Water Research X最新文献_第5页

Comprehensive evaluation of UV inactivation of E. coli using multiple gene targets and real-time quantitative PCR 利用多基因靶点和实时定量PCR技术对大肠杆菌紫外线灭活的综合评价

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-22 DOI: 10.1016/j.wroa.2024.100285

Natasha Rahman , Subba Rao Chaganti , Rajesh Seth , Daniel D. Heath

UV disinfection is extensively used for wastewater disinfection and disinfection efficiency is commonly monitored using culture-based enumeration of E. coli. While culture-independent real-time quantitative polymerase chain reaction (qPCR) based methods are attractive due to faster turnaround and easier application, previous attempts with qPCR to monitor disinfection have been unsuccessful. In this study, the effect of UV irradiation on a pure E. coli culture was examined in collimated beam (CB) experiments and monitored using both a culturing technique and DNA damage quantified using both short amplicon (SA; <∼200 bp) qPCR and longer amplicon (LA; ∼500-bp) qPCR. The results, covering a UV dose range of 0 - 20 mJ/cm² commonly used for wastewater disinfection, indicate a correlation between DNA gene damage quantified by both SA- and LA-qPCR and the decline in E. coli observed through culture-based methods. This demonstrates the potential of qPCR to serve as rapid alternative for monitoring wastewater disinfection efficacy. Furthermore, LA-qPCR was observed to be more sensitive than SA-qPCR. The results using LA-qPCR also revealed that UV exposure caused widespread and indiscriminate damage to E. coli’s genome, which is considered critical for its function and survival. The combined effect of UV on E. coli’s ability to function, grow or repair damage is suggested as the reason for the decline in culturability observed.

紫外线消毒广泛用于废水消毒，通常使用基于培养的大肠杆菌计数来监测消毒效率。虽然基于培养无关的实时定量聚合酶链反应（qPCR）的方法由于更快的周转和更容易应用而具有吸引力，但以前使用qPCR监测消毒的尝试都不成功。在本研究中，通过准直光束（CB）实验检测了紫外线照射对纯大肠杆菌培养物的影响，并使用培养技术和DNA损伤监测，使用短扩增子(SA；< ~ 200 bp) qPCR和更长的扩增子(LA；500 - bp) qPCR∼。结果表明，在通常用于废水消毒的0 - 20 mJ/cm2的紫外线剂量范围内，SA-和LA-qPCR量化的DNA基因损伤与通过培养方法观察到的大肠杆菌数量下降之间存在相关性。这证明了qPCR作为监测废水消毒效果的快速替代方法的潜力。此外，LA-qPCR比SA-qPCR更敏感。使用LA-qPCR的结果还显示，紫外线暴露对大肠杆菌的基因组造成广泛和不加区分的损伤，这被认为是其功能和生存的关键。紫外线对大肠杆菌功能、生长或修复损伤的能力的综合影响被认为是观察到的培养能力下降的原因。

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引用次数: 0

Leak detection and localization in water distribution systems via multilayer networks 基于多层网络的配水系统泄漏检测与定位

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-22 DOI: 10.1016/j.wroa.2024.100280

Daniel Barros , Ariele Zanfei , Andrea Menapace , Gustavo Meirelles , Manuel Herrera , Bruno Brentan

The continuous increase of water distribution networks (WDNs) in size and complexity poses significant management challenges, including a high risk of failures. Due to the intrinsic interconnected feature of water flow, including losses, this study proposes a methodology based on graph correlation and multilayer network analysis for leak detection and localization in WDNs with multiple components (infrastructure, control devices, hydraulic sensors). The detection process involves correlating monitored data to create a temporal graph and classify vertices. The classification values are then analyzed by the z-score and interquartile range algorithms to detect anomalies. The localization process uses a multi-graph approach that combines sensor data and network topology to determine the sensor coverage area. The Dynamic Time Warping algorithm calculates the similarity between monitored and simulated leak data, identifying likely leak locations. The results demonstrate the methodology’s effectiveness, detecting anomalies 15 minutes after the start of the leak and locating them within a 50-meter range from the actual location of the leak. Furthermore, the research highlights the advantages of using a method based on multilayer networks, which offers insights into leak location, sensor coverage, and reduction of the network’s sample space. Furthermore, the approach presents a proposal to reduce exhaustive hydraulic simulations.

