Journal of water process engineering最新文献

A breakthrough electrochemical reactor for the simultaneous production of hydrogen peroxide and ozone via solid electrolyte and gas diffusion electrode technologies 一个突破性的电化学反应器，通过固体电解质和气体扩散电极技术同时生产过氧化氢和臭氧

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-31 DOI: 10.1016/j.jwpe.2026.109636

Nicolas Perciani de Moraes , Rafael Granados-Fernández , Marcos Roberto de Vasconcelos Lanza , Manuel Andrés Rodrigo

This work reports the development of an innovative electrochemical reactor for the simultaneous on-site production of hydrogen peroxide (H₂O₂) and ozone (O₃) in a salt-free aqueous medium, based on a multilayer membrane–resin–electrode assembly (MMREA). The system employs a Printex L6 gas diffusion electrode as the cathode and a mesh boron-doped diamond anode, coupled through a compacted Nafion 117 membrane and Amberlite IR-120H⁺ resin layer to enable proton transport without supporting electrolytes. Under optimized conditions, the reactor achieved maximum current efficiencies of 19% for H₂O₂ and 4% for O₃, corresponding to production yields comparable to those reported for early stages laboratory-scale on-site electrochemical systems, while eliminating electrolyte-related downstream separation and corrosion issues. Hydrogen peroxide generation was favored at lower current densities and catholyte flow rates of 0.5–1.0 mL min⁻¹ (19.6 cm² electrode area), whereas ozone production increased with higher current densities, with stable current efficiencies over the evaluated range. The reactor exhibited stable performance under both continuous and discontinuous operation, indicating robustness for decentralized and intermittent operation scenarios. Although the current efficiencies remain lower than those of mature single-oxidant generators, the simultaneous and electrolyte-free production of H₂O₂ and O₃ enables direct in situ peroxone formation with reduced process complexity and chemical footprint. Additionally, the yields are sufficiently high to demonstrate the feasibility of the approach and the need for additional studies, given the high application potential. The applicability of this approach was demonstrated through the effective treatment of real pharmaceutical wastewater, highlighting its potential for decentralized advanced oxidation processes powered by renewable electricity.

这项工作报道了一种创新的电化学反应器的开发，该反应器基于多层膜-树脂-电极组件（MMREA），用于在无盐水介质中同时现场生产过氧化氢（H2O2）和臭氧（O3）。该系统采用Printex L6气体扩散电极作为阴极，网状硼掺杂金刚石阳极，通过致密的Nafion 117膜和Amberlite IR-120H+树脂层耦合，实现质子传输，而无需支持电解质。在优化条件下，反应器对H2O2和O3的最大电流效率分别达到19%和4%，与早期实验室规模的现场电化学系统的产量相当，同时消除了与电解质相关的下游分离和腐蚀问题。过氧化氢的生成有利于低电流密度和阴极液流速0.5-1.0 mL min - 1 （19.6 cm2电极面积），而臭氧的产生随着高电流密度而增加，在评估范围内电流效率稳定。反应器在连续和间断工况下均表现出稳定的性能，对分散和间歇工况具有鲁棒性。虽然目前的效率仍然低于成熟的单氧化剂发生器，但同时和无电解质生产H2O2和O3可以直接原位生成过氧化物，降低了工艺复杂性和化学足迹。此外，由于具有很高的应用潜力，产量足够高，证明了该方法的可行性和进一步研究的必要性。通过对实际制药废水的有效处理，证明了这种方法的适用性，突出了它在可再生电力驱动的分散高级氧化过程中的潜力。

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引用次数: 0

Integrating interpretable machine learning with multi-algorithm and encoding strategies for electrooxidation process optimization in rifampin degradation 集成可解释机器学习与多算法和编码策略的利福平降解电氧化过程优化

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-31 DOI: 10.1016/j.jwpe.2026.109588

