Water Research X最新文献_第9页

Water Research X is expanding its article types “水研究X”正在扩大文章种类

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-28 DOI: 10.1016/j.wroa.2025.100338

Zhiguo Yuan

引用次数: 0

Simultaneous electrochemical leaching, enrichment, and recovery of phosphorus as value-added vivianite from poly-aluminum chloride (PAC) sludge 从聚合氯化铝（PAC）污泥中同时进行电化学浸出、富集和回收磷作为增值钒石

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-25 DOI: 10.1016/j.wroa.2025.100337

Hongjie Guo , Xiaolong Lu , Hameer Chand , Changyong Zhang

{"title":"Simultaneous electrochemical leaching, enrichment, and recovery of phosphorus as value-added vivianite from poly-aluminum chloride (PAC) sludge","authors":"Hongjie Guo , Xiaolong Lu , Hameer Chand , Changyong Zhang","doi":"10.1016/j.wroa.2025.100337","DOIUrl":"10.1016/j.wroa.2025.100337","url":null,"abstract":"<div><div>Electrochemical recovery of phosphorus (P) from waste sludge presents a sustainable solution to mitigate the depletion of P rock reserves. However, its feasibility and cost have been persistent challenges. This study introduces an innovative strategy for simultaneous electrochemical leaching, enrichment, and recovery of P (ELER) from poly-aluminum chloride (PAC) sludge with minimal chemical and energy input. A high P leaching efficiency of 90.5% was achieved within the cathode chamber through the rapid elevation of pH induced by water electrolysis at an optimal current density of 30 A m<sup>−2</sup> during a single 5-hour cycle. The ELER system recovered approximately 68.8% P from the simulated PAC sludge at a specific energy consumption (SEC) of 214.4 kWh kg<sup>−1</sup> P. Notably, the selection and composition of the electrolytes played a crucial role in system performances, with Na<sub>2</sub>SO<sub>4</sub> outperforming NaCl in both efficiency and stability. Increasing catholyte concentration or reducing anolyte concentration significantly reduced P leaching and enrichment efficiency. Furthermore, when optimized for continuous operation over five successive cycles, the system can achieve an ultimate P enrichment efficiency of 96.5% for real PAC sludge, while maintaining a relative low SEC of 54.1 kWh kg<sup>−1</sup> P. The enriched P was crystallized as high-purity vivianite, a value-added product that can be utilized as a slow-release P fertilizer or a precursor for lithium-ion battery electrodes. The estimated cost of $4.3 kg<sup>−1</sup> P makes this approach economically viable compared to other existing technologies. This innovative approach holds promise for efficient and sustainable P recovery from PAC sludge or other P-rich waste solid.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100337"},"PeriodicalIF":7.2,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pattern recognition of operational states leading to N2O-emissions in full-scale biological wastewater treatment 全面生物废水处理中导致n2o排放的运行状态模式识别

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-19 DOI: 10.1016/j.wroa.2025.100336

