Geoscience frontiers最新文献

{"title":"Hydrochemistry and multi-isotopes for interpreting formation mechanisms of different-type geothermal waters in the Cuona-Woka Rift, southern Tibetan Plateau","authors":"Xingcheng Yuan ,&nbsp;Yunhui Zhang ,&nbsp;Jinhang Huang ,&nbsp;Zhonghe Pang ,&nbsp;Haoqing Huang ,&nbsp;Weibing Wang ,&nbsp;Ying Wang ,&nbsp;Ming Chang ,&nbsp;Marco Taussi ,&nbsp;Lisheng Wang","doi":"10.1016/j.gsf.2025.102170","DOIUrl":"10.1016/j.gsf.2025.102170","url":null,"abstract":"<div><div>High-temperature geothermal activities are widely distributed in rift tectonic zones, where significant volumes of geothermal waters with diverse hydrochemical characteristics are exposed. However, it is still unclear whether these geothermal waters have different formation mechanisms, which hinders the efficient exploitation and utilization of geothermal resources. Hence, this study investigates 41 geothermal water samples from the Cuona-Woka Rift (CWR) on the Tibetan Plateau to elucidate their hydrogeochemical evolutions and formation mechanisms. These geothermal waters are distributed along normal faults (N–S) and thrust faults (E–W), with discharge temperatures ranging from 34.0 to 85.5 °C. Self-organizing map classification identifies three distinct hydrochemical groups: Group 1 (Cl-Na and Cl·HCO₃-Na), Group 2 (HCO₃·Cl-Na), and Group 3 (SO₄·Cl-Ca·Na). The <em>δ</em>D and <em>δ</em>¹⁸O values indicate that meteoric and snow-melt waters are the dominant recharge sources for geothermal waters, with magmatic water contributions ranging from 18 % to 24 % (Group 1) and 12 % to 21 % (Group 2). The hydrochemical composition is primarily controlled by silicate and carbonate mineral dissolution, gypsum leaching, and cation exchange, with a higher contribution rate than the mixing of magmatic waters. All geothermal waters originate from the same deep sources, with Groups 2 and 3 undergoing mixing with 68 %–88 % and 57 %–70 % shallow cold groundwater, respectively. The significantly enriched trace alkali elements (Li, Rb, and Cs) in Group 1 are attributed to the input of crustal magma melts. Deep reservoir temperatures are estimated at 251–270 °C (Group 1), 226–229 °C (Group 2), and 189–194 °C (Group 3) based on empirical chemical geothermometers, silica-enthalpy mixing model, and geothermometric modeling. The maximum circulation depths are 4.8–5.2 km, 4.3–4.4 km, and 3.5–3.6 km, respectively. Three genesis conceptual models controlled by rift structures are proposed: melt intrusion heating type, hot–cold mixing heating type, and steam heating type. These findings will enhance the understanding of the origin of rift-type geothermal waters and provide valuable insights for the global exploitation and utilization of high-temperature geothermal resources.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102170"},"PeriodicalIF":8.9,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332900","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":"Spatiotemporal analysis of the FWI over Europe and North Africa: Historical trends and climate projections under RCP4.5 and RCP8.5","authors":"Fabio Di Nunno,&nbsp;Francesco Granata","doi":"10.1016/j.gsf.2025.102178","DOIUrl":"10.1016/j.gsf.2025.102178","url":null,"abstract":"<div><div>Wildfires represent an escalating environmental threat across Europe and North Africa, increasingly exacerbated by climate-driven shifts in temperature, precipitation, and drought patterns. However, there is still limited large-scale, methodologically consistent research that simultaneously assesses historical patterns and future projections of fire danger across these regions, particularly in terms of both frequency and duration of risk under different climate scenarios. This study addresses this gap by providing a high-resolution, spatiotemporal assessment of fire weather conditions, with the aim of offering critical insights to support climate-adaptive fire management strategies, extended preparedness frameworks, and the integration of future fire weather projections into land-use and risk governance policies. To achieve this, we investigate historical (1979–2021) and projected (2000–2098) trends in fire danger using the Canadian Fire Weather Index (FWI), based on ERA5 reanalysis data and outputs from five Global Climate Models (GCMs) under RCP4.5 and RCP8.5 scenarios. Over 50,000 land grid cells were analyzed to assess the frequency and duration of six FWI danger classes. Different metrics were used to quantify the agreement between historical reanalysis data and GCM outputs, while the Seasonal Kendall (SK) test was applied to detect trends. Results reveal a substantial decline in the duration of the very low FWI class, from 36 to 23 months, and significant increases in both the duration and frequency of the extreme FWI class, reaching up to 6.38 months and 14.42% under the RCP8.5 scenario. Correlation coefficients exceed 0.8 across much of Southern Europe and North Africa, indicating strong temporal agreement. Trend analyses reveal statistically significant increases in fire danger across southern latitudes, while Northern Europe shows mixed or decreasing trends. These findings project a dramatic intensification and expansion of fire-prone conditions, particularly under high-emission scenarios.