Water Environment Research最新文献

Bayannur City in northern China, which includes Urad Rear Banner, has a high concentration of non-ferrous metal mining activities and is a key region for the regulation of heavy-duty enterprises. There are 14 heavy-duty enterprises in Urad Rear Banner, involving a population of 48,000. The regulation of mining activities in this area necessitates effective ecological and human health risk assessments of the heavy metal(loid)s produced by the numerous lead-zinc ore and copper ore smelting operations. In this study, the pollution levels and pollution sources of toxic heavy metal(loid)s (Cr, As, Pb, Cd, and Hg) in topsoil and groundwater were analyzed using a self-organizing feature map (SOM) for the first time. So the pollution source impacts, site characteristics and geographic properties can be further evaluated. The results revealed significant Pb and Cd pollution, exceeding the standard established by China MEE, resulting from the high concentration of heavy industry in the study area. The distributions of toxic metals were linked to pollution source and site characteristics using the neural network-based SOM. Based on the optimal neurons, k-means clustering, and the Davies-Bouldin index (DBI), the SOM indicated five possible pollution sources: human factors, natural sources, natural settlement, wastewater leakage, and wind effect. Meanwhile, the ecological risk assessment showed that the ecological risk decreased in the order of Cd > Hg > As > Pb > Cr, which reflects the difference between ecotoxicological sensitivity and pollution level. That is, low-polluting metals may still have high toxicity. In the health risk assessment of heavy metal(loid)s in topsoil and groundwater, the hazard quotient (HQ) and hazard index (HI) were all below the safety limit of 1, while the carcinogenic risk (CR) and total carcinogenic risk (TCR) values were 10^-6 to 10^-4 (within the range of human tolerance). Among the heavy metal(loid)s evaluated, Pb and As had relatively high carcinogenic risks. Due to contributions from multiple sources, the southeastern part of the study area was heavily polluted. This study represents an innovative use of SOM in pollution source apportionment. This novel approach has the advantages of high precision, high efficiency, good visualization, and little human interference. SOM can be used to quantify sources while also comprehensively considering the hydrogeochemical characteristics, and it is especially suitable for case studies with large sample sizes. In this study, we applied SOM in an innovative way to evaluate the ecological and human health risks of heavy metal pollution in an area with numerous heavy industries and revealed the potential risk pathways. The findings provide a basis for the prevention, control, and remediation of pollution along with associated policymaking.

The global shortage of potable water and the rising environmental burden from industrial waste highlight the need for sustainable and low-cost desalination technologies. This study presents an enhanced passive solar still (PSS) that integrates recycled aluminum thin films and polypropylene insulation to improve thermal performance, freshwater productivity, and overall system sustainability. Material characterization confirms that waste-derived recycled aluminum plates possess high solar absorptivity and excellent thermal conductivity, enabling rapid heat absorption and extended thermal storage. Experimental evaluation under real climatic conditions shows that the PSS achieves a 35.5% increase in daily yield compared to the conventional solar still (CSS), supported by higher basin temperatures, improved evaporation-condensation dynamics, and reduced heat losses. Thermodynamic analysis reveals significant improvements in energy efficiency, exergy efficiency, gain output ratio, and productivity ratio, whereas economic assessment indicates a reduction in cost per liter and a shortened payback period. A machine-learning framework using RNN, XGBoost, Random Forest, and RVFL models accurately predicts hourly yield, and NSGA-II optimization identifies an optimal configuration of 18 recycled aluminum plates with 2 × 5 cm spacing. Environmental metrics confirm substantial reductions in material cost, energy consumption, and CO₂ emissions. The proposed system demonstrates a practical, scalable, and circular-economy-driven approach for decentralized freshwater production.

The growing global concern over oily wastewater pollution necessitates the development of advanced and efficient separation technologies. In this study, polyimide (PI) based mixed matrix membranes were fabricated by incorporating SiO₂, TiO₂, and metal organic frameworks (MOFs) into a polyethersulfone (PES) matrix to enhance oily wastewater treatment performance. The successful integration of these nanomaterials was confirmed through FTIR and XRD analysis. The modified membranes showed enhanced thermal stability (Tg PES/PI/MOF: 80.63°C) and increased surface hydrophilicity. Among the fabricated membranes, MOF incorporated exhibited the highest pure water flux of 50 L m^-2 h^-1. The PES/PI/MOF membrane achieved superior performance in separating different oil water emulsions, including DCM/SLS and PE/CTAB systems, with flux of 73.23 ± 0.82 L m^-2 h^-1 and 64.78 ± 0.59 L m^-2 h^-1, respectively. It also displayed a high flux recovery ratio (82.34%), demonstrating excellent antifouling behavior, and achieved an oil rejection efficiency of 83.02% for the DCM/SLS emulsion. Overall, this study highlights the synergistic effect of nanomaterial incorporation in enhancing membrane permeability, selectivity, and fouling resistance, showing PES/PI based mixed matrix membrane as promising candidates for sustainable oily wastewater treatment applications.

