Water Environment Research最新文献

Although sequential anaerobic/aerobic processes have recently emerged as viable domestic wastewater treatments, their performance under higher organic loading rates (OLRs) requires further investigation to meet economic and sustainability benchmarks. This study evaluates an integrated up-flow anaerobic sludge blanket (UASB) reactor followed by a downflow hanging sponge (DHS) system, comparing its techno-economic performance to a standalone UASB unit. Chemical oxygen demand (COD) mass balance analysis revealed that 32%-54% of influent COD was converted to methane (CH₄) and 17%-22% to sludge, yielding 205-255 L CH₄ per kg of COD removed. The subsequent DHS unit provided robust polishing, achieving total removal efficiencies of 62%-94% for COD, 75%-95% for biochemical oxygen demand (BOD), 81%-94% for total suspended solids (TSS), 28-72% for total Kjeldahl nitrogen (TKN), and 63-100% for NH₄ ⁺-N at an OLR of 0.84-5.43 kg COD/(m³·d). Furthermore, sludge pyrolysis produced a nutrient-rich, calcite-composed biochar (yield: 0.54 g/g dry sludge) suitable for soil amendment. Economic analysis, incorporating biogas and biochar sales, carbon credits, and pollutant shadow pricing, confirmed the system's feasibility. As such, the profitability criteria were estimated as a payback period of 5.9 years, an internal rate of return (IRR) of 11.0%, and a net present value (NPV) of 3485 US$. Given the superior life cycle assessment (LCA) results regarding carbon footprint and ecosystem health, this UASB/DHS/pyrolysis strategy warrants further research into biochar's role in enhancing biogas and digestate quality throughout the project lifetime.

Groundwater contamination has increased significantly due to population growth, land-use change, and unsustainable resource exploitation, necessitating advanced predictive tools for effective water governance. This study presents a multi-temporal, comparative machine learning (ML) to evaluate groundwater quality in the Muvattupuzha River Basin, Kerala, India, using datasets from 2003, 2013, and 2023. A total of five supervised ML models (i.e., decision tree [DT], logistic regression, support vector machine, random forest, and k-nearest neighbor) are systematically assessed to distinguish groundwater as safe or unsafe. Model performance is evaluated using accuracy, recall, F1-score, coefficient of determination, and root-mean-square error. Among the five models, the DT consistently outperforms others, achieving a maximum classification accuracy (96%). It also demonstrates strong interpretability under data-limited conditions. The novelty of the presented work lies in integrating model-specific feature importance with hydrochemical reasoning, revealing that salinity-related parameters serve as effective surrogate indicators for large-scale groundwater quality screening, while nutrients and hardness reflect localized anthropogenic and geogenic controls. The temporal analysis captures the evolving dynamics of groundwater quality over two decades. It is highlighting emerging risks despite partial improvements. Overall, the proposed model advances interpretable, data-driven groundwater assessment and provides actionable insights for early warning, sustainable monitoring, and policy-oriented water resource management in rapidly transforming river basins.

The heterogeneity of soil and groundwater media, combined with the complexity of contaminant hydro-biogeochemical behavior, limits the effectiveness of traditional high-disturbance, low-density methods, such as drilling, for characterizing contaminant transport and transformation processes. To address this, we developed a micro-disturbance detection and data interpretation method based on multiprocess coupling theory, focusing on key hydro-biogeochemical processes of organic pollutants. Validation was conducted at a petroleum-contaminated site in North China using a phased approach that integrated micro-disturbance screening with drilling verification. The results showed that the micro-disturbance screening successfully delineated a plume of approximately 1542 m², consistent with shallow soil exceedances and groundwater contamination, thereby demonstrating a strong correlation between surface gas anomalies and subsurface biogeochemical processes. This study enhances source-plume delineation capability, provides technical support for tracing contaminant biogeochemical processes, and offers a scientific basis for implementing remediation strategies such as enhanced natural attenuation.

