strong correlation was found between E. coli and BOD5 with TLF intensity normalized by total organic carbon (TOC) concentration (TLF intensity/TOC). The R2 value for E. coli was 0.92, and for BOD5, it was 0.77. This indicates the necessity of accounting for organic matter concentration when interpreting TLF intensity in water quality assessments. The study confirmed the potential of the IoT-TLF-PD to serve as a cost-effective, real-time indicator for assessing water quality, especially for detecting microbial contamination. This technology offers a valuable tool for environmental monitoring and water management.

The anomalous (i.e., non-Fickian) transport characteristics (e.g., early arrival/long tailing and other non-Gaussian plume properties) make it challenging to apply classical transport theories to the transport and retention of microplastics in soil due to their heterogeneity. This overview attempts 1) to delineate the previous studies on the transport of colloids and MPs, which used the recently developed analytical devices (e.g., microfluidics and micro-CT) and process-based (e.g., lattice Boltzmann method (LBM) and pore network modeling (PNM)) or data-driven models (e.g., machine learning (ML) techniques) and 2) to provide future directions for bridging the pore- and continuum-scale properties. Although the LBM and PNM offer significant advantages in depicting particle transport at the pore scale, their employment at larger scales is hindered by computational demands. Nonetheless, applying these methods to generate datasets for ML techniques is anticipated to provide a robust tool for an accurate and rapid continuum-scale microplastics transport model.