Livestock farming environments are major reservoirs of antimicrobial resistance (AMR), yet scalable genetic indicators that quantitatively capture both abundance and dissemination potential remain limited. Class 1 integrons (CL1s) integrate gene capture with horizontal transfer capacity and have been proposed as candidates, but their suitability as a direct proxy for livestock-associated AMR risk has not been rigorously tested at scale. Here we show that the abundance of intI1 functions as a robust quantitative indicator of livestock-associated AMR risk. Using a custom Class 1 Integrase Database expanded by 63.5% and integrating 4,017 livestock metagenomes, 9,625 isolate genomes, and approximately 1.2 million clinical genomes, we demonstrate that intI1 abundance tracks host- and geography-dependent risk patterns, that livestock CL1s carry compact, conserved resistance-cassette arrays matching clinical spectra, and that nearly all are plasmid-borne, with their efficient dissemination facilitated by Tn402-, ISCR-, and IS110-family elements. A random-forest model trained on these data predicts global intI1 abundance and associated risk with high accuracy (R2 = 0.93), revealing persistent hotspots across Asia, sub-Saharan Africa, and South America over two decades. These findings establish intI1 as a practical, single-platform proxy that can be incorporated into One Health surveillance and early-warning systems.
Rapid urbanization concentrates both opportunity and health risk across cities worldwide. Although urban green infrastructure is widely promoted for public health, most evidence examines single outcomes or simple area metrics and rarely tests how socioeconomic context modulates the magnitude and pathways of these benefits. Whether tree-canopy equity delivers stronger returns in areas with the highest poverty remains unresolved. Here, we show that poverty-modulated tree equity shapes health burdens across 497 cities in the United States. Socioeconomic disadvantage is the dominant structural driver of eleven physical and mental health outcomes, yet higher Tree Equity Score is consistently associated with lower prevalence; these protective associations are strongest in high-poverty cities, where greening acts partly by mitigating heat and air-pollution hazards, whereas in low-poverty cities direct restorative pathways predominate. Models explain up to 72.6 percent of the variation in poor mental health, and a five-point rise in the Tree Equity Score corresponds to a 2.7–35 percent lower prevalence of multiple conditions. These findings demonstrate that the health returns of urban greening are context-dependent and require equity-focused strategies stratified by city poverty level.
Understanding the sediment-water partitioning of emerging contaminants is essential for assessing their mobility, persistence and ecological risks in river systems. However, the mechanisms driving large differences in partitioning behaviour across contaminant classes remain poorly resolved at the basin scale. Here we show that major emerging contaminant classes follow distinct mechanistic regimes in sediment-water partitioning. Analysis of a nationwide dataset comprising 5085 paired sediment-water records across China's major river basins reveals that antibiotics are predominantly controlled by molecular descriptors, per- and polyfluoroalkyl substances are strongly modulated by ion-mediated interfacial processes, and endocrine-disrupting chemicals exhibit synergistic regulation by molecular, geochemical and basin-scale factors. Integration with molecular dynamics simulations confirms these class-specific mechanisms at the molecular interface, while a multi-branch multi-head attention framework enables accurate prediction (R 2 = 0.76-0.92) and spatially explicit mapping of high-accumulation versus high-mobility zones. By identifying class-specific mechanistic regimes, this work provides both improved predictive capability and a clearer mechanistic basis for basin-scale risk assessment of emerging contaminants.
Climate change is rapidly altering global glacier-fed rivers, with prevailing models assuming that water temperature increases dictate aquatic community succession. However, this thermal-centric paradigm struggles to explain biodiversity patterns within the extreme topographic and hydrologic gradients of the Third Pole. By analyzing macroinvertebrate assemblages across the Yarlung Tsangpo Basin, we show that hydrodynamic condition, rather than water temperature, primarily influences biodiversity and community assembly in these high-altitude alpine rivers. With hydrodynamic intensity indicated by specific stream power, taxa richness exhibits a universal unimodal response, consistently peaking under moderate hydrodynamic intensity (1 to 10 W m-2). Extreme stream power acts as a severe physical filter, driving a stark taxonomic shift from filamentous-gilled species in moderate flows to robust, flat-bodied specialists capable of resisting ultra-high-power environments. These findings demonstrate that localized hydrodynamic modulation-rather than unattainable temperature control-provides a highly viable, climate-resilient strategy to safeguard biodiversity in the Third Pole and analogous alpine river networks worldwide.
