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Citizen science powers wetland restoration 公民科学助力湿地恢复
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2026.100656
Shihao Cui , Haonan Guo , Lorenzo Pugliese , Gitte Kragh , Sonia Mena , Shubiao Wu
Wetlands provide essential ecosystem services, from carbon sequestration and flood mitigation to biodiversity support, yet over 20 % have been lost in recent centuries, prompting global restoration efforts backed by policies like the UN Decade on Ecosystem Restoration. Despite rapid expansion of restoration projects, conventional monitoring remains short-term, expert-driven, and often disconnected from site-specific ecological dynamics, limiting adaptive management and long-term success. Citizen science has revolutionized ecological monitoring in other domains by enabling scalable, participatory data collection, but its application to wetland restoration has been largely overlooked. In this Perspective, we assess 120 restoration project sites worldwide and find that citizen science is currently integrated into fewer than 20 % of projects even in high-activity regions like Europe, leaving significant social and geographic potential untapped. We find that recent advances in affordable remote sensing, miniaturized sensors, and mobile platforms—supported by rigorous data-validation frameworks—are now overcoming historical constraints regarding data reliability and spatial continuity. These technological shifts, when coupled with emerging institutional recognition, allow citizen-generated data to serve as a scalable, cost-effective infrastructure for monitoring ecological change over meaningful timescales. Systematically integrating public participation into restoration practice is therefore essential for closing critical monitoring gaps and ensuring the long-term sustainability of global wetland ecosystems.
湿地提供了重要的生态系统服务,从碳封存和洪水缓解到生物多样性支持,但近几个世纪以来,湿地已经损失了20%以上,这促使全球在联合国生态系统恢复十年等政策的支持下进行恢复工作。尽管恢复项目迅速扩大,但传统的监测仍然是短期的、专家驱动的,往往与特定地点的生态动态脱节,限制了适应性管理和长期成功。公民科学通过实现可扩展的、参与式的数据收集,已经彻底改变了其他领域的生态监测,但它在湿地恢复中的应用在很大程度上被忽视了。从这个角度来看,我们评估了全球120个修复项目地点,发现即使在像欧洲这样的高活动地区,公民科学目前也只有不到20%的项目被纳入,留下了巨大的社会和地理潜力尚未开发。我们发现,在经济实惠的遥感、小型化传感器和移动平台方面的最新进展——由严格的数据验证框架支持——正在克服有关数据可靠性和空间连续性的历史限制。这些技术转变,再加上新兴的制度认可,使公民产生的数据成为一种可扩展的、具有成本效益的基础设施,用于在有意义的时间尺度上监测生态变化。因此,将公众参与系统地纳入恢复实践对于缩小关键的监测差距和确保全球湿地生态系统的长期可持续性至关重要。
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引用次数: 0
Ultrahigh-resolution 3D monitoring reveals sediment-derived plumes as algal bloom precursors 超高分辨率3D监测显示,沉积物衍生的羽流是藻华的前兆
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2025.100652
Peng Xiao , Congchao Zhang , Yu Tao , Tiefu Xu , Ying Chen , Lian Feng , Lingchao Kong , Zhidan Wen , Weibin Zheng , Hao Xu , Longxin Guo , Hangyu Guo , Zheng Pang , Zhiling Li , Chuan He , Shujie Xu , Kaishan Song , Jie Feng , Zhugen Yang , Shu-Chien Hsu , Nanqi Ren
The global intensification of harmful algal blooms severely compromises freshwater ecosystems, threatening biodiversity and critical ecosystem services through toxin exposure, hypoxia, and water quality degradation. Bloom formation involves a complex interplay of nutrient dynamics, hydrology, and microbial activity. Although subsurface processes—such as the release of sediment-bound nutrients and the germination of dormant cyanobacteria—are thought crucial to bloom initiation, these phenomena occur at fine spatiotemporal scales beyond the reach of conventional monitoring. As a result, the exact, rapidly evolving triggers of bloom emergence remain mostly unknown. Here we show meter-scale chlorophyll a (Chl-a) plumes rising from the sediment–water interface, triggered by heavy rainfall and directly seeding surface blooms. We captured these dynamics using a custom underwater drone that collected over 2.8 million data points at 5-m horizontal and 1-m vertical resolution. Algal blooms exhibit a clear vertical sequence: anomalous Chl-a levels first appear in deep benthic layers after rainfall-driven resuspension, then intensify simultaneously across near-bed depths, and finally reach the surface after a median lag of 0.8–1.5 days. These observations provide in situ evidence associating benthic algal seed stocks with surface bloom initiation, revealing that the origin and spatial heterogeneity of such events arise from rainfall-driven disturbances at the sediment–water interface. This robotic approach not only deciphers the subsurface origins of algal blooms but also empowers predictive modeling and adaptive management strategies, advancing global efforts to combat eutrophication amid escalating climate pressures and safeguard vital water resources.
