The occurrence of massif-type anorthosite intrusions is a widespread Proterozoic phenomenon. They are usually associated with gabbroic, charnockitic, and granitic rocks, comprising the so-called anorthosite-mangerite-charnockite-granite (AMCG) suite. Although these rocks have been extensively studied worldwide, several aspects concerning their formation remain unsettled. Among them, the magma source and the tectonic setting are the most important. To evaluate these issues, we first compiled geochemical and isotopic data of Proterozoic anorthosite massifs and AMCG suites worldwide and stored it in a database named datAMCG. This plethora of data allows us to make some important interpretations. We argue that the wide-ranging multi-isotopic composition of this group of rocks reflects varying proportions of juvenile mantle-derived melts and crustal components. We interpret that the precursor magmas of most massive anorthosite bodies and associated mafic rocks have a mantle-dominated origin. However, we highlight that a crustal component is indispensable to generate these lithologies. Adding variable amounts of this material during succeeding multi-stage assimilation-fractional crystallization (AFC) processes gives these intrusions their typical mantle-crustal hybrid isotopic traits. In contrast, a crustal-dominant origin with a complementary mantle component is interpreted for most MCG rocks. In summary, the isotopic information in datAMCG indicates that both sources are necessary to generate AMCG rocks. Therefore, we suggest that hybridized magmas with different mantle-crust proportions originate these rocks. This interpretation might offer a more nuanced and accurate depiction of this phenomenon in future work instead of choosing a single-sourced model as in the past decades. Finally, tectonomagmatic diagrams suggest that the rocks under study were likely generated in a tectonic environment that transitioned between collision and post-collisional extension, sometimes involving subduction-modified mantle sources. This interpretation is supported by geological and geochronological information from most complexes, thus challenging the Andean-type margins as an ideal tectonic setting.
This study aims to investigate the combined use of multi-sensor datasets (Landsat 4–5 & 8 OLI satellite imagery, spatial resolution = 30 m) coupled with field studies to evaluate spatio-temporal dynamics of soil salinization along the coastal belt in West Bengal, India. This study assesses soil salinization by mapping the salinity and electrical conductivity of saturation extract (ECe) and utilizing spectral signatures for estimating soil salinity. The SI change (%) was analyzed (2021–1995), categorizing increases in salinity levels into 5%, 10%, and 50% changes possibly due to salt encrustation on the soil layers. The land use land cover (LULC) change map (2021–1995) demonstrates that the study area is continuously evolving in terms of urbanization. Moreover, in the study area, soil salinity ranges from 0.03 ppt to 3.87 ppt, and ECe varies from 0.35 dSm−1 to 52.85 dSm−1. Additionally, vulnerable saline soil locations were further identified. Classification of soil salinity based on ECe reveals that 26% of samples fall into the non-saline category, while the rest belong to the saline category. The Spectral signatures of the soil samples (n = 19) acquired from FieldSpec hand spectrometer show significant absorption features around 1400, 1900, and 2250 nm and indicate salt minerals. The results of reflectance spectroscopy were cross-validated using X-ray fluorescence and scanning electron microscopy. This study also employed partial least square regression (PLSR) approach to predict ECe (r2 = 0.79, RMSE = 3.29) and salinity parameters (r2 = 0.75, RMSE = 0.51), suggesting PLSR applicability in monitoring salt-affected soils globally. This study’s conclusion emphasizes that remote sensing data and multivariate analysis can be crucial tools for mapping spatial variations and predicting soil salinity. It has also been concluded that saline groundwater used for irrigation and aqua-cultural activities exacerbates soil salinization. The study will help policymakers/farmers identify the salt degradation problem more effectively and adopt immediate mitigation measures.
Constraining the processes associated with the formation of new (juvenile) continental crust from mantle-derived (basaltic) sources is key to understanding the origin and evolution of Earth’s landmasses. Here we present high-precision measurements of stable isotopes of potassium (K) from Earth’s most voluminous plagiogranites, exposed near El-Shadli in the Eastern Desert of Egypt. These plagiogranites exhibit a wide range of δ41K values (–0.31‰ ± 0.06‰ to 0.36‰ ± 0.05‰; 2 SE, standard error) that are significantly higher (isotopically heavier) than mantle values (–0.42‰ ± 0.08‰). Isotopic (87Sr/86Sr and 143Nd/144Nd) and trace element data indicate that the large variation in δ41K was inherited from the basaltic source rocks of the El-Shadli plagiogranites, consistent with an origin through partial melting of hydrothermally-altered mid-to-lower oceanic crust. These data demonstrate that K isotopes have the potential to better constrain the source of granitoid rocks and thus the secular evolution of the continental crust.
Biogenic carbonate structures such as rhodoliths and foraminiferal-algal nodules are a significant part of marine carbonate production and are being increasingly used as paleoenvironmental indicators for predictive modeling of the global carbon cycle and ocean acidification research. However, traditional methods to characterize and quantify the carbonate production of biogenic nodules are typically limited to two-dimensional analysis using optical and electron microscopy. While micro-computed tomography (µCT) is an excellent tool for 3D analysis of inner structures of geomaterials, the trade-off between sample size and image resolution is often a limiting factor. In this study, we address these challenges by using a novel multi-scale µCT image analysis methodology combined with electron microscopy, to visualize and quantify the carbonate volumes in a biogenic calcareous nodule. We applied our methodology to a foraminiferal-algal nodule collected from the Red Sea along the coast of NEOM, Saudi Arabia. Integrated µCT and SEM image analyses revealed the main biogenic carbonate components of this nodule to be encrusting foraminifera (EF) and crustose coralline algae (CCA). We developed a multi-scale µCT analysis approach for this study, involving a hybrid thresholding and machine-learning based image segmentation. We utilized a high resolution µCT scan from the sample as a ground-truth to improve the segmentation of the lower resolution full volume µCT scan which provided reliable volumetric quantification of the EF and CCA layers. Together, the EF and CCA layers contribute to approximately 65.5 % of the studied FAN volume, corresponding to 69.01 cm3 and 73.32 cm3 respectively, and the rest is comprised of sediment infill, voids and other minor components. Moreover, volumetric quantification results in conjunction with CT density values, indicate that the CCA layers are associated with the highest amount of carbonate production within this foraminiferal-algal nodule. The methodology developed for this study is suitable for analyzing biogenic carbonate structures for a wide array of applications including quantification of carbonate production and studying the impact of ocean acidification on skeletal structures of marine calcifying organisms. In particular, the hybrid µCT image analysis we adopted in this study proved to be advantageous for the analysis of biogenic structures in which the textures and components of the internal layers are distinctly visible despite having an overlap in the range of CT density values.
