Geosystems and Geoenvironment最新文献

Ozone patterns in Maceió: Insights into seasonal and geographic varibility

Geosystems and Geoenvironment

Pub Date : 2025-03-13 DOI: 10.1016/j.geogeo.2025.100379

Amaury de Souza , Celina M. Takemura , Deniz Özonur , Elias Silva de Medeiros , Ivana Pobocikova , Janice F. Leivas , José Francisco de Oliveira-Júnior , Kelvy Rosalvo Alencar Cardoso , Marcel Carvalho Abreu , Wagner Alessandro Pansera , Jose Roberto Zenteno Jimenez , Sneha Gautam

This study analyzes the Total Ozone Column (TCO) over six cities in Alagoas, Brazil, aiming to evaluate their spatial and temporal homogeneity and identify seasonal and annual patterns from 2008 to 2016. TCO is a key indicator for monitoring the ozone layer and its implications for public health, given ozone's role in filtering ultraviolet radiation. The analysis utilized satellite-derived TCO data, with variance homogeneity assessed using the Bartlett test at a 95% significance level. Descriptive statistical analyses characterized the temporal distribution of TCO values, and probability density functions (PDFs) identified the best-fitting statistical distribution.

The findings indicate significant homogeneity in annual and seasonal TCO concentrations, with an annual mean of 263.24 ± 9.91 DU. A biannual TCO cycle was observed, with peaks in spring and lows in fall, influenced by Earth's orbit and ozone photochemistry. The data were best represented by a normal distribution, reflecting the role of the Brewer-Dobson Circulation in maintaining ozone uniformity and mitigating disruptions from phenomena like the Antarctic Polar Vortex.

These results emphasize the need for continuous monitoring of ozone variability, as fluctuations in TCO can affect ultraviolet radiation levels and, consequently, public health outcomes such as skin cancer and ocular diseases. The study underscores the importance of integrating TCO data into environmental policies and public health strategies, particularly in regions with high solar radiation exposure. The study's limited statistical sensitivity and geographic coverage highlight the necessity of further research on factors influencing ozone distribution and its broader environmental and health implications.

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引用次数: 0

Assimilation of seismic attenuation model of NW Himalaya and its surrounding region

Geosystems and Geoenvironment

Pub Date : 2025-03-08 DOI: 10.1016/j.geogeo.2025.100378

Vandana, Naresh Kumar

In this study, we analyze the seismic attenuation characteristics of the Northwest Himalaya and adjacent regions using a dataset of 2,716 earthquakes (2.5 ≤ Mw ≤ 5.0) recorded from 2008 to 2015 by a network of 30 broadband seismographs. The single backscattering model was applied to estimate the quality factor of coda waves (Q_c) across three lapse time windows (LTWs) at varying frequencies. Our results reveal that Q_c increases with both frequency and LTW, suggesting a depth-dependent nature of seismic attenuation in the region. The average attenuation relationships for Q_c, Q_α and Q_β across the Northwest Himalaya are determined as follows for LTWs of 20, 30, and 40 s, respectively: Q_c = (74 ± 14)f ^(1.27±0.06), Q_c = (103 ± 26)f ^(1.16±0.08), and Q_c = (140 ± 41)f ^(1.10±0.09). Our findings reveal significant variability in Q_c, Q_α and Q_β across the Tethys (TH), High (HH), Lesser (LH), and Shiwalik (SH) Himalaya regions, as well as the adjacent Indo-Gangetic Plains (IGP), with this variability strongly linked to structural heterogeneity and seismogenic processes in each region. We further establish attenuation relations for distinct tectonic units, observing the following hierarchy: [Q_α,β,c⁻¹(HH) < Q_α,β,c⁻¹(SH) < Q_α,β,c⁻¹(IGP) < Q_α,β,c⁻¹(LH) < Q_α,β,c⁻¹(TH)]. The Tethys Himalaya exhibits the high attenuation, likely due to its sedimentary structure, while the Higher Himalaya shows the low attenuation. These insights into attenuation characteristics across geotectonic segments in the Northwest Himalaya contribute to a more comprehensive seismic hazard assessment for the region.