有害藻华的全球加剧严重损害了淡水生态系统,通过毒素暴露、缺氧和水质退化威胁生物多样性和关键的生态系统服务。水华的形成涉及营养动态、水文和微生物活动的复杂相互作用。虽然地下过程——如沉积物结合的养分的释放和休眠蓝藻的萌发——被认为对水华的开始至关重要,但这些现象发生在精细的时空尺度上,超出了传统监测的范围。因此,确切的、快速进化的水华出现的触发因素在很大程度上仍然未知。在这里,我们展示了米尺度的叶绿素a (Chl-a)羽流从沉积物-水界面上升,由强降雨和直接种子表面华花引发。我们使用定制的水下无人机捕获了这些动态,该无人机以5米水平和1米垂直分辨率收集了超过280万个数据点。藻华表现出明显的垂直序列:在降雨驱动的再悬浮后,异常的Chl-a水平首先出现在深底栖层,然后在近河床深度同时加剧,最后在0.8-1.5天的中位滞后后到达地表。这些观测结果提供了将底栖藻类种子库与地表水华发生联系起来的原位证据,揭示了这类事件的起源和空间异质性源于降雨驱动的沉积物-水界面扰动。这种机器人方法不仅可以破译藻华的地下起源,还可以增强预测建模和适应性管理策略,在气候压力不断上升的情况下推进全球对抗富营养化的努力,并保护重要的水资源。
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引用次数: 0
Ephedrine-disrupted synaptogenesis signaling and behavioral abnormalities in adult zebrafish 麻黄碱破坏成年斑马鱼突触发生信号和行为异常
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2026.100661
Yanghui Deng , Xingxing Yin , Changsheng Guo , Wenhui Qiu , Meng Zhang , Xu Tan , Jian Xu
Ephedrine is a prevalent sympathomimetic alkaloid and amphetamine-type stimulant precursor that has become a widespread contaminant in global aquatic ecosystems. While the neurotoxic effects of high-dose ephedrine exposure are documented in humans and other mammals, its impact on aquatic vertebrates at environmentally realistic concentrations remains poorly understood. Determining how these persistent residues affect neural development and physiological homeostasis is critical for evaluating ecological risks to aquatic life. Here we show that chronic, low-dose ephedrine exposure impairs neurodevelopment in adult zebrafish by simultaneously disrupting synaptogenesis architecture and neurotransmitter balance. Integrated transcriptomic and histopathological analyses reveal that ephedrine targets the synaptogenesis signaling pathway, resulting in reduced presynaptic vesicles and structural abnormalities in the postsynaptic density. Computational docking and biochemical assays further demonstrate that ephedrine engages the vesicular acetylcholine transporter and tyrosine hydroxylase with high affinity, triggering excitotoxic cascades and biphasic neurochemical dysregulation that manifest as anxiety-like phenotypes and cognitive impairments. These findings indicate that environmentally relevant concentrations of stimulant precursors pose a significant threat to the neural circuit integrity of aquatic species, necessitating urgent regulatory attention to pharmaceutical residues in surface waters.