Bio-clogging is critical to the efficiency of soil aquifer treatment. In this study, we utilized a percolation column device to investigate the dynamic evolution of biofilm and the corresponding responses changes of three typical hydraulic properties with the column within the percolation column. The results showed that the biofilm development exhibited five-stage growth morphology: bacterial stage, colony stage, biofilm with filamentous EPS stage, biofilm with mesh EPS stage, and dense biofilm stage. The hydraulic conductivity exhibited nonuniform decay across five stages: initial fluctuation period, swiftly declining period, accelerated declining period, gently decreasing period, and equilibrium stabilizing period. Both bacteria and EPS contribute to the attenuation of the infiltration properties. Due to its hydrophilic nature, EPS played a more prominent role in storing and dispersing water. As such, significant changes in water holding capacity and material transport mechanism occurred at EPS secretion onset. From 0-18 h, bacterial colonization slightly enhanced water retention, accompanied by a gradual rise in the hydraulic dispersion coefficient. After approximately 18 h, substantial EPS production markedly increased water-holding capacity and transformed the dominant transport mechanism from convection to dispersion.

Urban irregular shallow lakes are characterized by sinuous shorelines and substantial variations in water depth, which promote the accumulation of pollutants and nutrients. The interaction between nonpoint source pollution and internal pollution leads to rapid and frequent occurrences of eutrophication, complicating the prevention and remediation endeavors. To explore the mechanisms and causes of eutrophication under such circumstances, a two-dimensional hydrodynamic-water quality coupled model of Meijiang Lake was established using the MIKE 21 numerical model. A series of extensive field measurements conducted from April to September 2024 were utilized for model parameter calibration and validation. By simulating the spatiotemporal distribution of lake flow fields and key water quality parameters, such as total nitrogen, total phosphorus, and chlorophyll a, under both inflow and stagnant conditions, and by introducing the lake shape index (LSI) to quantify lake morphology, this study systematically analyzed the influence of lake shape on hydrodynamic conditions and the risk of eutrophication. The results suggest that the model demonstrates high reliability (Nash coefficient close to 0.9). Simulations reveal notable shape-dependent hydrodynamic effects. Lake A, with a regular shape and an LSI of 1.9, maintains optimal water quality owing to limited external inputs and strong water exchange capacity. Lake C, also with a regular shape and an LSI of 1.7, attains moderate water quality despite relatively high external inputs, benefiting from its robust exchange capacity. Lake B, featuring a tortuous morphology and an LSI of 4.65, exhibits low flow velocity and poor water exchange capacity. Coupled with high external inputs, this results in the formation of local stagnant areas with severe nutrient accumulation, rendering it a high-risk area for algal bloom outbreaks. Correlation analysis and quantitative results further demonstrate that chlorophyll a concentration is positively correlated with LSI, water temperature, and total phosphorus and negatively correlated with flow velocity and dissolved oxygen. With each one-unit increase in LSI, the lake's average flow velocity decreases by 35%, while the average eutrophication level rises by approximately 4.1% (range: 1%-7%). This confirms that lake morphology is one of the key factors regulating differences in eutrophication, providing a scientific basis for differentiated management and ecological restoration of urban landscape lakes.

Nitrate in drinking water is a known health hazard for infants, although a growing body of epidemiological evidence suggests an increased risk of adverse pregnancy outcomes and some cancers. A major constraint of epidemiological research is the ability to quantify nitrate concentrations in public drinking water supplies over time. Data on nitrate concentrations in public drinking water supplies were retrieved by information requests, linked to a national dataset on the spatial extent of water distribution zones (WDZs) and linked with census information. We applied a number of data cleaning and imputation processes to address complexities in the raw data as well as missingness. In total, 599 WDZs (95.4%) had at least one nitrate measurement between 2000 and 2024 (n = 20,875 raw observations). After applying a set of imputation methods, the final dataset covered 89.8% of all person-years (n = 92,800,000) of the population on a public drinking water supply during the most recent period from 2000 to 2024. Overall, XGBoost imputation outperformed a range of other imputation methods when synthetic missingness was added to the original data. The large majority (95.3%) of the population was estimated to be on drinking water supplies of less than 1 mg/L nitrate-nitrogen. The population-weighted median nitrate concentration was 0.05 mg/L (IQR 0.04-0.36). This extensive assessment provides the foundation for epidemiological research into the health effects of nitrate contamination of drinking water in New Zealand. The effectiveness of the system for drinking water nitrate surveillance could be enhanced in several ways that would improve its ability to meet its intended purpose.

