2021 Vol. 12, No. 6
As one of the fastest growing economies and further larger consumer of energy in the world, there has been a paradigm shift in India’s energy demand. Here we evaluate the growth of Indian economy its, diversification of agriculture-based economy to industrial production, service and digital-technology based economy and deepening of income sources, although the dependence on foreign sources for energy demands has not markedly improved. This situation has placed India at the crossroads for energy sufficiency, especially under the highly fluid and changing geopolitical, strategic, environmental and economic scenarios of the World order. We attempt to understand the issue from geological perspective and address some of the impediments.
Reliable 3D modelling of underground hydrocarbon reservoirs is a challenging task due to the complexity of the underground geological formations and to the availability of different types of data that are typically affected by uncertainties. In the case of geologically complex depositional environments, such as fractured hydrocarbon reservoirs, the uncertainties involved in the modelling process demand accurate analysis and quantification in order to provide a reliable confidence range of volumetric estimations. In the present work, we used a 3D model of a fractured carbonate reservoir and populated it with different lithological and petrophysical properties. The available dataset also included a discrete fracture network (DFN) property that was used to model the fracture distribution. Uncertainties affecting lithological facies, their geometry and absolute positions (related to the fault system), fracture distribution and petrophysical properties were accounted for. We included all different types of uncertainties in an automated approach using tools available in today’s modelling software packages and combining all the uncertain input parameters in a series of statistically representative geological realizations. In particular, we defined a specific workflow for the definition of the absolute permeability according to an equivalent, single porosity approach, taking into account the contribution of both the matrix and the fracture system. The results of the analyses were transferred into a 3D numerical fluid-dynamic simulator to evaluate the propagation of the uncertainties associated to the input data down to the final results, and to assess the dynamic response of the reservoir following a selected development plan. The “integrated approach” presented in this paper can be useful for all technicians involved in the construction and validation of 3D numerical models of hydrocarbon-bearing reservoirs and can potentially become part of the educational training for young geoscientists and engineers, since an integrated and well-constructed workflow is the backbone of any reservoir study.
Crushing and embedment are two critical downhole proppant degradation mechanisms that lead to a significant drop in production outputs in unconventional oil/gas stimulation projects. These persistent production drops due to the non-linear responses of proppants under reservoir conditions put the future utilization of such advanced stimulation techniques in unconventional energy extraction in doubt. The aim of this study is to address these issues by conducting a comprehensive experimental approach. According to the results, whatever the type of proppant, all proppant packs tend to undergo significant plastic deformation under the first loading cycle. Moreover, the utilization of ceramic proppants (which retain proppant pack porosity up to 75%), larger proppant sizes (which retain proppant pack porosity up to 15.2%) and higher proppant concentrations (which retain proppant pack porosity up to 29.5%) in the fracturing stimulations with higher in-situ stresses are recommended to de-escalate the critical consequences of crushing associated issues. Similarly, the selection of resin-coated proppants over ceramic and sand proppants may benefit in terms of obtaining reduced proppant embedment. In addition, selection of smaller proppant sizes and higher proppant concentrations are suggested for stimulation projects at depth with sedimentary formations and lower in-situ stresses where proppant embedment predominates. Furthermore, correlation between proppant embedment with repetitive loading cycles was studied. Importantly, microstructural analysis of the proppant-embedded siltstone rock samples revealed that the initiation of secondary induced fractures. Finally, the findings of this study can greatly contribute to accurately select optimum proppant properties (proppant type, size and concentration) depending on the oil/gas reservoir characteristics to minimize proppant crushing and embedment effects.
Methane hydrate in the South China Sea (SCS) has extensively been considered to be biogenic on the basis of its δ13C and δD values. Although previous efforts have greatly been made, the contribution of thermogenic oil/gas has still been underestimated. In this study, biomarkers and porewater geochemical parameters in hydrate-free and hydrate-bearing sediments in the Taixinan Basin, the SCS have been measured for evaluating the contribution of petroleum hydrocarbons to the formation of hydrate deposits via a comparative study of their source inputs of organic matters, environmental conditions, and microbial activities. The results reveal the occurrence of C14–C16 branched saturated fatty acids (bSFAs) with relatively high concentrations from sulfate-reducing bacteria (SRBs) in hydrate-bearing sediments in comparison with hydrate-free sediments, which is in accord with the positive δ13C values of dissolved inorganic carbon (DIC), increasing methane concentrations, decreasing alkalinity, and concentration fluctuation of ions (Cl−, Br−, SO42−, Ca2+, and Mg2+). These data indicate the relatively active microbial activities in hydrate-bearing sediments and coincident variations of environmental conditions. Carbon isotope compositions of bSFAs (−34.0‰ to −21.2‰), n-alkanes (−34.5‰ to −29.3‰), and methane (−70.7‰ to −69.9‰) jointly demonstrate that SRBs might thrive on a different type of organic carbon rather than methane. Combining with numerous gas/oil reservoirs and hydrocarbon migration channels in the SCS, the occurrence of unresolved complex mixtures (UCMs), odd-even predominance (OEP) values (about 1.0), and biomarker patterns suggest that petroleum hydrocarbons from deep oil/gas reservoirs are the most probable carbon source. Our new results provide significant evidence that the deep oil/gas reservoirs may make a contribution to the formation of methane hydrate deposits in the SCS.
Efflorescent nanophases (NPs) are found as a transitory accumulation of potentially hazardous elements (PHEs), particularly in tropical climates. The central objective of this study was to investigate the distribution of PHEs with NPs through the evaporative formation structures (EFS) of enormously PHEs-rich coal-mine drainages (CMD). The EFS were studied in natural coal mine drainage for five months in order to determine their geochemical and ecological structures and to assess their position in the reduction of PHEs in nature. The largest coal-fired power plant in South America, located in south Brazil, is used as an example of such a problem. In this work, a novel methodology for the analysis of PHEs in CMD precipitates is proposed for this affected coal area. The analytical method, combining X-Ray Diffraction (XRD) and advanced electron microscopies, shows the importance of nanomineralogy in understanding different circumstances of coal contamination. Several ultrafine-nanoparticles (UNPs) were identified in the sampled soils and river sediments together with the PHEs. A decrease in PHEs was identified in association with UNPs. However, further investigations are required with regard to the mobility of PHEs in water, atmosphere, soils, and sediments. The EPS was thoroughly studied, acquiring suitable understanding with investigational facts for Ca and Fe-sulphates, pickeringite, and several amorphous phases.