麻黄碱是一种普遍存在的拟交感生物碱和苯丙胺类兴奋剂前体,已成为全球水生生态系统中广泛存在的污染物。虽然高剂量麻黄碱暴露对人类和其他哺乳动物的神经毒性作用有文献记载,但其对水生脊椎动物在环境实际浓度下的影响仍知之甚少。确定这些持久性残留物如何影响神经发育和生理稳态对于评估水生生物的生态风险至关重要。本研究表明,慢性低剂量麻黄碱暴露会同时破坏突触发生结构和神经递质平衡,从而损害成年斑马鱼的神经发育。综合转录组学和组织病理学分析表明,麻黄碱靶向突触发生信号通路,导致突触前囊泡减少和突触后密度结构异常。计算对接和生化分析进一步表明,麻黄碱与囊泡乙酰胆碱转运体和酪氨酸羟化酶具有高亲和力,引发兴奋毒性级联反应和双相神经化学失调,表现为焦虑样表型和认知障碍。这些发现表明,环境相关浓度的兴奋剂前体对水生物种的神经回路完整性构成重大威胁,迫切需要对地表水中的药物残留进行监管。
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引用次数: 0
Construction activities drive half of China's ambient PM2.5 health burden 建筑活动造成了中国一半的环境PM2.5健康负担
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2026.100666
Zhanxiang Wang , Huizhong Shen , Ruixin Zhang , Ruibin Xu , Peng Guo , Zhiyu Zheng , Jinling He , Siqi Wu , Yilin Chen , Dong Xie , Jinjian Zhang , Lianming Zheng , Hang Su , Dabo Guan
Construction activities generate substantial air pollutants and greenhouse gas emissions, contributing heavily to ambient PM2.5 exposure and associated mortality worldwide. In China, rapid urbanization has driven a massive expansion of the construction sector, with emissions arising from building material production, onsite operations, upstream supply chains, and operational energy use in buildings. Although end-of-pipe controls have markedly lowered pollutant emissions since 2013, further reductions are increasingly costly, and air quality and climate policies remain poorly integrated. The full lifecycle health burden imposed by construction-related air pollution, its temporal evolution, and the scope for health co-benefits from decarbonization—particularly across urban and rural divides—have been incompletely characterized. Here we integrate a detailed construction emission inventory, input–output analysis, inverse atmospheric modelling, and health impact assessment to quantify these impacts in China from 2000 to 2019. We show that construction-related emissions, including upstream power and industrial sources, caused 1.10 million (95% CI: 0.83–1.37 million) premature deaths in 2019, accounting for 50% (95% CI: 38–62%) of national ambient PM2.5-attributed mortality. Health burdens evolved through three phases: rapid increase with 130% CO2 growth during intense urbanization (2000–2008), decoupling via pollution controls that averted 0.36 million deaths despite rising CO2 (2008–2015), and synergistic declines from energy-mix optimization and technology upgrades (2015–2019). Urban mortality stems predominantly from upstream industrial emissions, whereas rural mortality is driven by residential heating; decarbonizing power and heavy industry offers the largest urban co-benefits, while rural clean-electricity heating requires concurrent power-sector greening to prevent CO2 penalties. These results position the construction sector as a pivotal target for integrated policies that jointly advance air quality, public health, and climate objectives.
建筑活动产生大量的空气污染物和温室气体排放,在很大程度上导致了全球环境PM2.5暴露和相关死亡率。在中国,快速的城市化推动了建筑行业的大规模扩张,建筑材料生产、现场运营、上游供应链和建筑运营能源使用都产生了排放。尽管自2013年以来,终端控制措施显著降低了污染物排放,但进一步减排的成本越来越高,而且空气质量和气候政策仍然缺乏整合。与建筑有关的空气污染所造成的全生命周期健康负担、其时间演变以及脱碳(特别是跨越城市和农村的差异)对健康共同利益的范围尚未完全表征。在此,我们整合了详细的建筑排放清单、投入产出分析、反演大气模型和健康影响评估,以量化2000年至2019年中国的这些影响。研究表明,2019年,与建筑相关的排放,包括上游电力和工业源,导致110万人(95% CI: 0.83 - 137万)过早死亡,占全国环境pm2.5致死人数的50% (95% CI: 38-62%)。健康负担的演变经历了三个阶段:在剧烈城市化期间迅速增加,二氧化碳增长130%(2000-2008年);通过污染控制实现脱钩,尽管二氧化碳增加,但避免了36万人死亡(2008-2015年);以及能源结构优化和技术升级带来的协同下降(2015-2019年)。城市死亡率主要来自上游工业排放,而农村死亡率则由住宅供暖驱动;脱碳的电力和重工业为城市带来了最大的协同效益,而农村的清洁电力供暖需要同步的电力部门绿化,以防止二氧化碳的惩罚。这些结果将建筑行业定位为联合推进空气质量、公共卫生和气候目标的综合政策的关键目标。
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引用次数: 0
Selective eradication of pathogenic bacteria using amine-modified corn-straw carbon dots 胺修饰玉米秸秆碳点选择性根除致病菌
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2025.100651
