Nanogeochemistry of hydrothermal magnetite

Magnetite from hydrothermal ore deposits can contain up to tens of thousands of parts per million (ppm) of elements such as Ti, Si, V, Al, Ca, Mg, Na, which tend to either structurally incorporate into growth and sector zones or form mineral micro- to nano-sized particles. Here, we report micro- to nano-structural and chemical data of hydrothermal magnetite from the Los Colorados iron oxide–apatite deposit in Chile, where magnetite displays both types of trace element incorporation. Three generations of magnetites (X–Z) were identified with concentrations of minor and trace elements that vary significantly: SiO₂, from below detection limit (bdl) to 3.1 wt%; Al₂O₃, 0.3–2.3 wt%; CaO, bdl–0.9 wt%; MgO, 0.02–2.5 wt%; TiO₂, 0.1–0.4 wt%; MnO, 0.04–0.2 wt%; Na₂O, bdl–0.4 wt%; and K₂O, bdl–0.4 wt%. An exception is V₂O₃, which is remarkably constant, ranging from 0.3 to 0.4 wt%. Six types of crystalline nanoparticles (NPs) were identified by means of transmission electron microscopy in the trace element-rich zones, which are each a few micrometres wide: (1) diopside, (2) clinoenstatite; (3) amphibole, (4) mica, (5) ulvöspinel, and (6) Ti-rich magnetite. In addition, Al-rich nanodomains, which contain 2–3 wt% of Al, occur within a single crystal of magnetite. The accumulation of NPs in the trace element-rich zones suggest that they form owing to supersaturation from a hydrothermal fluid, followed by entrapment during continuous growth of the magnetite surface. It is also concluded that mineral NPs promote exsolution of new phases from the mineral host, otherwise preserved as structurally bound trace elements. The presence of abundant mineral NPs in magnetite points to a complex incorporation of trace elements during growth, and provides a cautionary note on the interpretation of micron-scale chemical data of magnetite.     

Statistical Variability and Tokunaga Branching of Aftershock Sequences Utilizing BASS Model Simulations

Aftershock statistics provide a wealth of data that can be used to better understand earthquake physics. Aftershocks satisfy scale-invariant Gutenberg–Richter (GR) frequency–magnitude statistics. They also satisfy Omori’s law for power-law seismicity rate decay and Båth’s law for maximum-magnitude scaling. The branching aftershock sequence (BASS) model, which is the scale-invariant limit of the epidemic-type aftershock sequence model (ETAS), uses these scaling laws to generate synthetic aftershock sequences. One objective of this paper is to show that the branching process in these models satisfies Tokunaga branching statistics. Tokunaga branching statistics were originally developed for drainage networks and have been subsequently shown to be valid in many other applications associated with complex phenomena. Specifically, these are characteristic of a universality class in statistical physics associated with diffusion-limited aggregation. We first present a deterministic version of the BASS model and show that it satisfies the Tokunaga side-branching statistics. We then show that a fully stochastic BASS simulation gives similar results. We also study foreshock statistics using our BASS simulations. We show that the frequency–magnitude statistics in BASS simulations scale as the exponential of the magnitude difference between the mainshock and the foreshock, inverse GR scaling. We also show that the rate of foreshock occurrence in BASS simulations decays inversely with the time difference between foreshock and mainshock, an inverse Omori scaling. Both inverse scaling laws have been previously introduced empirically to explain observed foreshock statistics. Observations have demonstrated both of these scaling relations to be valid, consistent with our simulations. ETAS simulations, in general, do not generate Båth’s law and do not generate inverse GR scaling.     