Marine controlled source electromagnetic (CSEM) data have been utilized in the past decade during petroleum exploration of the Barents Shelf, particularly for de-risking the highly porous sandstone reservoirs of the Upper Triassic to Middle Jurassic Realgrunnen Subgroup. In this contribution we compare the resistivity response from CSEM data to resistivity from wireline logs in both water- and hydrocarbon-bearing wells. We show that there is a very good match between these types of data, particularly when reservoirs are shallow. CSEM data, however, only provide information on the subsurface resistivity. Careful, geology-driven interpretation of CSEM data is required to maximize the impact on exploration success. This is particularly important when quantifying the relative resistivity contribution of high-saturation hydrocarbon-bearing sandstone and that of the overlying cap rock. In the presented case the cap rock comprises predominantly organic rich Upper Jurassic–Early Cretaceous shales of the Hekkingen Formation (i.e. a regional source rock). The resistivity response of the reservoir and its cap rock become merged in CSEM data due to the transverse resistance equivalence principle. As a result of this, it is imperative to understand both the relative contributions from reservoir and cap rock, and the geological significance of any lateral resistivity variation in each of the units. In this contribution, we quantify the resistivity of organic rich mudstone, i.e. source rock, and reservoir sandstones, using 131 exploration boreholes from the Barents Shelf. The highest resistivity (>10,000 Ωm) is evident in the hydrocarbon-bearing Realgrunnen Subgroup which is reported from 48 boreholes, 43 of which are used for this study. Pay zone resistivity is primarily controlled by reservoir quality (i.e. porosity and shale fraction) and fluid phase (i.e. gas, oil and water saturation). In the investigated wells, the shale dominated Hekkingen Formation exhibits enhanced resistivity compared to the background (i.e. the underlying and overlying stratigraphy), though rarely exceeds 20 Ωm. Marine mudstones typically show good correlation between measured organic richness and resistivity/sonic velocity log signatures. We conclude that the resistivity contribution to the CSEM response from hydrocarbon-bearing sandstones outweighs that of the organic rich cap rocks.
CO2 can be used as an alternative injectant to exploit geothermal energy from depleted high-temperature gas reservoirs due to its high mobility and unique thermal properties. However, there has been a lack of systematic analysis on the heat mining mechanism and performance of CO2, as well as the problems that may occur during geothermal energy exploitation at specific gas reservoir conditions. In this paper, a base numerical simulation model of a typical depleted high-temperature gas reservoir was established to simulate the geothermal energy exploitation processes via recycling CO2 and water, with a view to investigate whether and/or at which conditions CO2 is more suitable than water for geothermal energy exploitation. The problems that may occur during the CO2-based geothermal energy exploitation were also analyzed along with proposed feasible solutions. The results indicate that, for a depleted low-permeability gas reservoir with dimensions of 1000 m × 500 m × 50 m and temperature of 150 °C using a single injection-production well group for 40 years of operation, the heat mining rate of CO2 can be up to 3.8 MW at a circulation flow rate of 18 kg s−1 due to its high mobility along with the flow path in the gas reservoir, while the heat mining rate of water is only about 2 MW due to limitations on the injectivity and mobility. The reservoir physical property and injection-production scheme have some effects on the heat mining rate, but CO2 always has better performance than water at most reservoir and operation conditions, even under a high water saturation. The main problems for CO2 circulation are wellbore corrosion and salt precipitation that can occur when the reservoir has high water saturation and high salinity, in which serious salt precipitation can reduce formation permeability and result in a decline of CO2 heat mining rate (e.g. up to 24% reduction). It is proposed to apply a low-salinity water slug before CO2 injection to reduce the damage caused by salt precipitation. For high-permeability gas reservoirs with high water saturation and high salinity, the superiority of CO2 as a heat transmission fluid becomes obscure and water injection is recommended.
The capability of accurately predicting mineralogical brittleness index (BI) from basic suites of well logs is desirable as it provides a useful indicator of the fracability of tight formations. Measuring mineralogical components in rocks is expensive and time consuming. However, the basic well log curves are not well correlated with BI so correlation-based, machine-learning methods are not able to derive highly accurate BI predictions using such data. A correlation-free, optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation (Texas). This transparent open box (TOB) algorithm matches data records by calculating the sum of squared errors between their variables and selecting the best matches as those with the minimum squared errors. It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error (RMSE) between calculated and predicted (BI). The prediction accuracy achieved by TOB using just five well logs (Gr, ρb, Ns, Rs, Dt) to predict BI is dependent on the density of data records sampled. At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE ~ 0.056 and R2 ~ 0.790. At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE ~ 0.008 and R2 ~ 0.995. Adding a stratigraphic height index as an additional (sixth) input variable method improves BI prediction accuracy to RMSE ~ 0.003 and R2 ~ 0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of > ± 0.1. The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measurements but with similar lithofacies and burial histories. The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.