Pengzhao Lv , Yu Jiang , Jialin Wang , Yige Shi , Zhengda Lin , Duo Wei , Wei Zuo , Jun Zhang
The rise of antimicrobial resistance and the ecological harm inflicted by broad-spectrum disinfectants underscore the urgent need for species-specific strategies that eradicate pathogenic bacteria without disrupting beneficial microbial communities. Staphylococcus aureus thrives in diverse aquatic environments across wide temperature ranges, posing persistent risks to human health and exacerbating resistance challenges, yet existing agents lack the precision to target this pathogen selectively. Here we show that triethylenetetramine-functionalized carbon dots, derived from corn straw biomass via one-step hydrothermal synthesis, exhibit intrinsic oxidase-like activity that selectively eliminates S. aureus. These nanomaterials achieve complete bactericidal efficacy (100 %) against S. aureus at 50 μg mL−1 within 1 h at 37 °C, retaining robust activity (80 %) even at 4 °C, through synergistic preferential binding to cell-wall polysaccharides—facilitated by retained biomass cellulose moieties—combined with membrane disruption and generation of superoxide radicals (·O2) and singlet oxygen (1O2). This selectivity spares Bacillus subtilis and Gram-negative species such as Escherichia coli and Pseudomonas aeruginosa, owing to differences in cell-wall architecture and reduced affinity. Amine chain length tunes the oxidase-mimicking potency, enabling oxygen-dependent reactive oxygen species production without external stimuli. By upcycling abundant agricultural waste into rapidly photodegradable (within 11 days under visible light) precision disinfectants, this approach provides a sustainable way for ecologically compatible pathogen control, advancing rational design principles for next-generation nano-antimicrobials.
抗菌素耐药性的上升和广谱消毒剂造成的生态危害突出表明,迫切需要采取针对特定物种的策略,在不破坏有益微生物群落的情况下根除致病菌。金黄色葡萄球菌在各种温度范围的水生环境中茁壮成长,对人类健康构成持续风险并加剧耐药性挑战,但现有药物缺乏选择性靶向这种病原体的精确性。本研究表明,通过一步水热合成从玉米秸秆生物质中提取的三乙基四胺功能化碳点具有内在的类似氧化酶的活性,可以选择性地消除金黄色葡萄球菌。在37℃下,这些纳米材料在1小时内对金黄色葡萄球菌达到50 μg mL−1的完全杀菌效果(100%),即使在4℃下也能保持强大的活性(80%),这是通过与细胞壁多糖的协同优先结合-由保留的生物质纤维素部分促进-结合膜破坏和产生超氧自由基(·O2−)和单线态氧(1O2)。由于细胞壁结构的差异和亲和力的降低,枯草芽孢杆菌和革兰氏阴性菌如大肠杆菌和铜绿假单胞菌没有这种选择性。胺链长度调节氧化酶模拟的效力,使氧依赖的活性氧产生没有外部刺激。通过将大量农业废弃物升级为可快速光降解(在可见光下11天内)的精密消毒剂,该方法为生态相容的病原体控制提供了一种可持续的途径,推进了下一代纳米抗菌剂的合理设计原则。
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引用次数: 0
Beyond carbon sequestration: The critical oversight of emission avoidance in restoration of wetland ecosystems 超越碳固存:湿地生态系统恢复中碳排放避免的关键监督
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2026.100658
Shubiao Wu, Rebekka R.E. Artz, Alexandra Barthelmes, Shihao Cui, Diana Vigah Adetsu, Vera Eory, Mark S. Reed, Florian Humpenöder, Tom S. Heuts, Christian Fritz, Agata Klimkowska, Annalea Lohila
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引用次数: 0
Machine learning vs. ADM1: Reliable biogas prediction with minimal data requirements in full-scale plants 机器学习与ADM1:在全规模工厂中以最小的数据需求进行可靠的沼气预测
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2026-01-01 DOI: 10.1016/j.ese.2026.100662
Sofia Tisocco , Sören Weinrich , Henrik Bjarne Møller , Alastair James Ward , Liam Kilmartin , Xinmin Zhan , Paul Crosson
Anaerobic digestion harnesses microbial processes to convert organic wastes into renewable biogas, offering a sustainable pathway for energy production. In agricultural settings, biogas plants often co-digest livestock manure with crop residues, yet seasonal variations in feedstock quality introduce fluctuations that challenge process stability and yield optimization. Mechanistic models such as the Anaerobic Digestion Model No. 1 (ADM1) provide detailed biochemical simulations but require extensive substrate characterization, limiting their practicality for full-scale operations. Here we show