Geoscience frontiers最新文献

The Neoarchean Storø Supracrustal Belt in SW Greenland comprises a sequence of mature quartzite, metapelite, amphibolite, and ultramafic rocks that underwent amphibolite facies metamorphism during the amalgamation of the Mesoarchean Akia Terrane and the Eoarchean Færingehavn Terrane. In this belt, tourmaline is found in a transition zone between ultramafic and metapelitic rocks, but also occurs as orbicules within the ultramafic rocks. These tourmaline orbicules hosted by ultramafic rocks are reported for the first time in the North Atlantic craton, thus indicating a unique formation mechanism. We conducted a comprehensive examination of the petrology, whole-rock and mineral chemistry, and oxygen isotope compositions from borehole samples in the Storø Supracrustal Belt, to elucidate the metasomatic events associated with the formation of the orbicular tourmalines. The Storø ultramafic rocks have high MgO, Cr, and Ni contents, with low abundances of REE and HFSE, and preserve a typical cumulate texture. These features are similar to those of ultramafic cumulates found in other Archean supracrustal belts, suggesting a cumulate origin for the Storø ultramafic rocks. Furthermore, the morphology and composition of the tourmaline orbicules within these cumulates indicate that they originated from melts with high boron and high water concentrations that infiltrated the ultramafic rocks. The main factor influencing the morphology of the tourmaline orbicules is the silicification of the ultramafic rocks, driven by their lower chemical potential of SiO₂ compared to the surrounding rocks. This silicification process, in combination with compositional variations of cumulates during fractional crystallization, has contributed to the geochemical diversity observed in Archean ultramafic rocks. Thus, it is crucial to understand the effects of such selective metasomatism on Archean ultramafic rocks, as this will facilitate the extraction of original information preserved in the early rock record.

Carbon isotopes have been used extensively in tracing the sources of oil. However, primary source facies and secondary alteration controls on oil isotopic compositions have not been well resolved, resulting in application uncertainties. A case study was undertaken for an alkaline lacustrine oil system in a lower Permian formation in the Junggar Basin, NW China. Results indicate that increasing maturity causes the carbon isotopic composition to become heavier for only short–middle-chain compounds, whereas source facies-related carbon assimilation controls the compositions of short-, middle-, and long-chain compounds. In particular, light-carbon assimilation during organic-matter degradation makes the isotopic composition lighter, whereas heavy carbon from the water mass makes it heavier. Accordingly, oils in this study area were divided into Type U and Type N oils based on individual compound carbon isotopic compositions, reflecting the difference in source facies in a highly saline and reducing stratified water environment. The results provide a better understanding of the controls on carbon isotopes in oil in sedimentary basins, reducing the uncertainty in oil–source correlation and addressing the origin of oil.

The hydro-geochemistry and isotopic variations in groundwater, coupled with sediment geochemistry, were investigated in the Middle Gangetic Plain, India, to better understand the aquifer dynamics that influence the arsenic (As) evolution and mobilization. Eighty-four groundwater samples, thirteen River water samples, and two sediment cores (33 mbgl) were studied. The samples were analyzed for major ions and trace metals, including As and stable isotopic variability (δ²H, δ¹⁸O, and δ¹³C). The study area was categorized into older and younger alluvium based on existing geomorphological differences. Younger alluvium exhibits higher As enrichment in sediment and groundwater, ranging of 2.59–31.52 mg/kg and bdl to 0.62 mg/L. Groundwater samples were thermodynamically more stable with As(OH)₃ species ranging from 88.5% to 91.4% and FeOOH from 69% to 81%, respectively. PHREEQC and mineralogical analysis suggested goethite and siderite act as a source and sink for As. However, statistical analysis suggested reductive dissolution as the primary mechanism for As mobilization in the study area. Spatio-temporal analysis revealed elevated concentrations of As in the central and northeastern regions of the study area. Stable isotope (δ²H and δ¹⁸O) analysis inferred active recharge conditions primarily driven by precipitation. The depleted d-excess value and enriched δ¹⁸O in the groundwater of younger alluvium indicate the effect of groundwater recharge with significant evaporation enrichment. Groundwater recharge potentially decreased the quantity of arsenic in groundwater, whereas evaporation enrichment increased it. Rainwater infiltration during recharge introduces oxygenated water into the aquifer, leading to changes in the redox conditions and facilitating biogeochemical reactions. The carbon isotope (δ¹³C) results suggest that high microbial activity in younger alluvium promotes As leaching from sediment into the groundwater.