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102178"},"PeriodicalIF":8.9,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332899","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":"A proposed method for landslide detection based on transfer learning and graph neural network","authors":"Wanqi Luo ,&nbsp;Haijun Qiu ,&nbsp;Yingdong Wei ,&nbsp;Wenchao Huangfu ,&nbsp;Dongdong Yang","doi":"10.1016/j.gsf.2025.102171","DOIUrl":"10.1016/j.gsf.2025.102171","url":null,"abstract":"<div><div>Rapid landslide detection can give timely information for emergency responses when group-occurring landslides occurred. However, it is frequently difficult to quickly acquire sufficient data for landslide detection in a short period. Transfer learning harnesses the knowledge of landslide detection from the source domain to the target domain with little labeled data. Graph neural networks (GNN) explicitly models global or local relationships by constructing a graph structure where nodes represent pixels and edges represent connections, thereby improving segmentation consistency. Here, we proposed a deep learning model integrated the attention mechanism, multiscale connections, and GNN to capture contextual information and extract the important features for landslide detection. The proposed method was first pretrained in the large-scale dataset, then transferred and fine-tuned the parameters in the two case studies: 2013 Niangniangba rainfall-induced landslides in China and 2018 Hokkaido coseismic landslides in Japan. We examined the feasibility of the proposed model and studied how much impact the scale of the target domain would have on the landslide detection. The controlled experiments reported that our proposed method could achieve the best F1-score in the data-rich condition. Our results also reveal that the deep learning models with transfer learning in data-limited conditions can perform closely to those in data-rich conditions. The fine-tuning model updated parameters in the target domain besides gaining knowledge from the source domain; hence, performance was improved significantly in a new region despite having little new data. Our approach demonstrates a potential way to improve landslide detection assessment, particularly in areas where landslides are extremely difficult to label.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102171"},"PeriodicalIF":8.9,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332898","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":"Geology and genesis of the newly identified Early-Devonian Hatuzhongyou REE deposit, NW China: Insights from petrology, geochemistry, and isotopes","authors":"Chao Hui ,&nbsp;Fengyue Sun ,&nbsp;Yanqian Yang ,&nbsp;Shahzad Bakht ,&nbsp;Tao Tian ,&nbsp;Tao Yu ,&nbsp;Jianfeng Qiao ,&nbsp;Xingsen Chen ,&nbsp;Chengxian Liu ,&nbsp;Yajing Zhang","doi":"10.1016/j.gsf.2025.102174","DOIUrl":"10.1016/j.gsf.2025.102174","url":null,"abstract":"<div><div>The East Kunlun Orogenic Belt (EKOB) is an important Cu-Co-Ni-Au-Fe metallogenic belt in China, but the degree of exploration for rare earth elements (REE) mineralization remains very limited. Following the identification of the Dagelegouxi carbonatite-associated REE-Nb deposit (2022) and the Hatuzhongyou (HT) REE deposit (2017), the researchers have paid increasing attention to the REE mineralization potential in the EKOB. The former has been systematically studied in terms of the metallogenic processes. However, no systematic studies have been conducted on the HT deposit, resulting in a research gap. Therefore, this study applies petrology, whole-rock and in-situ mineral geochemistry, geochronology and Sr-Nd-Pb-Hf isotopes to investigate tectonic setting and metallogenic processes of the HT deposit.</div><div>The HT deposit represents an alkaline silicate complex (ASC)-hosted mineralization system. The ASC comprises hornblende gabbro (HG), clinopyroxene syenite (CS), hornblende-clinopyroxene syenite (HCS), and quartz-hornblende-clinopyroxene syenite (QS), displaying brecciated, stockwork, and disseminated REE ores. REE mineralization is dominated by allanite, xenotime, monazite, and bastnäesite. The zircon U-Pb concordant age of the HCS suggests that the HT ASC formed in an extensional setting induced by slab detachment and asthenospheric upwelling at <em>ca.</em> 413 Ma, marking a flare-up stage of magmatism and mineralization from <em>ca.