Environmental Science: Water Research & Technology最新文献

Water quality prediction is crucial for protecting aquatic ecosystems and ensuring human health. However, the water quality time series exhibits characteristics such as nonlinearity and nonstationarity, making efficient feature extraction crucial for improving prediction accuracy. To achieve more accurate and efficient prediction tasks, this study improves the traditional Transformer and proposes a novel water quality prediction framework based on a Transformer called BiMKANsDformer. Secondly, this study improves the interactive convolution block (ICB) by integrating dilated convolution, developing the D-ICB module suitable for extracting complex time series features. Finally, by combining the long-term dependency capturing capability of D-ICB with the feature extraction advantages of BiMamba+ and KANs, this study integrates these components with a Transformer to enhance its processing ability for time series data. Comparative experiments indicate that BiMKANsDformer shows significant advantages in NSE, MAE, RSR, and MAPE, demonstrating stronger robustness and predictive accuracy.

This study explores the use of rice husk biomass and its derived carbon materials—hydrochar (HC) and biochar (BC)—as supports for biogenic zerovalent iron (ZVI) nanocomposites (ZVI@RH, ZVI@HC, and ZVI@BC) in advanced oxidation processes (AOPs) for the degradation of oxytetracycline (OTC). The catalysts were characterized using FTIR, XRD, FESEM, and XPS techniques, and their performance in activating peroxymonosulfate (PMS) for OTC degradation was assessed. Results showed that the ZVI@BC nanocomposite outperformed ZVI@RH and ZVI@HC in OTC removal through heterogeneous Fenton-like processes. The addition of PMS further enhanced OTC degradation by generating more reactive oxygen species (ROS), making the process more efficient than the Fenton process alone. The higher surface defects in BC, resulting from pyrolysis, improved OTC adsorption and degradation, and facilitated more effective ZVI-mediated PMS activation in ZVI@BC, achieving nearly 98.3% OTC removal from the aqueous solution. The involvement of various ROS in OTC degradation was examined using radical scavengers, and DFT calculations proposed a degradation pathway by identifying ROS attack sites on the OTC chromophore. High-resolution mass spectrometry (HRMS) analysis was used to identify reaction intermediates. This study emphasizes the potential of using agricultural waste-derived materials in AOPs, presenting a sustainable and cost-effective method for environmental remediation and OTC antibiotic degradation.

Advanced oxidation processes (AOPs) are one of the highly effective alternatives for treatment of algal toxins in drinking water. Water that contains algal toxins commonly has organic matter of algal origin and elevated nitrate. Organic matter undergoes transformations during advanced oxidation processes and may change in a way that increases disinfection byproduct (DBP) formation when water is chlorinated post-AOP. Nitrate forms reactive nitrogen species under certain UV wavelengths that can also interact with organic matter and change its properties in a way that increases post-AOP DBP formation. Two types of advanced oxidation processes (UV/H₂O₂ and UV/Cl₂) were compared in their ability to change the formation potential of regulated DBPs [four trihalomethanes (THMs) and nine haloacetic acids (HAAs)] and an unregulated nitrogenous DBP (N-DBP) N-nitrosodimethylamine (NDMA) due to the interaction of the process with algal organic matter (AOM) and nitrate in the water. The two AOPs showed no significant differences in post-treatment DBP formation under any of the tested conditions. Higher levels of treatment with both processes led to slightly higher formation potential of some THMs. AOM made a poor precursor for additional THMs and three HAAs (six not consistently detected), but had a higher NDMA yield than background organic matter (0.59 ng mg⁻¹-C vs. 0.18 ng mg⁻¹-C, p = 0.038). Nitrate suppressed chlorinated THMs and favored increased concentrations of brominated THMs and HAAs, resulting in higher percent incorporation of background bromide into DBPs. Moreover, nitrate addition (20 mg-N L⁻¹ of added nitrate compared to the background level of 0.47 mg-N L⁻¹) led to 11 times higher NDMA formation. Formation of N-DBPs during post-AOP chlorination in the presence of AOM and nitrate warrants additional investigation.