that a simplified ADM1, alongside machine learning approaches—random forest and long short-term memory (LSTM) networks—achieves comparable accuracy in predicting daily biogas and methane production from a full-scale plant over 2023–2024. All models yielded Nash-Sutcliffe efficiencies above 0.78, with random forest excelling when incorporating feedstock quantities and maize silage volatile solids. While LSTM proved effective even with minimal inputs, it incurred a training time 141 times greater than ADM1, highlighting critical trade-offs in computational efficiency. These findings advance hybrid modelling strategies for real-time monitoring, enabling operators to balance predictive precision with data requirements to enhance renewable energy integration and agricultural sustainability.
厌氧消化利用微生物过程将有机废物转化为可再生沼气,为能源生产提供了可持续的途径。在农业环境中,沼气厂通常与作物残茬共同消化牲畜粪便,但原料质量的季节性变化会带来波动,从而挑战工艺稳定性和产量优化。机械模型如厌氧消化模型1 (ADM1)提供了详细的生化模拟,但需要广泛的底物表征,限制了其全面操作的实用性。在这里,我们展示了一个简化的ADM1,以及机器学习方法——随机森林和长短期记忆(LSTM)网络——在预测2023-2024年期间全规模工厂的每日沼气和甲烷产量方面达到了相当的准确性。所有模型的Nash-Sutcliffe效率均高于0.78,其中随机森林模型在考虑原料数量和玉米青贮挥发性固体时表现优异。尽管LSTM证明即使输入最小也有效,但它的训练时间是ADM1的141倍,突出了计算效率的关键权衡。这些发现推动了实时监测的混合建模策略,使运营商能够平衡预测精度和数据需求,从而提高可再生能源的整合和农业的可持续性。
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引用次数: 0
Chaperone-mediated thermotolerance in hyperthermophilic composting: Molecular-Level protein remodeling of microbial communities 在超嗜热堆肥中伴侣介导的耐热性:微生物群落的分子水平蛋白质重塑
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2025-11-01 DOI: 10.1016/j.ese.2025.100630
Xu Li , Youzhao Wang , Feng Ma , Chaoyue Zhao , Yanping Zhang , Yaonan Zhu , Yang Zhang , Shujie Hou , Bingzhen Li , Fuxin Yang , Liying Hao , Tong Zhu
Hyperthermophilic composting (HC) represents a promising approach for converting organic solid waste into valuable resources by leveraging extreme temperatures to enhance microbial degradation and detoxification processes. In this high-temperature environment, microbial communities undergo dynamic succession, where thermophilic bacteria dominate and drive efficient organic matter transformation through adapted metabolic pathways and stress responses. These adaptations include the stabilization of cellular structures and enzymes, often mediated by heat shock proteins (HSPs) that prevent protein misfolding under thermal stress. However, the integrated mechanisms linking community-level functional shifts to molecular-level protein remodeling in thermophiles during HC remain poorly understood. Here we show a coordinated interaction of functional succession and molecular adaptations within thermophilic bacteria in HC, which collectively achieve heat resistance. This interaction encompasses enhanced metabolic and genetic modules, accounting for 97 % of the variance observed in thermophile abundance. Metagenomic analyses revealed upregulation of translation, transcription, amino acid metabolism, and cell wall biosynthesis, coupled with suppression of mobilome functions to maintain genomic stability, as confirmed by partial least squares path modeling and Boruta analyses. Molecular dynamics simulations of key enzymes from the thermophile Truepera further demonstrated intrinsic structural rigidity, reduced hydrophobic exposure, and hierarchical chaperone activity involving DNAJ, DNAK, and GroEL for protein repair. These findings enhance our comprehension of microbial thermotolerance and establish a foundation for optimizing composting efficiency and advancing heat-resistant microbial applications in biotechnology and waste management. Additionally, they offer insights into the evolution of thermophiles, protein engineering, and stress adaptation across various biological and industrial systems, thereby promoting the integration of environmental engineering and systems biology.