Andreas Froemelt , Leon Zueger , Luzia von Kaenel , Daniel Braun , Wenzel Gruber

{"title":"Pattern recognition of operational states leading to N2O-emissions in full-scale biological wastewater treatment","authors":"Andreas Froemelt , Leon Zueger , Luzia von Kaenel , Daniel Braun , Wenzel Gruber","doi":"10.1016/j.wroa.2025.100336","DOIUrl":"10.1016/j.wroa.2025.100336","url":null,"abstract":"<div><div>Given the urgency to reduce greenhouse gas emissions in the whole economy, the abatement of nitrous oxide (N<sub>2</sub>O) built-up in biological wastewater treatment would be an important contribution of the waste sector. However, the complexity of N<sub>2</sub>O-formation in activated sludge and non-linear dynamics of operating factors pose difficulties to apply effective measures for a specific high-emission situation in a full-scale context. Facing such complex interactions and unknown relationships, data mining can provide useful support to analyze full-scale datasets. Therefore, the goal of this article is to investigate a data-driven method to understand high-emission patterns and their origins to provide a basis for the development of N<sub>2</sub>O-mitigation measures. We applied unsupervised artificial neural networks (self-organizing maps) and subsequent clustering to a 3-year, high-resolution dataset to identify and characterize operational states and to analyze the transitions among them. In the case study, hampered denitrification, anaerobic digestion supernatant addition, and indications of snowmelt were found among problematic situations. The transition analysis showed the importance of contextualizing a high-emission pattern as it can emerge from different origins, having implications when developing mitigation measures. Apart from analyzing the shift of operational states, a key advantage of the proposed methodology is the consideration of the combined effect of variables in specific situations. This renders it an effective tool to understand operational patterns. It can further be used to inform experiments by formulating hypotheses and prioritizing variables combinations; providing finally insights towards the development of situation-specific strategies for a low-N<sub>2</sub>O-operation of full-scale plants.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100336"},"PeriodicalIF":7.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Micropollutants removal, residual risk, and costs for quaternary treatments in the framework of the Urban Wastewater Treatment Directive 城市废水处理指令框架内的微污染物去除、残留风险和四元处理成本

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-15 DOI: 10.1016/j.wroa.2025.100334

Jessica Ianes, Sara Piraldi, Beatrice Cantoni, Manuela Antonelli

{"title":"Micropollutants removal, residual risk, and costs for quaternary treatments in the framework of the Urban Wastewater Treatment Directive","authors":"Jessica Ianes, Sara Piraldi, Beatrice Cantoni, Manuela Antonelli","doi":"10.1016/j.wroa.2025.100334","DOIUrl":"10.1016/j.wroa.2025.100334","url":null,"abstract":"<div><div>The revised Urban Wastewater Treatment Directive (UWWTD) imposes stringent regulations for the removal of micropollutants from urban wastewater treatment plants. The analyses conducted in this study are based on current knowledge extrapolated from literature WWTPs, to investigate the occurrence, removal and environmental risk related to the 12 target micropollutants: Amisulpride, Benzotriazole, 4,5-Methylbenzotriazole, Carbamazepine, Clarithromycin, Citalopram, Candesartan, Diclofenac, Hydrochlorothiazide, Irbesartan, Metoprolol, and Venlafaxine. The goal is to provide valuable insights into the challenges and opportunities associated with implementing quaternary treatment processes to comply with the UWWTD. Results indicate that the conventional biological treatment is insufficient, with median removal rates below 50 % for most target micropollutants (except for Benzotriazole and Irbesartan). The implementation of quaternary treatment processes, namely ozonation and activated carbon adsorption, significantly enhances WWTP micropollutants removal, with median removal efficiencies exceeding 80 % for all the target micropollutants, with Candesartan being the most recalcitrant. Environmental risk assessment reveals that some micropollutants pose a significant threat to aquatic ecosystems even with 80 % removal efficiency (Irbesartan, Candesartan, Diclofenac, and Venlafaxine), while others do not pose a risk even at WWTP influent concentrations (4,5-Methylbenzotriazole, Hydrochlorothiazide, Amisulpride, Citalopram, and Metoprolol).</div><div>Economic analysis shows that the selection of specific operating parameter values significantly impacts the cost of each treatment process, changing the economic feasibility ranking of the different treatment options.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100334"},"PeriodicalIF":7.2,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploration of deep learning leak detection model across multiple smart water distribution systems: Detectable leak sizes with AMI meters 探索跨多个智能配水系统的深度学习泄漏检测模型：使用AMI仪表检测泄漏大小

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-14 DOI: 10.1016/j.wroa.2025.100332