Nawid Ahmad Akhtar , Namatullah Wahidi , Mehmet Kobya

In this study, a novel and systematic prediction framework is proposed to optimize electrooxidation (EO) process parameters (anode material, applied current, reaction time, initial pH, type and concentration of supporting electrolyte, initial RIF concentration, and different real water matrices) during rifampin (RIF) degradation. This framework integrates machine learning (ML) algorithms (random forest, decision tree, gradient boosting, multilayer perceptron, support vector machine, and K-nearest neighbors) with various encoding strategies (one-hot, target, and label). Furthermore, hyperparameter optimization techniques (grid search, grid search with noise-augmented data, random search, and Bayesian optimization) were evaluated to enhance predictive performance and provide an in-depth examination of RIF degradation. The boron-doped diamond (BDD) anode achieved 100% RIF degradation under optimal conditions (i = 0.2 A, C_RIF = 10 mg/L, SEc = 51 mM NaCl/L). In the performance evaluation of ML algorithms, the one-hot encoding for the DT algorithm yielded the best predictive accuracy, with the highest R² = 0.952 and Adjusted R² = 0.920 scores, alongside the lowest error metrics: MAE = 3.909, RMSE = 7.594, RSR = 0.217, AAD = 0.0624, and MAPE = 10.391. However, future importance analysis using Shapley Additive Explanations (SHAP), Gini impurity, and Mean Decrease in Accuracy (MDA) revealed that reaction time and anode materials are the most influential parameters for the EO process, whereas the electrolyte types and concentration demonstrated limited impact. Overall, the findings provide important insights into the EO process optimization and demonstrate the statistical robustness of the proposed ML-based framework.

在这项研究中，提出了一个新的系统的预测框架来优化利福平（RIF）降解过程中电氧化（EO）工艺参数（阳极材料、施加电流、反应时间、初始pH、支持电解质的类型和浓度、初始RIF浓度和不同的实际水基质）。该框架将机器学习（ML）算法（随机森林、决策树、梯度增强、多层感知器、支持向量机和k近邻）与各种编码策略（one-hot、target和label）集成在一起。此外，还评估了超参数优化技术（网格搜索、带噪声增强数据的网格搜索、随机搜索和贝叶斯优化），以提高预测性能，并对RIF退化进行了深入研究。在最佳条件（i = 0.2 A, CRIF = 10 mg/L, SEc = 51 mM NaCl/L）下，掺硼金刚石（BDD）阳极的RIF降解率达到100%。在ML算法的性能评价中，DT算法的单热编码获得了最好的预测精度，最高的R2 = 0.952，调整后的R2 = 0.920，最低的误差指标：MAE = 3.909, RMSE = 7.594, RSR = 0.217, AAD = 0.0624, MAPE = 10.391。然而，未来使用Shapley添加剂解释（SHAP）、基尼杂质（Gini杂质）和Mean Decrease in Accuracy （MDA）进行的重要性分析表明，反应时间和阳极材料是影响EO工艺的最重要参数，而电解质类型和浓度的影响有限。总的来说，这些发现为EO流程优化提供了重要的见解，并证明了所提出的基于ml的框架的统计鲁棒性。

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引用次数: 0

Effect of enzyme-induced carbonate precipitation on nitrogen loss from sheet erosion on purple soil slopes in the Three Gorges Reservoir area 酶促碳酸盐降水对三峡库区紫色土坡面板蚀氮流失的影响

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-31 DOI: 10.1016/j.jwpe.2026.109557

Hai Xiao , Jiejie Hou , Lun Zhang , Rui Xiang , Deyu Liu , Feng Gao , Yu Ding , Zhenyao Xia