超嗜热堆肥(HC)是一种很有前途的方法,通过利用极端温度来增强微生物降解和解毒过程,将有机固体废物转化为有价值的资源。在这种高温环境中,微生物群落经历了动态演替,其中嗜热细菌占主导地位,并通过适应的代谢途径和应激反应驱动有效的有机质转化。这些适应性包括细胞结构和酶的稳定,通常由热休克蛋白(HSPs)介导,以防止蛋白质在热应激下错误折叠。然而,在HC过程中,将嗜热菌群落水平的功能转变与分子水平的蛋白质重塑联系起来的综合机制仍然知之甚少。在这里,我们展示了HC中嗜热细菌的功能演替和分子适应的协调相互作用,它们共同实现了耐热性。这种相互作用包括增强的代谢和遗传模块,占观察到的嗜热菌丰度方差的97%。宏基因组分析揭示了翻译、转录、氨基酸代谢和细胞壁生物合成的上调,以及对移动组功能的抑制,以维持基因组的稳定性,这一点得到了偏最小二乘路径模型和Boruta分析的证实。来自嗜热菌Truepera的关键酶的分子动力学模拟进一步证明了内在的结构刚性,减少了疏水暴露,以及涉及DNAJ, DNAK和GroEL的分层伴侣活性,用于蛋白质修复。这些发现增强了我们对微生物耐热性的理解,为优化堆肥效率和推进耐热微生物在生物技术和废物管理中的应用奠定了基础。此外,他们还提供了对各种生物和工业系统中嗜热菌,蛋白质工程和压力适应的进化的见解,从而促进了环境工程和系统生物学的整合。
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引用次数: 0
A hierarchical transformer and graph neural network model for high-accuracy watershed nitrate prediction 一种用于流域硝酸盐高精度预测的分层变压器和图神经网络模型
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2025-11-01 DOI: 10.1016/j.ese.2025.100632
Jun Sun , Xuesong Gao , Zhiyong Deng , Yudong Zhao , Qi Wang , Xiyi Zhao , Xu Liu
Non-point source pollution from agricultural activities poses a significant threat to water quality by introducing excess nutrients like nitrogen into aquatic ecosystems, leading to issues such as eutrophication and groundwater contamination. In agricultural watersheds, nitrate transport involves intricate physical, chemical, and biological processes influenced by meteorological conditions, hydrological features, and spatial topologies, making accurate short-term predictions challenging. Traditional data-driven deep learning models often fail to incorporate physical constraints and complex spatiotemporal dynamics, limiting their interpretability and predictive accuracy. Here we show a hierarchical transformer and graph neural network model that accurately predicts watershed nitrate concentrations by integrating multi-source data and simulating pollutant migration. The model captures nonlinear multivariate temporal patterns through hierarchical transformers, fuses global meteorological and local hydrological features via neural networks, and models runoff topologies with physically constrained graph neural networks. For predicting the concentration changes of pollutants discharged from watersheds, it outperforms baselines like multi-layer perceptrons, recurrent neural networks, and long short-term memory networks, with state-of-the-art performance in root mean square error, mean absolute error, and R2. Ablation studies confirm the essential roles of multi-source data integration and watershed topological modeling in enhancing performance. This method of directly modeling physical processes by leveraging the characteristics of different neural network architectures opens up a new path for addressing the interpretability problem in neural earth system modeling, apart from the process-guided deep learning and differentiable modelling methods.