Sanghoon Jun , Donghwi Jung

{"title":"Exploration of deep learning leak detection model across multiple smart water distribution systems: Detectable leak sizes with AMI meters","authors":"Sanghoon Jun , Donghwi Jung","doi":"10.1016/j.wroa.2025.100332","DOIUrl":"10.1016/j.wroa.2025.100332","url":null,"abstract":"<div><div>Numerous deep learning (DL) models have been developed for leak detection in water distribution systems (WDSs). However, significant lack of knowledge still remains concerning their detectability and the smallest detectable leak sizes across various WDSs. To address these research gaps, this study explores the performance of a DL leak detection model across eleven smart WDSs. A convolutional neural network (CNN) is employed to identify leaks using the spatially distributed pressure response images derived from the difference between advanced metering infrastructure (AMI) measurements and predictions from a well-calibrated hydraulic model (i.e., digital twin). Ten leak magnitudes are evaluated for each WDS, and three performance metrics (recall, precision, and F1 score) are calculated to assess the detectability and the detectable leak sizes of the CNN. The analysis reveals that the DL model's detection ability is highly impacted by WDS type, whether transmission- or distribution-oriented. The former networks exhibit low accuracy in identifying leaks due to the indistinguishability of pressure response images between normal and leak conditions. On the other hand, the latter networks generally achieve higher precision and recall results and can detect smaller leaks. Moreover, the smallest detectable leak sizes are more sensitive to WDS structural parameters (pipe diameter and length) than system hydraulics (system demand). Examining pipe characteristics along the leakage flow path provides most useful information in determining the detectability of leaks.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100332"},"PeriodicalIF":7.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using wastewater analysis to assess the health status of two distinct populations in China 利用废水分析评估中国两个不同人群的健康状况

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-14 DOI: 10.1016/j.wroa.2025.100335

Zhe Wang , Qiuda Zheng , Jianfa Gao , Jianan Ren , Fahad Ahmed , Yufang Chen , Cong Yang , Han Chen , Yuan Ren , Phong K. Thai

{"title":"Using wastewater analysis to assess the health status of two distinct populations in China","authors":"Zhe Wang , Qiuda Zheng , Jianfa Gao , Jianan Ren , Fahad Ahmed , Yufang Chen , Cong Yang , Han Chen , Yuan Ren , Phong K. Thai","doi":"10.1016/j.wroa.2025.100335","DOIUrl":"10.1016/j.wroa.2025.100335","url":null,"abstract":"<div><div>Wastewater-based epidemiology (WBE) is a powerful tool for monitoring biomarkers of human health conditions. The WBE approach could deliver robust public health data with high temporal and spatial resolution, making it highly effective for assessing the impact of public health interventions across different populations. This study applied WBE to compare substance use and explore public health implications across two distinct populations: a general urban population and a university population. Daily and weekly wastewater samples were collected from 2017 to 2018, originating from a wastewater treatment plant serving the urban catchment and a pump station encompassing 10 universities. Consumption of over-the-counter (OTC) medications, prescribed drugs, and chronic disease medications in these two populations were estimated. Additionally, previously published data on recreational substances, respiratory and allergy medications, sweeteners, stress markers, and anabolic steroids were analyzed to present a comprehensive overview of human lifestyles and health status. Our results indicated that the university population consumed more OTC painkillers, including ibuprofen and paracetamol, but fewer prescribed opioids, such as codeine and morphine, compared to the general population. In contrast, higher consumption of chronic disease medications in the urban catchment indicated poorer overall health compared to the younger university population. These findings highlight significant differences in pharmaceutical consumption patterns and associated public health profiles between younger and general populations. This study underscores the utility of WBE in identifying public health disparities and guiding targeted health interventions based on population-specific needs and behaviors.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100335"},"PeriodicalIF":7.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ageing underground water pipelines: Time-to-failure models, gaps and future directions 老化地下水管道：失效时间模型、缺口和未来方向

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-13 DOI: 10.1016/j.wroa.2025.100331

Beenish Bakhtawar , Tarek Zayed , Ibrahim Abdelfadeel Shaban , Nehal Elshaboury , Abdul-Mugis Yussif