Enzyme-induced carbonate precipitation (EICP) exhibits notable application potential for erosion reduction. However, the EICP reaction involves urea and ammonium, which may aggravate nitrogen loss. The effect of EICP on slope nitrogen loss during rainfall is uncertain. Therefore, purple soil was obtained from the Three Gorges Reservoir area to establish 7 slope treatments: bare slope control (CK), spraying of cementing solution (CK-C), spraying urease of solution (CK-U), and spraying of 0.5, 1.0, 1.5 and 2.0 mol/L of cementation solution concentrations for EICP treatments. Simulated rainfall experiments encompassing different rainfall intensities (60 and 120 mm/h) were conducted with slope gradients of 15°, 20° and 25°. The effects of various factors on nitrogen loss were analyzed using multivariate analysis of variance and partial least squares path modeling (PLS-PM). Compared with the CK treatments, the EICP treatments significantly increased total runoff by 31.30–47.93% and decreased total erosion by 87.14–92.40%. The EICP treatments significantly increased the concentrations of ammonium nitrogen (NH₄⁺-N) in the runoff, total nitrogen (TN) in the runoff, TN in the sediment by 54.88-fold, 19.79-fold and 30.57%, respectively, with increases positively correlated with the cementing solution concentration. The EICP treatments decreased the total loss of nitrate nitrogen (NO₃⁻-N) by 51.54% but increased the total losses of NH₄⁺-N and TN by 6.61-fold and 43.59%, respectively. The nitrogen loss pathway changed from particulate sediment in the CK, CK-C and CK-U to dissolved runoff in the EICP treatments. PLS-PM revealed that the EICP treatment primarily affected nitrogen loss through NH₄⁺-N, total runoff, and total sediment. Our results indicate nitrogen loss following EICP treatment is a concern, and strategies to reduce such loss should be established.

酶诱导碳酸盐沉淀（EICP）在减少侵蚀方面具有显著的应用潜力。然而，EICP反应涉及尿素和铵，可能会加剧氮的损失。降雨过程中EICP对坡面氮损失的影响尚不确定。因此，以三峡库区紫色土为研究对象，建立了裸坡控制（CK）、喷施胶结液（CK- c）、喷施溶液脲酶（CK- u）、喷施0.5、1.0、1.5和2.0 mol/L胶结液浓度EICP处理7种边坡处理方法。在坡度为15°、20°和25°的条件下，进行了不同降雨强度（60和120 mm/h）的模拟降雨试验。采用多变量方差分析和偏最小二乘路径模型（PLS-PM）分析了各因素对氮素损失的影响。与CK处理相比，EICP处理的总径流量显著增加31.30 ~ 47.93%，总侵蚀显著减少87.14 ~ 92.40%。EICP处理显著提高了径流中铵态氮（NH4+-N）、径流中总氮（TN）和底泥中TN的浓度，分别提高了54.88倍、19.79倍和30.57%，且与固结液浓度呈正相关。EICP处理使硝态氮（NO3−-N）总损失量减少了51.54%，使NH4+-N和TN总损失量分别增加了6.61倍和43.59%。在EICP处理下，氮的损失途径由CK、CK- c和CK- u的颗粒沉积物转变为溶解径流。PLS-PM显示，EICP处理主要通过NH4+-N、总径流和总泥沙影响氮损失。我们的研究结果表明，EICP处理后的氮损失是一个值得关注的问题，应该制定减少氮损失的策略。

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引用次数: 0

Activation of peroxydisulfate with N-doped CoFe2O4 for tetracycline hydrochloride degradation: the predominant role of radical and singlet oxygen cooperation n掺杂CoFe2O4活化过硫酸氢盐降解盐酸四环素：自由基和单重态氧协同作用的主导作用

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-30 DOI: 10.1016/j.jwpe.2026.109525