The persistence of pharmaceuticals and personal care products (PPCPs) through wastewater treatment and resulting contamination of aquatic environments and drinking water is a pervasive concern, necessitating means of identifying effective treatment strategies for PPCP removal. In this study, we employed machine learning (ML) models to classify 149 PPCPs based on their chemical properties and predict their removal via wastewater and water reuse treatment trains. We evaluated two distinct clustering approaches: C1 (clustering based on the most efficient individual treatment process) and C2 (clustering based on the removal pattern of PPCPs across treatments). For this, we grouped PPCPs based on their relative abundances by comparing peak areas measured via non-target profiling using ultra-performance liquid chromatography-tandem mass spectrometry through two field-scale treatment trains. The resulting clusters were then classified using Abraham descriptors and log K_ow as input to the three ML models: support vector machines (SVM), logistic regression, and random forest (RF). SVM achieved the highest accuracy, 79.1%, in predicting PPCP removal. Notably, a 58–75% overlap was observed between the ML clusters of PPCPs and the Abraham descriptor and log K_ow clusters of PPCPs, indicating the potential of using Abraham descriptors and log K_ow to predict the fate of PPCPs through various treatment trains. Given the myriad of PPCPs of concern, this approach can supplement information gathered from experimental testing to help optimize the design of wastewater and water reuse treatment trains for PPCP removal.

Perfluorinated compounds (PFCs) are a class of emerging pollutants that are commonly detected in surface water and pose significant risks to both the environment and public health. This study investigates a combined treatment method for removing perfluorooctanoic acid (PFOA), a prevalent PFC found in micro-polluted surface water. The method integrates nanoscale zero-valent iron (nFe)-activated persulfate (PS) pre-oxidation with conventional water treatment processes—coagulation, sedimentation, and sand filtration—combined with nanofiltration (NF). This study primarily aims to evaluate the efficiency of this combined process for PFOA removal and to elucidate the mechanisms underlying PS oxidation and NF separation. The treatment sequence, comprising nFe/PS pre-oxidation, conventional treatment, and NF, was strategically designed considering the specific roles of each process in PFOA removal. In the initial stage, nFe-activated PS generates sulfate radicals (SO₄⁻·) and hydroxyl radicals (OH·), which oxidize and degrade PFOA. The subsequent conventional treatment removes the majority of degradation byproducts and suspended solids. Finally, NF retains both PFOA and its oxidation products, thereby ensuring high removal efficiency. Experimental results indicate that an optimal PS dosage of 0.2 mM and an nFe-to-PS molar ratio of 1 : 1 achieved the maximum efficiency for PFOA removal. Among the tested sequences, “nFe/PS pre-oxidation + conventional treatment + NF” achieved the highest removal rate, exceeding 99%. Furthermore, this sequence resulted in the lowest surface potential of the NF membrane, which enhanced electrostatic interactions between the membrane and PFOA. This reduction in surface potential, combined with the formation of C–O bonds between PFOA and the NF membrane, further enhanced PFOA adsorption onto the membrane surface. The combined process of nFe/PS pre-oxidation, conventional treatment, and nanofiltration effectively removes PFOA from micro-polluted surface water, thereby contributing to improved drinking water safety.

Treatment of wastewater containing PF₆⁻ is required during hydrometallurgical recycling of lithium-ion batteries. Because of the kinetic stability of PF₆⁻ in aqueous solution, the decomposition study into PO₄³⁻ or F⁻ is required for wastewater treatment. In our previous report, the hydrolysis of PF₆⁻ was shown to be accelerated by adding Al³⁺ and elevating the solution temperature. In this work, the kinetics and mechanism of the hydrolysis of PF₆⁻ at several pH and Al³⁺ concentrations were investigated for more efficient wastewater treatment. The solutions containing LiPF₆ at various pH and AlCl₃ concentrations were kept at 90 °C, and the concentration changes of PF₆⁻, PO₂F₂⁻, PO₃F²⁻, PO₄³⁻, and F⁻ were measured by ion chromatography. The measurement results were analyzed assuming pseudo-first-order kinetics. The results showed that Al³⁺ and H⁺ accelerated the hydrolysis of PO₂F₂⁻ and PO₃F²⁻, but the levels of accelerating effects were different. More specifically, the accelerating effects of Al³⁺ are higher in the order PF₆⁻ > PO₂F₂⁻ > PO₃F²⁻, while the accelerating effects of H⁺ are in the opposite order. Based on the discussion, a more efficient treatment process for wastewater containing PF₆⁻ was proposed. The proposed process is expected to reduce heating costs and processing time compared to previously reported ones.