Submarine groundwater discharge (SGD) is being increasingly recognized as a significant source of nutrient into coastal waters, and generally comprises two components: submarine fresh groundwater discharge (SFGD) and recirculated saline groundwater discharge (RSGD). The separate evaluation of SFGD and RSGD is extremely limited as compared to the conventional estimation of total SGD and associated nutrient fluxes, especially in marginal-scale regions. In this study, new high-resolution radium isotopes data in seawater and coastal groundwater enabled an estimation of SGD flux in a typical marginal sea of the Yellow Sea. By establishing 226Ra and 228Ra mass balance models, we obtained the SGD-derived radium fluxes, and then estimated the SFGD and RSGD fluxes through a two end-member model. The results showed that the total SGD flux into the Yellow Sea was equivalent to approximately 6.6 times the total freshwater discharge of surrounding rivers, and the SFGD flux accounted for only 5.2%–8.8% of the total SGD. Considering the nutrient concentrations in coastal fresh and saline groundwater, we obtained the dissolved inorganic nutrient fluxes (mmol m−2 yr−1) to be 52–353 for nitrogen (DIN), 0.21–1.4 for phosphorus (DIP), 34–226 for silicon (DSi) via SFGD, and 69–262 for DIN, 1.0–3.9 for DIP, 70–368 for DSi via RSGD, with the sum of nutrient fluxes equaling to (1.8–9.3)-fold, (1.3–5.6)-fold and (2.0–9.5)-fold of the riverine inputs. Compared to the conventional estimation of the total SGD flux, the nutrient fluxes derived from the separation of SFGD and RSGD were (1.6–2.1), (1.6–1.8) and (4.0–4.9) times lower for DIN, DIP and DSi, respectively, indicating that the estimates by separating SFGD and RSGD could be conservative and representative results of the Yellow Sea. Furthermore, we suggested that SGD played an important role in nutrient sources among all the traditional nutrient inputs sources, providing 15%–48%, 33%–68% and 14%–43% of the total DIN, DIP and DSi input fluxes into the Yellow Sea, and the high nutrient stoichiometric ratios (i.e., DIN/DIP) in SGD probably contributed to the increasing ratios in the Yellow Sea. In addition delivering large amounts of nutrient into the Yellow Sea, SGD would create primary productivity of 10–49, 1.6–6.8 and 8.8–42 g C m−2 yr−1 based on N, P and Si, which were equivalent to 5.2%–27%, 0.9%–3.7% and 4.7%–23% of the total primary productivity, respectively. In particular, the SFGD-derived DIN flux can be converted to primary productivity of 4.2–28 g C m−2 yr−1 thus demonstrating the disproportionately large role of SFGD in ecological environment of the Yellow Sea relative to its flux. Therefore, we conclude that SGD, particularly SFGD, plays an important role as a nutrient source for the Yellow Sea, and not only affects nutrient budgets and structures but also enhances the primary productivity.
Bangladesh experiences frequent hydro-climatic disasters such as flooding. These disasters are believed to be associated with land use changes and climate variability. However, identifying the factors that lead to flooding is challenging. This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation (BRBP) neural network, classification and regression trees (CART), a statistical model (STM) using the evidence belief function (EBF), and their ensemble models (EMs) for three time periods (2000, 2014, and 2017). The accuracy of machine learning algorithms (MLAs), STM, and EMs were assessed by considering the area under the curve—receiver operating characteristic (AUC-ROC). Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4 (BRBP-CART-EBF) outperformed (AUC > 90%) standalone and other ensemble models for the three time periods analyzed. Furthermore, this study investigated the relationships among land cover change (LCC), population growth (PG), road density (RD), and relative change of flooding (RCF) areas for the period between 2000 and 2017. The results showed that areas with very high susceptibility to flooding increased by 19.72% between 2000 and 2017, while the PG rate increased by 51.68% over the same period. The Pearson correlation coefficient for RCF and RD was calculated to be 0.496. These findings highlight the significant association between floods and causative factors. The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.
Defining impact significance is the main technical task that influences decision-making during the Environmental Licensing Procedure (ELP). The ELP begins with screening to determine potentially significant impacts of the proposed project. Scoping then follows to address any interventions deemed worthy of attention in the production of an Environmental Impact Assessment (EIA). This will include consideration of relevant landforms and geomorphological processes. However, preliminary assessments of environmental impacts often lack the scientific robustness to procure substantive and transactive effectiveness. This review presents an examination of the established practices of screening and scoping while highlighting the foremost challenges to improve the technical grounds of the ELP. The analysis of screening and scoping practices stresses the need for novel methods that ensure the sequential reasoning between their criteria while improving the preliminary evaluation of impact significance. Reducing the inherent subjectivity of discretionary judgment requires scientific methodologies that acknowledge the interaction between the natural system and human interventions, which has been addressed by geomorphological research. The knowledge consolidated in this review opens the gate to explore the compatibility between the United Nations strategy of Ecosystem Approach (EA) with the ELP through a novel geomorphological interpretation of the EIA. Therefore, this diagnosis demonstrate that screening and scoping practices would benefit from reliable methods that balance the precautionary principle with the efficient character required in the ELP.
Accurate wind modeling is important for wind resources assessment and wind power forecasting. To improve the WRF model configuration for the offshore wind modeling over the Baltic Sea, this study performed a sensitivity study of the WRF model to multiple model configurations, including domain setup, grid resolution, sea surface temperature, land surface data, and atmosphere-wave coupling. The simulated offshore wind was evaluated against LiDAR observations under different wind directions, atmospheric stabilities, and sea status. Generally, the simulated wind profiles matched observations, despite systematic underestimations. Strengthening the forcing from the reanalysis data through reducing the number of nested domains played the largest role in improving wind modeling. Atmosphere-wave coupling further improved the simulated wind, especially under the growing and mature sea conditions. Increasing the vertical resolution, and updating the sea surface temperature and the land surface information only had a slight impact, mainly visible during very stable conditions. Increasing the horizontal resolution also only had a slight impact, most visible during unstable conditions. Our study can help to improve the wind resources assessment and wind power forecasting over the Baltic Sea.
