地球科学最新文献

{"title":"Finite-strain modelling of PVD-assisted consolidation in clayey soils using a novel elastic–viscoplastic model with destructuration based on the equivalent time concept","authors":"Peng-Lin Li ,&nbsp;Zhen-Yu Yin ,&nbsp;Ze-Jian Chen ,&nbsp;Jian-Hua Yin","doi":"10.1016/j.geotexmem.2026.01.008","DOIUrl":"10.1016/j.geotexmem.2026.01.008","url":null,"abstract":"<div><div>Prefabricated vertical drains (PVDs) are widely adopted to accelerate the consolidation of clayey soils. However, long-term settlement during the service period of infrastructure is often not adequately captured when soil structure degradation and creep are neglected. Existing models rarely consider the coupled effects of soil destructuration, creep, and nonlinear water flow in PVD-assisted consolidation. This study develops an axisymmetric finite-strain consolidation model incorporating an elastic–viscoplastic model with structuration (EVPS) based on the equivalent time concept. The formulation is applicable to clays possessing inherent structure that may undergo structure degradation under mechanical loading or PVD installation. The model considers soil creep, destructuration, smear effects, and nonlinear water flow, and is solved using an alternating direction implicit (ADI) finite-difference scheme. Finite-element comparisons are employed solely to verify the numerical implementation of the consolidation equations. Model performance is evaluated through comparisons with laboratory oedometer tests on natural structured clays and long-term field observations from the Haarajoki embankment. The results indicate that the proposed model can consistently reproduce pore-pressure dissipation and settlement evolution, including deformation occurring after primary consolidation over periods of several years to decades. Parametric studies reveal that soil destructuration, smear effect, and non-Darcian flow jointly govern the consolidation process. The proposed model enables more reliable prediction of consolidation behaviour in natural structured clays, which is essential for assessing long-term settlement and supporting rational design of ground improvement schedules.</div></div>","PeriodicalId":55096,"journal":{"name":"Geotextiles and Geomembranes","volume":"54 3","pages":"Pages 460-481"},"PeriodicalIF":6.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shifting baselines alter trends and emergence of climate extremes across Africa","authors":"Thierry N. Taguela,&nbsp;Akintomide A. Akinsanola","doi":"10.1016/j.atmosres.2026.108839","DOIUrl":"10.1016/j.atmosres.2026.108839","url":null,"abstract":"<div><div>World Meteorological Organization baselines used to identify climate extremes are routinely updated to reflect recent climate conditions. Yet the implications of these updates for the characterization, trends, and detectability of climate extremes remain poorly understood, particularly in data-sparse and highly vulnerable regions such as Africa. Here, we quantify how updating the reference period from 1981–2010 to 1991–2020 systematically alters the characterization of temperature and precipitation extremes across the continent. Using multiple observational and reanalysis datasets (BEST, ERA5, MERRA-2, CHIRPS), we assess the sensitivity of percentile-based thresholds, long-term trends, and the Time of Emergence (ToE) to changes in the reference period. ToE is employed here as a diagnostic of detectability rather than a definitive marker of anthropogenic signal onset. Our results show that the updated baseline leads to higher temperature thresholds, resulting in a reduced frequency and slower trends for warm extremes (TX90p, TN90p), and a concurrent increase in cold extremes (TX10p, TN10p). Precipitation extremes exhibit more heterogeneous and dataset-dependent responses: trends in extreme precipitation totals (R95pTOT, R99pTOT) generally weaken, whereas intensity-based metrics (R95pINT, R99pINT) often strengthen, particularly in MERRA-2. Moreover, the choice of baseline strongly influences the estimated ToE. Warm extremes emerge 2–8 years later under the newer baseline, while cold extremes emerge earlier (by up to 15 years) due to enhanced signal-to-noise ratios. For precipitation, ToE responses vary widely across datasets and regions. In CHIRPS, the ToE of intense rainfall events is delayed, whereas in MERRA-2 it advances by over 2 decades in some regions. These results indicate that ToE estimates derived from recent decades are highly sensitive to baseline selection. By explicitly isolating the effect of baseline choice, this study provides a critical framework for interpreting extremes, reconciling dataset discrepancies, and improving the robustness of climate monitoring and risk communication across Africa.