供水网络的规模和复杂性不断增加，对管理提出了重大挑战，包括高故障风险。由于水流固有的相互关联特征，包括损失，本研究提出了一种基于图关联和多层网络分析的多组件（基础设施、控制设备、液压传感器）wdn泄漏检测和定位方法。检测过程包括关联监控数据以创建时间图并对顶点进行分类。然后通过z-score和四分位间距算法分析分类值以检测异常。定位过程使用多图方法，结合传感器数据和网络拓扑来确定传感器覆盖区域。动态时间扭曲算法计算监测和模拟泄漏数据之间的相似性，识别可能的泄漏位置。结果证明了该方法的有效性，可以在泄漏开始后15分钟检测到异常，并在距离实际泄漏位置50米范围内定位异常。此外，该研究还强调了使用基于多层网络的方法的优势，该方法可以深入了解泄漏位置、传感器覆盖范围和减少网络样本空间。此外，该方法还提出了减少详尽的水力模拟的建议。

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引用次数: 0

Autonomous online optimization of a closed-circuit reverse osmosis system 闭路反渗透系统的自主在线优化

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-20 DOI: 10.1016/j.wroa.2024.100279

Dhrubajit Chowdhury , Aurora Kuras , Tani Cath , Amanda S. Hering , Alexander Melin , Tzahi Y. Cath , Kris Villez

As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.

随着淡水变得越来越稀缺，许多工业和市政供水公司着眼于室内规模的水处理和再利用，以满足水的需求。闭路反渗透（CCRO）被认为是一种很有前途的工艺设计。这种顺序批处理工艺可以通过循环流在更高的盐水盐度水平下进行操作。最佳操作要求膜表面的最大盐度水平代表卤水处理成本和能源效率之间的最佳权衡。随着给水成分的变化和电力市场的波动，这个最高盐度水平可能会随着时间的推移而变化。在这篇文章中，我们展示了一种被称为极值寻求控制的连续在线优化自动技术的实验评估结果。该技术在过程控制界有着悠久的历史，但迄今为止在水工业中几乎没有得到牵引力。我们修改了该技术，使其能够用于CCRO的在线优化，特别是考虑到其顺序批处理操作。我们通过几个实验测试对优化方案进行了挑战，并说明了极值寻求控制的优点和缺点。

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引用次数: 0

Making waves: Public health risks from arsenic in Mexico's water extraction practices 掀起波澜：墨西哥取水工艺中的砷对公众健康造成的风险

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-19 DOI: 10.1016/j.wroa.2024.100283

Gabriel López Porras , Patrick Allard

In response to water scarcity in Mexico´s urban areas, authorities have implemented significant measures to increase water access, primarily by overexploiting groundwater resources. However, this approach has unintentionally worsened human exposure to groundwater arsenic consumption, which is part of a broader phenomenon known as environmental problem shifting. This paper examines the public health implications of arsenic contamination in Mexico's groundwater. We particularly focus our analysis on urban areas to demonstrate the policy gap that leaves the issue of arsenic contamination caused by over-pumping, and its associated widespread health risks, largely unaddressed. We draw on evidence from Mexico, but also Bangladesh, to define and describe the issue of such problem-shifting and how it underlies the urgent need to develop integrative water management strategies that balance the demands of water access with the necessity of maintaining water quality. By analysing water data from Mexico, the paper calls for a reconsideration of water policies to prevent further health crises.

为了应对墨西哥城市地区的缺水问题，当局主要通过过度开采地下水资源，采取了大量措施来增加用水量。然而，这种做法无意中加剧了人类对地下水砷消耗的暴露，而这正是被称为环境问题转移的更广泛现象的一部分。本文探讨了墨西哥地下水砷污染对公众健康的影响。我们特别将分析重点放在城市地区，以说明过度抽水造成的砷污染问题及其相关的广泛健康风险在很大程度上未得到解决的政策空白。我们利用来自墨西哥和孟加拉国的证据来定义和描述这种问题转移的问题，以及它是如何成为制定综合水资源管理战略的迫切需求的基础，从而在获取水资源的需求和保持水质的必要性之间取得平衡。通过分析墨西哥的水数据，本文呼吁重新考虑水政策，以防止进一步的健康危机。