Mineralogy, geochemistry and stratigraphy of the Maslovsky Pt–Cu–Ni sulfide deposit, Noril’sk Region, Russia

We report new data on the stratigraphy, mineralogy and geochemistry of the rocks and ores of the Maslovsky Pt–Cu–Ni sulfide deposit which is thought to be the southwestern extension of the Noril’sk 1 intrusion. Variations in the Ta/Nb ratio of the gabbro-dolerites hosting the sulfide mineralization and the compositions of their pyroxene and olivine indicate that these rocks were produced by two discrete magmatic pulses, which gave rise to the Northern and Southern Maslovsky intrusions that together host the Maslovsky deposit. The Northern intrusion is located inside the Tungusska sandstones and basalt of the Ivakinsky Formation. The Southern intrusion cuts through all of the lower units of the Siberian Trap tuff-lavas, including the Lower Nadezhdinsky Formation; demonstrating that the ore-bearing intrusions of the Noril’sk Complex post-date that unit. Rocks in both intrusions have low TiO₂ and elevated MgO contents (average mean TiO₂ <1 and MgO?=?12?wt.%) that are more primitive than the lavas of the Upper Formations of the Siberian Traps which suggests that the ore-bearing intrusions result from a separate magmatic event. Unusually high concentrations of both HREE (Dy+Yb+Er+Lu) and Y (up to 1.2 and 2.1?ppm, respectively) occur in olivines (Fo_79.5 and 0.25% NiO) from picritic and taxitic gabbro-dolerites with disseminated sulfide mineralization. Thus accumulation of HREE, Y and Ni in the melts is correlated with the mineral potential of the intrusions. The TiO₂ concentration in pyroxene has a strong negative correlation with the Mg# of both host mineral and Mg# of host rock. Sulfides from the Northern Maslovsky intrusion are predominantly chalcopyrite–pyrrhotite–pentlandite with subordinate and minor amounts of cubanite, bornite and millerite and a diverse assemblage of rare precious metal minerals including native metals (Au, Ag and Pd), Sn–Pd–Pt–Bi–Pb compounds and Fe–Pt alloys. Sulfides from the Southern Maslovsky intrusion have δ ³⁴S?=?5–6‰ up to 10.8‰ in two samples whereas the country rock basalt have δ ³⁴S?=?3–4‰, implying there was no in situ assimilation of surrounding rocks by magmas.     

Geochemistry of Thermal Waters of Continental Margin of Far East of Russia

Studied waters belong to warm(T=30-50℃),alkaline(pH=8.9-9.3),low mineralized(TDS235 mg/1)Na-HCO_3 or Na-SO_4-HCO_3 thermal waters with high content of SiO_2(up to 81 mg/l)and F(up to 3.9 mg/1),occur on modern volcano-tectonic rejuvenated areas of Eastern Sikhote-Alin orogenic belt.Low~3He concentration as well as N_2/O_2 and N_2/Ar ratios exclude influence of deep mantle fluid.New rare earth element data constrain our understandmg of water-rock interaction occurring in the water source region.Meteoric origin of waters is proved by stable isotope values varying from-71‰to-136.1‰and from-10.8‰to-18.8‰forδ~2U andδ~(18)O respectively.REE patterns reflect high pH,resultfing from water-rock interaction and oxidative conditions.Calculations of deep aquifer temperature using Na-K and quartz geothermometers show 116.8-131.1°C and 82.2-125.8℃respectively.Presence of deep faults both with abnormal thermal gradient(~45-50 K/km)define unique geochemical shape of thermal waters of Sikhote-Alin,area,where no present volcanic activity is registered.     

Sulfur speciation in the upper Black Sea sediments

We report solid phase sulfur speciation of six cores from sediments underlying oxic, suboxic and anoxic-sulfidic waters of the Black Sea. Our dataset includes the five sulfur species [pyrite-sulfur, acid volatile sulfides (AVS), zerovalent sulfur (S(0)), organic polysulfides (RS_x), humic sulfur] together with reactive iron and manganese, as quantified by dithionite extraction, and total organic carbon. Pyrite – sulfur was the major phase in all cores [200-400 µmol (g dry wt)^- 1] except for the suboxic core. However, zerovalent sulfur and humic sulfur also reached very significant levels: up to about 109 and 80 µmol (g dry wt)^- 1, respectively. Humic sulfur enrichment was observed in the surface fluff layers of the eastern central basin sediments where Unit-1 type depositional conditions prevail. Elemental sulfur accumulated as a result of porewater sulfide oxidation by reactive iron oxides in turbidities from the anoxic basin margin and western central basin sediments. The accumulation of elemental sulfur to a level close to that of pyrite-S in any part of central Black Sea sediments has never been reported before and our finding indicates deep basin turbidites prevent the build-up of dissolved sulfide in the sediment. This process also contributes to diagenetic pyrite formation whereas in the non-turbiditic parts of the deep basin water column formed (syngenetic) pyrite dominates the sulfur inventory. In slope sediments under suboxic waters, organic sulfur (humic sulfur + organic polysulfides) account for 33-42% of total solid phase S, indicating that the suboxic conditions favor organosulfur formation. Our study shows that the interactions between depositional patterns (Unit 1 vs. turbidite), redox state of overlying waters (oxic-suboxic-sulfidic) and organic matter content determine sulfur speciation and enable the accumulation of elemental sulfur and organic sulfur species close to a level of pyrite-S.     