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"336 ","pages":"Article 108839"},"PeriodicalIF":4.4,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heavy metals in food: mechanisms of toxicity and migration through various routes in different foods","authors":"Md Faruque Ahmad ,&nbsp;Fakhruddin Ali Ahmad ,&nbsp;Md. Zeyaullah ,&nbsp;Farkad Bantun ,&nbsp;Ahmad O. Babalghith ,&nbsp;Mazen M. Ghaith ,&nbsp;Yousef Zahrani ,&nbsp;Hytham Hummad ,&nbsp;Boshra Mozaffar ,&nbsp;Mohammad Firoz Alam ,&nbsp;Abdullah Y. Otayf","doi":"10.1016/j.gr.2025.12.021","DOIUrl":"10.1016/j.gr.2025.12.021","url":null,"abstract":"<div><div>Heavy metals consist of a variety of elements, including lead, mercury, cadmium, arsenic, and chromium, among others. Industrial operations, packaging, mining, agricultural practices, and waste discharges are all examples of anthropogenic activities that contribute to the production of persistent environmental pollutants. These pollutants originate from natural causes, such as volcanic eruptions and rock weathering, as well as from anthropogenic activity. These metals infiltrate ecosystems, contaminating water, soil, and air, subsequently entering the food chain through consumption by animals and plants. The primary dietary sources of heavy metal exposure consist of contaminated vegetables, fruits, cereals, fish, and shellfish. Metals accumulate in these foods, and posing substantial risks to human health. Heavy metals present in foods produce toxicities through various mechanisms that include generation of reactive oxygen species (ROS), disruption of cellular processes, oxidative stress, protein and enzyme inactivation, and DNA damage and genomic instability, leading to organ impairment, cancer, reproductive disorders, cardiac disorders, and endocrine disruption. Study highlighting the serious need for regulation, monitoring, and remediation approaches to minimise the threat of heavy metals across the world.</div></div>","PeriodicalId":12761,"journal":{"name":"Gondwana Research","volume":"154 ","pages":"Pages 258-273"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-frequency street-level urban noise modeling and mapping through street view and remote sensing image fusion","authors":"Yan Zhang ,&nbsp;Entong Ke ,&nbsp;Mei-Po Kwan ,&nbsp;Libo Fang ,&nbsp;Mingxiao Li","doi":"10.1016/j.compenvurbsys.2026.102401","DOIUrl":"10.1016/j.compenvurbsys.2026.102401","url":null,"abstract":"<div><div>Urban noise pollution has become the third most significant environmental health threat following air and water pollution, while traditional noise modeling methods suffer from limitations including high costs, limited coverage, and an exclusive focus on total decibel values while neglecting frequency characteristics. This study proposes a method that combines street view imagery (SVI) and remote sensing imagery (RSI) to achieve precise modeling and mapping of multi-frequency noise exposure at the urban street scale. Using Xiangzhou District, Zhuhai City as a case study, we utilized approximately 6000 street view images and corresponding remote sensing images, and recorded 35,276 street noise audios containing 23 frequency bands (100 Hz-16,000 Hz) through volunteer cycling surveys. A multi-source fusion model was constructed based on a pre-trained vision transformer architecture, with 923 valid street noise-image paired samples used for training and validation. The sensitivity results demonstrate that: (1) the proposed multimodal fusion model achieves high predictive accuracy, with R² values for dBA prediction ranging from 0.417 to 0.649, with particularly higher accuracy observed for mid-frequency noise prediction; (2) 50-m resolution street-scale multi-frequency soundscape maps were successfully generated, providing scientific evidence for refined urban noise management; (3) explainable machine learning models revealed that buildings, roads, sidewalks, and terrain visual elements are the four most important factors affecting noise prediction, with road width showing a positive association with street noise levels. This study not only fills the gap in urban noise frequency characteristics research but also provides new methodological support for precise street-level noise pollution modeling and health-oriented urban planning. The source code is available at <span><span>https://github.com/giserzy/NoisePrediction</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"126 ","pages":"Article 102401"},"PeriodicalIF":8.