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引用次数: 0

Geohazard impact and gas reservoir pressure dynamics in the Zagros Fold-Thrust Belt: An environmental perspective

Geosystems and Geoenvironment

Pub Date : 2025-03-07 DOI: 10.1016/j.geogeo.2025.100362

Mahsa Asghari , Zahra Maleki , Ali Solgi , Mohammad Ali Ganjavian , Pooria Kianoush

The Zagros Fold-Thrust Belt (ZFTB) presents a unique intersection of geohazards and gas reservoir dynamics, shaped by the ongoing tectonic activity resulting from the collision of the Arabian and Eurasian plates. This study aims to assess the risk of earthquake-induced landslides and their impact on gas reservoir pressure dynamics – with a particular focus on the Kabir Kuh gas field – identified as a critical area for monitoring due to its vulnerability to seismic events. A novel hybrid model is introduced that integrates geographic information system (GIS) mapping, decision support system (DSS) modeling, and machine learning algorithms. By analyzing a century's worth of seismic data alongside real-time environmental parameters, the model demonstrates a predictive accuracy of 92% using Random Forest algorithms, significantly outperforming traditional methods. The findings reveal a strong correlation between seismic activity and fluctuations in gas reservoir pressure, with an average pressure change of ±150 psi observed during significant seismic events. A landslide susceptibility map was generated, pinpointing regions that require proactive management strategies, particularly where significant landslide potential threatens gas field stability. Identifying the Seymareh landslide as a monumental geological event underscores the impact of landslide hazards on gas field integrity. This research emphasizes the integration of advanced predictive techniques into seismic risk assessments, providing actionable insights for the sustainable gas reservoir management in seismically active regions. The necessity for continuous monitoring and the implementation of advanced geotechnical measures are highlighted as essential components of effective geohazard management. This study contributes to understanding the interplay between seismic hazards and gas reservoir dynamics, offering a comprehensive framework for future research and practical applications in risk management and environmental sustainability.

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引用次数: 0

Petrogenesis of gneisses and granitoids from Southern Bastar Craton, India: A geochemical insight to crustal evolution

Geosystems and Geoenvironment

Pub Date : 2025-03-04 DOI: 10.1016/j.geogeo.2025.100377

Soumya Mitra , Santa Dolui , Asutosh K Tripathy

This study investigates the geochemical evolution and petrogenesis of gneisses and granitoids from the southern part of the Bastar Craton, India, to understand the crustal evolution. The study incorporates the result on major, minor, trace and rare earth elements (REE) interpretation. The gneisses, classified as high alumina granodiorite to granite, peraluminous and exhibit geochemical signatures typical of Archaean TTGs, including enrichment in large ion lithophile elements (LILE) and depletion in high field strength elements (HFSE) with notable negative anomalies in elements like Nb, P, and Ti. In contrast, the granitoids show a meta-aluminous to per-aluminous composition, with higher K₂O/Na₂O ratios and pronounced enrichment in LILE with higher Sr, Ba, Zr, Nb, Y and Yb contents than the gneisses. These patterns suggest a progressive geochemical evolution from gneiss to granitoids. The study put forward two distinct subduction phases contributing to the formation of these rocks. The initial phase associated with a pre- to syn-collisional tectonic setting in a flat low-angle subduction at shallower depth and minimal interaction between slab melts and the mantle wedge. Whereas, the later one is characterized by a collision to subduction transition in a post-collisional setting with gradual increase in mantle-wedge interaction at a relatively greater depth, involving a steeply dipping subduction process. This dual-phase subduction model highlights the tectonic shift in the region over time and provides a comprehensive understanding of the geological evolution of the Bastar Craton.