Inorganic nitrogen and organic pollutants are commonly coexisted in various wastewaters. Bacteria capable of removing multiple pollutants simultaneously possess unique advantages in wastewater treatment. In this study, the heterotrophic nitrification-aerobic denitrification (HNAD) bacterium Pseudomonas sp. A2 simultaneously possessed the ability to degrade benzoic acid. Experimental data demonstrated that strain A2 exhibits outstanding nitrogen removal performance, with the maximum removal rates of 13.87 and 12.69 mg/L/h for ammonium and nitrate, respectively. Approximately 99.42% of ammonium and 100% of nitrate were efficiently removed under optimal conditions: sodium succinate as carbon source, C/N ratio 14, 30°C, pH 7.0, and shaking speed of 160 rpm. Batching test and genome analysis suggested that A2 achieved heterotrophic nitrification with hydroxylamine as an intermediate and reduced nitrate to N₂ under aerobic condition. Additionally, strain A2 could utilize benzoic acid as an electron donor for nitrogen removal, though the nitrogen removal efficiency decreased significantly. Genomic analysis indicated that strain A2 may degrade benzoic acid via both the ortho pathway and the protocatechuate pathway. Bioaugmentation with strain A2 improved both nitrogen removal performance and stability of sequencing batch reactor (SBR), suggesting its potential in application. The discovery of strain A2 enriches the understanding of the nitrogen removal mechanism of HNAD bacteria and provides novel insights into the simultaneous removal of nitrogen and benzoic acid from wastewater.

Contaminated groundwater must be treated to protect drinking water supplies. This study investigated the degradation of MTBE and TBA with UV/persulfate (PS) and UV/hydrogen peroxide (H₂O₂) advanced oxidation processes. Experiments were conducted at initial concentrations of MTBE and TBA of 7.4 and 6.2 mg/L respectively over a range of conditions and computational analysis was carried out to elucidate reaction mechanisms and pathways. Pseudo first-order rate constants were retrieved from temporal degradation profiles. MTBE degradation was faster than that of TBA, and UV/PS-driven oxidation of both chemicals was faster than that of UV/H₂O₂. Relative absorptivity measurements showed that PS absorbed a higher proportion of light than H₂O₂ did, which in turn created greater potential to generate radicals. Density Functional Theory (DFT) results provided additional new insights. UV/PS is a promising groundwater remediation technology for the removal of MTBE and TBA.

Waste management has become a major environmental challenge worldwide, particularly due to the rapid increase in solid waste generation associated with population growth and socioeconomic development. The accumulation of waste in landfills leads to the production of leachate, a highly contaminated liquid that poses serious risks to soil and groundwater. This study investigates the impact of the Hassi Bounif Technical Landfill, located in Oran, northwestern Algeria, on the physicochemical quality of nearby groundwater. Leachate and groundwater samples were collected during both summer and winter seasons and analyzed for physicochemical parameters and heavy metals using standard analytical methods. The leachate exhibited high contamination levels, with mean concentrations of Fe (17.55 mg/L), Pb (0.85 mg/L), and Cu (3.00 mg/L), while the average levels of Al, Cr, Mn, Hg, Ni, Cd, Mg, and Zn were 5.00, 1.25, 3.50, 0.04, 0.85, 0.60, 4.00, and 5.50 mg/L, respectively. Elevated organic loads were also recorded (COD = 28,653 mg/L; BOD₅ = 6223 mg/L), resulting in a leachate pollution index (LPI) value of 33.94, indicating a high pollution potential. Groundwater samples collected near the landfill showed electrical conductivity ranging from 3536 to 7905 μS/cm and elevated concentrations of major ions (Na⁺, Ca²⁺, Mg²⁺, Cl^-, and SO₄ ^2-), exceeding both World Health Organization (WHO) and Algerian standards. A distinct gradient was observed, with contamination levels decreasing with distance from the landfill. Seasonal variations were evident in both leachate and groundwater quality, with higher pollutant concentrations during the summer season, primarily due to enhanced evaporation and reduced groundwater dilution. The findings confirm the significant influence of landfill leachate on groundwater quality in the study area and underscore the urgent need for improved leachate treatment and management practices to mitigate environmental and public health risks in semiarid regions such as Oran.