Oil spills in tropical intertidal zones expose sandy shorelines to hydrocarbons under highly dynamic redox conditions, yet the fate of fuel oils in these systems remains poorly resolved. Here, we used replicated microcosms simulating unsaturated oxic and saturated anoxic regimes to quantify fuel oil degradation in tropical sands and applied functional metagenomics to resolve underlying microbial hydrocarbonoclastic processes. Abiotic depletion of petroleum hydrocarbons was 15-20% in oxic and anoxic sterile sand controls. Biodegradation under unsaturated oxic conditions was 3-fold higher than abiotic losses, whilst negligible (approximately 5%) biodegradation occurred in saturated anoxic sand over the 90 days, confirming a dominant role for aerobic microbial activity. Community composition diverged strongly by moisture regime, with aerobic Alphaproteobacteria and Gammaproteobacteria enriched under oxic conditions, and anaerobic sulfate-reducing lineages including Desulfobacteria and Desulfovibrionia dominating under anoxia. Functional analyses revealed a coordinated transition between dominant aerobic and anaerobic hydrocarbon degradation strategies, including terminal/biterminal oxidation versus fumarate addition pathways for alkanes, and ring cleavage versus carboxylation pathways for aromatics. Enhanced biosurfactant production potential suggested increased hydrocarbon bioavailability, facilitating efficient biodegradation across contrasting redox conditions. We further recovered 298 oil-associated bacterial genomes and characterized their repertoire of genes encoding oil hydrocarbon degradation pathways across diverse phylogenetic lineages. Together, these results demonstrate that moisture-driven redox dynamics regulate biodegradation rates, microbial succession, and functional partitioning in intertidal sediments, providing new mechanistic insight into the fate of fuel oil in tropical coastal systems.
Ammonia recovery from wastewater supports sustainable nitrogen circularity and reduces reliance on energy-intensive Haber-Bosch synthesis. Anaerobic digestion effluent represents a concentrated nitrogen resource, yet membrane contactors for selective NH3 recovery suffer from coupled wetting and fouling in complex real matrices, limiting long-term performance. Conventional hydrophobic modifications improve initial resistance but lack quantitative mechanistic understanding of how interface design governs pore-scale dynamics and sustained transport under realistic conditions. Here we show that systematic fluorosilane engineering of commercial PVDF membranes produces superhydrophobic contactors that, when guided by operando optical coherence tomography, establish a quantitative framework linking interfacial fluorination density to the stabilization of Cassie-Baxter-like states, suppression of pore wetting and fouling, and durable high-efficiency NH3 recovery from real anaerobic digestion effluent. The optimal PVDF@PFDTMS membrane achieves 98.4% recovery efficiency and 44.8 g m-2 d-1 flux while maintaining near-invariant porosity and thickness over 20 h and across multiple physical cleaning cycles. These results demonstrate that operando structural diagnostics can transform empirical surface modification into a rational, mechanism-informed design strategy for resilient membrane contactors. This framework advances durable, energy-efficient nutrient recovery technologies for high-strength waste streams and supports scalable nitrogen circularity.
Clean water scarcity intensifies the need for advanced treatment of emerging contaminants in nanofiltration (NF) concentrates. Conventional electro-Fenton (EF) systems face unstable oxygen supply and electrode wetting in bubbleless aeration, limiting selective reactive oxygen species generation in high-salinity matrices. Here we show a molecular oxygen confinement ladder strategy by developing a conductive aeration membrane cathode in which boron nitride spontaneously forms wedge-shaped structures inside carbon nanotubes. This architecture achieves kinetic antiwetting and physical oxygen confinement at the nanoscale, accelerating Fe(II)/Fe(III) cycling and directing the pathway to dominant singlet oxygen (1O2) generation. Experiments and simulations demonstrate fivefold faster degradation kinetics, complete sulfamethoxazole removal within 15 min, and sustained high efficiency over 48 h of continuous operation, including a switch to real NF concentrate. The structure-oriented gas confinement approach thus offers a robust platform for selective and stable EF treatment of complex industrial wastewater.