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引用次数: 0

The future of recycling for critical metals: The example of EV batteries

Geosystems and Geoenvironment

Pub Date : 2025-03-03 DOI: 10.1016/j.geogeo.2025.100376

Yanyan Zhao, Gurpreet Kaur

Across the globe, the uptake of electric vehicles (EVs) has grown rapidly in recent years. With most EVs using lithium-ion batteries, there is a keen focus on the recovery of key battery metals: lithium (Li), nickel (Ni) and cobalt (Co), as well as graphite for the sustainable growth of the electric vehicle industry. This short review briefly introduces EV batteries, discusses EV battery recycling status and market outlook, recent technology advancement, challenges and opportunities and current government initiatives.

近年来，全球范围内电动汽车（EV）的使用率迅速增长。由于大多数电动汽车使用锂离子电池，因此人们非常关注关键电池金属：锂（Li）、镍（Ni）和钴（Co）以及石墨的回收，以促进电动汽车行业的可持续发展。本短评简要介绍了电动汽车电池，讨论了电动汽车电池回收现状和市场前景、最新技术进展、挑战和机遇以及当前的政府举措。

引用次数: 0

Multiple drivers of the recent South Lhonak glacial lake outburst flood in Sikkim Himalaya and its aftermath on Teesta River Valley

Geosystems and Geoenvironment

Pub Date : 2025-03-03 DOI: 10.1016/j.geogeo.2025.100375

Soumik Saha , Biswajit Bera , Debashish Sengupta , Uttam Mukhopadhyay , Debasis Ghosh , Lakpa Tamang , Sumana Bhattacharjee , Nairita Sengupta

Glacial lake outburst floods (GLOFs) are the most severe cryospheric hazard in the ‘Third Pole’ region, encompassing the Tibetan Plateau and surrounding areas including the Himalayas, Hindu Kush, Kunlun, and Tianshan mountains. Understanding the proper response of glaciers to the current situation of global warming is vital because of their role as a water source in the Asian region. Numerous glacial lakes are formed in the higher Himalayan areas due to the contemporary increase in global temperature. The upper part of the Teesta Basin, Sikkim hosts several glacial lakes including one of the largest and fastest growing South Lhonak Lake (5200 m from the mean sea level). Recently, a devastating GLOF event occurred in South Lhonak Lake after the breaching of moraine dams on midnight of October 3, 2023. This disastrous GLOF event collapsed the Chungthang Dam, located approximately 65 km downstream of the lake and accelerated extensive casualties along with infrastructural damages. It is identified that; the impact of cloudburst may be a significant triggering factor behind this event. The satellite imagery and digital elevation models also revealed that a sudden collapse of lateral moraine eventually produced an impulse wave which accelerated the breaching process. Additionally, this study also combined with advanced remote sensing applications. Satellite imageries indicate a huge reduction of the lake area after the GLOF event (1.66 km² before the GLOF event and 0.63 km² after the GLOF). The overtopping volume of the water has been estimated as approximately 106,400

m^{3}

, with a duration of 12.78 s. The peak discharge during overtopping touched approximately 16,651.02 cumecs, indicating the maximum flow rate during the phase. The results have been validated by the high-resolution satellite data across various sites.

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引用次数: 0

Tonian shoshonitic to ultrapotassic granitoids from Chhotanagpur Gneissic Complex, Eastern Indian Shield: Age, origin and tectonic implications

Geosystems and Geoenvironment

Pub Date : 2025-02-28 DOI: 10.1016/j.geogeo.2025.100373

Ankita Basak , Bapi Goswami , Yoann Gréau , Susmita Das , Chittaranjan Bhattacharyya