Economic growth has brought a global climate change into the spotlight, and CO₂ emissions demonstrate significant challenges in reducing environmental shifts worldwide. Globally, the United States and China contribute the largest amount of CO₂ emissions. The purpose of this study is to examine the relationship between different types of CO₂ emissions and economic growth by using a modeling approach. We analyze total CO₂ emissions, coal CO₂ emissions, oil CO₂ emissions, the global share of coal CO₂ emissions, the global share of oil CO₂ emissions, and economic growth. This study provides unique insights into how to simultaneously reduce CO₂ emissions and sustain economic growth. A bootstrap autoregressive distributed lag (BARDL) simulation method is utilized to examine the long- and short-run effects of predictors on CO₂ emissions. Coal CO₂ emissions are found to have a significant positive effect on economic growth in the short run but a negative impact on economic growth over the long run in the United States. The United States needs to implement stronger measures to balance coal CO₂ emissions with economic growth for sustainable development. In contrast, oil CO₂ emissions have positive effect for China in both the long run and short run. Thus, China can continue to reduce CO₂ emissions from oil while maintaining positive economic growth. The China's policies promoting cleaner energy alternatives can be adapted and implemented to maintain a balance between economic growth and carbon reduction. The study has valuable insights for policymakers seeking to balance economic growth with carbon reduction strategies. It emphasizes the need to better understand the complex relationship between CO₂ emissions and economic growth.

Countries face the risk of natural resource curse because of making their economic growth excessively dependent on natural resources. Although excessive resource dependence causes such a risk, it is inevitable that resource-rich countries will need resource rent up to a certain level of economic maturity. On the other hand, transferring the wealth achieved after this maturity level to productive investment areas also reduces the resource dependency levels of countries. In this context, countries that capture the possible inverted U-shaped relationship between economic growth and resource dependence can escape the curse. Based on this, the aim of this research is to determine the validity of the Kuznets type relationship between resource dependence and economic growth for the first time in the literature. Nine nations that rely heavily on natural resources are used as a sample for this. The countries with a share of total resource rent in national revenue greater than 25% are taken into consideration throughout the selection process for these countries. Using novel panel data methodologies, the effects of capital accumulation, public spending, foreign direct investment, and economic growth on the dependence on natural resources is examined from 1993 to 2021. The results reveal that capital accumulation reduces resource dependency while foreign investments and government size increases it. In addition, the Resource-Based Kuznets curve concept is supported by empirical data demonstrating an inverted-U-shaped relationship between economic growth and resource dependence for these nations. The thresholds derived from the parameters show that Saudi Arabia and Kazakhstan are well beyond this cutoff. The Democratic Republic of the Congo and the Republic of the Congo, on the other hand, remain a long way from this threshold. Furthermore, Iraq, Mongolia, Iran, and Azerbaijan have national incomes that are close at the threshold.