Phosphorus is a finite resource essential to global food security, yet many import-dependent regions face increasing supply risks from concentrated reserves and geopolitical disruption. While municipal wastewater sludge offers a promising domestic secondary source of phosphorus, large-scale recovery remains limited by uncertainty over practical yields under real-world engineering and economic constraints. Previous assessments have often relied on aggregated data that obscure facility-specific conditions, leaving recoverable potential poorly constrained and potentially overstated. Here we developed an integrated facility-level framework connecting treatment scale, process configuration, phosphorus speciation, costs and spatial distribution, and applied it to a nationwide dataset for Japan. Results showed that engineering constraints reduced theoretical recovery by 34-63%, yet an integrated pathway combining decentralized aqueous-phase recovery with centralized ash leaching could still make a substantial contribution to the national target of agricultural phosphorus supply. Realizing this potential requires targeted incentives to address pronounced cost heterogeneity across facilities and coordinated spatial redistribution of recovered products. By establishing constraint-integrated modeling approaches, this work provides a transferable basis for evaluating recovery pathways, prioritizing investment and designing implementation strategies in other import-dependent regions seeking to advance circular phosphorus economies.
Resource recovery has gained substantial traction in urban water management in recent years, promising exciting opportunities for utilities to develop novel services, new income streams, and/or expand the environmental benefits of their operations. However, success stories that substantiate the high hopes remain scant. We will argue that a transition of the sanitation sector from providing a public good of waste disposal to running a resource mining venture will require a systemic innovation process in which technical, organizational, and regulatory routines of involved actors will be deeply reshuffled. We review the state of knowledge on the opportunities and barriers for scaling up innovative resource recovery solutions from wastewater and illustrate them with three short case studies of existing resource recovery systems. While the complexity of inducing resource recovery should not be underestimated, transformative innovation trajectories can be successful if technological, social, and organizational challenges are strategically and holistically addressed.
Drained peatlands are major sources of greenhouse gases, but rewetting them to restore carbon storage often triggers substantial methane emissions and faces resistance from agricultural land users. Wildfires are becoming more frequent on these drained landscapes and can sharply reduce agricultural productivity. It remains unclear whether severely wildfire-affected peatlands can serve as effective targets for rewetting. Here we show that rewetting severely wildfire-affected peat soils suppresses methane emissions by more than 90% compared with rewetting non-fire-affected soils. Severe wildfire legacies increase soil carbon stability, raise pH and electrical conductivity, reduce methanogenic functional gene abundance, and can override typical hydrological controls, turning what is usually a methane surge into a strong net climate benefit. These changes position recent severe wildfire footprints as overlooked low-emission, high-priority targets for peatland rewetting that also reduce land-use conflict. Global scaling indicates that prioritizing rewetting on severely wildfire-affected degraded peatlands could avoid up to 0.8 million tonnes of CO2-equivalent methane emissions per year, with more than 70% of the potential in Asia. The findings reveal a practical pathway to accelerate restoration by harnessing wildfire legacies rather than fighting them.
Vehicular emissions are a primary source of volatile organic compounds (VOCs), which drive urban ozone and secondary organic aerosol formation while posing direct risks to human health. Progressive emission standards and the widespread adoption of hybrid electric vehicles have successfully reduced total hydrocarbon outputs, establishing them as central strategies for climate and air quality management. However, the influence of these technological shifts on the molecular speciation of emissions-and their associated environmental and toxicological trade-offs-remains poorly understood, potentially masking hidden health risks. Here we apply a concentration-reactivity-toxicity framework to characterize species-resolved VOC emissions across conventional and hybrid vehicles under progressive emission standards. While stricter regulations reduced total VOC emissions by 75% in conventional vehicles, the relative contribution of highly reactive oxygenated VOCs (OVOCs) surged from 20% to 35%. Notably, a modern hybrid vehicle emitted nearly twice the mass of OVOCs (25.4 mg km-1) compared to its conventional counterpart (13.3 mg km-1), driven by frequent engine start-stop cycles that reduce aftertreatment efficiency. This distinct operational profile allows us to identify specific compounds-namely, vinyl acetate and methyl t-butyl ether-as molecular markers for hybrid powertrains in our study. Consequently, despite superior fuel economy, this tested hybrid vehicle exhibited a 69% increase in non-carcinogenic health risks and nearly double the carcinogenic risk, overwhelmingly dominated by aromatics and toxic OVOCs such as acrolein. Furthermore, while absolute emissions declined, persistent aromatics continued to account for over 70% of the secondary organic aerosol formation potential. These findings highlight a critical tension between fuel efficiency advancements and toxicological impacts, suggesting that future emission regulations must transition from total mass limits to species-specific controls to fully safeguard public health.