The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model (DEM) data. The unique terrain characteristics of a particular landscape are derived from DEM, which are responsible for initiation and development of ephemeral gullies. As the topographic features of an area significantly influences on the erosive power of the water flow, it is an important task the extraction of terrain features from DEM to properly research gully erosion. Alongside, topography is highly correlated with other geo-environmental factors i.e. geology, climate, soil types, vegetation density and floristic composition, runoff generation, which ultimately influences on gully occurrences. Therefore, terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility (GES) mapping. In this study, remote sensing-Geographic information system (GIS) techniques coupled with machine learning (ML) methods has been used for GES mapping in the parts of Semnan province, Iran. Current research focuses on the comparison of predicted GES result by using three types of DEM i.e. Advanced Land Observation satellite (ALOS), ALOS World 3D-30 m (AW3D30) and Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) in different resolutions. For further progress of our research work, here we have used thirteen suitable geo-environmental gully erosion conditioning factors (GECFs) based on the multi-collinearity analysis. ML methods of conditional inference forests (Cforest), Cubist model and Elastic net model have been chosen for modelling GES accordingly. Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods (Cforest = 21.4, Cubist = 19.65 and Elastic net = 17.08), followed by lithology and slope. Validation of the model’s result was performed through area under curve (AUC) and other statistical indices. The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs (AUC value of Cforest in ALOS DEM is 0.994, AW3D30 DEM is 0.989 and ASTER DEM is 0.982) used in this study, followed by elastic net and cubist model. The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.
The Nepal Himalayas is the source of many glacial and spring-fed river systems crisscrossing the mountainous terrain. There is an increasing recognition of small mountain rivers (SMRs) to have a significant combined export of dissolved and particulate organic carbon to the global carbon flux. We analyzed fluvial sediments from two SMRs and compared the results with two large mountain rivers (LMRs) in Nepal. We investigated the organic matter (OM), its compositional variability, and seasonal export using a suite of lipid biomarkers, namely n-alkanes, n-alkanoic acids, n-alkanols, and sterols. The SMRs indicated a similarity in lipid distribution and were affected by a strong seasonal variability. The LMRs showed a distinct contrast in the distribution of lipids in suspended sediments. Bedload sediments in SMRs were derived from diverse sources with weak terrigenous dominance all-year-round compared to the suspended load. Functional lipids (n-alkanoic acids and n-alkanols) were the major constituents in SMR sediments, indicating better preservation. In contrast, n-alkane concentration dominated over other fractions in suspended sediments retrieved from LMRs. The biomarker trends differentiate SMRs from LMRs with lower transformed/degraded OM in SMRs. A common observation was the strong presence of even carbon compounds in short-chain n-alkanes in SMR bedload sediments and their predominance in suspended sediments in LMRs. Such an unusual trend is attributed to specific biomarker sources from the catchment and ongoing processes in fluvial systems. Topsoil colonized by fungal species under moist acidic conditions and autochthonous bacteria contributes to the organic matter pool in shallow SMRs. In LMRs, the contribution from thermally mature sedimentary hydrocarbons and the diagenetic reduction of n-alkanoic acids to n-alkanes are additional contributors to the allochthonous carbon pool. The differences in lipid concentrations, their distribution, seasonality, and the size of rivers suggest differential preservation/degradation of the organic matter pool and their importance in contributing to the carbon budget.
One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs. To solve this problem, this study develops the Absence Point Generation (APG) toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies. The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude, slope degree, topographic wetness index, and distance from rivers, and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are generated. To test the APG toolbox, we applied two benchmark algorithms of random forest (RF) and boosted regression trees (BRT) in a case study to investigate groundwater potential using three absence datasets i.e., the APG, random, and selection of absence samples (SAS) toolbox. The BRT-APG and RF-APG had the area under receiver operating curve (AUC) values of 0.947 and 0.942, while BRT and RF had weaker performances with the SAS and Random datasets. This effect resulted in AUC improvements for BRT and RF by 7.2, and 9.7% from the Random dataset, and AUC improvements for BRT and RF by 6.1, and 5.4% from the SAS dataset, respectively. The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps, which proves the importance of absence points in environmental binary issues. The proposed APG toolbox could be easily applied in other environmental hazards such as landslides, floods, and gully erosion, and land subsidence.
The Yubei-Tangbei area in the southern Tarim Basin is one of the best-preserved Early Paleozoic northeast-southwest trending fold-and-thrust belts within this basin. This area is crucial for the exploration of primary hydrocarbon reservoirs in northwestern China. In this study, we constructed the structural geometric morphology of the Yubei-Tangbei area using geophysical logs, drilling, and recent two- and three-dimensional (2-D and 3-D) seismic data. The Early Paleozoic fault-propagation folds, the Tangnan triangle zone, fault-detachment folds, and trishear fault-propagation folds developed with the detachment of the Middle Cambrian gypsum–salt layer. According to a detailed chronostratigraphic framework, the growth strata in the Upper Ordovician–Lower Silurian layer formed by onlapping the back limb of the asymmetric fault-propagation folds, which therefore defines the timing of deformations. The changes in kink band hinges and amplitudes in the Permian–Carboniferous and Cenozoic folding strata suggest that the evolution of the fold-and-thrust belts followed a sequential evolution process rather than a simultaneous one. Above the pre-existing Precambrian basement structure, the Yubei-Tangbei fold-and-thrust belts can be divided into four tectonic evolution stages: Late Cambrian, Late Ordovician to Early Carboniferous, Carboniferous to Permian, and Cenozoic. The northwestern-verging Cherchen Fault is part of the piedmont fold-and-thrust system of the southern Tarim foreland basin. We interpreted its strata as a breakthrough trishear fault-propagation fold that developed in three phases: Mid–Late Ordovician, Silurian to Middle Devonian, and Triassic to present. These tectonic events are responses of the Altyn-Tagh and Kunlun collisional orogenic belts and the Indian-Eurasian collision. The inherited deformation and structural modification in the southern Tarim Basin may be an indicator of the growth and evolution of peripheral orogens.
In the recent years, exceptional fossil sites have revealed astonishing details on the anatomy, lifestyles and behaviour of Cambrian animals but surprisingly, very little is known about one of their most vital features, reproduction. We describe here in situ eggs (clusters of 3 to 30 oocytes) in the tube-dwelling priapulid worm Paraselkirkia sinica from the Cambrian Stage 3 Xiaoshiba Lagerstätte (ca. 514 Ma, South China). These oocytes were accommodated within paired tubular ovaries located in the posterior half of the primary body cavity as in modern meiobenthic priapulid worms, thus indicating that the general organization of female tubular gonads in priapulid worms has remained virtually unchanged for half a billion years. Our findings provide for the first time, key information on the reproductive organs and strategies of early ecdysozoans, a huge animal clade that dominated Cambrian marine ecosystems and accounts for a large part of today's biodiversity (e.g. arthropods). Moreover, we also emphasize the critical role of ecology on the reproductive strategies and lifestyles of both modern and Cambrian worms.