{"title":"Ageing underground water pipelines: Time-to-failure models, gaps and future directions","authors":"Beenish Bakhtawar , Tarek Zayed , Ibrahim Abdelfadeel Shaban , Nehal Elshaboury , Abdul-Mugis Yussif","doi":"10.1016/j.wroa.2025.100331","DOIUrl":"10.1016/j.wroa.2025.100331","url":null,"abstract":"<div><div>Accurate prediction of the failure time of individual pipelines of a water distribution network can assist in preventing sudden bursts and leaks. Failure prediction over time can help eliminate managerial uncertainty in pipe rehabilitation and replacement decision-making. Since time-based deterioration modeling has less focus in past research, the study focuses on a critical review of the current state-of-the-art for time-to-failure/failure age models related to water pipelines. A unique unsupervised learning-based clustering framework is used to perform an in-depth and robust literature analysis. Hierarchical clustering reveals the main modeling approaches, classified as 1) physical data-based models and 2) historical data-based failure models. Critical research gaps are further explored using t-SNE and Gaussian Mixture Models based clustering. Identified gaps include fragmented modeling approaches, lack of integration between physical and data-driven models, limited data related issues, and a lack of insight on practical translation of model findings for effective utility management. Future studies can consider several integration strategies to overcome individual model limitations, use of generative AI to enrich data, IoT implementation for physical data collection, improve feature engineering and feature extraction efforts, and consider domain knowledge from hydraulic models to improve AI models. Overall, the study offers practical insights for predicting the remaining time-to-failure and service life of water pipelines.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100331"},"PeriodicalIF":7.2,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leak detection in water supply networks using two-stage temporal segmentation and incremental learning for non-stationary acoustic signals 基于两阶段时间分割和非平稳声学信号增量学习的供水管网泄漏检测

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-12 DOI: 10.1016/j.wroa.2025.100333

Xingke Ma , Yipeng Wu , Guancheng Guo , Shuming Liu , Yuexia Xu , Jingjing Fan , Hongbin Wang , Liren Xu

{"title":"Leak detection in water supply networks using two-stage temporal segmentation and incremental learning for non-stationary acoustic signals","authors":"Xingke Ma , Yipeng Wu , Guancheng Guo , Shuming Liu , Yuexia Xu , Jingjing Fan , Hongbin Wang , Liren Xu","doi":"10.1016/j.wroa.2025.100333","DOIUrl":"10.1016/j.wroa.2025.100333","url":null,"abstract":"<div><div>Acoustic detection is a primary method for identifying leaks in urban water supply networks. However, acoustic signals within pipelines are highly susceptible to dynamic interference noise. This complicates the differentiation between leak and non-leak signals. To address this challenge, this paper presents a temporal segmentation-based approach for processing acoustic signals. Specifically, the two-stage temporal segmentation approach, which applies long-term segments to isolate non-stationary characteristics and short-term segments for capturing quasi-stationary features in acoustic signals, is introduced. We then applied the CNN model to recognize the Mel spectrogram features of the two-stage segmented signals and compared its performance with other models. Results indicate that this approach enhances both the accuracy and stability of leak detection, with the model achieving an average detection accuracy of 95 %. Moreover, the model is designed as an adaptive and continuous learning model, integrating its detection outcomes and newly labeled data segments into its training dataset. In practical applications, this continuous learning capability enables the model to improve its detection efficacy over time as data volume expands.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100333"},"PeriodicalIF":7.2,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fungal pretreatment as a promising approach for simultaneous recovery of phosphorus and carbon resource from garden waste: Performance and mechanism 真菌预处理作为园林废弃物同时回收磷碳资源的一种有前景的方法：性能与机理

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-10 DOI: 10.1016/j.wroa.2025.100330

Ruizhe Zhang , Qinyuan Lu , Cong Zhang , Yifeng Chen , Dunjie Li , Wenqiang Qi , Qian Ping , Yongmei Li