</em> 430 Ma to 359 Ma in the EKOB. All rocks in the HT deposit are enriched in large ion lithophile elements (LILEs) and REE, but depleted in Nb, Ta, Ti, and Eu. Petrology, mineral compositions, geochemical data, and Hf-Sr-Nd-Pb isotopic compositions suggest that the source of the HT deposit originated from low-degree partial melting of a metasomatized enriched lithospheric mantle, followed by fractional crystallization, magmatic-hydrothermal metasomatism, and fluid boiling.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102174"},"PeriodicalIF":8.9,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332896","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":"Carbon capture, utilization, and storage (CCUS) in the context of earth energy systems: A multidisciplinary review","authors":"Asif Raihan","doi":"10.1016/j.gsf.2025.102177","DOIUrl":"10.1016/j.gsf.2025.102177","url":null,"abstract":"<div><div>Carbon Capture, Utilization, and Storage (CCUS) has emerged as a critical technology for achieving global climate goals by enabling substantial reductions in carbon dioxide (CO₂) emissions from industrial and energy systems. This multidisciplinary review provides a comprehensive assessment of CCUS technologies, their integration with earth energy systems, and their broader economic, environmental, and societal implications. It begins by detailing the fundamentals of CO₂ capture, utilization, and geological storage, followed by an in-depth analysis of engineering infrastructure and geoscientific factors that underpin secure and efficient deployment. The review also examines how CCUS can be synergistically coupled with renewable and low-carbon technologies such as blue hydrogen, bioenergy, and geothermal systems to enhance sustainability and economic viability. In the policy and economic context, the study explores cost drivers, financing mechanisms, regulatory frameworks, market incentives, and deployment strategies, identifying both progress and persistent gaps. Furthermore, the environmental and societal impacts of CCUS are critically evaluated, with a focus on long-term storage risks, ecosystem concerns, and public acceptance challenges. A global overview of CCUS initiatives highlights regional progress, collaborative efforts, and the increasing momentum toward cluster-based infrastructure models. The article concludes by identifying key challenges—technical, regulatory, and social—and outlines future directions for innovation, policy harmonization, and global coordination. By synthesizing insights from geosciences, engineering, economics, and policy, this review underscores the pivotal role of CCUS as an enabling technology for a just and effective energy transition. It provides strategic guidance for researchers, policymakers, and industry stakeholders working to scale CCUS in alignment with net-zero targets and sustainable development goals (SDGs).</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102177"},"PeriodicalIF":8.9,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265361","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":"Strategic use of Sentinel-3A/B OLCI data for global water quality management: An overview","authors":"Emanuelle Goellner ,&nbsp;Brian William Bodah ,&nbsp;Alcindo Neckel ,&nbsp;Paloma Carollo Toscan ,&nbsp;Júlia Mognol Scopel ,&nbsp;Cleiton Korcelski ,&nbsp;Guilherme Peterle Schmitz ,&nbsp;Giana Mores ,&nbsp;Marcos L.S. Oliveira ,&nbsp;Eduardo Nuno Borges Pereira","doi":"10.1016/j.gsf.2025.102175","DOIUrl":"10.1016/j.gsf.2025.102175","url":null,"abstract":"<div><div>The Sentinel-3A/B satellites, operated by the European Space Agency (ESA), are equipped with the Ocean and Land Color Instrument (OLCI), which provides data through push-broom radiometers. Sentinel-3A was launched on February 16, 2016, and Sentinel-3B on April 25, 2018. Given their relevance in environmental monitoring, there is a growing need for literature reviews to deepen the functional understanding of their geospatial applications. This study aims to review the scientific literature on using Sentinel-3A/B OLCI data for monitoring aquatic environments, particularly focusing on chlorophyll-a (CHL), total suspended matter (TSM), and absorption of dissolved organic matter at 443 nm (ADG443). The review includes publications indexed in the Scopus and Web of Science (SCIE) databases between February 2016 and 2025. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was employed to select 26 relevant studies that apply spectral detections via Sentinel-3A/B satellites related to levels of CHL, TSM, and ADG443. Additionally, the Content Analysis Method (CAM) and MAXQDA software were used to analyze absolute (AF) and relative frequencies (RF) of key variables such as study location, sampling, objectives, use of Sentinel satellites, outcomes, innovations, and future research directions. CAM results showed an average frequency of ∼ 36.0%, with Sentinel-3A accounting for 35.3% and Sentinel-3B ranging between 31.89% and 40.08%. Chlorophyll-a was the most frequently cited term, with a frequency of 32.33% to 40.08% in MAXQDA. The consistency and reliability of spectral detections underscore the potential of these satellites to support the aquatic ecosystem preservation.