Joints shear strength is a critical parameter during the design and construction of geotechnical engineering structures. The prevailing models mostly adopt the form of empirical functions, employing mathematical regression techniques to represent experimental data. As an alternative approach, this paper proposes a new integrated intelligent computing paradigm that aims to predict joints shear strength. Five metaheuristic optimization algorithms, including the chameleon swarm algorithm (CSA), slime mold algorithm, transient search optimization algorithm, equilibrium optimizer and social network search algorithm, were employed to enhance the performance of the multilayered perception (MLP) model. Efficiency comparisons were conducted between the proposed CSA-MLP model and twelve classical models, employing statistical indicators such as root mean square error (RMSE), correlation coefficient (R2), mean absolute error (MAE), and variance accounted for (VAF) to evaluate the performance of each model. The sensitivity analysis of parameters that impact joints shear strength was conducted. Finally, the feasibility and limitations of this study were discussed. The results revealed that, in comparison to other models, the CSA-MLP model exhibited the most appropriate performance in terms of R2 (0.88), RMSE (0.19), MAE (0.15), and VAF (90.32%) values. The result of sensitivity analysis showed that the normal stress and the joint roughness coefficient were the most critical factors influencing joints shear strength. This paper presented an efficacious attempt toward swift prediction of joints shear strength, thus avoiding the need for costly in-site and laboratory tests.
The Huoshaoyun deposit in the Karakorum area of NW China is the world’s largest zinc-lead carbonate ore deposit. Here we investigate the genesis of the mineralization based on multiproxy investigations. The deposit contains zinc-lead carbonate and sulfide minerals, with smithsonite (Smt), cerussite (Cer), and sulfides accounting for 85%, 10%, and 5% of the total lead and zinc resources, respectively. Three ore-forming stages, involving Smt, Cer, and sulfides ores were summarized. The Smt mineralization is characterized by veined, massive, and stratified Smt forming horizontal sedimentary layered ore and vertical feeder veins similar to the SEDEX-type deposits. The sulfide and Cer veins display typical hydrothermal characteristics and are superimposed on the massive Smt ores. The Smt ores show high Li, Be, Cr, Y, Ba, Nd, Yb, and Zr contents, whereas the Cer veins have extremely high Sr contents (up to 3814–9174 ppm) and low Zr contents (less than 0.01 ppm). Galena and sphalerite show higher Cd concentrations compared to Smt and Cer ores.
Landslide inventory is an indispensable output variable of landslide susceptibility prediction (LSP) modelling. However, the influence of landslide inventory incompleteness on LSP and the transfer rules of LSP resulting error in the model have not been explored. Adopting Xunwu County, China, as an example, the existing landslide inventory is first obtained and assumed to contain all landslide inventory samples under ideal conditions, after which different landslide inventory sample missing conditions are simulated by random sampling. It includes the condition that the landslide inventory samples in the whole study area are missing randomly at the proportions of 10%, 20%, 30%, 40% and 50%, as well as the condition that the landslide inventory samples in the south of Xunwu County are missing in aggregation. Then, five machine learning models, namely, Random Forest (RF), and Support Vector Machine (SVM), are used to perform LSP. Finally, the LSP results are evaluated to analyze the LSP uncertainties under various conditions. In addition, this study introduces various interpretability methods of machine learning model to explore the changes in the decision basis of the RF model under various conditions. Results show that (1) randomly missing landslide inventory samples at certain proportions (10%–50%) may affect the LSP results for local areas. (2) Aggregation of missing landslide inventory samples may cause significant biases in LSP, particularly in areas where samples are missing. (3) When 50% of landslide samples are missing (either randomly or aggregated), the changes in the decision basis of the RF model are mainly manifested in two aspects: first, the importance ranking of environmental factors slightly differs; second, in regard to LSP modelling in the same test grid unit, the weights of individual model factors may drastically vary.
The Permian Fengcheng Formation of the Western Junggar region in the Southwestern Central Asian Orogenic Belt (CAOB) represents one of Earth’s oldest alkali lake deposits. Here, we present a comprehensive study of the stratigraphy, petrography, two-dimensional seismic data, U–Pb geochronology, and Hf isotope analysis of detrital zircons of this deposit. The results, in conjunction with published data, reflect the tectonic evolution of southwestern CAOB. The ages of detrital zircons indicate that the Fengcheng Formation deposition is inferred to have concluded the early Permian Kungurian. The Hf isotopes of detrital zircons indicate that the detritus for the Fengcheng Formation was derived from upper crustal magmatic sources. The West Junggar Basin preserves the records of three Paleozoic tectonic stages. The first stage occurred in the Early Paleozoic and involved intraoceanic subduction and arc-continent collision. The second stage involved the Carboniferous closure of the Junggar Ocean following successive filling of oceanic basins. The final stage occurred in the Early Permian and was related to intracontinental rifting and tectonic inversion. The results of comparing the comprehensive data of U–Pb ages and Hf isotopes of 2537 zircons from West Junggar, Tianshan and Altay show that the orogenic belts to the south of the CAOB experienced similar plate kinematics and vertical crustal growth in the Paleozoic.
