Environmental Science and Ecotechnology最新文献

{"title":"Plastic particle risk is shaped by transformation history","authors":"Swaroop Chakraborty","doi":"10.1016/j.ese.2026.100731","DOIUrl":"10.1016/j.ese.2026.100731","url":null,"abstract":"","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"32 ","pages":"Article 100731"},"PeriodicalIF":14.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148476780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}

{"title":"Anthropogenic disturbance decouples coastal soil organic carbon and bulk density","authors":"Feixue Shen,&nbsp;Lin Yang,&nbsp;Xiuqiang Peng,&nbsp;Dianpeng Li,&nbsp;Chenconghai Yang,&nbsp;Yue Pu,&nbsp;Mao Guo,&nbsp;Yuru Yan,&nbsp;Chenghu Zhou","doi":"10.1016/j.ese.2026.100728","DOIUrl":"10.1016/j.ese.2026.100728","url":null,"abstract":"<div><div>Coastal blue carbon ecosystems play a pivotal role in mitigating global climate change through rapid sediment burial and efficient carbon preservation. However, accurate carbon accounting is severely hindered by the systematic neglect of soil bulk density (BD) variations and the uncritical reliance on terrestrial-derived pedotransfer functions, masking hidden uncertainties in regional carbon stock assessments. Here we present a high-resolution, multi-depth assessment of soil organic carbon (SOC) content and BD across a 1-m vertical gradient in the intensively managed coastal zone of Jiangsu Province, China. Machine learning frameworks reveal a striking spatial and vertical decoupling between SOC and BD driven by divergent environmental controls: SOC content responds to soil depth and ocean salinity, whereas BD aligns with hydro-geomorphic distance to the coast. Vegetation mediates a tight vertical negative coupling (<em>p</em> &lt; 0.001) in natural salt marshes, whereas anthropogenic activities decouple this relationship in croplands, restricting standard pedotransfer function predictability in all layers (<em>R</em>² ≤ 0.22). Across all layers, conventional spatial estimation models yield high baseline prediction uncertainty (<em>RMSE</em> = 0.22 g cm⁻³). These findings demonstrate that independent, high-resolution BD profiling is indispensable for valid blue carbon verification. Our results establish a transferable baseline to optimize depth-specific sampling and refine global coastal carbon accounting models under intensifying human pressures.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"32 ","pages":"Article 100728"},"PeriodicalIF":14.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13355218/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148424932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}

{"title":"Cross-sector deep learning scales life cycle assessment using unified textual descriptions","authors":"Kai Zhao,&nbsp;Biao Luo,&nbsp;Xiting Peng,&nbsp;Zhu Deng,&nbsp;Peng Zhang,&nbsp;Chen Li,&nbsp;Tao Liu,&nbsp;Xiaonan Wang,&nbsp;Zhijun Gui,&nbsp;Shanying Hu","doi":"10.1016/j.ese.2026.100724","DOIUrl":"10.1016/j.ese.2026.100724","url":null,"abstract":"<div><div>Life cycle assessment (LCA) is a foundational framework for quantifying global environmental impacts to guide decarbonization and circular economy transitions. Yet, conventional inventory compilation remains severely bottlenecked by data scarcity and intensive manual curation, with existing machine learning solutions typically confined to isolated industrial sectors rather than offering a scalable way to overcome these limitations. This fragmentation prevents pan-industrial scaling, thereby masking hidden environmental risks and hindering rapid, data-driven sustainability interventions. Here we develop LCA-TextNet, a generalizable deep learning framework that bypasses domain-specific feature engineering by predicting 25 life cycle impact indicators across 20 distinct industrial sectors directly from knowledge-based textual descriptions. Leveraging a Transformer-based architecture trained on over 16,000 datasets, the model maps high-dimensional text embeddings into uniform semantic spaces, achieving high accuracy (<em>R</em>² &gt; 0.8) across 70% of sectors. Crucially, integrating application-domain stratification with an incremental learning strategy successfully mitigates distribution shifts during cross-version database validation, slashing climate change mean absolute error by 70%, from 2.0 to 0.6 kg CO₂-equivalent per unit. By exploiting the widespread asymmetry between ubiquitous descriptive text and scarce inventory metrics, this framework establishes a scalable paradigm that transforms textual knowledge into rapid, pan-industrial environmental intelligence to accelerate green transitions.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"32 ","pages":"Article 100724"},"PeriodicalIF":14.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13312156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148353834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}