Jiawei Wei, Xia Chen, Yawei Gu, Wenqiang Jiang

Advanced oxidation based on peroxodisulfate(PDS) is a promising water treatment processes, but its application is limited due to the high energy input required for activation. A simple sol-gel approach was adopted to synthesize N-doped CoFe₂O₄, which then served as an effective activator for PDS. The catalyst generated multiple radicals (O₂·-, SO₄·-, ·OH) and ¹O₂, which acted synergistically to degrade tetracycline hydrochloride (TCH). Within 10 min, TCH was almost completely degraded. Compared with CoFe₂O₄/PDS, the TCH degradation efficiency achieved by the N-CoFe₂O₄/PDS system increased by 26% within 10 min. A series of characterizations confirmed that nitrogen doping reduced the charge transfer resistance of CoFe₂O₄, This reduction greatly enhanced the material's electron transfer capability, promoted electron exchange between metal ions, and facilitated the bimetallic redox cycle. Consequently, the activation efficiency of PDS was significantly improved. Moreover, the high electron-donating capacity of nitrogen accelerated the continuous interconversion between the Fe²⁺/Fe³⁺ and Co²⁺/Co³⁺ redox couples. These properties endowed the N-CoFe₂O₄/PDS system with superior TCH degradation performance, compensating for the low efficiency associated with traditional metal-ion activation of PDS.

基于过硫酸盐的深度氧化是一种很有前途的水处理工艺，但由于激活所需的高能量输入，其应用受到限制。采用简单的溶胶-凝胶法合成了n掺杂的CoFe₂O₄，并将其作为PDS的有效活化剂。催化剂生成多个自由基（O2·-、SO4·-、·OH）和1O2，协同作用降解盐酸四环素。在10分钟内，TCH几乎完全降解。与CoFe2O4/PDS相比，N-CoFe₂O₄/PDS体系在10 min内对TCH的降解效率提高了26%。一系列表征证实，氮掺杂降低了CoFe2O4的电荷转移阻力，这种降低大大增强了材料的电子转移能力，促进了金属离子之间的电子交换，促进了双金属氧化还原循环。因此，PDS的活化效率显著提高。此外，氮的高给电子能力加速了Fe2+/Fe3+和Co2+/Co3+氧化还原对之间的连续相互转化。这些特性使N-CoFe2O4/PDS体系具有优异的TCH降解性能，弥补了传统金属离子活化PDS的低效率。

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引用次数: 0

A novel perspective on WWTP prediction: Enhancing accuracy and generalization through a systematic feature engineering framework 污水处理量预测的新视角：通过系统特征工程框架提高准确性和泛化

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-29 DOI: 10.1016/j.jwpe.2026.109604

Yaning Xiao , Bowei Zhao , Xiao Zhang , Xiuping Yue

The implementation of precise process control in wastewater treatment plants (WWTPs) is currently impeded by the limitations of traditional models in addressing the inherent nonlinearity and complex temporal dependencies present in raw monitoring data. To address this challenge, this study proposes a data-centric paradigm shift through the introduction of a systematic feature engineering framework. This framework operates through a three-stage workflow: initially, constructing historical lag variables to rigorously capture the temporal continuity of treatment processes; subsequently, employing a multi-evaluator system to identify dominant features and eliminate data redundancy; and finally, adopting an adaptive signal decomposition strategy to mitigate the inherent nonstationarity and fluctuations in water quality data. Validated across 144 independent experimental scenarios (encompassing four wastewater plants, three water quality indicators, and 12 models), this framework demonstrated strong universality, achieving an average reduction in prediction error of over 20%. Critically, this study verified a highly cost-effective pathway for the practical implementation of intelligent operations. This demonstrates that by maximizing the use of existing operational data, robust effluent quality predictions can be achieved without resorting to costly hardware upgrades or the maintenance of complex deep learning architectures. This significantly lowers the threshold for full-scale deployment and offers a scalable solution for optimizing the energy efficiency and ensuring stable, compliant effluents under fluctuating operating conditions.