This work reports petrogenesis of an ultrapotassic granitoid pluton emplaced in the Tonian (949.4 ± 2.3 Ma; new LA-ICPMS zircon U–Pb dating) along a regional shear zone during the post-collisional stage of the Grenvillian Satpura orogeny in Eastern India. The hypidiomorphic granitoids comprise dominantly perthite, microcline (BaO up to 5.85 wt.%), quartz, albite and subordinate amphibole ± diopside ± epidote, allanite, titanite, magnetite ± ilmenite ± biotite ± calcite. Preservation of magmatic epidotes and resorbed boundaries indicates rapid ascent of the granitoid magma. Mylonitic deformation overprinted the southern part of the E-W trending pluton. Magmatic epidote with resorbed boundaries suggests rapid magma ascent. The metaluminous granitoids display affinities with shoshonitic rocks, i.e., enrichment of K₂O (5.79–11.41 wt.%), large ion lithophile elements (Ba 461.5–7004.8 ppm; Sr 151.3–3548.3 ppm), light rare earth elements (LREE 111.2–1317.7 ppm) and high K₂O/Na₂O (1.77–11.35) and La_CN/Yb_CN (11.7–82.48) ratios with both negative and positive Eu-anomalies (Eu/Eu* = 0.58–1.43; average 0.89). Trace element characteristics of zircons demonstrate their magmatic origin. Pseudosection modeling displays high temperature (∼800°C), high fO₂ (ΔNNO +0.8 to +2.6), and CO₂ activity (0.9) of the magma that intruded at shallow crustal depth (∼300 MPa). Biotite remains unstable at this physicochemical condition of the shoshonitic magma. Metaluminous nature, high (La/Yb)_CN (11.7–82.48) and Sr/Y (6.46–277.21) ratios, and Nb/U (avg. 7.4), Ce/Pb (avg. 6.8), Nb/Ta (avg. 11.9), Zr/Hf (avg. 31.61), and low Rb/Sr (0.09–1.39) ratios of these rocks indicate the derivation of the magma from partial melting of the mafic lower crust. Batch melting modeling shows the granitoid magma originated from 5 to 30 % batch melting of K–Ba–Sr-rich shoshonitic mafic (hornblende granulite) source. The study proposes new (Ba + Sr)–Ti–P and Ba–Sr–Ti triangular diagrams for distinguishing mantle vs. crustal sources of post-collisional granitoids.

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引用次数: 0

Nappe tectonics in the Matomb-Hegba area, South-Central Cameroon: Implications on the tectonic evolution of the Yaoundé Group in the Central African Orogenic Belt

Geosystems and Geoenvironment

Pub Date : 2025-02-28 DOI: 10.1016/j.geogeo.2025.100372

Victor Metang, Henri Appolinaire Kenzo, Rose Noel Ngo Belnoun, Dior-Christelle Mboutchouang, Steve Franck Bamou-Wandji, Brigitte Domkam, Boris Toyi Tchouta

This paper documents the thrust tectonics in the Yaoundé Group using detailed field mapping and satellite imagery data. The litho-stratigraphic of the Matomb-Hegba area located W of the Pan-African Yaoundé series comprised two main metasedimentary units: (1) garnet-kyanite migmatites at the top, dated at 622 ± 43 Ma, and (2) garnet-rutile micaschists at the bottom, with ages ranging between 546 and 604 Ma. The contact between the two lithological units is materialized by a ductile shear zone evidenced by structural and remote sensing data: inversion of the foliation at the contact of the shear zone, P₂ folds with southern vergence, E-W to NE-SW sinistral shear planes, uniform dip (towards the SE) and several criteria indicating a sinistral and dextral kinematics respectively in light grey mylonites and in dark grey mylonites along the ductile shear zone. During D₂ deformation stage, subhorizontal S₂ foliation associated to NE-SW Lm₂ mineral lineations were developed in garnet-kyanite migmatites. The thrusting contact zone is characterized by mylonitized micaschists (light grey mylonites) and migmatites (dark grey mylonites) separated by talcschist and amphibolite boudins which would have served as a ‘‘soap layer’’ leading to the slipping of garnet-kyanite migmatites over garnet-rutile micaschists. The disposition of garnet-kyanite migmatites (sometimes outcrop in the form of klippes) over garnet-rutile micaschists, the presence of a ductile shear zone at the contact of the two lithological units, and the NE-SW mineral lineation suggest the existence of at least two tectonic nappes (garnet-kyanite migmatites and garnet-rutile micaschists) with NE-SW-trends in the Yaoundé Group. This nappe disposition induced by ductile shear corroborates well with the compressive shear tectonics as described in the NE of Brazil and in the northern and eastern part of the Saharan Block.