High arsenic (As) groundwater is a global problem primarily originating from As-enriched sediments. The provenance (source) and release mechanisms (sinks) of high As sediment have been identified, but the source-sink transfer is poorly understood, especially the influence of geological and surface processes. In this study, we explore the roles of tectonic movement and Yellow River evolution in provenance formation processes and evaluate the combined effects of provenance and sediment age on the As content of aquifer sediments in the northern Hetao Basin of Inner Mongolia. Based on optically stimulated luminescence (OSL) and 14C dating and detrital zircon U-Pb, As content, and lithological analyses of a 400 m core, we reconstructed As changes over the last 160 ka. Our results show clay deposited in a paleo-lake during the Gonghe movement period in the late Pleistocene (∼100 ka B.P.) is enriched in As (31.8 μg/g) due to significant provenance contributions of the As-bearing Langshan Group under tectonic uplift and mountain erosion. In contrast, clay deposited in the middle Pleistocene (∼160 ka B.P.) has lower As content (7.3 μg/g) due to the Yellow River as the primary provenance. Accordingly, the provenance of basin As forced by tectonic uplift and Yellow River evolution determines the background As of aquifer sediments. After deposition, sediment As content decays over time, with higher decay rates in coarse-grained sands than fine-grained. Overall, both provenance formation and sediment age, representing initial and dynamic states of solid phase As, jointly determine the As content of aquifer sediments. More solid phase As provided by younger sediments from the proximal orogenic provenance and reducing conditions due to frequent river–lake transitions, jointly lead to higher As concentrations in shallow groundwater. The study highlights the potential for using a combined analysis of the tectonic movement-surface processes-environment system to improve understanding of geogenic high As groundwater over global large sedimentary basins in the proximity of young orogenic belts.
Flood disasters pose serious threats to human life and property worldwide. Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts. This study proposes a comprehensive framework for integrating driving-factor optimization and interpretability, while considering spatial heterogeneity. In this framework, the Optimal Parameter-based Geographic Detector (OPGD), Recursive Feature Estimation (RFE), and Light Gradient Boosting Machine (LGBM) models were utilized to construct the OPGD–RFE–LGBM coupled model to identify the essential driving factors and simulate the spatial distribution of flood disasters. The SHapley Additive ExPlanation (SHAP) interpreter was employed to quantitatively explain the driving mechanisms behind the spatial distribution of flood disasters. Yunnan Province, a typical mountainous and plateau area in Southwest China, was selected to implement the proposed framework and conduct a case study. For this purpose, a flood disaster inventory of 7332 historical events was prepared, and 22 potential driving factors related to precipitation, surface environment, and human activity were initially selected. Results revealed that flood disasters in Yunnan Province exhibit high spatial heterogeneity, with geomorphic zoning accounting for 66.1% of the spatial variation in historical flood disasters. The OPGD–RFE–LGBM coupled model offers clear advantages over a single LGBM in identifying essential driving factors and quantitatively analyzing their impacts. Moreover, the simulation performance shows a slight improvement (a 6% average decrease in RMSE and an average increase of 1% in R2) even with reduced factor data. Factor explanatory analysis indicated that the combination of the essential driving factor sets varied across different subregions; nevertheless, precipitation-related factors, such as precipitation intensity index (SDII), wet days (R10MM), and 5-day maximum precipitation (RX5day), were the main driving factors controlling flood disasters. This study provides a quantitative analytical framework for the spatial drivers of flood disasters at large scales with significant heterogeneity, offering a reference for disaster management authorities in developing macro-strategies for disaster prevention.
Landslide susceptibility assessment is crucial in predicting landslide occurrence and potential risks. However, traditional methods usually emphasize on larger regions of landsliding and rely on relatively static environmental conditions, which exposes the hysteresis of landslide susceptibility assessment in refined-scale and temporal dynamic changes. This study presents an improved landslide susceptibility assessment approach by integrating machine learning models based on random forest (RF), logical regression (LR), and gradient boosting decision tree (GBDT) with interferometric synthetic aperture radar (InSAR) technology and comparing them to their respective original models. The results demonstrated that the combined approach improves prediction accuracy and reduces the false negative and false positive errors. The LR-InSAR model showed the best performance in dynamic landslide susceptibility assessment at both regional and smaller scale, particularly when identifying areas of high and very high susceptibility. Modeling results were verified using data from field investigations including unmanned aerial vehicle (UAV) flights. This study is of great significance to accurately assess dynamic landslide susceptibility and to help reduce and prevent landslide risk.
A reconciliation of the disagreement on whether financial globalization (FG) affects ecological footprint through the scale, technique and composition effects cannot be achieved without an explicit understanding of the direct and indirect interactions of FG with environmental sustainability. Hence, the novel perspective of this study lies in the investigation of how green innovations moderate the non-linear tendencies in the FG-environmental sustainability link among western African states given the abundance of natural resources and the prevailing pace of economic growth. The core findings are obtained from robust analysis based on cross-sectional autoregressive distributed lag (CS-ARDL) technique, the augmented mean group (AMG) technique, and the common correlated effects mean group (CCEMG) advanced estimators. Firstly, the beneficial ecological impacts of green innovations were observed. As per direct impact, enhanced financial globalization (FG) exhibits non-linear detrimental ecological effects. However, green innovations cushion the observed adverse ecological effects of FG. Furthermore, resource rents reduce ecological footprint within the moderating framework of green innovation as the environmental Kuznets curve (EKC) is validated among the states. Additionally, a bidirectional causal link between financial globalization, green innovations, economic growth, natural resources, and ecological footprint was observed. Thus, the significant policy implication is for the West African states to decisively increase their investments in green innovations while strategically encouraging the share of ecologically friendly resources in total resource utilization to guarantee a more sustainable environment.
