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Pathways to Carbon Neutrality in Water Systems: The Role of LCA, Ecological Engineering, and Pollution Control

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: 10 July 2026 | Viewed by 1477

Special Issue Editors

Prof. Dr. Shoubing Wang

E-Mail Website
Guest Editor
Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
Interests: life cycle assessment; carbon neutrality; ecological restoration; ecosystem services; material flow analysis; environmental economy; biodiversity conservation; environmental planning; ecological engineering; cleaner production
Prof. Dr. Yonghong Bi

E-Mail Website
Guest Editor
Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
Interests: carbon neutrality; ecological restoration; ecosystem services
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the past, significant attention has been devoted to protecting water environment systems, controlling pollution, and restoring ecosystems. However, in the face of increasingly severe global climate change and the growing emphasis placed on achieving carbon neutrality goals by countries worldwide, there is an urgent need to strengthen the role of water systems in carbon reduction and carbon sequestration. Life cycle assessment (LCA) serves as an effective tool for evaluating multiple environmental impacts, including carbon emissions. It provides a systematic perspective for assessing the environmental impacts of water-related technologies and management strategies. Under the guidance of a life cycle perspective, ecological engineering and pollution control measures not only help mitigate pollution but also create significant opportunities for carbon reduction and even carbon sequestration.

Researchers around the world are conducting extensive and fruitful studies in these fields. This Special Issue aims to provide a platform for showcasing these research achievements and fostering academic exchange. We warmly welcome the submission of original research and review papers that explore pathways to carbon neutrality in water systems, contributing to global efforts in building a low-carbon and sustainable future.

Prof. Dr. Shoubing Wang
Prof. Dr. Yonghong Bi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon footprint
  • ecological engineering
  • carbon neutrality
  • low-carbon fishery
  • photovoltaic fishery
  • water pollution control
  • life cycle assessment
  • low-carbon wastewater treatment facility
  • wetland ecosystem service
  • water–energy–carbon nexus

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Published Papers (2 papers)

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Research

19 pages, 2444 KB  
Article
Carbon Footprint and Sensitive Design Parameters of Residential and Industrial (Whey) Wastewater Treatment Plants: A Comparative Life Cycle Assessment (LCA)
by Quddus Tushar, Muhammed A. Bhuiyan, Ziyad Abunada, Zaved Khan, Md Nurun Nabi and Charles Lemckert
Water 2026, 18(4), 472; https://doi.org/10.3390/w18040472 - 12 Feb 2026
Viewed by 636
Abstract
This study calculates the carbon footprint of chemical coagulants and operational energy for residential and industrial (whey digestion) wastewater treatment using ReCiPe 2016 methodology within a clearly defined system boundary from cradle to gate. Data from water treatment facilities have been analyzed to [...] Read more.
This study calculates the carbon footprint of chemical coagulants and operational energy for residential and industrial (whey digestion) wastewater treatment using ReCiPe 2016 methodology within a clearly defined system boundary from cradle to gate. Data from water treatment facilities have been analyzed to quantify environmental impacts and identify sensitive design parameters. The estimated emission of treating 1 m3 of wastewater from whey digestion (7.1195 kg CO2 eq) is over 50 times higher than that of a residential one (0.1349 kg CO2 eq). Life cycle impact assessment (LCIA) reveals that iron (III) chloride (40% in H2O) and operational electricity consumption have higher impact categories compared to other design components. The uncertainty analysis indicates that electricity consumption (r = 0.4) is the dominant contributor to emissions, with a mean value of 4.22 kg CO2-eq per m3 of wastewater treated. In contrast, iron (III) chloride emerges as the most sensitive parameter (r = 0.88) with small variations in dosing causing a disproportionately large impact on overall emissions. Therefore, the optimized use of an iron-based coagulant, the adoption of membrane electrolysis, and the integration of renewable electricity into the process supply chains have been identified as effective strategies for reducing emissions. Full article
(This article belongs to the Special Issue Pathways to Carbon Neutrality in Water Systems: The Role of LCA, Ecological Engineering, and Pollution Control)
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24 pages, 4010 KB  
Article
Bridging Time-Scale Mismatch in WWTPs: Long-Term Influent Forecasting via Decomposition and Heterogeneous Temporal Attention
by Wenhui Lei, Fei Yuan, Yanjing Xu, Yanyan Nie and Jian He
Water 2026, 18(3), 295; https://doi.org/10.3390/w18030295 - 23 Jan 2026
Viewed by 593
Abstract
The time-scale mismatch between rapid influent fluctuations and slow biochemical responses hinders the stability of wastewater treatment plants (WWTPs). Existing models often fail to capture shock signals due to noise interference (“signal pollution”). To address this, we propose the HD-MAED-LSTM model, which employs [...] Read more.
The time-scale mismatch between rapid influent fluctuations and slow biochemical responses hinders the stability of wastewater treatment plants (WWTPs). Existing models often fail to capture shock signals due to noise interference (“signal pollution”). To address this, we propose the HD-MAED-LSTM model, which employs a “decompose-and-conquer” strategy. Targeting the dynamic characteristics of different components, this study innovatively designs heterogeneous attention mechanisms: utilizing Long-term Dependency Attention to capture the global evolution of the trend component, employing Multi-scale Periodic Attention to reinforce the cyclic patterns of the seasonal component, and using Gated Anomaly Attention to keenly capture sudden shocks in the residual component. In a case study, the effectiveness of the proposed model was validated based on one year of operational data from a large-scale industrial WWTP. HD-MAED-LSTM outperformed baseline models such as Transformer and LSTM in the medium-to-long-term (10-h) prediction of COD, TN, and TP, clearly demonstrating the positive role of differentiated modeling. Notably, in the core task of shock load early warning, the model achieved an F1-Score of 0.83 (superior to Transformer’s 0.77 and LSTM’s 0.67), and a Mean Directional Accuracy (MDA) as high as 0.93. Ablation studies confirm that the specialized attention mechanism is the key performance driver, reducing the Mean Absolute Error (MAE) by 56.7%. This framework provides precise support for shifting WWTPs from passive response to proactive control. Full article
(This article belongs to the Special Issue Pathways to Carbon Neutrality in Water Systems: The Role of LCA, Ecological Engineering, and Pollution Control)
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