{"title":"Nappe tectonics in the Matomb-Hegba area, South-Central Cameroon: Implications on the tectonic evolution of the Yaoundé Group in the Central African Orogenic Belt","authors":"Victor Metang, Henri Appolinaire Kenzo, Rose Noel Ngo Belnoun, Dior-Christelle Mboutchouang, Steve Franck Bamou-Wandji, Brigitte Domkam, Boris Toyi Tchouta","doi":"10.1016/j.geogeo.2025.100372","DOIUrl":"10.1016/j.geogeo.2025.100372","url":null,"abstract":"<div><div>This paper documents the thrust tectonics in the Yaoundé Group using detailed field mapping and satellite imagery data. The litho-stratigraphic of the Matomb-Hegba area located W of the Pan-African Yaoundé series comprised two main metasedimentary units: (1) garnet-kyanite migmatites at the top, dated at 622 ± 43 Ma, and (2) garnet-rutile micaschists at the bottom, with ages ranging between 546 and 604 Ma. The contact between the two lithological units is materialized by a ductile shear zone evidenced by structural and remote sensing data: inversion of the foliation at the contact of the shear zone, P<sub>2</sub> folds with southern vergence, E-W to NE-SW sinistral shear planes, uniform dip (towards the SE) and several criteria indicating a sinistral and dextral kinematics respectively in light grey mylonites and in dark grey mylonites along the ductile shear zone. During D<sub>2</sub> deformation stage, subhorizontal S<sub>2</sub> foliation associated to NE-SW Lm<sub>2</sub> mineral lineations were developed in garnet-kyanite migmatites. The thrusting contact zone is characterized by mylonitized micaschists (light grey mylonites) and migmatites (dark grey mylonites) separated by talcschist and amphibolite boudins which would have served as a ‘‘soap layer’’ leading to the slipping of garnet-kyanite migmatites over garnet-rutile micaschists. The disposition of garnet-kyanite migmatites (sometimes outcrop in the form of klippes) over garnet-rutile micaschists, the presence of a ductile shear zone at the contact of the two lithological units, and the NE-SW mineral lineation suggest the existence of at least two tectonic nappes (garnet-kyanite migmatites and garnet-rutile micaschists) with NE-SW-trends in the Yaoundé Group. This nappe disposition induced by ductile shear corroborates well with the compressive shear tectonics as described in the NE of Brazil and in the northern and eastern part of the Saharan Block.</div></div>","PeriodicalId":100582,"journal":{"name":"Geosystems and Geoenvironment","volume":"4 2","pages":"Article 100372"},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integration of geospatial techniques and machine learning in land parcel prediction

Geosystems and Geoenvironment

Pub Date : 2025-02-25 DOI: 10.1016/j.geogeo.2025.100371

Nekkanti Haripavan , Subhashish Dey , Chimakurthi Harika Mani Chandana

The integration of geospatial techniques and machine learning algorithms has revolutionized our ability to analyze and predict changes in land parcels. In this research work leverage the power of Google Earth Engine to observe and interpret historical data spanning the last 2014–2023 years, in order to make informed predictions about future land parcel transformations. Our research will highlight the key components of this plan including data acquisition, preprocessing, feature engineering, and the application of machine learning models. We will explore how Google Earth Engine provides a robust platform for accessing vast geospatial datasets and performing complex analyses. By harnessing the temporal and spectral information captured by Earth observation satellites, we aim to identify patterns and trends in land parcel changes. These insights are used to train and fine-tune our machine learning models, which will subsequently forecast future land parcel developments. The project underscores the practical significance of our research work, as it can be applied to more domains such as urban planning, agriculture, forestry, and environmental monitoring. Furthermore, it showcases the potential of technology to enhance our understanding of the dynamic nature of our environment, and the role that predictive analytics plays in informed decision-making. One significant benefit is the feature selection that may be customized thanks to machine learning and geospatial approaches. Researchers and practitioners can customize their models by choosing the most pertinent variables for each land parcel forecasts from a wide range of spatial features. This flexibility guarantees that models can concentrate on the spatial features that have the biggest influence on the desired outcomes, improving the forecasts' overall performance and interpretability.

