Acetaminophen (APAP) is widely detected in wastewater-impacted aquatic environments and may serve as a precursor of nitrogenous disinfection by-products during chlorination. In this study, a GO@Fe3O4/H2O2-assisted electro-oxidation process (EAO) was developed as an advanced treatment approach for APAP removal, and its influence on subsequent haloacetamide (HAcAm) formation potential was evaluated under different nitrogen-containing conditions. GO@Fe3O4 was synthesized by anchoring Fe3O4 nanoparticles onto graphene oxide, providing accessible catalytic sites for H2O2 activation. The EAO process achieved nearly complete APAP removal within 6 h, with an apparent rate constant approximately three times higher than that of electro-oxidation alone. Cyclic voltammetry and electron paramagnetic resonance analyses suggested that GO@Fe3O4 shifted APAP transformation from direct anodic oxidation toward catalyst-assisted radical-mediated oxidation. Density functional theory calculations and gas chromatography-mass spectrometry (GC–MS) identification further suggested that APAP transformation was initiated mainly through hydroxyl radical attack, hydrogen abstraction, and cleavage of the acetamide side chain. The presence of metformin (Met), ammonium sulfate, or ammonium chloride had limited influence on APAP removal, with final removals remaining higher than 97
The objective of this study is to facilitate the selection and operation of advanced oxidation processes (AOPs) to achieve desired remediation goals while avoiding downstream ecotoxicity during treatment of contaminated wastewater. Ecotoxicity of AOP treated waters was measured using Aliivibrio fischeri (A. fischeri) bioluminescence inhibition tests, and this work demonstrates important considerations for applying A. fischeri tests during AOP treatment. Nine high strength aqueous waste streams were investigated to represent a range of background matrix characteristics that may be found in wastewaters. Propanil was used as a model contaminant to systematically study the effects of these matrix factors on bioluminescence inhibition during AOP treatment. Because overlapping and sometimes conflicting matrix effects can limit the insight A. fischeri tests provide about the impact of treatment, experimental results were combined with literature to develop an A. fischeri Visual Guide (AFVG) to support operators and/or system remediators in interpretation of A. fischeri results. The AFVG is a novel decision support tool which facilitates timely, effective remediation while maintaining wastewater treatment system operations and minimizing impacts to downstream receiving waters. Advanced oxidation process (AOP) wastewater treatment can cause downstream ecotoxicity. Ecotoxicity measurement can help devise AOP treatment that minimizes downstream impacts. Complex water matrix effects can confound ecotoxicity measurement and AOP operation. A novel decision support tool is developed here to incorporate ecotoxicity into AOP treatment. The Visual Guide based tool supports operators in systematically treating complex matrices.
Water colour, derived from chromophoric dissolved organic matter (cDOM), is a key indicator of water quality. Increasing water colour trends worldwide and in Australia have raised concerns, yet the drivers of colour variability in natural ecosystems remain poorly understood. We aimed to investigate the drivers of spatial and temporal variability of water colour generation across well-drained temperate forested catchments in south-eastern Australia and tested its use as a proxy for dissolved organic carbon (DOC). Baseflow colour was measured across a diverse topographical range to model spatial variability, while automatic samplers captured temporal variability during rainfall events. Our spatial model explained 87
Climate change has increased environmental stressors such as temperature fluctuations, high salinity, chemical shocks, and extreme weather conditions to the detriment of conventional wastewater treatment technologies. This review investigates the performance, stability, and sustainability of nano-based wastewater treatment systems under these stressful conditions. The systematic literature review as part of the PRISMA 2020 framework was conducted using Scopus and Web of Science databases for publications published between 2005 and 2026 searching for nanomaterials, wastewater treatment, membranes, adsorption, advanced oxidation, and environmental stress. 3,450 records were searched against defined inclusion and exclusion criteria, and 740 studies were selected for qualitative analysis. The studies reviewed indicate that carbon-based, metal/metal oxide-based, two-dimensional, and bio-derived nanomaterials generally improve contaminant removal, membrane permeability, catalytic activity, and antifouling performance under stress. Despite this, chronic exposure to thermal, ionic, and chemical stress can accelerate nanomaterial aging, membrane degradation, release of nanoparticles, and energy consumption leading to reduced treatment efficiency over the long term. The reviews also note a lack of validation at the field scale and inconsistent procedures for durability and environmental safety. Nanotechnology has many potentials to address the problem of climate-induced wastewater treatment, but their adoption will only be successful if the technology’s material, health, and safety are improved. Future research should concentrate on standardization of testing, life-cycle assessment, piloting, and demonstrations for a long-term, reliable application. Nano-enabled systems improve treatment under environmental extremes. Nanomaterial stability governs long-term treatment performance. Environmental stress alters fouling, flux, and contaminant removal. Sustainability depends on nanomaterial durability and safe deployment. Research gaps limit climate-resilient water treatment implementation.