Covered by erodible loess and affected by significant seasonal climate variations, chemical weathering in the Chinese Loess Plateau (abbreviated as CLP) has important effects on the hydrochemistry of the Yellow River and the global carbon cycle. However, chemical weathering processes in the CLP are still unclear. Based on 296 river water samples in the CLP in the different seasons, hydrochemistry, weathering processes, and their controlling factors were revealed. River waters in the CLP exhibited slightly alkalinity (pH = 8.4 ± 0.5) with much high total dissolved solids (TDS) values (691 ± 813 mg/L). The water types of river water in the CLP were primarily SO₄²⁻ − Cl⁻ − Na⁺, HCO₃⁻ − Ca²⁺ − Mg²⁺, and SO₄²⁻ − Cl⁻ − Ca²⁺ − Mg²⁺. According to the forward model, evaporite dissolution has the largest contribution (55.1% ± 0.2%) to riverine solutes in the CLP, then followed by carbonate weathering (35.6% ± 0.2%) and silicate weathering (6.5% ± 0.1%). For spatio-temporal variations, the contribution of evaporite dissolution in the CLP decreased from northwest to southeast with higher proportion in the dry season, carbonate weathering increased from northwest to southeast with a higher proportion in the wet season, and silicate weathering showed minor spatio-temporal variations. Ca²⁺ and Mg²⁺ were affected by carbonate precipitation and/or incongruent calcite dissolution, and about 50% of samples exhibited cation exchange reactions. The physical erosion rate in the CLP, which was 372 ± 293 t·km⁻²·yr⁻¹, varied greatly and was greater than those of other worldwide rivers. Chemical weathering rates in the CLP showed an increasing trend southward. During the wet season, high runoff led to the release of evaporite and carbonate from loess, while the interfacial reaction kinetic limited the increase of the silicate weathering rates. The CO₂ consumption budget by carbonate weathering (6.1 × 10¹⁰ mol/yr) and silicate weathering (1.6 × 10¹⁰ mol/yr) in the CLP accounted for 0.29% and 0.08% of the global carbon cycle, respectively. Meanwhile, the weathering proportion by sulfuric acids was relatively high with a CO₂ release flux of 6.5 × 10⁹ mol/yr. By compiling the data, we propose that the interfacial reaction kinetic and runoff control CO₂ consumption rate by silicate and carbonate weathering, respectively. These results contribute to the understanding of modern weathering processes of loess in the CLP, thus helping to deduce the environmental and climatic evolution of the basin.

The Middle Paleozoic tectonic evolution of the central Korean Peninsula (Gyeonggi Massif, Hongseong-Imjingang, and Okcheon zone of Okcheon Belts) remains controversial. Particularly, the occurrence of high-grade metamorphism and sedimentation need further examination. In this study, we conducted zircon U-Pb-rare earth element analyses from in the ultramafic-mafic complex in the central Korean Peninsula (Cheonan and Gapyeong areas) and the Paleozoic metasedimentary rocks in the Okcheon Zone of the Okcheon Belt to constrain the timing of maximum depositional and metamorphic ages. We also examined the metamorphic P-T-t path from garnet-bearing amphibolite in the central Korean Peninsula by pseudosection modeling and geothermobarometer. The results show that (i) some of the ultramafic-mafic complex and metasedimentary rocks in the central Korean Peninsula formed during the Middle Paleozoic (ca. 450–374 Ma); (ii) garnet-bearing amphibolite underwent successive metamorphism from amphibolite facies condition (7.5–8.0 kbar and 540–630 °C) at pre-peak stage to granulite facies condition (10.9–11.8 kbar and 740–820 °C) at peak stage, and then retrograded into amphibolite facies condition (5.7–7.7 kbar and 530–670 °C) along the clockwise P–T path during ca. 403–362 Ma. This and previous studies suggest that the central Korean Peninsula underwent subduction-related orogenic events during the Middle Paleozoic era, and it is well correlated to those of the orogenic events in the North Qinling belt.

Earthquakes pose significant risks globally, necessitating effective seismic risk mitigation strategies like earthquake early warning (EEW) systems. However, developing and optimizing such systems requires thoroughly understanding their internal procedures and coverage limitations. This study examines a deep-learning-based on-site EEW framework known as ROSERS (Real-time On-Site Estimation of Response Spectra) proposed by the authors, which constructs response spectra from early recorded ground motion waveforms at a target site. This study has three primary goals: (1) evaluating the effectiveness and applicability of ROSERS to subduction seismic sources; (2) providing a detailed interpretation of the trained deep neural network (DNN) and surrogate latent variables (LVs) implemented in ROSERS; and (3) analyzing the spatial efficacy of the framework to assess the coverage area of on-site EEW stations. ROSERS is retrained and tested on a dataset of around 11,000 unprocessed Japanese subduction ground motions. Goodness-of-fit testing shows that the ROSERS framework achieves good performance on this database, especially given the peculiarities of the subduction seismic environment. The trained DNN and LVs are then interpreted using game theory-based Shapley additive explanations to establish cause-effect relationships. Finally, the study explores the coverage area of ROSERS by training a novel spatial regression model that estimates the LVs using geographically weighted random forest and determining the radius of similarity. The results indicate that on-site predictions can be considered reliable within a 2–9 km radius, varying based on the magnitude and distance from the earthquake source. This information can assist end-users in strategically placing sensors, minimizing blind spots, and reducing errors from regional extrapolation.