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102175"},"PeriodicalIF":8.9,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266531","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":"Craton boundary detection from full-waveform tomography model reveals links to critical metal deposits","authors":"Hojat Shirmard ,&nbsp;Ben Mather ,&nbsp;Ehsan Farahbakhsh ,&nbsp;Karol Czarnota ,&nbsp;R. Dietmar Müller","doi":"10.1016/j.gsf.2025.102176","DOIUrl":"10.1016/j.gsf.2025.102176","url":null,"abstract":"<div><div>Craton margins play a crucial role in mineral exploration as they host faults, fractures, and shear zones that facilitate hydrothermal fluid movement, transporting and depositing dissolved metals into valuable mineral deposits. We use the high-resolution full-waveform seismic inversion model REVEAL to extract horizontal shear wave velocity (<em>V</em>_SH), vertical shear wave velocity (<em>V</em>_SV), and isotropic P-wave velocity (<em>V</em>_P) across depth slices from 150 to 200 km, a range that captures most cratonic lithosphere based on tectonic age and lithospheric thickness analyses. Machine learning, applied through clustered maps, demonstrates that <em>V</em>_SH effectively delineates craton boundaries, aligning with target mineral deposits, including iron oxide copper–gold (IOCG) and sediment-hosted lead, zinc, and copper deposits. These boundaries are characterized by high horizontal shear velocities (4.58–4.68 km/s), and trace the edges of cratons, accreted passive margins, orogens, and thick volcanic arcs. Using published thermal and lithospheric thickness models, we distinguish cratons from other thick lithospheric features and identify their edges and associated deposits. Our results show that ∼85 % of the total metal content (Cu + Pb + Zn) in target deposits lies within ∼120 km of high-velocity cluster boundaries identified as craton edges. Near-craton deposits reveal ∼80 % of the total metal content within ∼90 km of craton boundaries. The weighted cumulative distribution function shows a steeper gradient in metal content closer to craton boundaries, indicating higher concentrations near these tectonic features. Focusing on just 16 % of Earth’s continental areas can reveal over 80 % of known target deposits, highlighting the significance of craton boundaries quantitatively mapped in this study.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102176"},"PeriodicalIF":8.9,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266530","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":"Noble gas constraints on fluid flow and hydrocarbon accumulation in the Yinggehai Basin, Northwestern South China Sea","authors":"Rui Liu ,&nbsp;Rui Xu ,&nbsp;Tao Wen ,&nbsp;Khi Atchinson ,&nbsp;Ziqi Feng ,&nbsp;Fang Hao ,&nbsp;Lin Hu ,&nbsp;Jinqiang Tian ,&nbsp;Yazhen Zhang ,&nbsp;Jianzhang Liu ,&nbsp;Lei Tuo","doi":"10.1016/j.gsf.2025.102169","DOIUrl":"10.1016/j.gsf.2025.102169","url":null,"abstract":"<div><div>Multiple physicochemical processes involving organic and inorganic components may alter hydrocarbon composition and isotopic signatures, posing a challenge in accurately tracing natural gas accumulation. In contrast, noble gases are chemically inert and highly sensitive to fluid flow processes, offering a powerful tool for precisely tracing natural gas accumulation. By analyzing and modeling noble gas geochemistry data of gas samples from gas fields in the Yinggehai Basin, South China Sea, we constrained fluid flow patterns and traced the natural gas accumulation process. In particular, the low ³He/⁴He and high ⁴⁰Ar/³⁶Ar values of gas samples suggested atmospheric-crustal mixing, with the suspected central fault significantly influencing the ⁴⁰Ar* (* denotes crustal noble gas) proportion and ⁴⁰Ar/³⁶Ar value in charging fluids. Binary mixing of atmospheric and crustal noble gases elevated the ⁴⁰Ar*/⁴He* value in well-preserved gas fields. Diapir activity and/or long-term artificial extraction had likely promoted noble gas leakage which further elevated the ⁴⁰Ar*/⁴He* to abnormally high levels. Three key time windows for ⁴He* accumulation, i.e., 4–4.5 Ma, 1–2 Ma, and 0–0.5 Ma, were identified in well-preserved gas fields. The suspected central fault facilitated the migration of both high ⁴⁰Ar/³⁶Ar fluids and highly mature hydrocarbons characterized by heavier <em>δ</em>¹³C₁ and high C₁/C_1-5 ratios. In most gas fields, methane (C₁) migration was dominated by the gas phase, as indicated by the high C₁/³⁶Ar value. However, in a few leaked or shallow-buried gas fields, low C₁/³⁶Ar ratios suggest that C₁ also migrated with water. The duration of trap sealing and the depth of the transport system played critical roles in hydrocarbon accumulation. Longer trap sealing and greater transport system depth favored hydrocarbons derived from the Lower Miocene Sanya Formation. In contrast, shorter trap sealing durations and limited transport system depth led to the accumulation of hydrocarbons sourced from the Middle Miocene Meishan Formation.