引用次数: 0

Cyanobacteria as dominant mediator of altitudinal gradient effects on phytoplankton community diversity in freshwater ecosystems: Evidences from the freshwater Lakes along the Hu Line 蓝藻是海拔梯度对淡水生态系统浮游植物群落多样性影响的主要中介：来自沪宁线淡水湖的证据

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-17 DOI: 10.1016/j.wroa.2024.100281

Wei Wang , Zhongshi He , Junping Lv , Xudong Liu , Shulian Xie , Jia Feng

Phytoplankton are vital components of freshwater ecosystems, serving as primary producers and ecological indicators of freshwater health. While substantial research has explored the dynamics and potential drivers of phytoplankton communities in freshwater lakes, the influence of altitude—a crucial geographic factor—remains unelucidated. In this study, we investigated 26 lakes located along the eastern section of the Hu Line (Heihe–Tengchong Line) from China, focusing on how altitudinal gradients shape phytoplankton communities. Our findings reveal that cyanobacteria increasingly dominate community abundance with rising altitude. However, this dominance results in a reduction of community diversity, as cyanobacteria outcompete other taxa, thereby narrowing the ecological niches available. Further analysis indicates that the effects of altitude are mediated primarily by dominant cyanobacteria, which are equipped with gas vesicles that provide an adaptive advantage under low atmospheric pressure conditions associated with higher altitudes. This physiological trait allows cyanobacteria to maintain buoyancy and occupy favorable niches in the water column, enhancing their proliferation at the expense of overall community diversity. The study underscores the critical role of altitude in modulating phytoplankton community structure through its direct influence on cyanobacteria. These findings contribute new insights into the ecological processes that regulate freshwater ecosystems across altitudinal gradients, and highlight the need for targeted management strategies in regions where cyanobacterial dominance (cyanobacterial blooms) may compromise water quality and biodiversity.

浮游植物是淡水生态系统的重要组成部分，既是初级生产者，也是淡水健康的生态指标。尽管已有大量研究探讨了淡水湖泊浮游植物群落的动态和潜在驱动因素，但海拔高度这一关键地理因素的影响仍未得到阐明。在这项研究中，我们调查了位于中国沪宁线（黑河-腾冲线）东段的 26 个湖泊，重点研究了海拔梯度如何塑造浮游植物群落。我们的研究结果表明，随着海拔的升高，蓝藻在群落丰度中越来越占主导地位。然而，这种优势导致群落多样性的减少，因为蓝藻与其他类群竞争，从而缩小了可用的生态位。进一步的分析表明，海拔高度的影响主要是由优势蓝藻介导的，这些蓝藻具有气囊，在与高海拔相关的低气压条件下具有适应优势。这种生理特性使蓝藻能够保持浮力并占据水体中的有利位置，从而在牺牲整体群落多样性的情况下提高蓝藻的繁殖能力。该研究强调了海拔高度通过对蓝藻的直接影响，在调节浮游植物群落结构中的关键作用。这些发现有助于深入了解调节不同海拔梯度淡水生态系统的生态过程，并强调了在蓝藻占优势（蓝藻藻华）可能损害水质和生物多样性的地区采取有针对性的管理策略的必要性。

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引用次数: 0

Identifying periods impacted by sewer inflow and infiltration using time series anomaly detection 利用时间序列异常检测确定受下水道流入和渗透影响的时段

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-12 DOI: 10.1016/j.wroa.2024.100278

Jingyu Ge , Jiuling Li , Ruihong Qiu , Tao Shi , Zi Huang , Yanchen Liu , Zhiguo Yuan

Accurate diagnosis of sewer inflow and infiltration (I/I) is crucial for ensuring the safe transportation of sewage and the stability of wastewater treatment processes. Identifying periods impacted by I/I is essential for I/I diagnosis, but current methods lack a standard criterion and require adaptation to specific conditions, resulting in low accuracy, complexity, and limited generalizability. This paper proposes a novel approach to distinguish I/I periods from time series of sewer measurements based on anomaly detection theory through an iterative use of a time-series reconstruction model. This method eliminates the need for external data such as rainfalls and avoids intensive manual data analysis. Operating directly on in-sewer data, it enhances accuracy compared to existing approaches and is applicable to various external factors such as rainfall, snowmelt, and seawater intrusion. The method can be applicable to a broad range of monitoring data, including flow rate, temperature, and conductivity. Validated through simulation studies and demonstrated via real-life applications, this method offers an efficient solution for I/I detection, facilitating further I/I diagnosis, including I/I quantification and location identification.