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating remote sensing and machine learning for flood modelling: A systematic literature review","authors":"Naledi Manyaka ,&nbsp;Cletah Shoko ,&nbsp;Siyamthanda Gxokwe ,&nbsp;Timothy Dube","doi":"10.1016/j.pce.2026.104315","DOIUrl":"10.1016/j.pce.2026.104315","url":null,"abstract":"<div><div>This paper provides a systematic review that synthesizes recent advancements in the integration of machine learning (ML) and remote sensing techniques for flood modelling in developing regions between 2010 and 2025. To achieve the main objective the study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) to search for articles in key databases such as Google Scholar, Web of Science and Science Direct. A total of 50197 articles were obtained and screened based on specific set criterion and a total of 126 articles were obtained after screening and were used in this study. These articles were then subjected to bibliometric analysis which revealed an exponential growth in the number of articles obtained with a sharp rise in publications post-2018. Further analysis revealed that most studies concentrated in South and East Asia, highlighting regional bias and underrepresentation of data-scarce areas such as Africa and Latin America. The results further indicated a widespread increase in the use of freely available remote sensing data (e.g., Sentinel-1/2, Landsat, MODIS) which was driven by accessibility and resolution advantages, while advanced but cost-prohibitive platforms (e.g., RADARSAT, UAVs) remain underutilized. Comparative analysis of model performance showed that traditional hydrological and hydraulic models remain relevant but often suffer from oversimplification and high data and computational demands. In contrast, ML models like CNNs, RF, and SVM demonstrated robust performance with AUC values frequently exceeding 0.90. However, the lack of consistent benchmarking, standardized evaluation metrics, and open-source codebases limits model comparability and reproducibility across studies. Furthermore, most reviewed studies overlook uncertainty quantification, compound event interactions, and tail dependence. To address these gaps, the review recommends integrating uncertainty-aware techniques such as Bayesian deep learning (e.g., MC-Dropout) and copula-based bivariate extreme value models. Moreover, emphasis should be placed on the ethical deployment of ML in flood-prone regions, advocating for transparency in model assumptions, fairness assessments, and participatory model design. Future research should prioritize scalable, interpretable, and equitable modelling approaches, particularly in underrepresented and high-risk regions.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"143 ","pages":"Article 104315"},"PeriodicalIF":4.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of watershed management on water balance components-a review","authors":"Saeedreza Moazeni ,&nbsp;Ali Salajegheh ,&nbsp;Shahram Khalighi-Sigaroodi ,&nbsp;Ali Golkarian ,&nbsp;Artemi Cerda","doi":"10.1016/j.pce.2026.104277","DOIUrl":"10.1016/j.pce.2026.104277","url":null,"abstract":"<div><div>Watersheds serve as fundamental units of hydrological systems, playing a crucial role in freshwater supply, biodiversity conservation, and ecosystem sustainability. This study conducts a bibliometric and qualitative analysis of global research (1979–2024) to evaluate the effectiveness of watershed management interventions on key water-balance components, including runoff, infiltration, evapotranspiration, and groundwater recharge. Findings indicate a significant increase in publications, particularly after 2011. We used VOSviewer and Bibliometrix to map publication trends, co-occurrence and co-citation networks, leading authors and journals, and thematic clusters. Prominent studies focus on Land-use impacts on water resources, the application of hydrological models, and the role of vegetation in water regulation. The United States, China, and Canada lead research efforts in this field. Our synthesis classifies interventions into biological, mechanical and managerial types and summarizes reported effects on runoff, infiltration, evapotranspiration (ET), soil moisture, surface storage and groundwater recharge. Results show a marked increase in publications after 2011 and concentration of research activity in the United States, China and Canada. Among water-balance components, runoff (n = 447) and ET (n = 308) dominate the literature, whereas soil moisture (n = 66), surface storage (n = 40) and baseflow (n = 38) are comparatively underrepresented. Hydrological process models were the most used estimation approach (n = 440), followed by remote sensing (n = 140), groundwater models (n = 82) and machine-learning methods (n = 38). From the reviewed studies we synthesise typical outcomes: mechanical structures (e.g., terraces, check-dams) are frequently associated with reductions in surface runoff (up to ∼25 % in reported cases) and context-dependent increases in recharge (reported ranges of ∼40–70 %), while biological measures (e.g., afforestation) often improve infiltration but can elevate ET in water-limited environments. We identify recurrent methodological shortcomings — inconsistent reporting of uncertainty, limited reproducibility of bibliometric settings, and scarce comparative field studies — and propose a focused research agenda: transparent bibliometric reporting, prioritized monitoring of underexplored components (soil moisture, baseflow), development of hybrid process–data modeling frameworks, and targeted, context-specific evaluations of interventions under climate variability. This synthesis provides a state-of-the-art overview and a structured set of priorities to guide future watershed management research and policy.