{"title":"Fungal pretreatment as a promising approach for simultaneous recovery of phosphorus and carbon resource from garden waste: Performance and mechanism","authors":"Ruizhe Zhang , Qinyuan Lu , Cong Zhang , Yifeng Chen , Dunjie Li , Wenqiang Qi , Qian Ping , Yongmei Li","doi":"10.1016/j.wroa.2025.100330","DOIUrl":"10.1016/j.wroa.2025.100330","url":null,"abstract":"<div><div>Garden waste (GW), which is rich in organic matter and nutrients such as nitrogen (N) and phosphorus (P), has not been fully utilized for resource recovery. This study investigates a novel approach to recover both P and carbon source from GW by fungal pretreatment. Four types of GW—<em>Zoysia matrella (</em>L.<em>) Merr</em> (ZMM), <em>Lolium perenne</em> L (LPL), <em>Platanus × acerifolia (Aiton) Willd</em> (PAW), and <em>Cinnamomum camphora (</em>L.<em>) Presl</em> (CCP)—were subjected to alkaline, thermal, and fungal pretreatments. Results showed that fungal pretreatment was more effective than alkaline and thermal methods, especially for turfgrass GW. After 7 days of fungal pretreatment, the orthophosphate (PO<sub>4</sub>-P) concentration in the LPL supernatant was 2.15 times that of the control. Enzyme activity and metagenomic data revealed higher abundances of lignin degrading enzymes in turfgrass GW, with laccase being the dominant enzyme. Fungi convert organic phosphorus into PO<sub>4</sub>-P by secreting 3-phytase. Ammonium was also produced during fungal pretreatment, resulting in a weakly alkaline supernatant that promoted the precipitation of P as struvite. Consequently, a 43.51 % recovery of P from LPL as struvite with 91.3 % purity was achieved. The residual leachate served as a carbon source, achieving 78.67 % nitrate removal and 76.48 % total nitrogen removal. This study proposes a sustainable strategy for simultaneous P and carbon recovery from GW.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100330"},"PeriodicalIF":7.2,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Balancing energy recovery and direct greenhouse gas emissions in wastewater treatment 平衡废水处理中的能源回收和直接温室气体排放

IF 7.2 2区环境科学与生态学

Water Research X Pub Date : 2025-03-08 DOI: 10.1016/j.wroa.2025.100328

Kaili Li , Haoran Duan , Shuting Wang , Ziping Wu , Peter Wardrop , James Lloyd , Nathali Christy , Pieter De Jong , Liu Ye

{"title":"Balancing energy recovery and direct greenhouse gas emissions in wastewater treatment","authors":"Kaili Li , Haoran Duan , Shuting Wang , Ziping Wu , Peter Wardrop , James Lloyd , Nathali Christy , Pieter De Jong , Liu Ye","doi":"10.1016/j.wroa.2025.100328","DOIUrl":"10.1016/j.wroa.2025.100328","url":null,"abstract":"<div><div>Achieving net-zero emissions is a critical goal for the water industry. This study provides a comprehensive evaluation of energy recovery and direct greenhouse gas (GHG) emissions from a full-scale wastewater treatment plant (WWTP), highlighting the important balance between carbon capture and emissions reduction. Long-term monitoring results revealed that upstream carbon capture, while recovering significant energy for carbon offset (40 % of total emission), stimulated downstream nitrous oxide (N<sub>2</sub>O) emissions, a major contributor to Scope 1 emissions. In response, integrated mitigation strategies were developed using mechanistic modelling, incorporating process optimizations (adjusting split ratios, DO setpoints, and mixing ratio) and retrofitting solution (raw wastewater diversion). The identified strategies reduced N<sub>2</sub>O emissions by 50 % and the overall carbon footprint by 40 %, despite a 31 % decrease in energy recovery, compared with the baseline case (N<sub>2</sub>O emission factor: 1.31 % of TKN load, net emissions: 354.29 kg CO<sub>2</sub>-e/ML, and energy recovery: 386.02 kg CO<sub>2</sub>-e/ML). The findings demonstrated the need for a holistic assessment of carbon capture, energy recovery, and GHG emissions across the entire treatment process. The outcome offers actionable insights for improving WWTP operations towards net-zero emissions.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"28 ","pages":"Article 100328"},"PeriodicalIF":7.2,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0