Karst groundwater vulnerability assessment methods were originally developed in temperate regions of Europe and have since been modified to accommodate varying hydrogeological and climatic conditions. This study aims to identify the origins of groundwater vulnerability methods, analyze their methodological development, and evaluate their applicability in tropical karst environments. This systematic literature review based on the Population–Concept–Context framework was conducted R RStudio using the Biblioshiny and Bibliometrix packages, complemented by a manual review to trace method evolution and modification trends. The results showed four main categories of groundwater vulnerability methods: original karstic methods, non-karstic methods with modification, karstic methods with modification, and combined karstic–non-karstic methods with modification. Over the past decade, groundwater vulnerability studies have primarily adopted PCSM-based approaches, with increasing numbers of parameters, modifications to weighting and rating schemes, and other refinements. However, applying temperate-region methods directly to tropical karst often leads to inconsistencies and reduced accuracy due to fundamental differences in tropical karst characteristics and to overestimation of parameter weights and ratings. Consequently, tropical karst vulnerability methods have been adapted by adjusting parameters related to protective cover, rainfall, infiltration, soil, and vegetation, and incorporating additional parameters such as lineament density, degree of karst development, and tropical karst hydrological characteristics. Despite these advances, groundwater vulnerability assessment in tropical karst remains less developed than in porous media aquifers, particularly in sensitivity analysis, map removal analysis, and the application of machine learning techniques to determine rating, weighting, and groundwater vulnerability classes.
Urbanization critically reduces groundwater recharge and elevates flood risks, making rainwater harvesting from rooftops (RWHR) for managed aquifer recharge (MAR) an essential strategy. While the technical implementation of MAR is well-established, our understanding of RWHR water quality and its subsequent impact on the hydrochemical status of groundwater remains ambiguous. A primary concern is the ‘first flush’ – the initial, often contaminated runoff after dry periods. This study defines the first flush and evaluates roof rainwater quality from bitumen-sheet covered flat roofs. In this research, we continuously monitored roof rainwater from three bitumen roofs in Israel, sampled groundwater, and conducted controlled rain simulator experiments on sun-exposed and shaded bitumen samples, analyzing the release of major ions, total organic carbon (TOC), total nitrogen (TN), trace elements (TE), and electrical conductivity (EC). The results show strong EC-inorganic solute correlations, enabling effective first flush identification. The first flush defined as the initial 10 mm of cumulative rainfall, and beyond this threshold, most pollutant concentrations significantly decrease, making ‘subsequent flow’ water suitable for MAR. Critically, TOC behaves differently; despite substantial reduction in subsequent flow, its concentrations remain two orders of magnitude higher than typical groundwater concentrations. Rain simulator tests confirmed high TOC release from sun-exposed bitumen, with low biodegradability, indicating TOC as a persistent concern.