{"title":"Global data–water symbiosis reduces AI infrastructure's carbon and water footprint","authors":"Aijie Wang ,&nbsp;Congchao Zhang ,&nbsp;Tiefu Xu ,&nbsp;Dragan Savic ,&nbsp;Jingjing Jiang ,&nbsp;Peng Xiao ,&nbsp;Chuan He ,&nbsp;Yu Tao ,&nbsp;Glen Daigger ,&nbsp;Nanqi Ren","doi":"10.1016/j.ese.2026.100702","DOIUrl":"10.1016/j.ese.2026.100702","url":null,"abstract":"<div><div>Data centres support artificial intelligence (AI) development but place rapidly increasing demands on electricity and freshwater resources, with cooling representing a significant portion of their total energy consumption. Wastewater treatment plants (WWTPs) discharge large volumes of treated effluent with substantial cooling potential; however, their integration with data centre infrastructure has not been evaluated. Here we construct a global geodatabase of over 4775 data centres and 57,547 municipal WWTPs across 98 countries, integrating spatial analysis, engineering systems modelling, optimisation, and life-cycle assessment to quantify the benefits of combining treated water reuse with bidirectional thermal recovery. The analysis reveals a strong global spatial co-occurrence between data centres and WWTPs, enabling optimized national-scale pairings in which treated effluent is used for data centre cooling and the return heat is recovered to support sludge drying and anaerobic digestion. This symbiotic approach reduces greenhouse gas emissions by approximately 84 million tonnes of CO₂ equivalent annually, conserves approximately 1300 million m³ of freshwater, and provides net annual cost savings of approximately US$95.4 billion. The greatest mitigation and water-saving potential lies in the United States, Japan, China, the Netherlands, and the United Kingdom. These findings establish data–water symbiosis as a readily scalable infrastructure solution that decouples AI from its carbon and water footprints. WWTPs are poised to evolve from disposal facilities into critical energy-coupling hubs, enabling efficient thermal and water exchange across urban systems and accelerating progress towards multiple Sustainable Development Goals.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100702"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802982","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}

{"title":"Plastic leachates drive conjugative transfer of antibiotic resistance genes","authors":"Yongsheng Chen ,&nbsp;Kaiqiang Yu ,&nbsp;Yuhong Sun ,&nbsp;Yuxi Yan ,&nbsp;Gege Yin ,&nbsp;Junjian Wang ,&nbsp;Xia Li ,&nbsp;Song Tang ,&nbsp;Paul Pronyk ,&nbsp;Yu Xia","doi":"10.1016/j.ese.2026.100705","DOIUrl":"10.1016/j.ese.2026.100705","url":null,"abstract":"<div><div>Plastic pollution pervades aquatic ecosystems worldwide, releasing leachates that interact intimately with microbial communities. Antibiotic resistance genes (ARGs) disseminate rapidly through horizontal gene transfer via plasmid conjugation, posing a severe and accelerating threat to public health and environmental stability. While microplastic particles are known to promote ARG exchange within biofilms, the influence of soluble chemical leachates derived from degrading plastics has remained unclear. Here we show that photodegraded leachate from polyvinyl chloride (PVC)—a widely used material in water infrastructure—substantially enhances conjugative transfer of ARGs in both laboratory model systems and natural aquatic microbiomes. Exposure increased transconjugant abundance up to 26.4-fold and conjugation efficiency up to 44.6-fold, with non-monotonic responses modulated by leachate concentration and microbial community diversity. Characterization of the leachate revealed high proportions of biolabile dissolved organic matter alongside additives; mechanistic assays demonstrated that these effects arise through elevated intracellular reactive oxygen species (21% increase), activation of the SOS response and DNA-repair pathways, increased extracellular protein production facilitating cell–cell contact, and compensatory adjustments in the electron transport chain that maintain ATP homeostasis. These results demonstrate that plastic leachates act as potent but previously overlooked facilitators of ARG dissemination beyond the physical effects of microplastics. Our findings reveal a critical synergy between plastic pollution and the global antimicrobial-resistance crisis, underscoring the urgent need for targeted regulations on plastic additives and degradation products in aquatic systems.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100705"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147859092","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}

{"title":"Quorum sensing for carbon-neutral wastewater treatment: Mechanisms, challenges, technological pathways, and future prospects","authors":"Wen-Qian Wang ,&nbsp;Yong-Mei Wang ,&nbsp;Xiao-Chi Feng ,&nbsp;How Yong Ng ,&nbsp;Nan-Qi Ren","doi":"10.1016/j.ese.2026.100701","DOIUrl":"10.1016/j.ese.2026.100701","url":null,"abstract":"<div><div>Global climate targets demand a rapid transition to carbon neutrality across all industrial sectors, including wastewater management. Wastewater treatment plants are historically energy-intensive and remain significant sources of potent greenhouse gases, primarily nitrous oxide (N₂O) and methane (CH₄). Recent biological interventions have targeted quorum sensing (QS)—a microbial communication mechanism regulating gene expression and community behavior—to optimize biological treatment efficiency. However, the highly context-dependent and sometimes paradoxical effects of QS on simultaneous greenhouse gas mitigation and energy recovery remain poorly resolved. Here we synthesize recent advancements to show that QS operates as a master biological regulator of both direct emissions and energy consumption in wastewater ecosystems. Evidence indicates that QS distinctly modulates N₂O production through concentration- and signal-dependent pathways, while actively suppressing CH₄ escape and enhancing aerobic granulation to cut aeration energy demands. Furthermore, targeted QS deployment in anaerobic digestion accelerates direct interspecies electron transfer, substantially boosting methane recovery to offset operational energy use. These insights reveal that manipulating microbial social networks presents a viable, albeit complex, biological lever for balancing emission reductions with energy optimization. Ultimately, precision control of QS systems offers a transformative technological pathway for achieving carbon-positive wastewater infrastructure.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100701"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147956793","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}