农业活动产生的非点源污染通过向水生生态系统引入过量的氮等营养物质,导致富营养化和地下水污染等问题,对水质构成重大威胁。在农业流域,硝酸盐的运输涉及复杂的物理、化学和生物过程,受气象条件、水文特征和空间拓扑的影响,这使得准确的短期预测具有挑战性。传统的数据驱动深度学习模型往往无法纳入物理约束和复杂的时空动态,从而限制了其可解释性和预测准确性。在这里,我们展示了一个分层变压器和图形神经网络模型,该模型通过集成多源数据和模拟污染物迁移来准确预测流域硝酸盐浓度。该模型通过分层变换捕获非线性多元时间模式,通过神经网络融合全球气象和当地水文特征,并使用物理约束图神经网络模拟径流拓扑。对于预测流域排放污染物的浓度变化,它优于多层感知器、循环神经网络和长短期记忆网络等基线,在均方根误差、平均绝对误差和R2方面具有最先进的性能。消融研究证实了多源数据集成和流域拓扑建模在提高性能方面的重要作用。这种利用不同神经网络架构的特点直接建模物理过程的方法,为解决神经地球系统建模中的可解释性问题开辟了一条新的途径,除了过程导向的深度学习和可微建模方法。
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引用次数: 0
Microbial protein-derived bioplastics from renewable substrates: pathways, challenges, and applications in a circular economy 可再生基质微生物蛋白衍生的生物塑料:途径、挑战和在循环经济中的应用
IF 14.3 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2025-11-01 DOI: 10.1016/j.ese.2025.100635
Myrsini Sakarika , Joost Brancart , Shreyash Anil Gujar , Steven De Meester , Luis Diaz Allegue , Leen Bastiaens , Peter Ragaert , Siegfried E. Vlaeminck , Heleen De Wever , Korneel Rabaey
Microbial protein (MP)—the protein-rich biomass derived from recovered or virgin resources—is attracting interest as a source of food and feed. However, its potential as a feedstock for protein-based bioplastics remains underexplored. Proteins offer desirable properties, including superior oxygen-barrier capabilities and complete biodegradability, making them ideal for applications from food packaging to agricultural mulches. Currently, most protein-based bioplastics derive from crops such as wheat, restricting applications and competing with food production. MP can overcome these limitations by supplying diverse proteins from various inputs, including CO2, biomass, and liquid side-streams. In this review, we evaluate bioprocessing pathways for producing MP from renewable and waste-derived substrates from an interdisciplinary viewpoint. We also examine the technical, regulatory, market, and environmental factors to address, delineating the pathway from substrate to MP-based plastics and highlighting key challenges throughout the production chain. Novel strategies—such as efficient co-recovery of proteins with other cellular products like polyhydroxyalkanoates or direct use of microbial biomass without extraction—are essential to maximize environmental and economic sustainability. Carefully chosen processing methods for recovered proteins, including wet and dry blending or extrusion with other biopolymers, can yield diverse products. Concurrently, policy and market developments are vital for adopting MP-based bioplastics. Addressing these challenges will enable MP-based bioplastics to propel the shift toward a circular economy, diminishing dependence on fossil-derived plastics and alleviating plastic pollution.
微生物蛋白(MP)是一种从回收或原始资源中提取的富含蛋白质的生物质,作为一种食物和饲料来源正引起人们的兴趣。然而,它作为蛋白质基生物塑料原料的潜力仍未得到充分开发。蛋白质具有理想的特性,包括卓越的阻氧能力和完全的生物降解性,使其成为从食品包装到农业覆盖物应用的理想选择。目前,大多数基于蛋白质的生物塑料来自小麦等作物,这限制了应用并与粮食生产竞争。MP可以通过从不同的输入(包括二氧化碳、生物质和液体侧流)中提供不同的蛋白质来克服这些限制。在这篇综述中,我们从跨学科的角度评估了从可再生和废物来源的基质生产MP的生物加工途径。我们还研究了需要解决的技术、监管、市场和环境因素,描绘了从基材到mp基塑料的途径,并强调了整个生产链中的关键挑战。新的策略——如与其他细胞产物如聚羟基烷酸酯有效地共同回收蛋白质或直接利用微生物生物量而不进行提取——对于最大限度地提高环境和经济的可持续性至关重要。精心选择的加工方法回收的蛋白质,包括湿和干混合或挤压与其他生物聚合物,可以产生不同的产品。同时,政策和市场发展对于采用mp基生物塑料至关重要。解决这些挑战将使基于mp的生物塑料能够推动向循环经济的转变,减少对化石衍生塑料的依赖并减轻塑料污染。
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Environmental Science and Ecotechnology
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