Cotreatment of mine drainage (MD) in existing wastewater treatment plants (WWTPs) could provide treatment benefits for both waste streams. The alkalinity that is innate to most WW may be sufficient to neutralize MD acidity, elevating pH and correspondingly decreasing concentrations of dissolved metals. Additionally, PO₄ in WW interacts with Fe and Al in MD and is removed from solution, potentially decreasing the need for enhanced biological treatment or chemical precipitation techniques. However, there are concerns about how adding MD to a WWTP may impact the treatment efficiency of the WWTP. Hence, the objective of this study was to determine the impact of AMD addition on the kinetics of BOD removal, in addition to the extent of metals, acidity, and PO₄ removal when WW and MD were mixed in a bench-scale primary clarifier. MD was mixed with primary influent WW in 10:90 and 40:60 MD:WW ratios and allowed to settle for 2 h before the supernatant was transferred to BOD respirometers. The pH remained circumneutral 2 h after mixing, ranging from 7.44 to 8.27 for 10% MD and 6.66 to 7.36 for 40% MD. The BOD oxidation rate was unaffected by MD addition, with first-order kinetic rates ranging from 0.50 to 0.77 day^-1 for raw WW, 0.54 to 0.97 day^-1 for 10% MD, and 0.45 to 0.95 day^-1 for 40% MD. PO₄ removal increased linearly with the molar ratio of ([Fe] + [Al])/[PO₄-P] for the conservative mixture of raw WW and MD and reached > 99% removal when (([Fe] + [Al])/[PO₄-P]) > 2. Overall, this work establishes a practical framework for leveraging mine drainage chemistry within conventional wastewater primary treatment to enhance phosphorus capture without compromising downstream biological performance. The approach offers a scalable pathway for utilities to turn a problematic influent into a controllable unit-process benefit, supporting tighter nutrient limits with minimal new infrastructure and chemical inputs.

The valorization of pretreated waste Salvinia molesta biomass represents a sustainable and circular strategy to address both water contamination and biomass disposal. This study investigated the biosorption performance of pretreated and powdered S. molesta biomass in controlled aqueous solutions of ciprofloxacin (CIP), a widely detected fluoroquinolone antibiotic, under environmentally relevant conditions. The biomass was characterized by a high cell wall fraction (~61%) and moderate protein and polyphenol content, offering a multifunctional surface for biosorption. Batch experiments were conducted to evaluate the effects of pH (4-8) and contact time (up to 60 min) on CIP removal (initial concentration = 1.5 μg/L). The maximum biosorption efficiency (~95%) occurred at pH 6, which aligned with the biomass's point of zero charge ( ${\text{pH}}_p\text{zc}$  = 6.2) and the CIP zwitterionic speciation. Biosorption was rapid in the first 30 min, although equilibrium was rapidly reached within 30 min, consistent with the classical biosorption behavior of dead biomass at low concentrations. The kinetic model followed a pseudo-second-order trend, which was interpreted empirically rather than mechanistically, reflecting surface-controlled adsorption dynamics. Pearson correlations revealed that the protein and polyphenol contents were positively associated (r > 0.85) with biosorption at pH 6-7, highlighting a multi-mechanistic interaction involving electrostatic, hydrogen bonding, and π-π interactions. These findings suggest that S. molesta is a naturally abundant, low-cost biosorbent suitable for decentralized water remediation, particularly in small-scale or proof-of-concept systems using model aqueous matrices, with potential applications in passive treatment units and community-based sanitation systems. Future studies should evaluate isotherm behavior, thermodynamic parameters, and the regeneration potential of the biosorbent to determine scalability under real wastewater conditions.

Water resource recovery facilities often receive landfill leachate (LL), which can disrupt biological processes due to its toxicity and low biodegradability. This study evaluates the anaerobic codigestion (AcoD) of municipal wastewater (MWW), LL, and crude glycerin (CG) as a strategy to enhance organic matter removal and methane yield. Batch reactors were operated under varying conditions defined by a Plackett-Burman screening design, and methane production kinetics were modeled using modified Gompertz and Cone equations. Soluble chemical oxygen demand (sCOD) removal ranged from 67.4% to 94.3%, whereas methane yield varied between 0.076 and 0.349 L _NCH4/g tCOD_add (liters of normalized methane per gram of total COD added). The highest yield was achieved with 2% LL and 1% CG, approaching the theoretical maximum. Statistical analysis revealed that increasing CG content reduced methane yield, and extending the digestion time to 40 days offered limited performance gains. Despite the presence of inhibitory compounds, most conditions showed stable digestion, with short latency phases and effective microbial adaptation. These findings demonstrate the feasibility of codigesting MWW, LL, and CG, especially under optimized proportions, and highlight the potential for energy recovery in wastewater treatment plants using biodiesel by-products.