Pub Date : 2026-02-04DOI: 10.1016/j.jclepro.2026.147711
Laís Coura Soranço, Gabrielle Quadra, Jesper Wien, Ana Paula Dalbem Barbosa, Anderson Machado de Melo Júnior, Giovana Machado Cardoso, Vitor Luís da Cunha Duque, Caique Rodrigues Soares, Tarcila Silva, Giovanni Resende de Oliveira, Sarian Kosten, Nathan Oliveira Barros
Aquaculture plays a key role in addressing the global protein demand. However, its long-term sustainability depends on minimizing its environmental impacts, particularly eutrophication and greenhouse gas (GHG) emissions. The fate of fish feed that is not ingested by the fish remains an overlooked factor, yet it is crucial for accurately assessing the carbon footprint of fish production. To assess the fate of undigested fish feed under different conditions, we used complementary in situ and ex situ approaches to separate the effect of feed composition from the influence of pond conditions. First, we performed an in situ experiment to investigate the breakdown of four common fish feed types, and secondly, quantified their associated carbon dioxide (CO2) and methane (CH4) production in an ex situ experiment. We explored potential drivers, including feed physicochemical properties. Results showed that the feeds varied significantly in their properties (CN ratio range: 5.4–10.7; decay constant k range: 0.023–0.05 h−1). This variation was critical: feeds with lower physical stability and lower CN ratios disintegrated fastest. In ex situ incubations, CO2 production significantly increased with the addition of all feed types compared to controls that contained only fishpond sediment (±15 nmol g−1 h−1). Conversely, CH4 production was minimal across all treatments even under anoxic conditions. Our findings indicate that while feed decomposition directly stimulated CO2 production, it did not constitute a determining factorin CH4 production in this system. Critically, we show that feed physicochemical properties, particularly physical stability and CN ratio, are key regulators of the rate of these microbial processes. To effectively reduce aquaculture's carbon footprint, future development must embed precision feeding (i.e. prevention of overfeeding), along with improved feed composition and stability, into comprehensive GHG mitigation strategies.
{"title":"A combined in situ–ex situ assessment of fish feed fate and associated carbon emissions","authors":"Laís Coura Soranço, Gabrielle Quadra, Jesper Wien, Ana Paula Dalbem Barbosa, Anderson Machado de Melo Júnior, Giovana Machado Cardoso, Vitor Luís da Cunha Duque, Caique Rodrigues Soares, Tarcila Silva, Giovanni Resende de Oliveira, Sarian Kosten, Nathan Oliveira Barros","doi":"10.1016/j.jclepro.2026.147711","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147711","url":null,"abstract":"Aquaculture plays a key role in addressing the global protein demand. However, its long-term sustainability depends on minimizing its environmental impacts, particularly eutrophication and greenhouse gas (GHG) emissions. The fate of fish feed that is not ingested by the fish remains an overlooked factor, yet it is crucial for accurately assessing the carbon footprint of fish production. To assess the fate of undigested fish feed under different conditions, we used complementary <em>in situ</em> and <em>ex situ</em> approaches to separate the effect of feed composition from the influence of pond conditions. First, we performed an <em>in situ</em> experiment to investigate the breakdown of four common fish feed types, and secondly, quantified their associated carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) production in an <em>ex situ</em> experiment. We explored potential drivers, including feed physicochemical properties. Results showed that the feeds varied significantly in their properties (CN ratio range: 5.4–10.7; decay constant k range: 0.023–0.05 h<sup>−1</sup>). This variation was critical: feeds with lower physical stability and lower CN ratios disintegrated fastest. In <em>ex situ</em> incubations, CO<sub>2</sub> production significantly increased with the addition of all feed types compared to controls that contained only fishpond sediment (±15 nmol g<sup>−1</sup> h<sup>−1</sup>). Conversely, CH<sub>4</sub> production was minimal across all treatments even under anoxic conditions. Our findings indicate that while feed decomposition directly stimulated CO<sub>2</sub> production, it did not constitute a determining factorin CH<sub>4</sub> production in this system. Critically, we show that feed physicochemical properties, particularly physical stability and CN ratio, are key regulators of the rate of these microbial processes. To effectively reduce aquaculture's carbon footprint, future development must embed precision feeding (i.e. prevention of overfeeding), along with improved feed composition and stability, into comprehensive GHG mitigation strategies.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"19 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