GNSS Software Receivers

Software Global Navigation Satellite Systems (GNSS) receivers are those that implement signal correlation processing not in hardware, but in their software. The main problem for the development of real-time software (SW) multichannel GNSS receivers is the tremendous amount of calculations to perform signal correlation. The article reviews recent developments of SW GNSS receivers. The emphasis is made on the computationally effective correlation processing algorithms and the optimization of processing allocation to the receiver's hardware (HW) and SW. An architecture is suggested that implements the PRN signals despreading in a special HW preprocessor while all the other correlation processing functions are still kept in SW. The combination of the most time-consuming processing in HW, and all signal structure-dependent processing in SW, enables unique flexibility of sophisticated GNSS receiver design based on inexpensive digital signal processors. ? 2000 John Wiley & Sons, Inc.     

综合数字区域模型和大范围有机废弃产品处理的测试系统的开发(英文)

综合数字区域模型在区域可持续发展的任何模型实现中都是不可或缺的,而空间数据基础设施为综合数字区域模型提供了一个可靠的基础。其可以很方便地在地图信息或者直接在地理信息系统(GIS)内形成。这种GIS系统具有开发良好的模型函数,能够集成专家系统,也能被设计全尺度多媒体产品。GIS允许集成不同的信息资源、模型、可视化和分析、各种假设的详尽细节和为诸如自然-社会-经济等的复杂系统提供可选开发方案。一个综合辅助信息系统的结构包括紧密相关的社会-政治、经济(或生产)、自然资源和环境模块。它提供了对于不同区域范围社会生态系统的全面描述,显示了自然和人类资源的重要性。人们在这个研究领域将会谈及自然和社会管理。根据它们的变化层次体系(从全局范围到局部范围)可以描述所有专题,并且考虑在不同尺度上描述的现象的专业特征。超媒体系统原理可以通过链接集成主题来实现。这种系统的日益复杂性使得系统的智能化成为必要,专家系统和神经元网络可以从很复杂并且非常模糊的问题中得出可行的解决方案。现代GIS配有很多设备,对用户来说,这使得用基础地图和互联网获取必要的数据来编制专题图成为可能。数学建模的专业方法具有特殊的重要性,特别是那些旨在追求在区域变换到可持续发展模型时设想的详尽细节的方法。最高级的AIS能作为全尺度的决策支持系统使用。莫斯科国立大学试图实现上述思想,开发了俄罗斯可持续发展信息系统框架,特以俄罗斯南部地区为一案例。该示例一方面作为更大区域即国家的一部分进行描述,另一方面作为一个或多或少、基于资源发展的单元进行描述。也能对区域发展战略和改革措施提出建议。我们已经对所有俄罗斯地区进行了分类,并且指出了不同组(工业、农业等)的最典型代表。将精心设计几个系统的区域分支来描述整个国家的不同地域类型。计算机辅助信息系统提供用户以各种各样传统地图集的计算机的模拟,为决策者对未来的设计和区域发展变量评估等创造了条件。我们正在开发一个大范围有机废弃产品处理的测试GIS系统。其主要目标是为在废弃物储存和掩埋场所的生物降解进行方法研究。其应用包括:存放生活和工业废品的场所的使用和改进(包括工业和农业的场所和废品产生的地方);污水处理设备的建设和重建等。