{"title":"Electron transfer drives hydroxyl radical formation in peroxone reactions","authors":"Yishi Wang,&nbsp;Wei Qiu,&nbsp;Yongbo Yu,&nbsp;Jun Ma","doi":"10.1016/j.ese.2026.100704","DOIUrl":"10.1016/j.ese.2026.100704","url":null,"abstract":"<div><div>Ozone is a powerful oxidant widely used in water treatment for the degradation of organic pollutants and removal of colour, odor, and pathogens. In aqueous solution, ozone decomposes to generate hydroxyl radicals through chain reactions that are accelerated by the addition of hydrogen peroxide in the peroxone process. Yet the precise initiation mechanisms of these chains and the efficiency of hydroxyl radical production have remained controversial, with prior models proposing adduct formation as the rate-limiting step and yielding only approximately 50% hydroxyl radicals in peroxone process. Here we show that the hydroxyl radical yield in the peroxone reaction is approximately 67%, substantially higher than previously reported. Through complete-capture scavenger assays, competition experiments, and high-precision quantum-chemical calculations informed by Marcus electron-transfer theory, we establish that ozone reacts with hydroxide exclusively by oxygen-atom transfer, while its reaction with the hydroperoxide anion proceeds through parallel electron transfer (approximately 50%) and oxygen-atom transfer (approximately 50%) pathways. Spin-orbit coupling enables spin-forbidden release of triplet oxygen in the atom-transfer channel. We also determine the p<em>K</em>_a of the hydroxyl radical precursor hydrotrioxide as approximately 6.15 and quantify the long-disputed hydroxyl radical–ozone reaction rate constant as 1.1 × 10⁸ M⁻¹ s⁻¹. These results revise classical ozonation and peroxone mechanisms and provide a mechanistic foundation for optimizing ozone-based advanced oxidation technologies for water purification.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100704"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147956917","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}

{"title":"Oceanographic regime and foraging behaviour structure compound-specific PFAS variability in arctic-atlantic guillemots","authors":"Rui Shen ,&nbsp;Ralf Ebinghaus ,&nbsp;Daniel Giddings Vassão ,&nbsp;Norman Ratcliffe ,&nbsp;Thomas Larsen","doi":"10.1016/j.ese.2026.100707","DOIUrl":"10.1016/j.ese.2026.100707","url":null,"abstract":"<div><div>Current chemical exposures studies characterise chemical risk through mean-based concentrations, treating individual-level variability as statistical noise. However, this variability may carry structured ecological information that mean-based approaches systematically overlook. Here, we propose that individual per- and polyfluoroalkyl substance (PFAS) exposure variability constitutes a structured ecological signal, shaped by habitat use across oceanographic gradients and individual foraging behaviour, one that mean-based approaches are not designed to capture. To test the variability-as-signal hypothesis, we integrated two independent indices of individual stability using two sympatric guillemot species (<em>Uria aalge, n = 67</em> and <em>Uria lomvia, n = 45</em>) sampled across five Icelandic colonies during the 2018 breeding season. We paired PFAS variability scores, derived from plasma PFAS concentrations, with isotopic consistency scores derived from dual-tissue stable isotopes (δ¹³C and δ¹⁵N in plasma and red blood cells). These consistency scores represent individual foraging stability across the breeding season, enabling a reconstruction of foraging histories and oceanographic habitat use. Our results reveal that PFAS variability is highly structured by compound class, dominated by long-chain perfluoroalkyl carboxylic acids (PFCAs; 79% of variance) and perfluorooctane sulfonate (PFOS; 13%). Cluster analysis identified two main divergent exposure states: constrained PFOS variability versus constrained PFCA variability. Bivariate segmented regression revealed a hierarchical structure to contaminant acquisition: oceanographic regime (proxied by δ¹³C_consist) functioned as the primary driver, with PFOS variability intensifying in Atlantic-influenced waters. Within these regimes, trophic sources (proxied by δ¹⁵N_consist) emerged as a secondary, conditional modulator, specifically constraining PFCA variability among high-trophic individuals. At the colony scale, fine-scale niche partitioning, such as vertical foraging strategies and individual specialisation using glacial fjords and ice margins, produced compound-specific patterns that diverged from regional hierarchies. As climate change continues to redistribute Arctic and Atlantic water masses and reshape the food web structures, approaches that treat contaminant variability as ecological signal will be increasingly valuable for anticipating exposure regime shifts.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100707"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148001363","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}