The adoption of manufactured sand (MS) in concrete production offers a dual environmental advantage by conserving natural sand resources and mitigating solid waste disposal burdens, which is an effective way to promote sustainable development. However, the research on MS ultra-high performance concrete (UHPC) remains limited, and MS may lead to poor workability and significant flowability loss of concrete, which hinders its further promotion in UHPC. To address these challenges, this study develops an eco-friendly UHPC by utilizing crushed tuff tunnel waste as MS, modified by an independently developed surface modifier and nano-CaCO3. The synergistic effects of these modifications are evaluated through multi-scale macroscopic and microscopic performance characterizations. Results indicate that surface modifiers significantly improve the flowability and workability retention ability of UHPC, with 1 h flowability loss dramatically reduced from 27.1% in the reference group to 7.4%. Although surface modifiers prolong the setting time and delay the hydration peaks, nanomaterials can effectively offset these effects and further enhance the mechanical strengths. Modified sand can also inhibit autogenous shrinkage, optimize pore structure (reduce cumulative porosity at low dosage), and densify the interfacial transition zone (ITZ) without elemental enrichment. Furthermore, the production of MS generates 69% lower CO2 emissions than conventional quartz sand, and the modified MS UHPC demonstrates 14 kg reduction in CO2 emissions per cubic meter, 24.8% and 25.0% reductions in costs per cubic meter and unit compressive strength versus the conventional UHPC, showing superior environmental and economic benefits and contributing to circular and sustainable construction practices.
{"title":"Synergistic effects of surface modifier and nanomaterial on eco-friendly UHPC containing crushed tunnel waste as manufactured sand—Towards cleaner production and circular resource utilization","authors":"Rui Ma, Yufeng Song, Hongwei Xie, Xiaoqian Qian, Yulin Zhan, Ruizhe Si, Shaoqin Ruan","doi":"10.1016/j.jclepro.2026.147715","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147715","url":null,"abstract":"The adoption of manufactured sand (MS) in concrete production offers a dual environmental advantage by conserving natural sand resources and mitigating solid waste disposal burdens, which is an effective way to promote sustainable development. However, the research on MS ultra-high performance concrete (UHPC) remains limited, and MS may lead to poor workability and significant flowability loss of concrete, which hinders its further promotion in UHPC. To address these challenges, this study develops an eco-friendly UHPC by utilizing crushed tuff tunnel waste as MS, modified by an independently developed surface modifier and nano-CaCO<sub>3</sub>. The synergistic effects of these modifications are evaluated through multi-scale macroscopic and microscopic performance characterizations. Results indicate that surface modifiers significantly improve the flowability and workability retention ability of UHPC, with 1 h flowability loss dramatically reduced from 27.1% in the reference group to 7.4%. Although surface modifiers prolong the setting time and delay the hydration peaks, nanomaterials can effectively offset these effects and further enhance the mechanical strengths. Modified sand can also inhibit autogenous shrinkage, optimize pore structure (reduce cumulative porosity at low dosage), and densify the interfacial transition zone (ITZ) without elemental enrichment. Furthermore, the production of MS generates 69% lower CO<sub>2</sub> emissions than conventional quartz sand, and the modified MS UHPC demonstrates 14 kg reduction in CO<sub>2</sub> emissions per cubic meter, 24.8% and 25.0% reductions in costs per cubic meter and unit compressive strength versus the conventional UHPC, showing superior environmental and economic benefits and contributing to circular and sustainable construction practices.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"62 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2026-02-04DOI: 10.1016/j.jclepro.2026.147673
Ming Zeng, Weike Zhang
Park city construction (PCC), as an innovative urban construction concept, has been given a high hope of improving air quality. Chengdu, as the first pilot city to build a park city in China, has made a series of achievements in PCC. This study aims to assess the impact of Chengdu's PCC on its air quality and the underlying mechanisms, using the Synthetic Control Method (SCM). The findings demonstrate a substantial enhancement in air quality in Chengdu due to the PCC. In the four-year period following the implementation of the PCC, it is estimated that the Air Quality Index (AQI) experienced reductions of 7.826, 6.579, 7.817, and 0.861 units, respectively. Nevertheless, the available evidence indicates that the role of Chengdu's PCC in PM2.5 reduction is not significant. Path analysis reveals that the enhanced air quality in Chengdu can be attributed to the expansion of green spaces, acceleration of industrial green transformation, and increased energy efficiency facilitated by the PCC. These findings offer evidence to enhance the PCC in Chengdu, particularly with regard to the mitigation of PM2.5 levels. Additionally, this study presents empirical evidence supporting the advancement of PCC in a greater number of urban areas.