Shallow crustal faults are passive features mobilized by the dissipation of the potential energy and the shear stress accumulated in the brittle volume surrounding them. However, the stored energy in the volume differs from the tectonic setting, i.e., it is mainly gravitational in extensional tectonic settings, whereas it is elastic in strike-slip and contractional tectonic environments. In extensional settings, below about 1 km, the horizontal tensile stress is overwhelmed by the confining pressure of the lithostatic load, and it becomes positive, i.e. compressive. Therefore, there is no horizontal tension in extensional tectonic settings and the pro-gravity motion of the crustal volume is provided by the lithostatic load, which is the vertical maximum principal stress. The elastic energy is rather accumulated by the maximum horizontal principal stresses, i.e., iso-gravity in transcurrent settings and counter-gravity in contractional tectonic settings. The different relation with the gravitational force in the different tectonic settings generates several relevant differences in the three main tectonic environments. The extensional tectonic settings, both in continental and oceanic rift zones generate normal fault-related earthquakes, i.e., pro-gravity movements, or graviquakes. They differ from the other tectonic setting because are marked by (i) lower energy and lower differential stress to activate faults with respect to strike-slip and contractional tectonics; (ii) lower maximum earthquake magnitude; (iii) a larger number of low magnitude earthquakes in extensional settings because the crust moves downward as soon as it can move, whereas contractional settings require larger accumulation of energy to move counter-gravity; (iv) consequently, the b-value of the Gutenberg-Richter is higher than 1 and the aftershocks are more numerous and last longer in extensional settings; (v) the downward motion of the hangingwall determines more diffuse cataclastic deformation with respect to the other tectonic settings because the lithostatic load works everywhere, whereas in the other tectonic settings is concentrated where the elastic energy accumulates; (vi) in extensional settings the volume dimension is determined by thickness of the brittle layer, and its length is in average three times the seismogenic thickness; in strike-slip and contractional settings dominates the elastic energy (elastoquakes), and the mobilized volume may be ten to thirty times longer in a single seismic sequence, being its size proportional both to the brittle thickness and the relative speed of plates. These differences characterize the seismic cycle of graviquakes with respect to the elastoquakes. The bigger the volume, the wider the seismogenic fault in all tectonic settings. The interplay between the horizontal tectonic forces and the lithostatic load, which is ubiquitous, varies in the three main tectonic settings, generating different seismotectonic styles and an increase of magnitude as the effect of the vertical gravitational force becomes a minority relative to the elastic storage and coseismic rebound.
Green environmental technologies, renewable energy and globalization are interconnected pillars that impact economies and societies. By effectively fostering these resources, environmental policies can help achieve economic prosperity, sustainable development and environmental protection. The current study seeks to address environmental and economic predicaments by empirically examining the role of green technology and renewable energy in influencing the load capacity factor and ecological footprint with the highest ecological impact. Given that these nations are also significant players in the global economy, we also examine the impact of Globalization and economic growth within econometric investigation. The current study uses moments quantile regression (MMQR) as an econometric strategy to report that while innovations in green technology and renewable energy positively influence load factor capacity and help reduce ecological footprint, certain facets of globalization worsen the ecological footprint, thereby unsettling its load factor capacity. These findings underscore the pressing need for policymakers to prioritize integrating environmental and trade policy agreements to ensure progress towards long-term environmental goals.
As an essential property of frozen soils, change of unfrozen water content (UWC) with temperature, namely soil-freezing characteristic curve (SFCC), plays significant roles in numerous physical, hydraulic and mechanical processes in cold regions, including the heat and water transfer within soils and at the land–atmosphere interface, frost heave and thaw settlement, as well as the simulation of coupled thermo-hydro-mechanical interactions. Although various models have been proposed to estimate SFCC, their applicability remains limited due to their derivation from specific soil types, soil treatments, and test devices. Accordingly, this study proposes a novel data-driven model to predict the SFCC using an extreme Gradient Boosting (XGBoost) model. A systematic database for SFCC of frozen soils compiled from extensive experimental investigations via various testing methods was utilized to train the XGBoost model. The predicted soil freezing characteristic curves (SFCC, UWC as a function of temperature) from the well-trained XGBoost model were compared with original experimental data and three conventional models. The results demonstrate the superior performance of the proposed XGBoost model over the traditional models in predicting SFCC. This study provides valuable insights for future investigations regarding the SFCC of frozen soils.
Volatiles in the mantle are crucial for Earth’s geodynamic and geochemical evolution. Understanding the deep recycling of volatiles is key for grasping mantle chemical heterogeneity, plate tectonics, and long-term planetary evolution. While subduction transfers abundant volatile elements from the Earth’s surface into the mantle, the fate of hydrous portions within subducted slabs during intensive dehydration processes remains uncertain. Boron isotopes, only efficiently fractionating near the Earth’s surface, are valuable for tracing volatile recycling signals. In this study, we document a notably large variation in δ11B values (−14.3‰ to +8.2‰) in Cenozoic basalts from the South China Block. These basalts, associated with a high-velocity zone beneath East China, are suggested to originate from the mantle transition zone. While the majority exhibit δ11B values (−10‰ to −5‰) resembling the normal mantle, their enriched Sr-Nd-Pb isotope compositions and fluid-mobile elements imply hydrous components in their source, including altered oceanic crust and sediments. The normal δ11B values are attributed to the dehydration processes. Remarkably high δ11B values in the basalts indicate the presence of subducted serpentinites in their mantle source. A small subset of samples with low δ11B values and radiogenic isotope enrichments suggests a contribution from recycled detrital sediments, though retaining minimal volatile elements after extensive dehydration. These findings provide compelling evidence that serpentinites within subducted slabs predominantly maintain their hydrous nature during dehydration processes in subduction zones. They may transport a considerable amount of water into deep mantle reservoirs, such as the mantle transition zone.