Microplastic pollution is ubiquitous across the global ocean, threatening marine ecosystems. While environmental baselines often treat contamination as a temporally uniform stressor, the reproductive period represents the most physiologically vulnerable window in the life cycle of marine fishes. However, it remains unknown how seasonal reproductive aggregations spatiotemporally interact with microplastic accumulation hotspots and vector-driven co-contaminants at a global scale. Here we show that the spatiotemporal overlap between peak spawning and pollution intensity poses a disproportionate threat to marine fish communities, particularly critically endangered species. Integrating 6327 seawater microplastic observations and reproductive traits of 992 species across 65 large marine ecosystems, we reveal that microplastic-mediated vector effects for polycyclic aromatic hydrocarbons and perfluorooctane sulfonate peak precisely during the critical spring spawning window, amplifying synergistic bio-risks by up to 42.3%. This reproductive-period vulnerability is exacerbated by climate-driven warming and hypoxia, which synergistically maximize microplastic bioconcentration factors, leading critically endangered fishes to endure compound vector exposures nine times higher than least-concern taxa. With 7.8% of global critical spawning grounds currently exceeding ecological safety thresholds, these findings fundamentally challenge existing static conservation paradigms. Explicitly incorporating these seasonal life-cycle dimensions into global marine management is imperative to safeguard threatened biodiversity and fisheries sustainability.
Harmful algal blooms are expanding globally across freshwater ecosystems due to climate change and accelerating eutrophication, posing escalating threats to public health and economic stability. Robust early warning requires predictive frameworks that are accurate at hourly resolution, uncertainty-aware, and mechanistically interpretable. Existing process-based models are limited by sparse parameterization, while statistical and deep-learning approaches typically operate at daily resolution, produce only point predictions, and rely on threshold-based classifications or post-hoc explanations that fail to capture high-frequency temporal dynamics or quantify predictive uncertainty, thereby hindering proactive intervention and masking hidden ecological risks. Here we present BloomNet, an intrinsically interpretable deep neural network architecture configured for multi-horizon quantile forecasting, resolves these limitations by integrating future environmental covariates with historical observations from a hyper-eutrophic lake. Evaluated on a four-year hourly record, BloomNet achieves exceptional predictive stability across 24-, 48-, and 72-h horizons (R 2 up to 0.78, 24-h MAPE = 25.7%), outperforming long short-term memory, Transformer, and temporal convolutional network baselines while circumventing iterative error accumulation. The network's dual-path variable-selection and attention mechanisms decode shifting ecological drivers directly across horizons, revealing a transition from short-term thermal regulation (water temperature weight up to 0.640) to medium-term nutrient governance (total phosphorus weight up to 0.689), while isolating distinct multimodal attention spikes 24h prior to bloom onset. Real-time interpretability further reveals that driver importance and temporal dependencies shift dynamically between bloom-onset and non-bloom states. These probabilistic quantiles establish a graduated, risk-oriented warning protocol that transforms reactive water resource administration into precision ecotechnology.
Escalating global temperatures threaten economic stability by worsening occupational heat stress and reducing workforce productivity. Despite advancements in macroeconomic modeling, current risk assessments rely on coarse annual aggregations and ignore internal labor mobility, thereby masking highly unequal sub-national vulnerabilities and underestimating how labor mobility buffers cascading supply-chain losses. Here we present a high-resolution, agent-based dynamic supply chain network model that integrates empirical daily mobility data across 313 Chinese cities to quantify the spatiotemporal cascading economic impacts of occupational heat exposure. We show that annual heat stress costs China 2933.5 billion CNY (2.6% of GDP), with systemic propagation through supply chains driving 59% of these losses. Crucially, labor mobility redistributes risk: net labor inflows into industrialized, high-heat southeastern regions provide a factor-compensation effect that buffers cascading losses by offsetting direct local productivity shocks, saving a net 7.2 billion CNY directly and 24.6 billion CNY indirectly nationwide. Under a 2030 warming scenario (SSP3-7.0), total losses expand 1.6-fold to 4672.9 billion CNY, though integrated multi-level adaptations-combining industrial restructuring with work-hour shifting-can mitigate these future losses by 30%. These findings reveal that demographic mobility dictates the economic geometry of climate vulnerability, highlighting that resilient climate adaptation requires synchronized network-level interventions rather than isolated local policies.