下水道流入和渗出（I/I）的准确诊断对于确保污水的安全运输和污水处理工艺的稳定性至关重要。识别受流入/渗出影响的时期对于流入/渗出诊断至关重要，但目前的方法缺乏标准准则，需要根据具体条件进行调整，因此准确性低、复杂性高、通用性有限。本文以异常检测理论为基础，通过迭代使用时间序列重建模型，提出了一种从污水测量时间序列中区分内/外溢期的新方法。这种方法不需要降雨量等外部数据，也避免了密集的人工数据分析。与现有方法相比，该方法直接利用下水道内部数据，提高了准确性，并适用于降雨、融雪和海水入侵等各种外部因素。该方法适用于各种监测数据，包括流速、温度和电导率。通过模拟研究和实际应用的验证，该方法为内/外入侵检测提供了高效的解决方案，有助于进一步诊断内/外入侵，包括内/外入侵量化和位置识别。

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引用次数: 0

Effluent quality soft sensor for wastewater treatment plant with ensemble sparse learning-based online next generation reservoir computing 基于集合稀疏学习的在线下一代储层计算的污水处理厂出水水质软传感器

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-10 DOI: 10.1016/j.wroa.2024.100276

Gang Fang , Daoping Huang , Zhiying Wu , Yan Chen , Yan Li , Yiqi Liu

Real-time monitoring of key quality variables is essential and crucial for stable and safe operations of wastewater treatment plants (WWTPs). Next generation reservoir computing (NG-RC) has recently garnered significant attention in quality prediction, such as COD and BOD, as an effective alternative to traditional reservoir computing (RC), then is able to act as a data-driven soft sensor to twin a hardware sensor for quality variable measurements. Unlike RC, NG-RC does not require random sampling matrices to define the weights of recurrent neural networks and has fewer hyperparameters. However, NG-RC is usually used online but trained offline, thus leading to model degradation under dynamic scenarios. This paper proposes a sparse online NG-RC approach to meet the real-time requirements of WWTPs and mitigate the impact of measurement noise on the model. First, inspired by the Woodbury matrix identity, an incremental strategy is designed, using sequentially arriving data blocks to learn the output weights of NG-RC online. Then, an ensemble sparse strategy is combined to alleviate overfitting issues of the prediction model. Moreover, a soft sensor based on the ensemble sparse online NG-RC is developed to perform real-time prediction of quality indicators in wastewater treatment processes. Finally, two datasets from actual WWTPs are used to validate the effectiveness of the proposed model.

实时监测关键水质变量对于污水处理厂（WWTP）的稳定和安全运行至关重要。下一代水库计算（NG-RC）作为传统水库计算（RC）的有效替代方法，最近在化学需氧量（COD）和生化需氧量（BOD）等水质预测领域引起了广泛关注。与 RC 不同，NG-RC 不需要随机抽样矩阵来定义递归神经网络的权重，超参数也较少。然而，NG-RC 通常是在线使用但离线训练，因此会导致动态场景下的模型退化。本文提出了一种稀疏在线 NG-RC 方法，以满足污水处理厂的实时性要求，并减轻测量噪声对模型的影响。首先，受伍德伯里矩阵同一性的启发，设计了一种增量策略，利用连续到达的数据块来在线学习 NG-RC 的输出权重。然后，结合集合稀疏策略来缓解预测模型的过拟合问题。此外，还开发了一种基于集合稀疏在线 NG-RC 的软传感器，用于实时预测污水处理过程中的质量指标。最后，利用两个来自实际污水处理厂的数据集来验证所提模型的有效性。

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引用次数: 0

Leveraging multi-level correlations for imputing monitoring data in water supply systems using graph signal sampling theory 利用图信号采样理论，利用多级相关性对供水系统中的监测数据进行归类

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-08 DOI: 10.1016/j.wroa.2024.100274