This work examines the environmental and geochemical impact of recycled aggregate concrete production with properties representative for structural applications. The environmental influence of cement content, aggregate production, transportation, and waste landfilling is analysed by undertaking a life cycle assessment and considering a life cycle inventory largely specific for the region. To obtain a detailed insight into the optimum life cycle parameters, a sensitivity study is carried out in which supplementary cementitious materials, different values of natural-to-recycled aggregate content ratio and case-specific transportation distances were considered. The results show that carbon emissions were between 323 and 332 kgCO2e per cubic metre of cement only natural aggregate concrete. These values can be reduced by up to 17% by replacing 25% of the cement with fly ash. By contrast, carbon emissions can increase when natural coarse aggregates are replaced by recycled aggregates in proportions of 50% and 100%, and transportation is not included in analysis. However, the concrete with 50% recycled aggregate presented lower increase, only 0.3% and 3.4% for normal and high strength concrete, respectively. In some cases, the relative contribution of transportation to the total carbon emissions increased when cement was replaced by fly ash in proportions of 25%, and case-specific transportation distances were considered. In absolute values, the concrete mixes with 100% recycled aggregates and 25% fly ash had lower carbon emissions than concrete with cement and natural aggregates only. Higher environmental benefits can be obtained when the transportation distances of fly ash are relatively short (15–25 km) and the cement replacement by fly ash is equal or higher than 25%, considering that the mechanical properties are adequate for practical application. The observations from this paper show that recycled aggregate concrete with strength characteristics representative for structural members can have lower carbon emissions than conventional concrete, recommending them as an alternative to achieving global sustainability standards in construction.
Air pollution is a grand challenge of our time due to its multitude of adverse impacts on environment and society, with the scale of impacts more severe in developing countries, including China. Thus, China has initiated and implemented strict air pollution control measures over last several years to reduce impacts of air pollution. Monitoring data from Jan 2015 to Dec 2019 on six criteria air pollutants (SO2, NO2, CO, O3, PM2.5, and PM10) at eight sites in southwestern China were investigated to understand the situation and analyze the impacts of transboundary air pollutants in this region. In terms of seasonal variation, the maximum concentrations of air pollutants at these sites were observed in winter or spring season depending on individual site. For diurnal variation, surface ozone peaked in the afternoon while the other pollutants had a bimodal pattern with peaks in the morning and late afternoon. There was limited transport of domestic emissions of air pollutants in China to these sites. Local emissions enhanced the concentrations of air pollutants during some pollution events. Mostly, the transboundary transport of air pollution from South Asia and Southeast Asia was associated with high concentrations of most air pollutants observed in southwestern China. Since air pollutants can be transported to southwestern China over long distances from the source regions, it is necessary to conduct more research to properly attribute and quantify transboundary transport of air pollutants, which will provide more solid scientific guidance for air pollution management in southwestern China.
The Sichuan–Yunnan–Guizhou (SYG) Zn–Pb metallogenic zone in SW China contains >400 carbonate-hosted hydrothermal Zn–Pb deposits. Some of these, such as the Huize, Tianbaoshan, and Daliangzi deposits, are super-large deposits with significant reserves of Cd, Ge, and Ag. However, the sources of these metals remain controversial. This study investigated the Cd isotopic geochemistry of the Huize deposit, the largest Zn–Pb deposit in the SYG area. Sphalerites formed at three stages in the deposit have different colors: black or dark brown (Stage I), red (Stage II), and light-yellow (Stage III). The δ114/110Cd values of the sphalerites are in the order Stage III < Stage I < Stage II. Kinetic isotopic fractionation is likely the key factor causing the lower δ114/110Cd values in the early formed Stage I sphalerites than in later-formed Stage II sphalerites, with cooling of ore-forming fluids being responsible for the still lower values of the Stage III sphalerites. In galena, the δ114/110Cd values are inversely correlated with Cd contents and tend to be higher in high-Zn galena. We speculate that Cd isotopic fractionation was significant during the precipitation of sphalerite and galena, with light Cd isotopes being enriched in galena rather than sphalerite. Comparison of the Cd isotopic signatures and Zn/Cd ratios of different endmembers suggests that the δ114/110Cd values and Zn/Cd ratios of sphalerite from the Huize deposit, as well as other large-scale deposits from the SYG area, are lie in those range of Emeishan basalts and sedimentary rocks and the mean δ114/110Cd values of these deposits show good negative correlation with 1/Cd, suggesting that the ore-forming materials of these deposits were derived from the mixing of Emeishan basalts and sedimentary rocks. This study demonstrates that Cd isotopes can be useful proxies in elucidating ore genesis in large Zn–Pb deposits.
The Wandashan accretionary complex (AC), consisting of the Raohe and Yuejinshan complexes, is located on the continental margin of Northeast Asia and represents an excellent source of information about Paleo-Pacific subduction and accretion. However, the protolith nature and tectonic evolution of the Wandashan AC are under debate. This contribution reports new geochronological, geochemical, and Sr-Nd-Pb-Hf isotopic data for ophiolitic rocks from the Wandashan AC. The 169–166 Ma plagioclasites and homogeneous gabbros from the Raohe complex are OIBs while 228–214 Ma homogeneous gabbros are continental VABs. Cumulate gabbros from the Yuejinshan complex formed at 280–278 Ma and ~220 Ma and have similar characteristics with E-MORB and N-MORB, respectively. They are BABBs and their primary magma was derived from a source region between EMI and EMII that was affected by continental crustal contamination as well as subduction-zone metasomatism. Combined with previous studies, we suggest that the onset of subduction of the Paleo-Pacific Plate was in the Early Permian. Subsequently, a back-arc basin, whose present suture is on the eastern margin of the Jiamusi Massif, formed and widened during 280–232 Ma, after which the basin closed and BABBs were emplaced to form the Yuejinshan complex during 210–180 Ma. The formation of VABs of the Raohe complex is coincident with the closure of the back-arc basin, and together with the 169–166 Ma OIBs, they constitute a major part of the Raohe complex. The accretionary process was completed during 133–131 Ma. Taken together, the ophiolitic rocks indicating multistage magmatism in the Paleo-Wandashan region recorded the formation-closure process of back-arc basin and the accretionary process of the Wandashan AC, during the westward subduction of the Paleo-Pacific plate. The back-arc basin identified in our study sheds new lights on geodynamic evolution model of subduction and accretion of the Paleo-Pacific Plate on the continental margin of NE Asia.