{"title":"Clear skies ahead: How park city construction improved air quality?","authors":"Ming Zeng, Weike Zhang","doi":"10.1016/j.jclepro.2026.147673","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147673","url":null,"abstract":"Park city construction (PCC), as an innovative urban construction concept, has been given a high hope of improving air quality. Chengdu, as the first pilot city to build a park city in China, has made a series of achievements in PCC. This study aims to assess the impact of Chengdu's PCC on its air quality and the underlying mechanisms, using the Synthetic Control Method (SCM). The findings demonstrate a substantial enhancement in air quality in Chengdu due to the PCC. In the four-year period following the implementation of the PCC, it is estimated that the Air Quality Index (AQI) experienced reductions of 7.826, 6.579, 7.817, and 0.861 units, respectively. Nevertheless, the available evidence indicates that the role of Chengdu's PCC in PM<sub>2.5</sub> reduction is not significant. Path analysis reveals that the enhanced air quality in Chengdu can be attributed to the expansion of green spaces, acceleration of industrial green transformation, and increased energy efficiency facilitated by the PCC. These findings offer evidence to enhance the PCC in Chengdu, particularly with regard to the mitigation of PM<sub>2.5</sub> levels. Additionally, this study presents empirical evidence supporting the advancement of PCC in a greater number of urban areas.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"108 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2026-02-04DOI: 10.1016/j.jclepro.2026.147722
Ismael Santana, Manuel Félix, Sara Cabezudo, Pedro Guerrero, Carlos Bengoechea
{"title":"Assessment of Rugulopteryx okamurae seaweed as source of sustainable alginate gels with polyphenols from orange peel","authors":"Ismael Santana, Manuel Félix, Sara Cabezudo, Pedro Guerrero, Carlos Bengoechea","doi":"10.1016/j.jclepro.2026.147722","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147722","url":null,"abstract":"","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"21 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Deep reinforcement learning has been recognized as a promising online energy management approach for hybrid electric vehicles, contributing significantly to energy saving and emission reduction. However, the random exploration of deep reinforcement learning may violate the safety limits of critical components under complex driving conditions, limiting the practical reliability. To address this issue, this paper proposes a safe reinforcement learning energy management strategy for hybrid electric vehicles. First, a labeled dataset is constructed from simulated driving conditions and expert-defined safety rules. A supervisory action safety assessment model is then trained based on this dataset to identify unsafe actions generated by the agent. Second, a physics-informed action correction layer is designed to minimally adjust any detected unsafe actions, ensuring that the output actions always remain within the safe operating range of the system. Results under various test driving cycles demonstrate that, compared with existing deep reinforcement learning methods, the proposed approach not only effectively ensures the safety of control actions, but also further improves overall driving economy by 5.79–12.27%, including both fuel consumption and battery degradation costs. The proposed approach has been demonstrated to be both environmentally friendly and energy-efficient.