目前，由于传统模型在处理原始监测数据中存在的固有非线性和复杂的时间依赖性方面的局限性，阻碍了污水处理厂（WWTPs）精确过程控制的实施。为了应对这一挑战，本研究通过引入系统特征工程框架，提出了以数据为中心的范式转变。该框架通过三个阶段的工作流程运行：首先，构建历史滞后变量，以严格捕获处理过程的时间连续性；随后，采用多评价器系统识别优势特征，消除数据冗余；最后，采用自适应信号分解策略减轻水质数据固有的非平稳性和波动。通过144个独立实验场景（包括4个污水厂、3个水质指标和12个模型）的验证，该框架具有很强的通用性，预测误差平均降低了20%以上。至关重要的是，本研究为实际实施智能操作验证了一条高成本效益的途径。这表明，通过最大限度地利用现有的操作数据，可以实现强大的污水质量预测，而无需诉诸昂贵的硬件升级或维护复杂的深度学习架构。这大大降低了全面部署的门槛，并提供了一个可扩展的解决方案，以优化能源效率，并确保在波动的操作条件下稳定、合规的废水。

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引用次数: 0

Mechanistic insights into magnetite-enhanced Indoleacetic acid production by a mixed culture 混合培养对磁铁矿增强吲哚乙酸生产的机理研究

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-29 DOI: 10.1016/j.jwpe.2026.109611

Yun-Xin Ge , Wei Gao , Zi-Han Fan , Yun Niu , Long-Tao Fang , Xi-Zhen Zou , Wei Zhang

Low conversion efficiency and low product yield are key limitations of mixed culture indoleacetic acid (IAA) production. Although zero-valent iron can enhance IAA synthesis, iron sludge accumulation remains a major bottleneck, necessitating more efficient and alternative strategies. In this study, magnetite was found to significantly improve IAA production by mixed culture. At 8 g·L⁻¹, magnetite increased the IAA production rate from 2.67 ± 0.11 to 7.01 ± 0.06 mg·L⁻¹·h⁻¹, the tryptophan consumption rate from 6.19 ± 0.55 to 11.16 ± 1.18 mg·L⁻¹·h⁻¹, and the conversion rate from 50.46% to 73.77%. Klebsiella, the dominant IAA-producing genus (35.84 ± 0.30%), was promoted by magnetite, along with electroactive Clostridium (increased by 1.44 ± 0.38%). Microbial community analysis suggested strengthened interactions between electroactive bacteria and IAA producers. Dissolved Fe²⁺ and Fe³⁺ inhibited IAA production, indicating that iron ions were not responsible for the enhancement. Instead, magnetite increased intracellular Na⁺/K⁺-ATPase activity by 12.47 ± 1.60% and relative electron transport by 42.81 ± 1.16%. Macrotranscriptomic data revealed upregulation of cytochrome c genes (0.21 ± 0.06 to 310 ± 6 folds) and the amiE gene (3.03 ± 0.52 folds), which is involved in converting indole-3-acetamide to IAA. These results demonstrate that magnetite enhances IAA synthesis by stimulating cytochrome c and IAA synthetase expression, providing a promising strategy for improving mixed culture IAA production.

低转化效率和低产品收率是混合培养生产吲哚乙酸的主要限制因素。虽然零价铁可以提高IAA合成，但铁污泥积累仍然是主要瓶颈，需要更有效的替代策略。本研究发现，磁铁矿可显著提高混合培养的IAA产量。在8 g·L−1条件下，磁铁矿使IAA产率从2.67±0.11提高到7.01±0.06 mg·L−1·h−1，色氨酸消耗率从6.19±0.55提高到11.16±1.18 mg·L−1·h−1，转化率从50.46%提高到73.77%。产iaa的优势属克雷伯菌（35.84±0.30%）和电活性梭状芽孢杆菌（1.44±0.38%）均受磁铁矿的促进。微生物群落分析表明，电活性菌与IAA产生菌之间的相互作用增强。溶解的Fe2+和Fe3+抑制了IAA的产生，表明铁离子对IAA的增强作用不起作用。相反，磁铁矿使细胞内Na+/K+- atp酶活性增加了12.47±1.60%，相对电子传递增加了42.81±1.16%。大转录组学数据显示，参与吲哚-3-乙酰酰胺转化为IAA的细胞色素c基因上调（0.21±0.06至310±6倍），amiE基因上调（3.03±0.52倍）。这些结果表明，磁铁矿通过刺激细胞色素c和IAA合成酶的表达来促进IAA的合成，为提高混合培养IAA产量提供了一种有希望的策略。