The East Kunlun Orogenic Belt (EKOB), which is in the northern part of the Greater Tibetan Plateau, contains voluminous Late Triassic intermediate-felsic volcanic rocks. In the east end of the EKOB, we identified highly differentiated peralkaline-like Xiangride rhyolites (~209 Ma) that differ from the widespread andesitic-rhyolitic Elashan volcanics (~232–225 Ma) in terms of their field occurrences and mineral assemblages. The older, more common calc-alkaline felsic Elashan volcanics may have originated from partial melting of the underthrust Paleo-Tethys oceanic crust under amphibolite facies conditions associated with continental collision. The felsic Elashan volcanics and syn-collisional granitoids of the EKOB are different products of the same magmatic event related to continental collision. The Xiangride rhyolites are characterized by elevated abundances of high field strength elements, especially the very high Nb and Ta contents, the very low Ba, Sr, Eu, P, and Ti contents; and the variably high 87Sr/86Sr ratios (up to 0.96), exhibiting remarkable similarities to the characteristic peralkaline rhyolites. The primitive magmas parental to the Xiangride rhyolites were most likely alkali basaltic magmas that underwent protracted fractional crystallization with continental crust contamination. The rock associations from the early granitoids and calc-alkaline volcanic rocks to the late alkaline basaltic dikes and peralkaline-like rhyolites in the Triassic provide important information about the tectonic evolution of the EKOB from syn-collisional to post-collisional. We infer that the transition from collisional compression to post-collisional extension occurred at about 220 Ma.
Fine characterization of pore systems and heterogeneity of shale reservoirs are significant contents of shale gas reservoir physical property research. The research on micro-control factors of low productivity in the Qiongzhusi Formation (Fm.) is still controversial. The lower Cambrian Qiongzhusi Fm. in the Qujing, Yunnan was taken as the object to investigate the influence of mineral compositions on the physical properties of the reservoir and the heterogeneity of shale, using the algorithm to improve the characterization ability of Atomic Force Microscopy (AFM). The results showed that: (1) The pores are mainly wedge-shaped pores and V-shaped pores. The pore diameter of the main pore segment ranges from 5 to 10 nm. Mesopores are mainly developed in the Qiongzhusi Fm. shale in Well QD1, with the average pore diameter of 6.08 nm. (2) Microscopic pore structure and shale surface properties show strong heterogeneity, which complicates the micro-migration of shale gas and increases the difficulty of identifying high-quality reservoirs. (3) The increase of clay mineral content intensifies the compaction and then destroys the pores. Conversely, brittle minerals can protect pores. The support and protection of brittle minerals to pores space depend on their content, mechanical properties and diagenesis. (4) Compression damage to pores, large microscopic roughness and surface fluctuations and strong pore structure heterogeneity are the reasons for the poor gas storage capacity of the Qiongzhusi Fm., which will lead to poor productivity in the Qiongzhusi Fm.
We performed spectral analyses on the ages of 89 well-dated major geological events of the last 260 Myr from the recent geologic literature. These events include times of marine and non-marine extinctions, major ocean-anoxic events, continental flood-basalt eruptions, sea-level fluctuations, global pulses of intraplate magmatism, and times of changes in seafloor-spreading rates and plate reorganizations. The aggregate of all 89 events shows ten clusters in the last 260 Myr, spaced at an average interval of ~ 26.9 Myr, and Fourier analysis of the data yields a spectral peak at 27.5 Myr at the ≥ 96% confidence level. A shorter period of ~ 8.9 Myr may also be significant in modulating the timing of geologic events. Our results suggest that global geologic events are generally correlated, and seem to come in pulses with an underlying ~ 27.5-Myr cycle. These cyclic pulses of tectonics and climate change may be the result of geophysical processes related to the dynamics of plate tectonics and mantle plumes, or might alternatively be paced by astronomical cycles associated with the Earth’s motions in the Solar System and the Galaxy.
Deep hot mantle upwelling is widely revealed around the Qiongdongnan Basin on the northwestern South China Sea margin. However, when and how it influenced the hyper-extended basin is unclear. To resolve these issues, a detailed analysis of the Cenozoic time-varying residual subsidence derived by subtracting the predicted subsidence from the backstripped subsidence was performed along a new seismic reflection line in the western Qiongdongnan Basin. For the first time, a method is proposed to calculate the time-varying strain rates constrained by the faults growth rates, on basis of which, the predicted basement subsidence is obtained with a basin- and lithosphere-scale coupled finite extension model, and the backstripped subsidence is accurately recovered with a modified technique of backstripping to eliminate the effects of later episodes of rifting on earlier sediment thickness. Results show no residual subsidence in 45–28.4 Ma. But after 28.4 Ma, negative residual subsidence occurred, reached and remained ca. −1000 m during 23–11.6 Ma, and reduced dramatically after 11.6 Ma. In the syn-rift period (45–23 Ma), the residual subsidence is ca. −1000 m, however in the post-rift period (23–0 Ma), it is positive of ca. 300 to 1300 m increasing southeastwards. These results suggest that the syn-rift subsidence deficit commenced at 28.4 Ma, while the post-rift excess subsidence occurred after 11.6 Ma. Combined with previous studies, it is inferred that the opposite residual subsidence in the syn- and post-rift periods with similar large wavelengths (>102 km) and km-scale amplitudes are the results of transient dynamic topography induced by deep mantle upwelling beneath the central QDNB, which started to influence the basin at ca. 28.4 Ma, continued into the Middle Miocene, and decayed at ca. 11.6 Ma. The initial mantle upwelling with significant dynamic uplift had precipitated considerable continental extension and faulting in the Late Oligocene (28.4–23 Ma). After ca. 11.6 Ma, strong mantle upwelling probably occurred beneath the Leizhou–Hainan area to form vast basaltic lava flow.