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102169"},"PeriodicalIF":8.9,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265362","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":"Unlocking marginal SDG dynamics: A KRLS machine learning analysis of AI technologies and solar energy","authors":"Zahoor Ahmed ,&nbsp;Stefania Pinzon ,&nbsp;Muhammad Qamar Rasheed","doi":"10.1016/j.gsf.2025.102167","DOIUrl":"10.1016/j.gsf.2025.102167","url":null,"abstract":"<div><div>Studies quantifying AI’s impact on Sustainable Development Goals (SDGs) often rely on proxies that inaccurately reflect AI progress. Moreover, focusing solely on environmental and growth indicators provides an incomplete picture of AI’s overall contribution to the SDGs, as the SDG framework encompasses a broader set of interconnected goals. Therefore, this study unveils the marginal impacts of AI and solar energy (SEN) directly on the SDG Index (SDGI) by using the Kernel-Based Regularized Least Squares (KRLS) machine learning approach for the 10 largest economies from 2000‒2022. While the study found an overall positive average marginal impact of AI on the SDG Index, indicating significant progress driven by AI technologies, the analysis across different quantiles revealed variability. Specifically, at the 25th quantile, AI appears to hinder SDG progress. This could be due to negative externalities from AI adoption, like its use in accelerating non-renewable energy production and resource-intensive consumption, or from countries’ insufficient technological application capabilities. However, at higher quantiles (likely representing countries with better SDG achievement and greater AI maturity), the marginal effects of AI become increasingly positive, suggesting its beneficial use in areas that support SDGs. Marginal effects of SEN on SDGI are found to be positive, showing a positive connection between SDGs’ achievements and solar energy adoption. The marginal effects of economic globalization (EGB) and institutional productive capacity (INP) on SDGI are found to be positive. Finally, policies to boost AI and solar energy adoption, as well as exploring potential applications of AI across various sectors for sustainable development, are discussed.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 6","pages":"Article 102167"},"PeriodicalIF":8.9,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266544","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":"Searching for the age of the upper Vindhyan basin, India: A view from paleomagnetism and geochronology","authors":"Samuel Kwafo ,&nbsp;Joseph G. Meert ,&nbsp;Manoj K. Pandit ,&nbsp;Anup K. Sinha ,&nbsp;Nirmal Kant Verma","doi":"10.1016/j.gsf.2025.102168","DOIUrl":"10.1016/j.gsf.2025.102168","url":null,"abstract":"<div><div>The closure age of the Proterozoic Vindhyan basin is a long-standing puzzle, unresolved due to inconsistencies between paleontological, geochronological, and paleomagnetic data. Some fossil findings from the Upper Vindhyan basin suggest an Ediacaran closure age, Pb-Pb dating of carbonate units yield dates ranging from ∼750–910 Ma, and detrital zircon data generally support a Kleisian (800–1000 Ma) closure age. In this study, we review published detrital zircon data and apply a statistically robust method to estimate the maximum depositional age (MDA) of the upper Vindhyan Kaimur, Bhander, and Rewa groups. Additionally, we present new paleomagnetic data from the folded Bhander sandstones near the Great Boundary fault to establish the primary nature of the Bhander-Rewa paleomagnetic pole. Our analysis reveals an MDA of 945 ± 7 Ma, which aligns closely with the youngest zircon population in the spectra. This MDA also corresponds to the onset of the Delhi Orogeny to the west of the Vindhyan basin; collisional orogenesis in the Central Indian Tectonic Zone to the south; and more distal high-grade metamorphism and collisional tectonism in the northern Eastern Ghats belt providing a geologically meaningful context for the basin closure age. Our paleomagnetic data offers a robust field test for the Vindhyan pole and we demonstrate that proposals for terminal Tonian closure of the basin (∼850–770 Ma) are incompatible with extant paleomagnetic data from India.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"17 1","pages":"Article 102168"},"PeriodicalIF":8.9,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145361147","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}