2022年6月1日四川芦山6.1级地震应急产品及震源参数初步分析

北京时间2022年6月1日17时0分四川雅安市芦山县(30.37°N,102.94°E)发生6.1级地震,中国地震台网中心于震后3min发布自动速报结果、震后9min发布正式速报结果,同时联合多家单位启动地震应急产品产出工作,共产出震源参数、历史地震、地震构造、震源机制、余震精定位、推测烈度和震源破裂过程等9类应急产品。结果显示,本次地震发生在龙门山断裂带,位于青藏高原巴颜喀拉地块、岷山构造带、川滇构造带的交汇处;震源机制解表明该地震为一次逆冲型事件;余震精定位结果显示余震展布呈近NE向,与震中区域断裂走向基本一致;烈度速报推测极震区烈度达Ⅸ度,区域面积约2km²,Ⅷ度及以上区域总面积约197km²,涉及四镇一乡。     

2022年9月5日四川泸定6.8级地震初步研究结果

北京时间2022年9月5日12时52分四川甘孜州泸定县(29.59°N,102.08°E)发生6.8级地震,中国地震预警网于震后6.1s产出首报预警结果;中国地震台网中心于震后3min发布自动速报结果,震后11min发布正式速报结果,同时联合中国地震局地球物理研究所、地质研究所、地震预测研究所和应急管理部国家自然灾害防治研究院启动地震应急产品产出工作,共产出震源基本参数、历史地震、地震构造、地震矩张量、余震精定位、地震烈度和震源破裂过程等9类应急产品。结合上述应急产品,对本次地震进行了研究,初步刻画了地震的构造环境、震源特征、断层形态和受灾区域,并分析了地震成因。结果表明,本次地震是发生在鲜水河断裂带南东段雪门坎—磨西断裂上的一次倾角近直立的走滑型事件,自起始破裂点向南东破裂,破裂长度约20km,最大滑移点深度约6km。余震精定位结果显示余震呈NW—SE向展布,长度约50km,深度主要集中在3～14km,展布方向与震中区域断裂走向基本一致,主震震中处断层倾角近乎垂直,与震源机制揭示的特征一致。烈度速报推测与地震烈度图显示极震区烈度达Ⅸ度,区域面积约280km²,Ⅷ度及以上区域总面积约505km²,涉及17个乡镇。认为本次地震是青藏高原隆升和高原上地壳物质向南东挤出,导致鲜水河断裂南东段雪门坎—磨西断裂上积累的应力的一次快速释放过程。     

Mercury isotope constraints on the genesis of late Mesozoic Sb deposits in South China

The late Mesozoic antimony(Sb)mineralization belt in South China hosts a large portion of the world’s Sb reserves.However,the source and mineralization processes of these Sb deposits remain controversial.Here,we measured mercury(Hg)concentrations and isotopic compositions of stibnite in the Banpo Sb-only and Woxi Sbpolymetallic ore deposits,as well as associated rocks in the Yangtze Block in order to constrain the metal sources and ore formation processes in the South China Sb mineralization belt.Stibnite samples from both deposits exhibit significant enrichment in Hg(4.23–50.6 ppm)and have higher δ²⁰²Hg values(?0.47‰to 2.03‰)than the studied Precambrian basement rocks(?1.42‰to 0.59‰),Paleozoic sedimentary rocks(?2.40‰to?0.32‰),and other natural Hg reserves(e.g.,marine and continental systems).This indicates that significant mass-dependent fractionation of Hg isotopes occurred during hydrothermal processes.Negative to slightly positive Δ¹⁹⁹Hg values of?0.17‰to 0.02‰were obtained for stibnite from the studied deposits,similar to values for the Precambrian basement rocks,but different from those of the Paleozoic sedimentary rocks and data previously reported for mantle materials.This suggests that Precambrian basement rocks were the source of Hg and associated metals.Our data and the tectonic evolution of South China indicate that late Mesozoic asthenospheric upwelling,in response to the Paleo-Pacific oceanic slab foundering,generated heat that drove the circulation of fluids in the basement and crustal basinal rocks.These fluids leached Sb,Hg,and other metals from the Precambrian basement rocks and formed the world-class Sb mineralization belt in South China.     

Relationship between polar motion and key hydrological elements at multiple scales

Science China Earth Sciences - Changes in the elements of the Earth system are closely related. Finding the key factors linked with hydrological changes is significant for in-depth analysis of...     

汉南杂岩体袁家沟辉长岩锆石U-Pb年龄及构造意义

袁家沟辉长岩体位于陕西省西乡县白勉峡镇,是汉南杂岩体白勉峡超单元的组成部分.本次研究对袁家沟辉长岩锆石U-Pb年龄,地球化学特征进行了研究.辉长岩的成岩年龄为905±11 Ma,源区继承性锆石年龄为984±4 Ma.岩石地球化学特征显示,袁家沟辉长岩w(SiO2)为49.70％～51.38％,w(K2O)为0.78％～1.27％,属于钙碱性系列.辉长岩中大离子亲石元素富集,稀土含量为143.12～240.72×10-6,稀土含量中等.LREE/HREE的比值为1.46～2.04,平均值为1.73,轻重稀土分馏程度较弱.辉长岩的源区为岩石圈地幔—混合软流圈地幔区域,表现出壳幔混合的特征,形成于火山岛弧环境.     