We present new U–Pb zircon and monazite ages from the Sunsas belt granitic magmatism in Bolivia, SW Amazonian Craton. The geochronological results revealed four major magmatic events recorded along the Sunsas belt domains. The older igneous event formed a granitic basement coeval to the Rio Apa Terrane (1.95 – 1.85 Ga) in the southern domain. The second magmatic episode is represented by 1.68 Ga granites associated to the Paraguá Terrane (1.69–1.66 Ga) in the northern domain. The 1.37–1.34 Ga granites related to San Ignacio orogeny represent the third and more pervasive magmatic event, recorded throughout the Sunsas belt. Moreover, magmatic ages of ~1.42 Ga revealed that the granitogenesis associated to the Santa Helena orogeny also affected the Sunsas belt, indicating that it was not restricted to the Jauru Terrane. Lastly, the 1.10–1.04 Ga youngest magmatism was developed during the Sunsas orogeny and represents the final magmatic evolution related to Rodinia assembly. Likewise, the 1.95–1.85 and 1.68 Ga inherited zircon cores obtained in the ~1.3 Ga and 1.0 Ga granite samples suggest strong partial melting of the Paleoproterozoic sources. The 1079 ± 14 Ma and 1018 ± 6 Ma monazite crystallization ages can be correlated to the collisional tectono-thermal event of the Sunsas orogeny, associated to reactions of medium- to high-grade metamorphism. Thus, the Sunsas belt was built by heterogeneous 1.95–1.85 Ga and 1.68 Ga crustal fragments that were reworked at 1.37–1.34 Ga and 1.10–1.04 Ga related to orogenic collages. Furthermore, the 1.01 Ga monazite age suggests that granites previously dated by zircon can bear evidence of a younger thermal history. Therefore, the geochronological evolution of the Sunsas belt may have been more complex than previously thought.
China is one of the countries where landslides caused the most fatalities in the last decades. The threat that landslide disasters pose to people might even be greater in the future, due to climate change and the increasing urbanization of mountainous areas. A reliable national-scale rainfall induced landslide susceptibility model is therefore of great relevance in order to identify regions more and less prone to landsliding as well as to develop suitable risk mitigating strategies. However, relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area. The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China. In this context, it is aimed to explore the benefit of mixed effects modelling to counterbalance associated bias propagations. Six influencing factors including lithology, slope, soil moisture index, mean annual precipitation, land use and geological environment regions were selected based on an initial exploratory data analysis. Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information: Set 1 (disregards the presence of incomplete landslide information), Set 2 (excludes factors related to the incompleteness of landslide data), Set 3 (accounts for factors related to the incompleteness via random effects). The variable sets were then introduced in a generalized additive model (GAM: Set 1 and Set 2) and a generalized additive mixed effect model (GAMM: Set 3) to establish three national-scale statistical landslide susceptibility models: models 1, 2 and 3. The models were evaluated using the area under the receiver operating characteristics curve (AUROC) given by spatially explicit and non-spatial cross-validation. The spatial prediction pattern produced by the models were also investigated. The results show that the landslide inventory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models. The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9. However, although Model 1 reached the highest AUROCs within non-spatial cross-validation (median of 0.9), it was not associated with the most plausible representation of landslide susceptibility. The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias. The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility. However, a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data (e.g., the Kuenlun Mountains in the northern Tibetan Plateau). The non-linear mixed-effects model (Model 3) reduced the impact of these biases best by introducing bias-describing variables as random effects. Among the three models, Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive performance (median AUROC of spatial cross validation 0.84) compared to the other two models (median AUROCs of 0.81 and 0.79, respectively). We conclude that ignoring landslide inventory-based incompleteness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.
Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation. This study presents a machine learning approach based on the C5.0 decision tree (DT) model and the K-means cluster algorithm to produce a regional landslide susceptibility map. Yanchang County, a typical landslide-prone area located in northwestern China, was taken as the area of interest to introduce the proposed application procedure. A landslide inventory containing 82 landslides was prepared and subsequently randomly partitioned into two subsets: training data (70% landslide pixels) and validation data (30% landslide pixels). Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model. Susceptibility zonation was implemented according to the cut-off values calculated by the K-means cluster algorithm. The validation results of the model performance analysis showed that the AUC (area under the receiver operating characteristic (ROC) curve) of the proposed model was the highest, reaching 0.88, compared with traditional models (support vector machine (SVM) = 0.85, Bayesian network (BN) = 0.81, frequency ratio (FR) = 0.75, weight of evidence (WOE) = 0.76). The landslide frequency ratio and frequency density of the high susceptibility zones were 6.76/km2 and 0.88/km2, respectively, which were much higher than those of the low susceptibility zones. The top 20% interval of landslide occurrence probability contained 89% of the historical landslides but only accounted for 10.3% of the total area. Our results indicate that the distribution of high susceptibility zones was more focused without containing more “stable” pixels. Therefore, the obtained susceptibility map is suitable for application to landslide risk management practices.