{"title":"Integration of geospatial techniques and machine learning in land parcel prediction","authors":"Nekkanti Haripavan , Subhashish Dey , Chimakurthi Harika Mani Chandana","doi":"10.1016/j.geogeo.2025.100371","DOIUrl":"10.1016/j.geogeo.2025.100371","url":null,"abstract":"<div><div>The integration of geospatial techniques and machine learning algorithms has revolutionized our ability to analyze and predict changes in land parcels. In this research work leverage the power of Google Earth Engine to observe and interpret historical data spanning the last 2014–2023 years, in order to make informed predictions about future land parcel transformations. Our research will highlight the key components of this plan including data acquisition, preprocessing, feature engineering, and the application of machine learning models. We will explore how Google Earth Engine provides a robust platform for accessing vast geospatial datasets and performing complex analyses. By harnessing the temporal and spectral information captured by Earth observation satellites, we aim to identify patterns and trends in land parcel changes. These insights are used to train and fine-tune our machine learning models, which will subsequently forecast future land parcel developments. The project underscores the practical significance of our research work, as it can be applied to more domains such as urban planning, agriculture, forestry, and environmental monitoring. Furthermore, it showcases the potential of technology to enhance our understanding of the dynamic nature of our environment, and the role that predictive analytics plays in informed decision-making. One significant benefit is the feature selection that may be customized thanks to machine learning and geospatial approaches. Researchers and practitioners can customize their models by choosing the most pertinent variables for each land parcel forecasts from a wide range of spatial features. This flexibility guarantees that models can concentrate on the spatial features that have the biggest influence on the desired outcomes, improving the forecasts' overall performance and interpretability.</div></div>","PeriodicalId":100582,"journal":{"name":"Geosystems and Geoenvironment","volume":"4 2","pages":"Article 100371"},"PeriodicalIF":0.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence and machine learning to enhance critical mineral deposit discovery 人工智能和机器学习加强关键矿藏的发现

Geosystems and Geoenvironment

Pub Date : 2025-02-16 DOI: 10.1016/j.geogeo.2025.100361

Rhys S. Davies , McLean Trott , Jaakko Georgi , Alexander Farrar

The application of machine learning (ML) in mineral exploration has garnered significant attention and investment, yet greenfield mineral deposit discovery rates remain unchanged. This limited success stems from challenges such as low data quality outside existing mines, inconsistent sampling, limited interdisciplinary collaboration, and the unique complexity of geoscientific problems. Unlike traditional ML applications, mineral exploration demands a focus on subtle variations within finite search spaces, requiring an exploratory rather than accuracy-driven approach. Effective implementation necessitates collaboration between data scientists and geoscientists, leveraging ML as a tool to test hypotheses and analyse diverse datasets. However, reliance solely on ML overlooks the critical role of human creativity in generating and evaluating novel search strategies. Broader adoption of statistical methods, integrated spatial models, and innovative data preparation techniques can address the inconsistencies in exploration datasets. Furthermore, subjective modelling approaches, such as Delphi methods, can complement ML by incorporating expert judgment to overcome predictive limitations. By combining technological advancements with human expertise, the mineral exploration industry can enhance discovery success and achieve long-term sustainability. There is an important short-term requirement to secure the supply of critical metal resources, as their supply from existing mines and brownfield exploration is finite and commercial recycling of critical metals is still in its infancy.

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引用次数: 0