This study analyzes the influence of the El Niño-Southern Oscillation (ENSO) on energy generation at the Jirau and Santo Antônio Hydroelectric Plants and on downstream navigation within the 1.4-million km2 Madeira River basin, a strategic sub-basin of the Amazon River. Using the PHYSITEL/HYDROTEL semi-distributed hydrological modeling platform, the basin’s streamflow dynamics were simulated with KGE values ranging from 0.80 to 0.89 and NSE_Log values ranging from 0.78 to 0.82. Results indicate that the integrated distributed hydrological and LSTM models significantly outperform traditional approaches, achieving test R2 values > 0.88 in simulating water levels at ungauged stations. Furthermore, Maximal Information Coefficient (MIC) analysis revealed a strong non-linear dependence (MIC = 0.61) between ENSO-induced climatic signals and the operational constraints of run-of-river hydropower plants and downstream navigation depth. The results demonstrate that high-intensity ENSO events have induced pronounced flow reductions, which have directly impacted hydroelectric output, reducing hydropower generation to below 20
Municipal solid waste (MSW) generation is projected to reach 3.8 billion tonnes annually by 2050, placing increasing pressure on waste management systems and resource recovery pathways. Although machine learning (ML) and deep learning (DL) methods are widely applied across individual MSW tasks, no prior review has systematically linked algorithm performance to enhanced resource recovery (ERR) outcomes across the full waste management chain. This study addresses that gap through a structured, PRISMA-compliant review of 155 peer-reviewed studies published predominantly within the last five years. The review covers artificial neural networks (ANNs), support vector machines (SVMs), ensemble tree-based methods, convolutional neural networks (CNNs), and recurrent architectures, evaluated across waste generation prediction, sorting and recycling, biological and thermochemical treatment, emissions monitoring, and collection and routing. It was found that three factors consistently govern model performance; data type, dataset scale, and deployment context. Ensemble tree-based models excel on structured tabular data; CNNs lead in image-based sorting tasks, exceeding 98 • AI transforms MSW management from schedule-driven to data-driven adaptive systems. • Ensemble models like RF and XGBoost efficiently predict MSW generation on structured data. • Hybrid ML-DL models consistently outperform standalone algorithms across MSW tasks. • CNN with transfer learning achieves up to 100
Understanding long-term variability in infiltration rates (Ir) in Soil Aquifer Treatment (SAT) systems is important for effective operation, yet the relative contributions of environmental and operational drivers remain insufficiently quantified under field conditions. This study analyzes a 10-year dataset (2015–2025) from 50 recharge basins at the Shafdan SAT facility (Israel) to separate temperature-driven seasonal variability from non-periodic influences. Daily soil temperature and water viscosity were estimated using predictive relationships, and Ir time series were decomposed into seasonal, trend, and residual components using Seasonal-Trend decomposition based on LOESS (STL). The results show that temperature-driven seasonality produces consistent annual patterns but accounts for a limited portion of total variability, with a median contribution of approximately 25
Conventional sand filtration monitoring is often treated as a non-transparent process with limited ability to resolve internal clogging. This study investigates the use of Electrical Resistivity Tomography (ERT) for non-invasive, real-time characterization of clogging dynamics in sand filtration systems. By incorporating prior knowledge of porous media conductivity based on Archie’s Law, resistivity variations can be related to changes in pore structure and fluid transport. A comparison of electrode configurations shows that a stainless-steel Wenner array provides stable measurements, with a root mean square (RMS) error of 2.9
Excessive suspended-sediment from predominantly agricultural landscapes remains a major environmental challenge in the Illinois River Basin, degrading water quality, altering channel morphology, accelerating backwater infilling, and increasing navigation and restoration costs. Understanding how sediment concentration and flux respond to hydrologic variability and watershed change is critical for effective river management. This study evaluates long-term suspended-sediment dynamics across six major Illinois River tributaries using the Weighted Regressions on Time, Discharge, and Season (WRTDS) and its autoregressive extension (WRTDS-K) applied to the Illinois Benchmark Sediment Monitoring Program records. Flow-normalized concentration and flux trends were analyzed at annual and seasonal scales and combined with flow-class sediment regime diagnostics. Results show that sediment responses are highly heterogeneous across tributaries and cannot be explained by streamflow change alone. Elevated discharge, particularly mid-high and high flows, dominates sediment export across all sites, while seasonal responses are strongest during spring and fall and, in some tributaries, winter. The Spoon River at London Mills and the downstream LaMoine River at Ripley showed sustained increases in both flow-normalized concentration and flux, indicating persistent sediment availability and strong sediment mobilization. In contrast, the Vermilion River, the upstream LaMoine River, and the Sangamon River showed declining or weakly responsive sediment trends under modest or decreasing long-term flow changes, suggesting sediment supply limitation, enhanced watershed retention, or other watershed-scale controls. These findings show that basin-scale sediment dynamics emerge from tributary-specific sediment regimes rather than uniform system-wide responses. The combined use of WRTDS and WRTDS-K provides a robust framework for distinguishing hydrologic amplification from sediment-supply controls and supports spatially targeted sediment management across the Illinois River Basin.