Xiao Zhou , Yacan Man , Shuming Liu , Juan Zhang , Rui Yuan , Wei Wang , Kuizu Su

Data missing and anomalies in monitoring equipment have become critical barriers to developing intelligent Water Supply Systems (WSS). The valid data preceding and after the missing segments can be utilized to impute missing values. However, traditional imputation methods, such as linear interpolation and prediction-based methods, have limited capacity to use data relationships or can only utilize information before the missing values. Therefore, existing methods still need to work on efficiently and conveniently achieving high-accuracy imputation. According to the continuity and periodicity of WSS data, missing values often exhibit multi-level correlations with valid data. This paper innovatively employs graph structures to analyze the multi-level correlations at different timestamps and applies graph signal sampling algorithms to extract low-frequency features for imputation. A novel Graph-based Data Imputation (GDI) method has been developed, which leverages multi-level correlations to propagate information and completes imputation tasks without requiring complex feature engineering and pre-training processes. Results indicate that GDI outperforms Holt-Winters, Support Vector Regression, and Gated Recurrent Unit in the task of imputing continuous missing data. It can still achieve

R^{2} > 0.8

even when the proportion of missing values reaches 80 %. These results demonstrate that GDI ensures a more streamlined and efficient imputation with high robustness and accuracy.

监测设备中的数据缺失和异常已成为开发智能供水系统（WSS）的关键障碍。可以利用缺失段前后的有效数据来估算缺失值。然而，传统的估算方法，如线性插值法和基于预测的方法，利用数据关系的能力有限，或者只能利用缺失值之前的信息。因此，现有方法仍需在高效、便捷地实现高精度估算方面下功夫。根据 WSS 数据的连续性和周期性，缺失值往往与有效数据呈现多层次的相关性。本文创新性地采用图结构分析不同时间戳的多级相关性，并应用图信号采样算法提取低频特征进行归约。我们开发了一种新颖的基于图的数据归约（GDI）方法，该方法利用多级相关性传播信息，无需复杂的特征工程和预训练过程即可完成归约任务。结果表明，在连续缺失数据的归约任务中，GDI 优于 Holt-Winters、支持向量回归和门控循环单元。即使缺失值比例达到 80%，它仍能达到 R2>0.8。这些结果表明，GDI 可以确保更简化、更高效的归因，并具有很高的稳健性和准确性。

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引用次数: 0

A hybrid oxidation approach for converting high-strength urine ammonia into ammonium nitrate 将高浓度尿氨转化为硝酸铵的混合氧化法

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-06 DOI: 10.1016/j.wroa.2024.100277

Zhiqiang Zuo , Tianyi Zhang , Xin Huang , Xiaotong Cen , Xi Lu , Tao Liu , Ho Kyong Shon , Min Zheng

Nutrient resources contained in human urine have great potential to alleviate global agricultural fertilizer demand. Microbial nitrification is a recognized strategy for stabilizing urine ammonia into ammonium nitrate, a common fertilizer worldwide, but faces a core bottleneck of process instability due to microbial inhibition. This study reports a new approach by developing a hybrid oxidation process involving three stages—microbial ammonia oxidation, chemical nitrite oxidation and microbial nitrite oxidation. Candidatus Nitrosoglobus, a γ-proteobacterial ammonia oxidizer highly tolerant to free nitrous acid, was introduced in the first stage to oxidize half of the total ammonia in the influent (8 g NH₄⁺-N/L) to nitrite. The nitrite was then chemically oxidized by using hydrogen peroxide via a rapid chemical reaction to form nitrate. The third stage, microbial nitrite oxidation, was employed to ensure the complete removal of residual nitrite following chemical oxidation. The overall concept demonstrated in this work showcased the robust performance of the hybrid system. Moreover, the system also had a dual advantage in achieving antimicrobial ability in the first and second stages, making treated urine a safe fertilizer.