The phenomenon of carbon isotopic fractionation, induced by the transport of methane in tight sedimentary rocks through processes primarily involving diffusion and adsorption/desorption, is ubiquitous in nature and plays a significant role in numerous geological and geochemical systems. Consequently, understanding the mechanisms of transport-induced carbon isotopic fractionation both theoretically and experimentally is of considerable scientific importance. However, previous experimental studies have observed carbon isotope fractionation phenomena that are entirely distinct, and even exhibit opposing characteristics. At present, there is a lack of a convincing mechanistic explanation and valid numerical model for this discrepancy. Here, we performed gas transport experiments under different gas pressures (1–5 MPa) and confining pressures (10–20 MPa). The results show that methane carbon isotope fractionation during natural gas transport through shale is controlled by its pore structure and evolves regularly with increasing effective stress. Compared with the carbon isotopic composition of the source gas, the initial effluent methane is predominantly depleted in 13C, but occasionally exhibits 13C enrichment. The carbon isotopic composition of effluent methane converges to that of the source gas as mass transport reaches a steady state. The evolution patterns of the isotope fractionation curve, transitioning from the initial non-steady state to the final steady state, can be categorized into five distinct types. The combined effect of multi-level transport channels offers the most compelling mechanistic explanation for the observed evolution patterns and their interconversion. Numerical simulation studies demonstrate that existing models, including the Rayleigh model, the diffusion model, and the coupled diffusion-adsorption/desorption model, are unable to describe the observed complex isotope fractionation behavior. In contrast, the multi-scale multi-mechanism coupled model developed herein, incorporating diffusion and adsorption/desorption across multi-level transport channels, effectively reproduces all the observed fractionation patterns and supports the mechanistic rationale for the combined effect. Finally, the potential carbon isotopic fractionation resulting from natural gas transport in/through porous media and its geological implications are discussed in several hypothetical scenarios combining numerical simulations. These findings highlight the limitations of carbon isotopic parameters for determining the origin and maturity of natural gas, and underscore their potential in identifying greenhouse gas leaks and tracing sources.
Reliability analysis plays an important role in the risk management of geotechnical engineering. For the random field-based method, it is expected that the uncertainty characterization of geo-material parameters and the realization of random field can be integrated effectively. Moreover, as the increase in measured data size is generally difficult in the field investigation of geotechnical engineering due to limitation of budget and time etc., the statistical uncertainty resulting from sparse data should be paid great attention. Therefore, taking the determination of hyper-parameters for Bayesian-based conditional random field as the breakthrough, this study proposed a reliability analysis framework to achieve the expectation above. In this proposed reliability analysis framework, the present characterization method of statistical uncertainty is improved by setting the lognormal distribution as the prior distribution of scale of fluctuation (SOF). Subsequently, the performance of statistical uncertainty characterization method is tested by a set of unconfined compressive strength (UCS) database about rocks. Then, a case study about the stability analysis of slope is employed to demonstrate the beneficial effect of the proposed reliability analysis framework. It is found that the uncertainty in both the realization of random field and the reliability analysis results can be significantly mitigated by the proposed reliability analysis framework.
In a paper in 1970, Brian Windley first recognised that early terrestrial and lunar anorthosites both have calcic plagioclase, and low TiO2 and high CaO and Al2O3 contents. Despite these similarities, the geochemistry of early terrestrial and lunar anorthosites has not been rigorously compared and contrasted. To this end, we compiled 425 analyses from 212 early terrestrial anorthosite occurrences and 306 analyses from 16 lunar anorthosite occurrences. This was supplemented by a compilation of plagioclase anorthite (An) contents and pyroxene Mg# from early terrestrial and lunar anorthosites. Early terrestrial anorthosites have lower whole-rock An contents but similar Mg# to lunar anorthosites. The CaO contents of lunar anorthosites are higher than those of early terrestrial anorthosites for a given MgO and Al2O3 content, early terrestrial anorthosites have higher SiO2 contents than lunar anorthosites at a given MgO content, and lunar anorthosites have higher Eu/Eu* anomaly ratios yet broadly similar La/Yb and Nd/Sm ratios than early terrestrial anorthosites. Some early terrestrial anorthosites have less fractionated chondrite-normalised rare earth element (REE) patterns and less prominent positive Eu anomalies than lunar anorthosites. Lunar anorthosites have higher plagioclase An contents, yet a similar range of pyroxene Mg# compared to their early terrestrial counterparts. Some early terrestrial anorthosites are more fractionated than some lunar anorthosites. Our interpretations imply that most early terrestrial anorthosites crystallised from basaltic parental magmas that were generated by high-degree partial melting of sub-arc asthenosphere mantle wedge sources that were hydrated by slab-derived fluids, with the remainder being associated with mid-ocean ridge and mantle plume settings. Some of the arc-related early terrestrial anorthosites were influenced by crustal contamination. In addition, early terrestrial anorthosites originated from partial melting of the mantle at various depths with variable garnet residua, whereas lunar anorthosites formed without any significant garnet residua. Lower plagioclase CaO contents and pyroxene Mg# in early terrestrial anorthosites can be explained by higher proportions of clinopyroxene and olivine fractionation in terrestrial magma chambers than in the lunar magma ocean where orthopyroxene and olivine fractionation occurred. Low TiO2 contents in both terrestrial and lunar anorthosites reflect rutile and/or ilmenite fractionation.