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"143 ","pages":"Article 104277"},"PeriodicalIF":4.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Maxout-enhanced robust deep convolutional neural network model for flood mapping using Sentinel-1 SAR data","authors":"Shubham Awasthi ,&nbsp;Gopal Singh Phartiyal ,&nbsp;Divyesh Varade ,&nbsp;Kamal Jain","doi":"10.1016/j.pce.2026.104316","DOIUrl":"10.1016/j.pce.2026.104316","url":null,"abstract":"<div><div>Timely and accurate flood detection is critical for minimizing loss of life and assessing disaster-induced damage. Remote sensing technologies enable consistent, near–real-time mapping of flood extents, which is essential for effective disaster response and preparedness. Among these, Synthetic Aperture Radar (SAR) data have proven particularly valuable due to their all-weather, day–night imaging capability. This study presents a robust and computationally efficient deep learning framework for flood mapping using Sentinel-1 SAR imagery. Using the Sen1Floods11 benchmark dataset, which encompasses 11 geographically and temporally diverse flood events, we propose DeeplabV3PlusMX (DB-SEN1FloodNet)—a ‘Maxout’ enhanced semantic segmentation model derived from the DeeplabV3+ architecture. The proposed model strategically integrates ‘Maxout’ activation layers at multiple stages of the encoder–decoder pipeline to reduce feature-space redundancy, enhance robustness to speckle noise, and improve generalization across heterogeneous flood scenarios. By enabling adaptive piecewise linear feature representations and synergistic regularization with dropout, the ‘Maxout’ strategy improves discrimination of flooded areas under complex scattering conditions. Experimental results demonstrate strong performance, achieving an overall accuracy of 96%, average precision of 98%, mean recall of 94%, an F1-score of 96%, and a mean Intersection over Union (mIoU) of 65%. Furthermore, the model exhibits superior transferability when evaluated on unseen geographic regions, outperforming existing approaches that are often limited to event- or region-specific training. The reduced reliance on auxiliary datasets further underscores the operational potential of the proposed framework for scalable, global flood monitoring using SAR data.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"143 ","pages":"Article 104316"},"PeriodicalIF":4.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An actinopterygian-dominated fish fauna from the Upper Cretaceous Williams Fork Formation, northwestern Colorado, and evidence for provinciality across Laramidia at the Campanian/Maastrichtian boundary","authors":"Joel Crothers ,&nbsp;Jaelyn Eberle ,&nbsp;Donald Brinkman ,&nbsp;Alyssa Wurtz ,&nbsp;Andrew B. Heckert ,&nbsp;ReBecca K. Hunt-Foster ,&nbsp;John R. Foster ,&nbsp;Ida C. Dirkes ,&nbsp;Renee Dunn","doi":"10.1016/j.cretres.2026.106313","DOIUrl":"10.1016/j.cretres.2026.106313","url":null,"abstract":"<div><div>The Williams Fork Formation (WFF) of northwestern Colorado preserves an understudied freshwater biota from the Campanian/Maastrichtian boundary. Here we describe a diverse actinopterygian-dominated fish assemblage from the ReBecca's Hollow locality of Rio Blanco County. Chondrichthyans are rare from this site, but include a hybodontid, <em>Lonchidion</em>, and the hemiscyllid <em>Chiloscyllium</em>. A fragmentary element may represent a pycnodontiform. Chondrosteans are represented by a tentative acipenserid. Holosteans include the lepisosteids <em>Atractosteus</em> and an unnamed taxon, and the amiids <em>Melvius</em>, <em>Cyclurus</em> and <em>Palaeolabrus</em>. Teleosteomorphs at this site include <em>Belonostomus</em>, <em>Paralbula casei</em>, <em>Coriops</em>, <em>Estesesox foxi</em>, <em>Acronichthys</em>, hiodontids, and acanthomorphs. This locality yields at least 17 fish taxa, most of which have not been described previously from the WFF. Although the WFF is temporally correlative with the St. Mary River and Horseshoe Canyon Formations in Alberta and the Prince Creek Formation in Alaska, the ReBecca's Hollow fish assemblage is markedly different from its northern contemporaries. Specifically, it contains several warm-climate taxa such as <em>Lonchidion</em>, <em>Chiloscyllium</em>, <em>Melvius</em>, <em>Atractosteus</em>, and <em>Paralbula</em>, and lacks higher latitude taxa such as Holostean A, documented from Alberta. The differences in these broadly contemporaneous fish assemblages supports the hypothesis that there was provincialism amongst freshwater fishes in Laramidia at the Campanian/Maastrichtian boundary. The fish fauna thus resembles that of Campanian localities in Utah, New Mexico, and Texas, and Maastrichtian (Lancian) localities in Montana, North Dakota, South Dakota, and Wyoming, suggesting that the boundary between these provincial zones remained north of the WFF locality throughout these periods of climate change.