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引用次数: 0

Electrochemical detection of anticancer drug in aquatic environments using multiwall carbon nanotube decorated on cerium tungsten oxide modified disposable carbon electrode 多壁碳纳米管修饰的氧化铈钨修饰一次性碳电极在水生环境中抗癌药物的电化学检测

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-29 DOI: 10.1016/j.jwpe.2026.109589

Sharmila Tharuman , Agalya Mahalingam , Tse-Wei Chen , Nandini Nataraj , Sivaprakash Sengodan , Shen-Ming Chen , Keerthi Murugan

Pharmaceutical pollutants, particularly anti-androgenic drugs used in cancer therapy, have emerged as persistent contaminants in aquatic environments, posing potential risks to both ecosystems and human health. Nilutamide (NLT), an anti-androgen medication used in prostate cancer treatment, is metabolized in the liver, generating toxic by-products. Alarming concentrations of NLT have recently been reported in natural ecosystems, highlighting the need for thorough monitoring. In response, electrochemical sensors have emerged as powerful tools, providing compact, highly sensitive, and selective detection capabilities. This study reports electrochemical sensor based on Ce₂W₂O₉/f-MWCNT nanocomposite for the determination of NLT in environmental samples. The prepared sensor demonstrated a LOD of 12 nM, linear range of 0.049–1589.09 mM and a sensitivity of 1.4 mA mM⁻¹ cm⁻² towards the electrochemical reduction of NLT. The Ce₂W₂O₉/f-MWCNT nanocomposite works synergistically to create a conductive, catalytically active interface that accelerates electron transfer kinetics and allows for highly sensitive detection of NLT at low concentrations. In addition, the material's flexibility combined with its structural integrity ensures reliable operation and repeatable sensor responses.

药物污染物，特别是用于癌症治疗的抗雄激素药物，已成为水生环境中的持久性污染物，对生态系统和人类健康构成潜在风险。尼鲁胺（NLT）是一种用于前列腺癌治疗的抗雄激素药物，在肝脏中代谢，产生有毒副产物。最近在自然生态系统中报告了令人震惊的NLT浓度，突出表明需要进行彻底监测。作为回应，电化学传感器已经成为强大的工具，提供紧凑，高灵敏度和选择性的检测能力。本研究报道了基于Ce2W2O9/f-MWCNT纳米复合材料的电化学传感器用于环境样品中NLT的测定。该传感器的LOD为12 nM，线性范围为0.049 ~ 1589.09 mM，对NLT的电化学还原灵敏度为1.4 mA mM−1 cm−2。Ce2W2O9/f-MWCNT纳米复合材料协同作用，形成导电、催化活性界面，加速电子转移动力学，并允许在低浓度下高度敏感地检测NLT。此外，该材料的灵活性及其结构完整性确保了可靠的操作和可重复的传感器响应。

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引用次数: 0

FiTiformer: A fluctuation–trend modulation model for multi-step forecasting of wastewater influent parameters FiTiformer：一种用于污水输入参数多步预测的波动趋势调制模型

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-29 DOI: 10.1016/j.jwpe.2026.109600

Yiqi Liu , Shuyang Ren , Gang Fang

Accurate multi-step forecasting of key influent parameters is of great importance for the stable operation, energy optimization and early warning of wastewater treatment plants (WWTPs). However, existing Transformer-based approaches often fail to capture the strong non-stationarity and complex local fluctuations of wastewater data. To address these challenges, we propose a novel forecasting model, termed the Fluctuation-injected Trend inverted Transformer (FiTiformer), which enhances predictions by jointly modeling trend and fluctuation components. In this model, we design a Gated Fluctuation-to-Trend Modulation (GFTM) module that adaptively injects high-frequency fluctuation signals into the trend representation, thereby enhancing robustness under non-stationary conditions. This module is complemented by an inverted Transformer network that captures inter-variable dependencies to extract informative fluctuation features, while a Patch-wise Structural Loss ensures that local patterns are preserved in predictions, rather than focusing solely on global errors. Extensive experiments on the BSM2 benchmark and a full-scale WWTP dataset validate the effectiveness of FiTiformer. On the BSM2 dataset, the model achieves an average R

