The statistical and numerical study of the global distribution of coronal plasma and magnetic field near 2.5 Rs over a 10-year period

The basic characteristics of the global distribution for the corona plasma and magnetic field near 2.5 Rs are analyzed with the statistical and numerical methods for 136 Carrington Rotations (CRs) covering four different phases of solar activity. By using the observational data and the velocity distribution model in the corona, the statistical average distribution of the magnetic field, density and the coronal mass outputs are analyzed for the four different phases. Then, a numerical study of the global distribution near 2.5 Rs has been made by solving a self-consistent MHD system. Finally, the solar wind speed at 1 AU is given by mapping the speed at 2.5 Rs to that near 1 AU, and the comparison of the numerical results with the observational measurements and the simulation result of the Wang–Sheeley–Arge (WSA) model are made during more than 5 years. The numerical results indicate that the global distributions on the source surface of 2.5 Rs at different phases of solar activity could be used to predict the change of the solar wind in interplanetary space.     

A three-dimensional surface wave–ocean circulation coupled model and its initial testing

A theoretical framework to include the influences of nonbreaking surface waves in ocean general circulation models is established based on Reynolds stresses and fluxes terms derived from surface wave-induced fluctuation. An expression for the wave-induced viscosity and diffusivity as a function of the wave number spectrum is derived for infinite and finite water depths; this derivation allows the coupling of ocean circulation models with a wave number spectrum numerical model. In the case of monochromatic surface wave, the wave-induced viscosity and diffusivity are functions of the Stokes drift. The influence of the wave-induced mixing scheme on global ocean circulation models was tested with the Princeton Ocean Model, indicating significant improvement in upper ocean thermal structure and mixed layer depth compared with mixing obtained by the Mellor–Yamada scheme without the wave influence. For example, the model–observation correlation coefficient of the upper 100-m temperature along 35° N increases from 0.68 without wave influence to 0.93 with wave influence. The wave-induced Reynolds stress can reach up to about 5% of the wind stress in high latitudes, and drive 2–3 Sv transport in the global ocean in the form of mesoscale eddies with diameter of 500–1,000 km. The surface wave-induced mixing is more pronounced in middle and high latitudes during the summer in the Northern Hemisphere and in middle latitudes in the Southern Hemisphere.     

Removal of Ni(II) from Aqueous Solutions by Nanoscale Magnetite

Magnetite nanoparticles were applied to remove Ni(II) from aqueous solutions as a function of pH, contact time, supporting electrolyte concentration, and analytical initial Ni(II) concentration. The highly crystalline nature of the magnetite structure with diameter of around 10 nm was characterized with transmission electron microscopy (TEM) and X‐ray diffractometry (XRD). The surface area was determined to be 115.3 m²/g. Surface chemical properties of magnetite at 25°C in aqueous suspensions were investigated. The point of zero charge (pHzpc) was found to be 7.33 and the intrinsic acidity constants (${\rm p}K_{{\rm a}1}^{{\rm s}} $ and ${\rm p}K_{{\rm a}2}^{{\rm s}} $ ) were found to be 9.3 and 5.9, respectively. The surface functional groups were investigated with Fourier transform‐infrared spectroscopy (FTIR) as well. Batch experiments were carried out to determine the adsorption kinetics and mechanism of Ni(II) by these magnetite nanoparticles. The adsorption process was found to be pH dependent. In NaCl solutions, Ni(II) adsorption increased with increasing ionic strength while in NaClO₄ solutions, Ni(II) adsorption exhibited little dependence on the ionic strength of the solution. The adsorption process better followed the pseudo‐second order equation and Freundlich isotherm.     

Copula‐based joint probability function for PGA and CAV: a case study from Taiwan

This study aims to develop a joint probability function of peak ground acceleration (PGA) and cumulative absolute velocity (CAV) for the strong ground motion data from Taiwan. First, a total of 40,385 earthquake time histories are collected from the Taiwan Strong Motion Instrumentation Program. Then, the copula approach is introduced and applied to model the joint probability distribution of PGA and CAV. Finally, the correlation results using the PGA‐CAV empirical data and the normalized residuals are compared. The results indicate that there exists a strong positive correlation between PGA and CAV. For both the PGA and CAV empirical data and the normalized residuals, the multivariate lognormal distribution composed of two lognormal marginal distributions and the Gaussian copula provides adequate characterization of the PGA‐CAV joint distribution observed in Taiwan. This finding demonstrates the validity of the conventional two‐step approach for developing empirical ground motion prediction equations (GMPEs) of multiple ground motion parameters from the copula viewpoint. Copyright © 2016 John Wiley & Sons, Ltd.     