Hydraulic implications occur when rainfall and overland flow move across the vegetative structure of the Caatinga, the shrubland native to Brazil’s semi-arid region, which is a climate change hotspot. Can the Caatinga structure’s effects on rain interception, along with water retention caused by hydraulic resistance, significantly increase water infiltration? How can overland flow at low Reynolds numbers be affected? Twelve simulated rain events were conducted in a Brazilian semi-arid watershed, focusing on these questions in a degraded Caatinga area also used for growing semi-arid crops. The entire Caatinga vegetation and litter reduced flow velocity by 55.24
The fractured mountain aquifers provide drinking water to millions of the world population but the instruments in preventive vulnerability examination of low-background systems are not well advanced. The paper formulates and field tests a framework of vulnerability screening which combines regular hydrochemical monitoring with modelling of groundwater flow and solute transport to assist in adaptive groundwater management. The structural form is shown in a representative fractured Himalayan aquifer in which natural uranium is a process-sensitive geochemical tracer of groundwater transport behaviour, and is not a contaminant of concern. On-site sampling shows that the background system is persistently low and the uranium concentrations are often below the analytical detection limit (0.2 µg L− 1). Springs and handpumps showed 8.8 and 13.3
The Po River (Italy) floodplain is a fragile environment extremely vulnerable to pollution and salinization risk. Here, freshwater availability for agricultural needs has become of concern and farmers are facing crops production decline due to droughts, increasing soil and groundwater salinity. To address salinization problems in complex systems, density dependent numerical flow and transport models are key tools. This study explored the role of stagnant zones, sorption and salt release from peats in modelling salinity dynamics in a coastal shallow aquifer. SEAWAT 4.2 was used to reproduce groundwater heads and salinity dynamics in two adjacent agricultural fields: a cultivated plot where groundwater and soil salinity are not yet reducing crop yields (model A1); and second field plot already unsuitable for cultivation (model A2). Both models were successful in grasping the magnitude and timing of groundwater level and salinity fluctuations over time. Transport models set-up with stagnant zones, sorption and salt release from peats best reproduced the observed trends in comparison to classical advection-dispersion equation simulations that overestimated salinity distribution within both plots. Sorption resulted to be crucial in representing the underlying processes of buffering and delaying salinity pulses, together with additional salt mass accounting for long-term source of salinity within peaty horizons. Mass budget calculations revealed high quantity of salt released from both the domains confirming the low efficiency of subirrigation in freshening these organic-rich peaty environments. This study improves the understanding of key phenomena driving salinization in these fragile lowlands, adding process realism and management relevance.
Understanding and managing environmental processes governing indoor air quality in healthcare facilities is essential for mitigating health risks associated with airborne microorganisms. This study proposes an integrated experimental and life cycle assessment (LCA) framework to support sustainability-oriented process design and decision-making for indoor air disinfection systems, using electrochemically generated ozone as a representative case study. A proton exchange membrane (PEM) electrochemical reactor was used to generate controlled ozone gas streams (0.00, 0.24 and 1.16 mg min− 1), which were applied to the continuous treatment of simulated hospital bioaerosols containing antibiotic-resistant Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria under conditions representative of ventilation and air-handling systems. Disinfection performance was interpreted through mechanistic analyses, including membrane permeability alteration, DNA damage and attenuation of antibiotic resistance genes (mecA and blaTEM). Experimental data were subsequently integrated into a scalable cradle-to-gate LCA model designed to evaluate environmental impacts across different room configurations, ventilation rates and energy supply scenarios. Environmental performance was assessed in terms of global warming potential, water footprint, human toxicity (non-cancer) and freshwater ecotoxicity. Electricity consumption was identified as the dominant contributor to most impact categories (80–89
This study is an initial approach to the investigation the fate and transport of neutrally buoyant particles released in the Gulfs of Patras and Corinth system, a semi-enclosed microtidal marine system in central Greece. Hydrodynamics and particle movement were numerically simulated using the MIKE 21/3 Flow Model FM Hydrodynamic (HD) and Particle Tracking (PT) modules. First, a 2D barotropic model was applied to simulate the transport of neutral particles driven only by tidal currents in the absence of wind. Results showed limited dispersion, with most particles remaining close to their release points, except in areas with strong tidal flows such as the Rio–Antirio Strait, central of the Gulf of Patras and the western part of the Gulf of Corinth. In the second case, a 3D model was implemented that included the combined action of tidal flow and river outflows. The 3D simulations suggest that particles released near river mouths were transported farther and followed more complex pathways, influenced by coastal circulation and river freshwater plumes. River outflows significantly modify circulation patterns, affecting the fate of neutrally buoyant particles in the system. Local hydrodynamic features and complex coastline geometry also play an important role. Areas of enhanced particle retention were indicated mainly in the northern Gulf of Corinth and the central to southern Gulf of Patras, while particles released near the Rio–Antirio Strait were rapidly exported toward the open Ionian Sea. • Tidal currents in the absence of wind cause limited transport of neutrally buoyant particles within the Gulfs system. • River discharges significantly enhance particle dispersion and alter circulation pathways. • Three-dimensional hydrodynamics reveal significant vertical particle movement and distinct accumulation zones.