Wastewater treatment is shifting from simply removing pollutants to recovering valuable resources. Although membrane and bioelectrochemical technologies are promising tools for this transition, they typically operate independently and rely heavily on external power, limiting their scalability. Here we develop an energy-neutral system that couples electrically assisted forward osmosis (eFO) with a microbial desalination cell (MDC) to autonomously extract nutrients and water recovery from wastewater. Bioelectricity generated from organic oxidation in the MDC (>7.0 mW) directly powers the eFO module (<1.0 mW). This internal energy transfer drives magnesium ion migration to trigger struvite precipitation, boosting nutrient recovery by 184% and water flux by 57% compared to standalone operations. Using a hybrid model to optimize these complex dynamics, our closed-loop design sustains ideal concentration gradients and improves total desalination efficiency by 45%. By eliminating the need for external grids, this self-powered framework offers a practical and scalable blueprint for zero-energy wastewater refineries.
Microplastics (MPs) in sewer systems can be transported extensively before entering wastewater treatment plants. Sewer systems harbor complex microbial communities under low-oxygen, sulfide-rich conditions that drive key biogeochemical cycles. These conditions drive microplastic aging, whereas these particles concurrently perturb sewer microbial ecology and metabolic functions. However, the underlying mechanisms of in-sewer microplastic aging and their subsequent impacts on sewer microbiomes remain unclear. Here we show that hydroxyl radicals preferentially attack ester bonds (C–O) in polyethylene terephthalate (PET) and polybutylene adipate terephthalate (PBAT) MPs, increasing surface roughness, reducing particle size, promoting surface oxidation, and ultimately inducing polymer chain scission. Exposure to PET and PBAT MPs at 30–500 particles L−1 intensified oxidative stress, disrupted membrane integrity and permeability, impaired microbial activity, and suppressed sulfide production in a dose-dependent manner. These disruptions coincided with weakened microbial co-occurrence networks and a shift from stochastic toward deterministic community assembly. High doses of PET and PBAT MPs reduced hydrolytic/fermentative bacteria and sulfate-reducing bacteria by up to 63.4% and 49.7%, respectively, while enriching hydrogen-producing acetogenic bacteria and methanogenic archaea by 48.4–67.0%, consistent with reduced sulfidogenic potential and enhanced methanogenic potential. Changes in genes related to antioxidant defense, SOS response, quorum sensing (e.g., sodA, katG, lexA, and luxS), and redox signaling suggested potential mechanisms of microbial metabolic perturbations aggravated by PET and PBAT MPs. Our results indicate that sewer systems are not passive conduits but active reactors that promote MP aging, and that MPs reshape microbial functions. Microplastic control may therefore help reduce downstream particle pollution and limit perturbations to urban sewage biogeochemistry.
Trait-based frameworks, notably Grime's competitor–stress-tolerant–ruderal theory, offer a powerful lens for predicting how environmental fluctuations govern community structure. Yet, classical ecological models assume environments combining extreme stress and intense disturbance are non-viable for sustained colonisation, leaving a critical bottleneck in our ability to predict how microbial systems withstand compounded operational pressures. This gap severely hinders the predictive management of engineered microbiomes critical for global waste-to-energy conversion. Here we extend the application of classic ecological frameworks by demonstrating that anaerobic digester microbiomes deploy distinct, predictable life-history strategies across a 182-day compounded gradient of biomass turnover and organic loading. High-intensity single-event disturbances drive severe volatile fatty acid accumulation (propionate reaching 2,955 mg L−1), selectively shifting the microbiome toward stress-tolerant and stress-tolerant–ruderal strategies. Traits associated with ribosome function, molecular chaperones, and enzymatic reactive oxygen species detoxification were particularly enriched under highly disturbed conditions. Conversely, intermediate regimes were associated with ruderal strategies that prioritise rapid growth over resource-uptake efficiency, dropping total chemical oxygen demand removal to 41%. Cross-system comparisons encompassing anaerobic digestion, activated sludge, and soil ecosystems, revealed both universal and context-dependent ecological traits. Survival-associated traits linked to cell maintenance and repair, protective mechanisms, and cell motility were universally associated with stress-tolerant or ruderal strategies across ecosystems, whereas nutrient transport and metabolic traits exhibited greater context dependency. These insights establish a gene-resolved framework that reconciles microbial trait selection with ecological theory, providing a roadmap to engineer microbiome resilience against process failures.