大岗山库区主动震源探测系统性能及其影响因素

利用大岗山水库地震监测台网,在大岗山库区建立了主动震源探测系统。主动震源设备为10t精密控制机械震源,接收台站包括大岗山水库地震台网的8个固定台站、2个加密流动台站和1个震源接收台。本文介绍了大岗山库区主动震源探测系统的基本情况、震源与地基的耦合特征、系统的性能及其影响因素等,并通过初步数据处理获取了大岗山库区地壳波速的相对变化。     

3D modeling of geological anomalies based on segmentation of multiattribute fusion

3D modeling of geological bodies based on 3D seismic data is used to define the shape and volume of the bodies, which then can be directly applied to reservoir prediction, reserve estimation, and exploration. However, multiattributes are not effectively used in 3D modeling. To solve this problem, we propose a novel method for building of 3D model of geological anomalies based on the segmentation of multiattribute fusion. First, we divide the seismic attributes into edge- and region-based seismic attributes. Then, the segmentation model incorporating the edge- and region-based models is constructed within the levelset-based framework. Finally, the marching cubes algorithm is adopted to extract the zero level set based on the segmentation results and build the 3D model of the geological anomaly. Combining the edge-and region-based attributes to build the segmentation model, we satisfy the independence requirement and avoid the problem of insufficient data of single seismic attribute in capturing the boundaries of geological anomalies. We apply the proposed method to seismic data from the Sichuan Basin in southwestern China and obtain 3D models of caves and channels. Compared with 3D models obtained based on single seismic attributes, the results are better agreement with reality.     

2015年7月3日新疆皮山M_S6.5级地震震害特征分析

2015年7月3日新疆皮山M_S6.5级地震灾区地处塔里木盆地南缘,该地自然条件恶劣,经济极为落后,灾区农村的民房除了抗震安居工程建设的房屋外,还有大量抗震性能较差的民居,在地震中受损严重,经济损失较大。灾区大部分位于山前溢出带,地下水位浅、地基土层软弱等场地条件对地震动有放大作用,震害影响范围较大。灾后重建中应继续加大安居富民工程的经费投入力度。灾区北部人口密集,地基土层软弱,工程地质条件差,建议在今后的安居富民建设中加强地基处理。     

新疆地区县(市)地震应急能力指标体系的建立与区域差异初探

从新疆地区地震活动性、灾害背景及区域协同联动应急模式出发,在遵循科学性、系统优化和可操作性及区域特性等原则的基础上,采用层次分析法建立了县级行政单元的地震应急能力评价指标体系;继而建立了基于基础设施条件、基础人力物力财力、(县级)专项能力和专项经验及基础环境背景4个一类指标集的县(市)绝对地震应急能力综合评价模型,并根据新疆地区4类人员问卷调查资料,计算和分析了样本支持条件下各指标的权重及结果,将其应用在新疆地区县(市)地震应急能力等级划分中。结果表明,地震应急能力的空间分布格局的产生与区域经济发展水平和地理位置等方面所具备的优势是相适应的,安居富民工程对提升区域地震应急能力发挥了重要作用,少数民族聚集区应急能力有待加强,寒旱、高海拔地区等特殊地理因素影响不可忽视。     

Geochemistry and possible origin of the hydrocarbons from Wells Zhongshen1 and Zhongshen1C,Tazhong Uplift

In 2013, a great breakthrough of deep petroleum exploration was achieved in the Cambrian pre-salt intervals of Wells Zhongshen1 (ZS1) and Zhongshen1C (ZS1C), Tazhong Uplift. However, the hydrocarbon discovery in the Cambrian pre-salt intervals has triggered extensive controversy regarding the source of marine oils in the Tarim Basin. The geochemistry and origin of the Cambrian pre-salt hydrocarbons in Wells ZS1 and ZS1C were investigated using GC, GC-MS and stable carbon isotope technique. These hydrocarbons can be easily distinguished into two genetic families based on their geochemical and carbon isotopic compositions. The oil and natural gases from the Awatage Formation of Well ZS1 are derived from Middle- Upper Ordovician source rocks. In contrast, the condensate and gases from the Xiaoerbulake Formation of Wells ZS1 and ZS1C probably originate from Cambrian source rocks. The recent discovery of these hydrocarbons with two different sources in Wells ZS1 and ZS1C suggests that both Middle-Upper Ordovician-sourced hydrocarbons and Cambrian-sourced petroleums are accumulated in the Tazhong Uplift, presenting a great exploration potential.     

On the accumulative contribution of CO2 emission from China to global climate change

A study of the contribution to global climate change from China’s CO₂ emission is conducted using the FIO-ESM v1.0 climate model. A series of sensitivity experiments are performed to identify two kinds of contributions to global climate change of China’s CO₂ emission due to fossil fuel combustion: one is the pure contribution which is the historical climate response from the sensitivity experiment forced only by China’s CO₂ emission, the other is the accumulative contribution which is proposed in this research and defined as the difference of historical climate responses between the experiments forced by all countries’ CO₂ emission and other countries’ CO₂ emission excluding China. The pure contribution approach considers the total CO₂ discharged by China, while the accumulative contribution approach considers not only the discharge amount of China but also the discharge order of China and other countries. The latter is a more realistic approach to quantify the contribution of CO₂ emission to the historical change of atmospheric CO₂ concentration, surface air temperature (SAT), sea surface temperature (SST) and sea ice coverage in the Arctic. Model results show that from the accumulative perspective, the ratio of the contribution of CO₂ emission from China for the increase of atmospheric CO₂ concentration, SAT and SST, and the decrease of the sea ice coverage in the Arctic to that from all other countries excluding China varies from 8% to 92%, 5% to 95%, 9% to 91% and 18% to 82%, respectively. Here we take the contribution of China’s CO₂ emission as an example, the contribution of CO₂ emission from any other country or area can be evaluated by the same approach.