Characterization of wastewater concentrations of human enteric pathogens and human fecal indicators provides valuable insights and data for use by regulators and other stakeholders when developing treatment criteria for water reuse applications, performing quantitative microbial risk assessments, or conducting microbial source tracking. Wastewater samples collected over three years during and after the COVID-19 pandemic were analyzed retrospectively (March 2020–September 2022) and prospectively (October 2022–December 2023) by qPCR for molecular markers of adenovirus, enterovirus, norovirus GI & GII, as well as the human fecal indicators pepper mild mottle virus, crAssphage, and HF183 (n = 1112). A sub-campaign was conducted, and wastewater samples were tested for the culturable enteric viruses adenovirus and enterovirus (n = 56) and the protozoan parasites Cryptosporidium and Giardia (n = 73) over one year (January–December 2023). All assays had high detection rates, ranging from 71% to 100%, and were fit to log-normal distributions. All molecular markers for enteric pathogens displayed seasonal and geographic variation, potentially explained by seasonal epidemiology of gastrointestinal illness, differing populations, and differing sample types. Additionally, the impact of Nevada-specific COVID-19 public health guidance (e.g., mask mandates, stay-at-home orders) on enteric pathogen concentrations was characterized, with significantly higher concentrations of molecular markers observed in “non-pandemic” conditions. This study provides high quality (i.e., high sensitivity, minimally censored, recovery adjusted) pathogen and indicator datasets with insights for use in academic, public health/epidemiological, and industry/regulatory applications.

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Lead (Pb²⁺) has adverse effects on the human body due to its non-biodegradability and bioaccumulation. In this study, a flow analysis device was designed for in situ determination. A poly(pyrrole thiourea) electrode was used for the determination of Pb²⁺ in water coupled with this flow analysis device. The interference of co-existing ions and the precision, as well as the repeatability were examined. The relative standard deviation of Pb²⁺ was found to be 4.35% by repeating the test 25 times of 15 μg L⁻¹ standard solution. Under the optimized detection conditions, a limit of detection (3σ/slope) of 0.25 μg L⁻¹ was obtained between 2.5 and 100 μg L⁻¹. Finally, continuous determination of Pb²⁺ in drinking water and lake water in campus was carried out, which verified the applicability of the device in the detection of Pb²⁺ in natural water.

This study introduces a revolutionary nanofiltration membrane capable of significantly enhancing the removal of Pb(II), MO, and NaCl from industrial wastewater. The performance of polyethersulfone (PES) membranes was enhanced by incorporating PMO-PPD and CQD nanomaterials. The composite membranes demonstrated improved hydrophilic properties, reduced fouling, enhanced antibacterial activity, and increased pollutant removal capabilities. Characterization techniques confirmed the successful synthesis and integration of the nanomaterials into the membrane matrix. The inclusion of PMO-PPD/CQDs significantly improved pure water flux and fouling resistance compared to pristine PES membranes. The M3 membrane, containing 0.1 wt% PMO-PPD and 0.4 wt% CQDs nanofiller, exhibited the highest performance in terms of water flux (81.3 L m⁻² h⁻¹), bovine serum albumin rejection (29.5 L m⁻² h⁻¹), foul resistance ratio (63.7%), total resistance (58%), reversible resistance (21.6%), and irreversible resistance (36.3%). Among fabricated membranes, M3 demonstrated the highest pollutant removal rates, reaching 89.76%, 93.7%, and 36.77% for Pb(II) (initial concentration of 30 mg L⁻¹), methyl orange (MO) (initial concentration of 40 mg L⁻¹), and NaCl (initial concentration of 200 mg L⁻¹), respectively. Response surface methodology was employed to optimize the simultaneous removal of these pollutants. Additionally, the incorporation of CQDs enhanced the antibacterial properties of the membranes against E. coli (17.99%) and S. aureus (22.70%). It was found that the simultaneous application of two nanofillers significantly enhanced the efficiency and features of the nanofiltration membrane.