{"title":"Safe reinforcement learning energy management for hybrid electric vehicles: A supervisory action assessment and correction approach","authors":"Fei Li, Mingjie Li, Yue Wu, Heng Li, Yundong Song, Zhiwu Huang","doi":"10.1016/j.jclepro.2026.147720","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147720","url":null,"abstract":"Deep reinforcement learning has been recognized as a promising online energy management approach for hybrid electric vehicles, contributing significantly to energy saving and emission reduction. However, the random exploration of deep reinforcement learning may violate the safety limits of critical components under complex driving conditions, limiting the practical reliability. To address this issue, this paper proposes a safe reinforcement learning energy management strategy for hybrid electric vehicles. First, a labeled dataset is constructed from simulated driving conditions and expert-defined safety rules. A supervisory action safety assessment model is then trained based on this dataset to identify unsafe actions generated by the agent. Second, a physics-informed action correction layer is designed to minimally adjust any detected unsafe actions, ensuring that the output actions always remain within the safe operating range of the system. Results under various test driving cycles demonstrate that, compared with existing deep reinforcement learning methods, the proposed approach not only effectively ensures the safety of control actions, but also further improves overall driving economy by 5.79–12.27%, including both fuel consumption and battery degradation costs. The proposed approach has been demonstrated to be both environmentally friendly and energy-efficient.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"15 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2026-02-03DOI: 10.1016/j.jclepro.2026.147706
Josef Brousek, Tomas Petr, Pavel Brabec
Battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (FCEVs) are considered vehicles that do not produce local <span><span style=""></span><span data-mathml='<math xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="normal" is="true">CO</mi></math>' role="presentation" style="font-size: 90%; display: inline-block; position: relative;" tabindex="0"><svg aria-hidden="true" focusable="false" height="2.086ex" role="img" style="vertical-align: -0.235ex;" viewbox="0 -796.9 1501 898.2" width="3.486ex" xmlns:xlink="http://www.w3.org/1999/xlink"><g fill="currentColor" stroke="currentColor" stroke-width="0" transform="matrix(1 0 0 -1 0 0)"><g is="true"><use xlink:href="#MJMAIN-43"></use><use x="722" xlink:href="#MJMAIN-4F" y="0"></use></g></g></svg><span role="presentation"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true" mathvariant="normal">CO</mi></math></span></span><script type="math/mml"><math><mi mathvariant="normal" is="true">CO</mi></math></script></span> <sub>2</sub> emissions. However, their life cycle carbon footprint depends on the carbon intensity of the electricity or hydrogen that powers them and on emissions associated with vehicle production and recycling. This study aimed to compare the life cycle carbon footprint of conventional internal combustion engine vehicles (ICEVs), BEVs, and FCEVs during the production and use phases (Cradle-to-Gate, Well-to-Tank, and Tank-to-Wheel) in Central European countries. The analysis was based on three reference vehicles and publicly available data, including the carbon footprint of vehicle manufacturing, batteries, gasoline, electricity, and hydrogen. The national energy mix largely determines variation in carbon footprints: BEVs emit 25<!-- --> <span><span style=""></span><span data-mathml='<math xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="normal" is="true">tCO</mi></math>' role="presentation" style="font-size: 90%; display: inline-block; position: relative;" tabindex="0"><svg aria-hidden="true" focusable="false" height="2.086ex" role="img" style="vertical-align: -0.235ex;" viewbox="0 -796.9 1890.5 898.2" width="4.391ex" xmlns:xlink="http://www.w3.org/1999/xlink"><g fill="currentColor" stroke="currentColor" stroke-width="0" transform="matrix(1 0 0 -1 0 0)"><g is="true"><use xlink:href="#MJMAIN-74"></use><use x="389" xlink:href="#MJMAIN-43" y="0"></use><use x="1112" xlink:href="#MJMAIN-4F" y="0"></use></g></g></svg><span role="presentation"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true" mathvariant="normal">tCO</mi></math></span></span><script type="math/mml"><math><mi mathvariant="normal" is="true">tCO</mi></math></script></span> <sub>2</sub> in Austria (50% less than ICEVs) compared with 55<!-- --> <span><span style=""></span><span data-mathml='<math xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="normal" is="true">tCO</mi></math>' role="presen