Water temperature is a critical indicator and weathervane of aquatic ecosystems. However, the vast majority of rivers lack long-term continuous and complete water temperature datasets. In this study, ensemble models by combining NARX (nonlinear autoregressive network with exogenous inputs) and air2stream were used to reconstruct daily river water temperatures for 27 hydrological stations in the Odra River Basin, one of the largest river systems in Europe. For each hydrological station, both the NARX and air2stream models were calibrated and validated, and the better-performed model was selected to reconstruct daily river water temperatures from 1985 to 2022. The results showed that hybrid modeling by combining NARX and air2stream is promising for reconstructing daily river water temperatures. Based on the reconstructed dataset, annual and seasonal trends of water temperature and characteristics of river heatwaves were evaluated. The results indicated that annual river water temperatures showed a consistent warming trend over the past 40 years with an average warming rate of 0.315 °C/decade. Seasonal river water temperatures indicated that summer warms faster, followed by autumn and spring, and winter river water temperatures showed an insignificant warming trend. River heatwaves are increased in frequency, duration, and intensity in the Odra River Basin, and 6 out of 27 hydrological stations have river heatwaves categorized as ‘severe’ and ‘extreme’, suggesting that mitigation measures are needed to reduce the impact of climate warming on aquatic systems. Moreover, results showed that air temperature is the major controller of river heatwaves, and river heatwaves tend to intensify with the warming of air temperatures.
Climate change is the most phenomenal challenge to humanity, and its roots are intervened with unsustainable industrialization, exercising overexploitation of natural resources. Therefore, the departure from non-renewable to renewables has become inevitable, though thought-provoking. In this respect, we explore how green energy transformation moderates the impacts of multifaceted natural resources on sustainable industrial development in the presence of other covariates involving technological progress, financial development, and economic progress. We compiled data from Group of Seven (G-7) members over the 1995−2018 period and applied panel quantile regression (PQREG) to capture the effects across varying levels of quantiles of sustainable industrial development. Results revealed a positive role of natural gas rents, while coal, forest, and total natural resource rents contributed adverse implications for sustainable industrial development. However, the green energy transformation proved to be the game changer because it not only directly induced sustainable industrial development improvement but also turned the unfavorable effects of coal, forest, and total natural resources into favorable ones by interacting with those multifaceted natural resources. Technological, financial, and economic progress supported sustainable industrial development in G-7 nations, particularly in members with existing middle and upper scales of sustainable industrial development. These findings are robust enough when subjected to different estimation tools. In light of these outcomes, the interaction between green energy transformation and natural resource policy is inevitably critical to attaining natural resource efficiency for sustainable industrial development. Therefore, it is imperative to establish a close policy coordination between advancing green energy technology and allocating natural resource revenue to achieve sustainable development goals (SDGs), with a particular emphasis on SDG-7 and SDG-13.
Understanding the tectono-magmatic evolution history of the Tengchong block is crucial for elucidating the formation of the Eastern Tethys tectonic domain. However, the correlation and evolution of the Tengchong block with the Sibumasu and Lhasa blocks is controversial during the Permian and Cretaceous. This study explores the information contained within magmatic rocks using big data and spatio-temporal analysis, providing quantitative constraints for the discussion of the tectono-magmatic evolution of the Tengchong block. To more accurately assess true magma activities and reduce errors caused by preservation and sampling processes, we utilized local singularity analysis to obtain the singularity index time-series. Correlation analysis of zircon ages and εHf(t) (correlation coefficient ≥ 0.5) values indicates that the Tengchong block is more similar to the Sibumasu block. Results from time-lagged cross-correlation analysis indicate that the Tengchong block and Sibumasu block exhibit a shorter lag in magmatic activities (3 Myr). Wavelet analysis reveals similar periods of collision-related magmatic activities (57 Myr and 43 Myr). Integrating evidence from paleontology and ophiolite belts, we propose that the Tengchong block co-evolved more closely with the Sibumasu block than with the Lhasa block, suggesting similar tectonic processes during the Early Permian to Early Cretaceous. Approximately 250–236 Ma, in the western Tengchong block, partial melting of the lower crust occurs due to crustal thickening. Around 219–213 Ma and 198–180 Ma, after the Tengchong block collided with the Eurasian continent, the subduction of the Meso-Tethys Ocean commenced. Around 130–111 Ma, the overall tectonic feature was a scissor-like closure of the Meso-Tethys Ocean from north to south.
Shale gas is being hailed as the green energy of the future due to high heating value, low carbon emissions, and large reserves. Gas content of shale is a key parameter for evaluating the shale gas potential and screening for the shale gas sweet spots. Although the concept of gas content has been well defined, obtaining a reliable gas content data still remains a challenge. A significant barrier is the method for evaluating the gas content. In this paper, we provide a review of the long-established and recently developed gas content evaluation methods. In the first part of this review article, the history of gas content evaluation methods is summarized since 1910s, relied on published and unpublished literatures as well as our own experiences. Then, the fundamental contents and concepts involved in gas content evaluation are introduced to provide a clear theoretical foundation for the methods. In the third part, eleven evaluation methods, including four direct methods and seven indirect methods, are systematically reviewed. In each method, its application to evaluating the gas content is presented, the key advances are highlighted, and the advantages and limitations are discussed. Finally, future directions are discussed to promote creative thinking across disciplines to develop new methods or improve current methods for evaluating the gas content more accurately and efficiently.