The presence of anthropogenic contaminants, known as emerging pollutants (EPs), poses a major challenge for wastewater treatment. In line with the European Union’s vision for water recycling, efforts have focused on developing more sustainable advanced treatment technologies. To achieve this, circular economy principles can be applied by repurposing waste from other sectors. Consequently, drinking water treatment residuals (DWTR), by-products of drinking water treatment plants (DWTP), have emerged as promising, low-cost adsorbents for the removal of EPs in wastewater treatment. This study assessed the adsorption, in aqueous solution, of a mixture of three steroid hormones: estrone (E1), 17β-estradiol (E2), and 17α-ethinylestradiol (EE2), while also providing proof-of-concept insights using real wastewater. The adsorption process was evaluated by analysing the underlying mechanisms involved, with a focus on dosage, kinetics, and isotherm adsorption studies. The results showed that DWTR reached a maximum adsorption capacity of approximately 4 mg EPs/g DWTR within 24 h, suggesting potential compatibility with WWTP hydraulic retention times. In real wastewater (0.5 µg/L of E1, E2, and EE2), removal efficiency exceeded 50
Meteorological and climate reports indicate that the last ten years rank among the warmest on record. In recent decades, the impacts of climate change on lake water quality and energy budget have become a major concern for scientists and local communities. In this study, trend analyses of monthly and annual historical time series of thermal and water quality parameters were conducted for two Mediterranean Lakes, Vegoritis and Volvi in Greece. These parameters were analysed using a process-based lake water quality model QUALAKE, calibrated for the period 2009–2024. Trend analysis for multiple lake variables indicated limited impacts on most parameters with both Mann-Kendall and Spearman’s rho tests. Trends were detected in several parameters at both annual and monthly time scales, although discrepancies were observed for some variables. Water temperature and dissolved oxygen concentrations in the epilimnion exhibited consistent temporal changes, identified by both statistical tests. Among the heat budget components, the incoming shortwave radiation (Rs) and the net radiation (Rn) showed weak trends, while soluble reactive phosphorus (SRP) displayed weak downward trend in both epilimnetic and depth-averaged concentrations. No significant trends were detected in air temperature, rainfall, evaporation or several other examined parameters. Mann-Kendall and Spearman’s rho tests yielded largely consistent results. Water temperature and dissolved oxygen concentrations in the epilimnion exhibited consistent temporal changes in both lakes. No significant trends were detected in air temperature, rainfall and evaporation. Model demonstrated good performance in simulating water temperature, chlorophyll-α and dissolved oxygen concentrations in both lakes. Changes became more pronounced after 2015, with clearer trends across several variables.
Accurate forecasting of lake water levels is critical for sustainable water resource management, mitigating flood risks, and supporting ecological conservation. This study addresses the challenge of predicting the complex, non-stationary behavior of hydrological systems by developing and comparing three predictive models: Support Vector Regression (SVR), a Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) hybrid, and a novel hybrid that integrates Signal Variational Mode Decomposition with a BiLSTM network (SVMD-BiLSTM). The models were trained and tested on data from Lakes Huron and Winnebago, utilizing a dataset from January 2000 to September 2025 that included maximum/minimum temperatures and average relative humidity, with a three-month lag applied to the target water level data. The results demonstrate a clear performance hierarchy, with the SVMD-BiLSTM model achieving superior accuracy. For Lake Huron, it attained an R² of 0.983, an RMSE of 0.058 m, and a MAPE of 0.03