{"title":"Comparative analysis of CO 2 emissions from conventional internal combustion engine vehicles, battery electric vehicles, and fuel cell electric vehicles in selected Central European countries","authors":"Josef Brousek, Tomas Petr, Pavel Brabec","doi":"10.1016/j.jclepro.2026.147706","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147706","url":null,"abstract":"Battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (FCEVs) are considered vehicles that do not produce local <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi mathvariant=\"normal\" is=\"true\">CO</mi></math>' role=\"presentation\" style=\"font-size: 90%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"2.086ex\" role=\"img\" style=\"vertical-align: -0.235ex;\" viewbox=\"0 -796.9 1501 898.2\" width=\"3.486ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g is=\"true\"><use xlink:href=\"#MJMAIN-43\"></use><use x=\"722\" xlink:href=\"#MJMAIN-4F\" y=\"0\"></use></g></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi is=\"true\" mathvariant=\"normal\">CO</mi></math></span></span><script type=\"math/mml\"><math><mi mathvariant=\"normal\" is=\"true\">CO</mi></math></script></span> <sub>2</sub> emissions. However, their life cycle carbon footprint depends on the carbon intensity of the electricity or hydrogen that powers them and on emissions associated with vehicle production and recycling. This study aimed to compare the life cycle carbon footprint of conventional internal combustion engine vehicles (ICEVs), BEVs, and FCEVs during the production and use phases (Cradle-to-Gate, Well-to-Tank, and Tank-to-Wheel) in Central European countries. The analysis was based on three reference vehicles and publicly available data, including the carbon footprint of vehicle manufacturing, batteries, gasoline, electricity, and hydrogen. The national energy mix largely determines variation in carbon footprints: BEVs emit 25<!-- --> <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi mathvariant=\"normal\" is=\"true\">tCO</mi></math>' role=\"presentation\" style=\"font-size: 90%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"2.086ex\" role=\"img\" style=\"vertical-align: -0.235ex;\" viewbox=\"0 -796.9 1890.5 898.2\" width=\"4.391ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g is=\"true\"><use xlink:href=\"#MJMAIN-74\"></use><use x=\"389\" xlink:href=\"#MJMAIN-43\" y=\"0\"></use><use x=\"1112\" xlink:href=\"#MJMAIN-4F\" y=\"0\"></use></g></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi is=\"true\" mathvariant=\"normal\">tCO</mi></math></span></span><script type=\"math/mml\"><math><mi mathvariant=\"normal\" is=\"true\">tCO</mi></math></script></span> <sub>2</sub> in Austria (50% less than ICEVs) compared with 55<!-- --> <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi mathvariant=\"normal\" is=\"true\">tCO</mi></math>' role=\"presen","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"95 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146101342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
The integration of decoupled water electrolysis with batteries enables flexible conversion and storage of renewable energy. Herein, an integrated syst…
解耦水电解与电池的集成使可再生能源的灵活转换和存储成为可能。在这里，一个集成的系统…
{"title":"Synergistic hydrogen and electricity co-production via a decoupled amphoteric water electrolysis system integrated with a phenazine-based Zn battery","authors":"Liwu Zhou, Baichuan He, Xinlong Lu, Zilong Zeng, Jiwei Li, Bohao Li, Zizuo Liu, Qingfan Liu, Fei Lv, Lijing Ma, Guorong Wang, Dengwei Jing","doi":"10.1016/j.jclepro.2026.147721","DOIUrl":"https://doi.org/10.1016/j.jclepro.2026.147721","url":null,"abstract":"The integration of decoupled water electrolysis with batteries enables flexible conversion and storage of renewable energy. Herein, an integrated syst…","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"29 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
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