XRF半定量分析技术在矿石光片鉴定中的应用

偏光显微镜反光镜下鉴定金属矿物是最常用、最快捷有效的方法,然而鉴定结果容易受到鉴定者主观因素或磨片情况的影响。为了更快速、准确地在反光镜下鉴定矿物,利用XRF半定量分析技术快速、无损、前处理简单等特点,以及磨平抛光的矿石矿物在半定量分析过程中能较好地避免楔入效应和阴影效应的有利因素,采取了先用XRF半定量分析测得的结果去反推矿物,再在显微镜下鉴定矿物的方法。以多金属硫化物矿石、含铀多金属矿石及含微量铀的矿石样品为例进行鉴定,结果表明,在鉴定前知道光片上的元素及其质量分数,通过地球化学方法和经验法反推矿物,结合显微镜观察需要鉴定的矿物,可有效避免忽略掉透明/半透明矿物（锡石）、小粒径矿物（沥青铀矿）、易混淆矿物（铀黑）,提高光片鉴定工作的效率和准确性。     

“Source to Sink”: A Review of Tectonics-Erosion-Sedimentation Interactions in the Analogue Experiments of Accretionary WedgeEI北大核心CSCD

It is believed that the tectonics-erosion-sedimentation interaction in the analogue experiments was essentially improved by the theory of “from source to sink”. In particular, the widespread uplift and exhumation in the western China occurred in Cenozoic can be considered to be a typical natural laboratory in the world. Here we review our current understanding from tectonic sandbox models of tectonics-erosion-sedimentation and their interactions, as well as from natural laboratory. As we known, there are widespread erosion occurred predominantly at hinterland of the accretionary wedge, in contrast to the sedimentation occurred widely at foreland of the wedge. Therefore, fold-and-thrust belts with low syntectonic sedimentation and erosion would evolve in a self-similar fashion to produce a narrow accretionary wedge, while high syntectonic sedimentation and erosion would produce accretionary wedge with very active hinterland thrusts, and a large width. Furthermore, the critically tapered wedge model suggests that the crust-scale thrust-and-fold belts under a horizontal compressive force would come into a self-similar growth of a forward-tapering wedge when it reaches a critical taper angle of the combined angles of the base dip and the wedge slope. Such a process has important influence on the tectonics-erosion- sedimentation and their interactions both in accretionary wedges and their analogue experiments. Although there is a significant similarity between the analogue experiments and natural accretionary wedges in the surface processes of tectonics- erosion-sedimentation and their interactions, it is difficult to get more universal parameters between them. It should be noted that sandbox models of the accretionary wedges in the natural laboratory would improve significantly our understanding of the theory of the tectonics-erosion-sedimentation interactions and “from source to sink”. © 2018, Science Press. All right reserved.     

Research Progress of Relative Humidity and Its Changing Annual Cycle

Studies on the characteristics of relative humidity annual cycle change include the frequency, phase, and amplitude of the time series and their changes. The effective diagnosis of the relative humidity annual cycle can provide important help in the monitoring and regulation of seasonal haze, the spatial distribution of epidemic outbreaks and their prevention and control, and the real-time forecasting and decision-making of monsoon precipitation. Different from studies on the trend of the relative humidity, the diagnosis in the annual cycle is scarce. This paper summarized the research status of relative humidity and its annual cycle, introduced several current methods for extracting common signals, and evaluated the feasibility of these methods for extracting annual cycle signals. Due to the time-varying characteristics of the annual cycle of relative humidity and complex structures such as asymmetric triangular waves, square-like waves, and state transients, harmonic-based extraction methods are difficult to succeed. The nonlinear signal extraction method with high noise immunity will solve this problem. At present, the relative humidity annual cycle studies urgently need to be improved and improve the quality of relative humidity observation data, accurately extract and quantify the time-varying characteristics and complex structure of the annual cycle. Moreover, combining the dynamic process and statistical analysis, we also need to study the physical mechanism of the change of relative humidity annual cycle (frequency, phase, amplitude, etc.) in China.     

Prediction of landslide displacement with an ensemble-based extreme learning machine and copula models

Research on the dynamics of landslide displacement forms the basis for landslide hazard prevention. This paper proposes a novel data-driven approach to monitor and predict the landslide displacement. In the first part, autoregressive moving average time series models are constructed to analyze the autocorrelation of landslide triggering factors. A linear ensemble-based extreme learning machine using the least absolute shrinkage and selection operator is applied in predicting the displacement of landslides. Five benchmarking data-driven models, the support vector machine, neural network, random forest, k-nearest neighbor, and the classical extreme learning machine, are considered as baseline models for validating the ensemble-based extreme learning machines. Numerical experiments demonstrated that the proposed prediction model produces the smallest prediction errors among all the algorithms tested. In the second part, parametric copula models are fitted on the predicted displacement, to investigate the relationship between the triggering factors and landslide displacement values. The Gumbel-Hougaard copula model performs best, which indicates strong upper tail correlation between the triggering factors and displacement values. Thresholds for the triggering factors can be obtained by monitoring the landslide moving patterns with large displacement values. The effectiveness and utility of the proposed data-driven approach have been confirmed with the landslide case study in the region of the Three Gorges Reservoir.