人尿中含有的营养资源在缓解全球农业肥料需求方面具有巨大潜力。微生物硝化是一种公认的将尿液中的氨稳定转化为硝酸铵（一种全球常用的肥料）的策略，但面临着一个核心瓶颈，即微生物抑制导致的工艺不稳定性。本研究报告了一种新方法，即开发一种混合氧化工艺，包括三个阶段--微生物氨氧化、化学亚硝酸盐氧化和微生物亚硝酸盐氧化。在第一阶段，引入了对游离亚硝酸具有高度耐受性的γ-蛋白细菌氨氧化菌 Candidatus Nitrosoglobus，将进水中一半的总氨（8 克 NH4+-N/L）氧化为亚硝酸盐。然后使用过氧化氢通过快速化学反应将亚硝酸盐氧化成硝酸盐。第三阶段是微生物亚硝酸盐氧化，以确保完全去除化学氧化后的残留亚硝酸盐。这项工作中展示的整体概念展示了混合系统的强大性能。此外，该系统还具有双重优势，在第一和第二阶段实现了抗菌能力，使处理后的尿液成为安全的肥料。

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引用次数: 0

Application of organic silicon quaternary ammonium salt (QSA) to reduce carbon footprint of sewers: Long-term inhibition on sulfidogenesis and methanogenesis 应用有机硅季铵盐（QSA）减少下水道的碳足迹：对硫化物生成和甲烷生成的长期抑制作用

IF 7.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2024-11-01 DOI: 10.1016/j.wroa.2024.100275

Suwan Dai , Haixiao Guo , Yiming Li , Jiaqi Hou , Yufen Wang , Tingting Zhu , Bing-Jie Ni , Yiwen Liu

Sulfidogenic and methanogenic processes are undesirable in sewer management, yet the derived problems regarding organic losses are often neglected. Traditional chemical dosing methods aimed at sulfide and methane control commonly involve similar mechanisms of oxidation and/or precipitation. Moreover, previous focuses were centered on elevating control efficacy rather than investigating interactions between dosed chemicals and biofilms. In this work, organic silicon quaternary ammonium salt (QSA) of 75 mg-N/L was firstly applied in laboratory pressurized sewer reactors. After three dosing events, it took 20 days for sulfidogenic activities to recover to 50 % without further elevations. Meantime, methanogenic activities were stable ca. 11 % without significant inclinations to recover. Notably, consumption rate of chemical oxygen demand (COD) was suppressed to 50 % at most, and no microbial resistance to QSA but better control efficacy was observed. Characterizations of physicochemistry, microbial community and metabolism were conducted to elucidate mechanisms. Results showed that QSA was attached on sewer biofilms via electrostatic attraction to exert enduring control efficacy. Biofilms tended to become more hydrophobic and compact after QSA exposure. Microbial analyses indicated that relative abundances of microbes regarding hydrolysis, acidogenesis and methanogenesis were sharply decreased together with down-regulation of pivotal enzymatic activities. Additionally, denitrification batch tests initially suggested that the biodegradability of effluent was significantly enhanced, which ensured the safety of QSA dosing into sewers. Overall, results of this work were expected to lay a theoretical foundation on employing QSA to wastewater management.

在下水道管理中，产生硫化物和甲烷的过程是不可取的，但由此产生的有机物损失问题却往往被忽视。旨在控制硫化物和甲烷的传统化学加药方法通常涉及类似的氧化和/或沉淀机制。此外，以往的重点都集中在提高控制效果上，而不是研究投加的化学品与生物膜之间的相互作用。在这项研究中，75 mg-N/L 的有机硅季铵盐（QSA）首先被用于实验室加压下水道反应器中。经过三次加药，硫化物生成活性在 20 天后恢复到 50%，且没有进一步升高。与此同时，甲烷生成活性稳定在约 11%，没有明显的恢复趋势。11 %，没有明显的恢复趋势。值得注意的是，化学需氧量（COD）的消耗率最多被抑制到 50%，没有观察到微生物对 QSA 产生抗性，但控制效果更好。对物理化学、微生物群落和新陈代谢进行了表征，以阐明其机理。结果表明，QSA 通过静电吸引附着在下水道生物膜上，从而发挥持久的控制效果。生物膜在接触 QSA 后会变得更加疏水和紧密。微生物分析表明，水解、产酸和产甲烷微生物的相对丰度急剧下降，关键酶活性也出现下调。此外，反硝化批量试验初步表明，污水的生物降解能力显著增强，这确保了向下水道投加 QSA 的安全性。总之，这项工作的结果有望为采用 QSA 进行污水管理奠定理论基础。

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引用次数: 0