Understanding the intricate relationships between the solid Earth and its surface systems in deep time necessitates comprehensive full-plate tectonic reconstructions that include evolving plate boundaries and oceanic plates. In particular, a tectonic reconstruction that spans multiple supercontinent cycles is important to understand the long-term evolution of Earth’s interior, surface environments and mineral resources. Here, we present a new full-plate tectonic reconstruction from 1.8 Ga to present that combines and refines three published models: one full-plate tectonic model spanning 1 Ga to present and two continental-drift models focused on the late Paleoproterozoic to Mesoproterozoic eras. Our model is constrained by geological and geophysical data, and presented as a relative plate motion model in a paleomagnetic reference frame. The model encompasses three supercontinents, Nuna (Columbia), Rodinia, and Gondwana/Pangea, and more than two complete supercontinent cycles, covering ∼40% of the Earth’s history. Our refinements to the base models are focused on times before 1.0 Ga, with minor changes for the Neoproterozoic. For times between 1.8 Ga and 1.0 Ga, the root mean square speeds for all plates generally range between 4 cm/yr and 7 cm/yr (despite short-term fast motion around 1.1 Ga), which are kinematically consistent with post-Pangean plate tectonic constraints. The time span of the existence of Nuna is updated to between 1.6 Ga (1.65 Ga in the base model) and 1.46 Ga based on geological and paleomagnetic data. We follow the base models to leave Amazonia/West Africa separate from Nuna (as well as Western Australia, which only collides with the remnants of Nuna after initial break-up), and South China/India separate from Rodinia. Contrary to the concept of a “boring billion”, our model reveals a dynamic geological history between 1.8 Ga and 0.8 Ga, characterized by supercontinent assembly and breakup, and continuous accretion events. The model is publicly accessible, providing a framework for future refinements and facilitating deep time studies of Earth’s system. We suggest that the model can serve as a valuable working hypothesis, laying the groundwork for future hypothesis testing.
Despite the growing concern regarding post-mineralization thermo-tectonic processes in recent years, the relative roles in exhuming and preserving ore deposits remain highly controversial. This study presents new apatite fission track and (U-Th)/He data from the Xishimen iron skarn deposit in the Handan-Xingtai district, central North China Craton. Apatite fission track dating yielded central ages ranging from 88 ± 18 Ma to 125 ± 9 Ma, with mean confined track lengths varying between 11.9 ± 0.4 μm and 13.3 ± 0.2 μm. Integrated apatite (U-Th)/He dating provided ages of 42.5 ± 0.8 Ma to 48.1 ± 3.3 Ma. Our new data, combined with previous zircon U-Pb and potassium-bearing mineral 40Ar/39Ar ages, revealed three cooling episodes: very rapid cooling (100–140 °C/Ma) at ca. 130–120 Ma, a protracted slow cooling period (0.2–0.4 °C/Ma) at ca. 120–50 Ma, and moderate cooling (0.8–1.0 °C/Ma) since ca. 50 Ma. The initial rapid cooling phase was primarily attributed to post-magmatic thermal equilibration following the shallow emplacement of the Xishimen deposit. The subsequent cooling phases were controlled by uplift and exhumation processes. Our thermal models indicate an estimated total unroofing thickness of < 3 km, which is shallower than the emplacement depth of the ore deposit (3–5 km). This suggests significant potential for mineral exploration. Furthermore, a comprehensive review of preservation mechanisms for various ore deposits underscores the significant role of tectonics in both exhuming and preserving ore bodies.
Constraining the melting temperature of iron under Earth’s inner core conditions is crucial for understanding core dynamics and planetary evolution. Here, we develop a deep potential (DP) model for iron that explicitly incorporates electronic entropy contributions governing thermodynamics under Earth’s core conditions. Extensive benchmarking demonstrates the DP’s high fidelity across relevant iron phases and extreme pressure and temperature conditions. Through thermodynamic integration and direct solid–liquid coexistence simulations, the DP predicts melting temperatures for iron at the inner core boundary, consistent with previous ab initio results. This resolves the previous discrepancy of iron’s melting temperature at ICB between the DP model and ab initio calculation and suggests the crucial contribution of electronic entropy. Our work provides insights into machine learning melting behavior of iron under core conditions and provides the basis for future development of binary or ternary DP models for iron and other elements in the core.
In recent years, the characteristics and sources of fertile adakites has received considerable attention. As well, most recently the geodynamic environment of convergent margins subducting oceanic crust aiding arc formation, evolving to slab rollback, then slab break-off after collision (i.e. late- to post-collisional slab failure (arc-like magmatism) and transpression) has gained more recognition, although their relationship to each other has yet to be explored. The geochemical characteristics imply that adakites/adakite-like, in particular high-silica adakites (HSA), can form by partial melting of subducting hydrothermally altered oceanic crust in convergent plate boundary settings during the terminal stages of subduction, lithosphere thickening, and then failure (all late to post collisional), while the melting of the mantle wedge during subduction-related dehydration creates more typical calc-alkaline basalt-andesite-dacite-rhyolite series (ADR) to form intraoceanic island arc to intracontinental margin arc systems, before the collisional stage. HSAs are characterized by high-silica (SiO2 > 67 wt.%), Al2O3 > 15 wt.%, Sr > 300 ppm, Y<20 ppm, Yb < 1.8 ppm, and Nb ≤ 10 ppm, and MgO < 3 wt.%, with high Sr/Y (>50), and La/Yb (>10). Some specific geochemical features, such as high Mg# (ave 0.51), Ni (ave 924 ppm), and Cr (ave 36 ppm), in HSAs are typical, in contrast to calc-alkaline arcs, although both groups display similar but less pronounced negative anomalies of Nb, Ta, and Ti in primitive mantle-normalized trace element spider diagram profiles. These unique geochemical features are likely ascribed to the involvement of garnet, hornblende, and titanite either during partial melting of hydrous MORB-like oceanic crust with only minor assimilation and fractional crystallization (AFC) within the mantle and crustal during ascent in a transpressional collisional environment. Hypotheses for origin of HSA derivative from melting in convergent margins from young, hot oceanic plates subducting into the mantle is applicable to only some adakitic systems. The difference in geochemical characteristics of adakites compared to ADR, such as relative higher MgO, Cr, Cu, and Ni, are due to their slab source, as well as interaction of the slab-derived adakitic melts with overlying hot lithospheric mantle; altered oceanic slabs are also relatively rich in siderophile and other chalcophile elements, as well as sulfates and sulfides. HSA magmas related to slab failure have special geochemical properties, such as Sr/Y > 20, Nb/Y > 0.4, Ta/Yb > 0.3, La/Yb > 10, Gd/Yb > 2, and Sm/Yb > 2.5. Slightly higher Nb + Ta is due to high T melting of rutile. Varieties of Nb/Ta compared to silica are also significant in HSA as a result of slab failure (roll back to break-off). High T-P partial melting of the hydrothermally altered oceanic slab produces HSA with quite high activities of H2O, SO2, HCl, with chalcophile metals that remain incompatible at higher fO2 (low fH2); these situations happen in late- to post-collisional settings where the subducting oceanic crust experienced slab failure, resulting in advective heat addition to the system from upwelling asthenosphere. In such a slab failure setting, transpression and transtension play a significant role in the rapid emplacement of a high amount of fertile adakitic magmas through the subduction-modified lithosphere and crust into the upper crust. When oxidized slab melts interact with the subduction-modified lithospheric mantle, the resulting magmas stay oxidized, potentially contributing to the special conditions conducive to formation of porphyry Cu-Au mineralization.