^{2}

above 0.88 while reducing RMSE by more than 7.4%. On the full-scale WWTP dataset, FiTiformer attains an average R

^{2}

above 0.70 with an RMSE reduction exceeding 8.0%. These results demonstrate that FiTiformer enhances both global trend modeling and local fluctuation preservation, offering reliable and interpretable multi-step forecasting for practical WWTP operations.

关键进水参数的准确多步预测对污水处理厂的稳定运行、能源优化和预警具有重要意义。然而，现有的基于变压器的方法往往无法捕获废水数据的强非平稳性和复杂的局部波动。为了应对这些挑战，我们提出了一种新的预测模型，称为波动注入趋势反转变压器（FiTiformer），它通过联合建模趋势和波动分量来增强预测。在该模型中，我们设计了一个门控波动趋势调制（GFTM）模块，该模块自适应地将高频波动信号注入趋势表示中，从而增强了非平稳条件下的鲁棒性。该模块由倒置的Transformer网络补充，该网络捕获变量间依赖关系以提取信息波动特征，而Patch-wise Structural Loss确保在预测中保留局部模式，而不是仅仅关注全局误差。在BSM2基准测试和全尺寸WWTP数据集上的大量实验验证了FiTiformer的有效性。在BSM2数据集上，模型的平均R2在0.88以上，均方根误差降低了7.4%以上。在全面的WWTP数据集上，FiTiformer的平均R2高于0.70，RMSE降低超过8.0%。结果表明，FiTiformer增强了全局趋势建模和局部波动保存能力，为实际污水处理厂运行提供了可靠的、可解释的多步预测。

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引用次数: 0

First synergistic application of photocatalysis by novel graphitic carbon nitride nanomaterial and low-temperature plasma technology for highly efficient removal of pharmaceuticals from real wastewater 首次将新型石墨氮化碳纳米材料与低温等离子体技术协同应用于光催化高效去除实际废水中的药物

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-29 DOI: 10.1016/j.jwpe.2026.109545

František Zažímal , Anna Podmanická , Miriama Malček Šimunková , Zuzana Imreová , Shalu Atri , Alexandra Paulína Drdanová , Martin Markovič , Peter Kóóš , Olivier Monfort , Andrea Vojs Staňová , Tomáš Mackuľak , Tomáš Homola

This study investigates, for the first time, the combined application of visible-light photocatalysis using a novel graphitic carbon nitride (gCN) nanomaterial and low-temperature plasma generated in air by a multi-hollow surface dielectric barrier discharge (MSDBD) for the treatment of real wastewater effluent. The combined photocatalysis+plasma process exhibited high performance for a broad range of pharmaceutical compounds, with efficiencies that nearly achieved or exceeded the 80% removal threshold defined by the new EU Urban Wastewater Treatment Directive 2024/3019 (EU UWWTD 2024/3019). Analysis of reactive oxygen species (ROS) demonstrated that the pollutant degradation in the combined photocatalysis+plasma system was primarily driven by plasma-generated species, such as ozone (O₃), nitrates (NO₃⁻), and nitrites (NO₂⁻), whereas the contributions of superoxide anion radical (O₂^-·) and singlet oxygen (¹O₂) generated by plasma and photocatalysis individually were minor. Fixation of ammonia in wastewater treated by MSDBD was not detected. The presence of gCN mitigated plasma-induced acidification, maintaining the wastewater pH near neutral. Investigation of the sulfamethoxazole (SMX) degradation pathway revealed an approximately 50% reduction in N4-acetyl-sulfamethoxazole, indicating partial mitigation of this persistent transformation product of environmental concern and underscoring the advantages of the combined plasma+photocatalytic process.