The location of Central Asia, almost at the center of the global dust belt region, makes it susceptible for dust events. The studies on atmospheric impact of dust over the region are very limited despite the large area occupied by the region and its proximity to the mountain regions (Tianshan, Hindu Kush-Karakoram-Himalayas, and Tibetan Plateau). In this study, we analyse and explain the modification in aerosols’ physical, optical and radiative properties during various levels of aerosol loading observed over Central Asia utilizing the data collected during 2010–2018 at the AERONET station in Dushanbe, Tajikistan. Aerosol episodes were classified as strong anthropogenic, strong dust and extreme dust. The mean aerosol optical depth (AOD) during these three types of events was observed a factor of ~3, 3.5 and 6.6, respectively, higher than the mean AOD for the period 2010–2018. The corresponding mean fine-mode fraction was 0.94, 0.20 and 0.16, respectively, clearly indicating the dominance of fine-mode anthropogenic aerosol during the first type of events, whereas coarse-mode dust aerosol dominated during the other two types of events. This was corroborated by the relationships among various aerosol parameters (AOD vs. AE, and EAE vs. AAE, SSA and RRI). The mean aerosol radiative forcing (ARF) at the top of the atmosphere (ARFTOA), the bottom of the atmosphere (ARFBOA), and in the atmosphere (ARFATM) were −35 ± 7, −73 ± 16, and 38 ± 17 Wm−2 during strong anthropogenic events, −48 ± 12, −85 ± 24, and 37 ± 15 Wm−2 during strong dust event, and −68 ± 19, −117 ± 38, and 49 ± 21 Wm−2 during extreme dust events. Increase in aerosol loading enhanced the aerosol-induced atmospheric heating rate to 0.5–1.6 K day−1 (strong anthropogenic events), 0.4–1.9 K day−1 (strong dust events) and 0.8–2.7 K day−1 (extreme dust events). The source regions of air masses to Dushanbe during the onset of such events are also identified. Our study contributes to the understanding of dust and anthropogenic aerosols, in particular the extreme events and their disproportionally high radiative impacts over Central Asia.
The selection of a suitable discretization method (DM) to discretize spatially continuous variables (SCVs) is critical in ML-based natural hazard susceptibility assessment. However, few studies start to consider the influence due to the selected DMs and how to efficiently select a suitable DM for each SCV. These issues were well addressed in this study. The information loss rate (ILR), an index based on the information entropy, seems can be used to select optimal DM for each SCV. However, the ILR fails to show the actual influence of discretization because such index only considers the total amount of information of the discretized variables departing from the original SCV. Facing this issue, we propose an index, information change rate (ICR), that focuses on the changed amount of information due to the discretization based on each cell, enabling the identification of the optimal DM. We develop a case study with Random Forest (training/testing ratio of 7 : 3) to assess flood susceptibility in Wanan County, China. The area under the curve-based and susceptibility maps-based approaches were presented to compare the ILR and ICR. The results show the ICR-based optimal DMs are more rational than the ILR-based ones in both cases. Moreover, we observed the ILR values are unnaturally small (<1%), whereas the ICR values are obviously more in line with general recognition (usually 10%–30%). The above results all demonstrate the superiority of the ICR. We consider this study fills up the existing research gaps, improving the ML-based natural hazard susceptibility assessments.
Air pollutants can be transported to the pristine regions such as the Tibetan Plateau, by monsoon and stratospheric intrusion. The Tibetan Plateau region has limited local anthropogenic emissions, while this region is influenced strongly by transport of heavy emissions mainly from South Asia. We conducted a comprehensive study on various air pollutants (PM2.5, total gaseous mercury, and surface ozone) at Nam Co Station in the inland Tibetan Plateau. Monthly mean PM2.5 concentration at Nam Co peaked in April before monsoon season, and decreased during the whole monsoon season (June–September). Monthly mean total gaseous mercury concentrations at Nam Co peaked in July and were in high levels during monsoon season. The Indian summer monsoon acted as a facilitator for transporting gaseous pollutants (total gaseous mercury) but a suppressor for particulate pollutants (PM2.5) during the monsoon season. Different from both PM2.5 and total gaseous mercury variabilities, surface ozone concentrations at Nam Co are primarily attributed to stratospheric intrusion of ozone and peaked in May. The effects of the Indian summer monsoon and stratospheric intrusion on air pollutants in the inland Tibetan Plateau are complex and require further studies.
The mechanism of formation of lacustrine deposits within stable orogenic belts and their potential for shale oil and gas exploration are frontier themes of challenge in the fields of sedimentology and petroleum exploration. Orogenic belts witness strong tectonic activities and normally cannot host stable lacustrine basins and deep shale formations. Therefore, basins in orogenic belts are considered to have no potential to form shale hydrocarbon reservoirs. Here we investigate the Luanping Basin located in the Yanshan orogenic belt where previous studies regarded rivers and fan deltas as the major main Mesozoic deposits. Based on detailed field exploration and scientific drilling, we report the finding of a large number of lacustrine shale continental deep-water deposits in the Mesozoic strata. Our finding of the occurrence of active shale oil and gas also in this basin also subvert the previous perceptions.We report SHRIMP zircon U-Pb age that define the bottom boundary of the target interval as 127.6 ± 1.7 Ma belonging to the early Cretaceous strata. Tectonics and climate are considered to be the main factors that controlled the deep-water sedimentation during this period. The drill cores revealed evidence of shale gas and the TOC of shale is 0.33%–3.60%, with an average value of 1.39% and Ro is 0.84%–1.21%, with an average value of 1.002%. The brittleness index of shale is between 52.7% and 100%. After vertical well fracturing, the daily gas production is more than 1000 m3. Our findings show that the basin has considerable potential for shale oil and gas. The geological resources of the shale gas in the Xiguayuan Fm. are estimated as 1110.12 × 108 m3, with shale oil geological resources of 3340.152 × 104 t. Our findings indicate that the Yanshan orogenic belt has potential exploration prospect. This work not only redefines the Luanping Basin as a rift deep-water Mesozoic Lake Basin, but also rules out the previous notion that the basin is dominated by shallow water sediments. The discovery of shale oil and gas also provides an important reference for subsequent petroleum exploration and development in this basin. Our study shows that shale oil and gas reservoirs can be found in the lacustrine basins of orogenic belts which were strongly influenced by volcanism. These results have significant implications for the sedimentology and oil exploration in the Qinling and Xingmeng Orogenic Belts of China, as well as those in other terranes of the world including the New England Orogenic Belt in Australia.