{"title":"Enzyme-constrained genome-scale modeling resolves growth-production trade-offs in fermentative biohydrogen production","authors":"Wei Xing ,&nbsp;Jianfeng Liu ,&nbsp;Bin Liu ,&nbsp;Yanan Hou ,&nbsp;Jia Zhang ,&nbsp;Shuang Gao ,&nbsp;Ai-Jie Wang ,&nbsp;Qianqian Yuan ,&nbsp;Nan-Qi Ren ,&nbsp;Cong Huang","doi":"10.1016/j.ese.2026.100706","DOIUrl":"10.1016/j.ese.2026.100706","url":null,"abstract":"<div><div>Hydrogen is central to sustainable energy systems, with biological production from waste offering a low-energy, environmentally compatible route. Anaerobic dark fermentation by microbes converts organic substrates into hydrogen, yet yields remain limited by competing metabolic pathways and poor understanding of cellular resource allocation in hydrogen-producing strains. Conventional genome-scale models rely on stoichiometric constraints alone, often failing to capture realistic enzyme limitations or strain-specific biomass composition. Here we show that an enzyme-constrained genome-scale metabolic model (ecGEM) of the hydrogen-producing bacterium <em>Ethanoligenens harbinense</em> YUAN-3, built with experimentally measured biomass composition and predicted <em>k</em>_cat values, quantitatively captures the trade-off between growth and hydrogen production. Enzyme constraints eliminate unrealistic flux predictions of standard models, accurately matching experimental growth rates and yields, and reveal that diversion of carbon and NADH flux into glutamate and glutamine biosynthesis enhances hydrogen production by reducing ethanol formation. In silico single-gene knockouts identify targets such as phosphoglycerate kinase that increase hydrogen flux by up to 30% under low-carbon conditions. These findings elucidate system-level metabolic regulation in fermentative hydrogen production and provide a predictive framework for rational strain engineering. The approach offers a scalable platform for optimizing biohydrogen processes and advancing sustainable hydrogen economies.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100706"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148001361","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}

{"title":"Trace lanthanum activation drives deep biological phosphorus removal","authors":"Bohan Liu ,&nbsp;Jun Nan ,&nbsp;Rongcheng He ,&nbsp;Haiyang Wei ,&nbsp;Tianyi Zhao ,&nbsp;Yibo Zhang ,&nbsp;Ruixue Jiang ,&nbsp;Fangmin Wu ,&nbsp;Zhencheng Ge ,&nbsp;Xuesong Ye ,&nbsp;Wei Wang ,&nbsp;Jun Ma","doi":"10.1016/j.ese.2026.100708","DOIUrl":"10.1016/j.ese.2026.100708","url":null,"abstract":"<div><div>Eutrophication driven by excessive phosphorus discharge threatens global aquatic ecosystems. Enhanced biological phosphorus removal (EBPR) is a sustainable, widely deployed wastewater treatment technology, yet it often requires optimization to meet increasingly stringent global phosphorus emission standards. Conventional chemical supplements can achieve deep phosphorus removal, but they require excessive dosing, generate large volumes of sludge, and can inhibit the essential polyphosphate-accumulating organisms (PAOs) that drive biological treatment. Here we show that a low-dose, slow-release lanthanum aerogel (LZGA) activates PAO metabolism, enabling deep biological phosphorus removal with a near-zero chemical footprint. By releasing La³⁺ into sequencing batch reactors, the LZGA platform reduced effluent total phosphorus from 0.85 mg L⁻¹ to 0.14 mg L⁻¹ at an optimal dose of 15 mg L⁻¹. This represents a two-order-of-magnitude reduction in chemical consumption compared to conventional precipitation methods, requiring 0.7 g of lanthanum to treat one ton of wastewater. Proteomic and microbial analyses reveal that trace La³⁺ stimulates potassium channels, upregulating key energy metabolism pathways and driving an order-of-magnitude increase in the protein expression of the core PAO <em>Candidatus</em> Accumulibacter. Furthermore, the system enhances extracellular polymeric substance (EPS) production, and improves the phosphorus absorption capacity of EPS. These findings demonstrate that targeted trace-metal activation of microbial metabolic pathways offers a strategy to upgrade existing bioreactors. This strategy provides a versatile paradigm for global wastewater management and advanced eutrophication control.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"31 ","pages":"Article 100708"},"PeriodicalIF":14.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148001362","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}