</div></div>","PeriodicalId":55207,"journal":{"name":"Cretaceous Research","volume":"182 ","pages":"Article 106313"},"PeriodicalIF":1.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Historical and projected variability of sea surface height and temperature: A novel downscaling approach","authors":"Mohammad Reza Nikoo ,&nbsp;Erfan Zarei ,&nbsp;Malik Al-Wardy","doi":"10.1016/j.atmosres.2026.108828","DOIUrl":"10.1016/j.atmosres.2026.108828","url":null,"abstract":"<div><div>Global climate change is intensifying sea level rise (SLR) and sea surface temperature (SST) variability, placing low-lying coastal regions at increasing risk. This study evaluates historical (1993–2023) and future (2030–2089) trends in sea surface height (SSH) and SST along Oman's coast by combining satellite data, CMIP6 GCMs, and a novel hybrid downscaling approach capable of addressing non-stationarity biases, unlike Quantile Mapping (QM) alone. Historical analysis reveals significant trends, with SSH rising to 47.86 mm/decade and SST warming by 0.48 °C/decade, driven by steric expansion, monsoon dynamics, and regional heat fluxes. Empirical Orthogonal Function (EOF) analysis identifies dominant variability modes linked to the Indian Ocean Dipole and ENSO. Among 15 CMIP6 models, HadGEM3-GC31-LL performs best in simulating SSH/SST and is selected for future projections under SSP126, SSP245, and SSP585 scenarios. For downscaling, a hybrid Quantile Mapping–Random Forest (QM + RF) model is introduced, demonstrating superior accuracy (NSE = 0.77–0.90) compared to standalone QM. Projections highlight stark spatial contrasts: under SSP126, mid-century SSH rebounds to +14.3 mm/decade after an initial decline, while SSP585 drives a relentless SST rise (0.85 °C/decade by 2089), exacerbating marine heatwaves. Coastal urban centers like Muscat and Salalah face compounded risks from SLR-induced inundation and ecosystem degradation, with northern Oman emerging as a warming hotspot. This study underscores the importance of integrating hybrid downscaling methods for regional climate adaptation and emphasizes the need for Oman to prioritize nature-based defenses and adaptive infrastructure in its National Adaptation Plan.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"336 ","pages":"Article 108828"},"PeriodicalIF":4.4,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Montmorillonite-olivine combination for synergistic enhancement of marine diatom growth and particulate organic carbon production","authors":"Fucheng Yao ,&nbsp;Wei Yan ,&nbsp;Lulu Qin ,&nbsp;Rongda Yu ,&nbsp;Dong Liu ,&nbsp;Yanfu Wei ,&nbsp;Li Li ,&nbsp;Qingcheng Zhang ,&nbsp;Peng Yuan","doi":"10.1016/j.clay.2026.108147","DOIUrl":"10.1016/j.clay.2026.108147","url":null,"abstract":"<div><div>To address the limited efficiency of vertical organic carbon export in ocean iron fertilization (OIF), the “Mineral-enhanced Biological Pump” (MeBP) was proposed, aiming to enhance the transport of diatom-derived carbon to deep sea by adding clay minerals such as montmorillonite. Coastal Enhanced Weathering (CEW) seeks to boost ocean alkalinity and carbon sequestration by applying silicate minerals like olivine. However, whether these two mineral-based carbon sequestration strategies can be synergistically combined, particularly the effects of combinations of clay minerals and olivine in marine environments, remains unexplored. In this study, microcosm experiments were conducted to investigate the effects of combined addition of montmorillonite and olivine on the growth and primary productivity of the diatom <em>Thalassiosira weissflogii</em>, as well as their interfacial interactions. The results showed that montmorillonite released more dissolved silicon than olivine in seawater over a short period, providing a richer silicon source for diatoms. This effectively promoted the diatom growth, total chlorophyll <em>a</em> concentration, and particulate organic carbon (POC) production. However, the addition of olivine alone had limited effects on promoting the diatom growth and the POC production. Notably, the combined application of both minerals exhibited a synergistic effect on diatom-derived POC accumulation and diatom growth. Meanwhile, aggregation between montmorillonite and diatom frustules and the incorporation of Al into frustule structures can jointly enhance the protection of diatom-derived POC. In addition, the combined addition also increased seawater pH. These findings reveal the synergistic enhancement of the montmorillonite–olivine combination on the diatom biological pump, offering new insights and experimental evidence for the potentially comprehensive application of MeBP and CEW strategies to enhance marine carbon sequestration.</div></div>","PeriodicalId":245,"journal":{"name":"Applied Clay Science","volume":"285 ","pages":"Article 108147"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}