本研究首次将新型石墨氮化碳（gCN）纳米材料与多空心表面介质阻挡放电（MSDBD）在空气中产生的低温等离子体在可见光催化下的结合应用于实际废水的处理。光催化+等离子体联合工艺对多种药物化合物表现出高性能，效率接近或超过欧盟城市废水处理指令2024/3019 （EU UWWTD 2024/3019）规定的80%的去除率。活性氧（ROS）分析表明，在光催化+等离子体联合系统中，污染物的降解主要由等离子体生成的臭氧（O3）、硝酸盐（NO3−）和亚硝酸盐（NO2−）驱动，而等离子体和光催化单独产生的超氧阴离子自由基（O2-·）和单态氧（1O2）的贡献较小。未检测到MSDBD处理废水中氨的固定作用。gCN的存在减轻了等离子体引起的酸化，使废水pH值保持在中性附近。对磺胺甲恶唑（SMX）降解途径的研究表明，n4 -乙酰-磺胺甲恶唑的含量减少了约50%，这表明这种持续转化产物的环境问题得到了部分缓解，并强调了等离子体+光催化联合工艺的优势。

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引用次数: 0

Enterprise-oriented optimization of carbon accounting methods for wastewater treatment plants: Comparative analysis, modeling, and application in China 面向企业的污水处理厂碳核算方法优化：比较分析、建模及在中国的应用

IF 6.7 2区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of water process engineering

Pub Date : 2026-01-28 DOI: 10.1016/j.jwpe.2026.109598

Xiangyu Zhang, Baoyi Tian, Guanmin Li, Rongguang Li, Kai Ma, Xinfei Li, Shichao Jia, Changchun Xin

This study examines challenges in carbon emission accounting for wastewater treatment enterprises, particularly the diverse guidelines and difficulty in selecting appropriate methods. A comparative analysis of six mainstream methodologies, focusing on accounting boundaries and emission factors, was conducted. The case calculations for three wastewater treatment plants in northern China indicate significant discrepancies in carbon emission estimates between different methods, with a range of 61% and a standard deviation of 17.35%. An improved accounting method was proposed, integrating operational and extended responsibility emissions, localized emission factors, and simplified procedures. The carbon emission intensity ranged from 0.78 to 1.02 kg CO₂-eq/m³, with electricity consumption, sodium hypochlorite usage, and nitrous oxide emissions as major contributors. Sensitivity analysis showed strong correlations between carbon intensity and nitrogen removal. Each additional 1 mg/L of nitrogen removed increased carbon intensity by approximately 0.014 kg CO₂-eq/m³. A ridge regression model confirmed total nitrogen and biochemical oxygen demand removal as key drivers. Furthermore, a support vector regression model using influent quality parameters achieved robust prediction performance with coefficient of determination values of 0.759, supporting feedforward carbon management for small- and medium-sized plants. This study offers a closed-loop framework for carbon emission management and practical tools for wastewater sector decarbonization.

本研究探讨了污水处理企业碳排放核算的挑战，特别是不同的指导方针和选择适当方法的困难。以计算边界和排放因子为重点，对六种主流方法进行了比较分析。对中国北方三个污水处理厂的实例计算表明，不同方法之间的碳排放估算存在显著差异，其范围为61%，标准差为17.35%。提出了一种改进的核算方法，将经营责任排放和延伸责任排放、局部排放因子和简化程序结合起来。碳排放强度范围为0.78 ~ 1.02 kg CO2-eq/m3，其中电力消耗、次氯酸钠使用和一氧化二氮排放是主要排放源。敏感性分析表明，碳强度与氮去除率之间存在较强的相关性。每增加1 mg/L的氮去除量，碳强度增加约0.014 kg CO2-eq/m3。脊回归模型证实总氮和生化需氧量去除是关键驱动因素。采用水质参数构建的支持向量回归模型具有较好的预测效果，决定系数为0.759，支持中小电厂的前馈碳管理。本研究提供了碳排放管理的闭环框架和废水部门脱碳的实用工具。

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引用次数: 0