The impact of reverse osmosis (RO) rejects in the groundwater presents a significant challenge in arid regions. This study collected groundwater samples, product water, and reverse osmosis brine (ROB) from evaporation ponds and analyzed them for major ions and trace elements. Test boreholes were drilled near the ROB site along the flow direction, and borehole sediment samples were collected. The samples were predominantly gravelly sand, and the depth to water level fluctuated around 30 m below ground level (bgl), with minerals mainly consisting of calcite, gypsum, and quartz. Data loggers reflected a rise in water level (<22 m bgl) corresponding to higher electrical conductivity (>16 mS/cm) during the cropping period in many locations, confirming the impact of ROB in groundwater. The results were further supported by enriched signatures of δ18O (∼ +1.5‰) and δ2H (∼ +15‰). The saturation index of the minerals reflected that carbonate minerals (Calcite > Dolomite) were saturated in the ROB relative to the groundwater. The vertical variation of mineral assemblages in the boreholes indicated gypsum precipitation in the capillary zone along with calcite and dolomite. The assemblage varies as the groundwater moves from the disposal site. The speciation of different compounds along the groundwater path indicated higher carbonate and sulfate species (CaCO3 > CaHCO3> CaSO4 > NaSO4 > MgSO4) near the disposal site, with variations along the flow direction. Considering the significant variation in temperature in the region (5 to 50 ℃), the water sample composition was modeled using PHREEQC, suggesting that the increase in temperature led to supersaturation of epsomite and gypsum compositions. The ROB was theoretically mixed with groundwater and product water in different proportions, and an optimum composition (10:90) for safe disposal was derived and tested fit for reuse in agriculture.
Uncertainty can affect both macroeconomic indicators and the environment. Countries are implementing various energy policies to combat global warming, but these policies contain some uncertainties and contradictions. The environmental impact of uncertainties in energy policies is a research topic that has just begun to be investigated by researchers. This study examines the effects of energy policy uncertainty (ENERPU) on renewable energy R&D (RR&D), energy efficiency R&D (EER&D) and renewable energy consumption in the four countries with the highest RR&D expenditures (USA, Germany, Japan, and Spain). The study uses the novel multivariate quantile-on-quantile (M-QQR) approach from 2003m1 to 2022m9. The results of the study show: (i) The impact of ENERPU varies by quantile and country. (ii) ENERPU causes a decrease in renewable energy consumption and hinders RR&D expenditures. (iii) ENERPU increases EER&D. The Fourier quantile causality test confirms the robustness of the empirical results. Based on these findings, policymakers are recommended to minimize ENERPU and implement stable energy policies to develop the renewable energy sector and technologies.
Due to limited spatial and temporal in-situ runoff data availability, Himalaya-Karakoram (HK) glaciohydrology has a significant knowledge gap between large-scale and small-scale runoff modelling studies. This study reconstructs longest basin-wide runoff series in Chandra-Bhaga Basin by applying a high-resolution glaciohydrological model SPHY (Spatial Processes in Hydrology) over 1950–2022. Two-tier model calibration is done using in-situ basin-wide runoff (1973–2006) and MODIS snow cover (2003–2018). Model validation is done against in-situ Chhota Shigri Glacier catchment-wide runoff (2010–2015). The modelled mean annual basin-wide runoff is 60.21 ± 6.17 m3/s over 1950–2022, with maximum runoff in summer-monsoon months, peaking in July (182.69 m3/s). Glacier runoff (ice melt + snowmelt over glacier) contributes maximum (39%) followed by equal contributions from snowmelt runoff from non-glacierized basin area and baseflow (25%), while rainfall-runoff contributes minimum (11 %) to total runoff. There is a significant volumetric increase by ∼7% from pre- (59.17 m3/s) to post-2000 (63.47 m3/s) mainly because of early onset of snowmelt post-2000 that resulted in a hydrograph shift by ∼25 days earlier in spring. The glacier runoff is overestimated by 3% from RGI 7.0 inventory compared to different manually delineated inventories over 1950–2022, because of higher glacierized area from RGI 7.0. The precipitation shows a negative trend, but total runoff shows a positive trend due to positive trend of temperature that resulted in more glacier runoff and rainfall-runoff for basin over last 72 years. Basin-wide runoff is mainly governed by summer temperature which directly controls the amount of glacier and snowmelt runoffs and is supported by summer rainfall. This study highlights importance of basin-scale model calibration with in-situ data in large scale studies and stresses the need for in-situ observations in high-altitude Himalayan region. Basin-scale calibrated model parameters are transferable to glacier catchment scale within Chandra-Bhaga Basin, showing the model robustness at a small catchment scale.