Green corrosion inhibitors have gained attention as natural and eco-friendly solutions for microbiologically induced corrosion in various industries. This study investigates the potential of Agave sisalana saponins (ASS) combined with glycerol, a green solvent, to control biofilm-induced corrosion on copper surfaces. Bacterial strains with strong biofilm-forming abilities were isolated from Koel River water and identified through 16S rRNA gene amplification. Phylogenetic analysis confirmed the presence of Acinetobacter spp., Exiguobacterium sp. BFR12y, and Solibacillus sp. BFR13. Structural characterization of ASS using FTIR spectroscopy, NMR, and high-resolution mass spectroscopy confirmed the surfactant properties of extracted saponins. The Agave sisalana saponins-glycerol combination (ASSG) exhibited no antibacterial activity at the tested concentrations. However, colony-forming unit (CFU/biofilm) counts, CLSM, and SEM revealed a significant biofilm inhibition efficacy of 80.14%. Corrosion rate and electrochemical impedance spectroscopy study demonstrated 76.42% corrosion inhibition. The inhibitory effect of ASSG was attributed to its adsorption onto metal surfaces, resulting in a reduction in bacterial motility and adhesion, and Cu₂O formation, as confirmed by motility assay, contact angle measurement, and Raman spectroscopy analysis. The findings suggest the potential use of the Agave sisalana saponins-glycerol combination as a green, prospective corrosion inhibitor, with promising applications in cooling water systems across various industries.

Polyethersulfone (PES) membranes, while widely used in ultrafiltration, are hindered by their inherent hydrophobicity and susceptibility to fouling. This study investigates the incorporation of aluminum oxide hydroxide-tannic acid (AlOOH-TA) hybrid nanoparticles into PES membranes via phase inversion to enhance hydrophilicity and antifouling behavior. The AlOOH-TA hybrid introduces abundant hydroxyl and phenolic groups that promote hydration layer formation and reduce foulant adhesion, while alumina contributes structural reinforcement. The modified membranes were characterized using SEM, FTIR, contact angle, and porosity analyses to correlate surface and structural changes with filtration performance. The optimized membrane (M4) achieved a pure water flux of 37.71 L·m^-2·h^-1 and a contact angle of 56.7°, representing a 38.95% flux improvement and enhanced surface wettability compared to pristine PES. In humic acid filtration, M4 exhibited a rejection efficiency of 61.4% and a flux recovery ratio (FRR) of 99.72%, confirming its excellent antifouling and reusability performance. These findings demonstrate that AlOOH-TA hybrid incorporation effectively improves membrane hydrophilicity and antifouling resistance through synergistic chemical and structural modification.

This review explores the links, challenges, and gaps among six key elements of water management: watershed models, optimization algorithms, artificial intelligence, surrogate models, monitoring, and decision support systems. The main goals of this review are twofold: (1) to examine the established interrelationships among these key elements and analyze how these connections contribute to improved management effectiveness and (2) to identify and explore potential, yet unexplored, synergies among these elements that could lead to enhanced management practices. This study adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, following steps for identification, screening, eligibility assessment, and selection while applying exclusion criteria and cross-referencing. The findings highlight that while advanced watershed models leveraging high-resolution datasets offer valuable insights, they face scalability challenges in capturing spatial and temporal variations. Additionally, the adaptability and performance of machine learning approaches are constrained by data limitations, including insufficiencies and inconsistencies across diverse sources. Overall, this synthesis provides actionable insights for advancing water quality protection and resource recovery by integrating emerging technologies with established management frameworks.

Studies evaluating the sedimentation of solid particles in carwash wastewater (CWW) are scarce. This research is innovative because it is the first to study solid sedimentation specifically in CWW. The motivation lies in the fact that existing parameters (for sanitary sewage) are inadequate due to the peculiar physicochemical characteristics of CWW. This study evaluated the settleability of solids present in CWW, aiming to generate empirically validated parameters to support the optimized design of sedimentation units. Granulometric characterization of the settleable material and column settling tests for total suspended solids (TSS) were performed. The granulometric analysis of the settleable solids revealed a predominance of the sandy fraction (D_90% = 1.1 mm), with an average of 87.44%. This characteristic confirms the coarse texture of the retained material and its high sedimentation velocity during the first hour. The column settling tests for TSS demonstrated highly variable removal efficiency, which did not directly correlate with the initial concentration of solids or with rainfall conditions. Results indicated the need for hybrid sedimentation models to adequately represent TSS sedimentation. A surface application rate of 1.5 m·h^-1 is suggested, which corresponds to an average TSS removal efficiency of approximately 80%. The adoption of specific design parameters for CWW provides greater reliability in the sizing of treatment units, supporting both operational efficiency and the economic viability of the system.