大陆裂谷中断层的演化：北贝加尔盆地西南端构造地貌证据

北贝加尔盆地西南端位于贝加尔盆地中部,包括Olkhon岛及其邻区,文中研究了这个区域的构造地貌格架。北贝加尔盆地西南端的构造地貌类型是由走滑构造末端的一系列雁列构造、裂谷断层及次级断层的末端复合构造控制。朝着海的方向Olkhon地区次级断层包括4个连续的末端复合构造Primorsky断层带,Buguldeika-Chernorud地堑—MaloyeMore裂谷盆地—Ushkaniy断层带,Tazheran高原—Olkhon岛鞍部和淹没的Akademichesky山脊,Olkhon断层带。这个末端构造被横向断层切为几段,其活动时间在南西最年轻,向北东逐渐加大,同时断层垂直断距从数十米增至2000余米,且断层带变得更为宽阔,也更为复杂。Pri-morsky断层带向北东从西南端简单的线性断层崖,变为断层围限的断块系统,再变为上升和沉降(盆地)块体系统,并最终汇入一个盆地之中;沿着这个方向裂谷边界断层则突然地复合于盆地构造中。这种构造地貌类型记录了断层演化的时间和空间关系,即从属于递进的沉降和加宽直至最终发育为盆地。因此其趋势是发育完好的湖盆、陆地构造直至被水淹没。陆地构造淹没趋势及没有断层围限块体的盆内构造组合可能是与犁式断层旋转相关的陆内裂谷的共同特点,并具一般裂谷的打开机制。     

Prediction of Indoor Air Quality from Soil-Gas Data at Industrial Buildings

Subslab or shallow soil-gas data are often compared with indoor air concentration data in vapor intrusion (VI) evaluations. If no indoor air data are available or confounding sources are present, or if future scenarios are considered, the soil-gas data may be used to estimate the indoor air concentrations due to VI. The typical approach in risk assessments is to use the 95th percentile values from a set of concentration data. For VI studies, however, this rarely is an option because the data sets tend to be quite small. Therefore, various guidance documents urge the use of maximum soil-gas values. This may be reasonable for small residential buildings, but can lead to very conservatively biased estimates if applied to large industrial buildings with localized areas of contamination, especially given that the sampling locations may not be randomly selected and instead are biased toward worst-case locations. By this approach, VI guidance implicitly tolerates a large percentage of false positive decision errors to minimize the number of false negative decision errors. In this paper, implications of using maximum values are discussed and illustrated with data sets from a number of large industrial buildings at various sites. An alternative approach to using maximum soil-gas values is proposed that serves to reduce the number of false positive results while controlling the number of false negatives to an acceptable level.     

Low energy neutral atom imaging on the Moon with the SARA instrument aboard Chandrayaan-1 mission

This paper reports on the Sub-keV Atom Reflecting Analyzer (SARA) experiment that will be flown on the first Indian lunar mission Chandrayaan-1. The SARA is a low energy neutral atom (LENA) imaging mass spectrometer, which will perform remote sensing of the lunar surface via detection of neutral atoms in the energy range from 10 eV to 3 keV from a 100km polar orbit. In this report we present the basic design of the SARA experiment and discuss various scientific issues that will be addressed. The SARA instrument consists of three major subsystems: a LENA sensor (CENA), a solar wind monitor (SWIM), and a digital processing unit (DPU). SARA will be used to image the solar wind-surface interaction to study primarily the surface composition and surface magnetic anomalies and associated mini-magnetospheres. Studies of lunar exosphere sources and space weathering on the Moon will also be attempted. SARA is the first LENA imaging mass spectrometer of its kind to be flown on a space mission. A replica of SARA is planned to fly to Mercury onboard the BepiColombo mission.     

A simple method to classify diamicts by scanning electron microscope from surface microtextures

Interpretation of quartz sand grain surface microtextures with scanning electron microscopy has been riddled with inconsistencies, invalid assumptions and much subjectivity. Therefore, a novel classification for analysing grain surface microtextures is presented based on the origin of complete grain surfaces. This novel method has solved most of the earlier problems of interpretation of surface microtextures, and it is easy to use and to quickly find evident genetic interpretations of diamicts. The data are plotted graphically in ‘2‐History Diagrams’ or ‘3‐History Diagrams’ for quick visual inspection and statistical evaluation. Source rocks and Quaternary glacial deposits from Scandinavia and Southern Ontario, representing different ice‐substrate dynamics, are analysed to define surface microtextures from typical glacigenic grains, bedrock and fluvially transported grains. Typical glacially crushed grains display large‐scale fractures and abrasion. Shield bedrock grains display large or small‐scale fractures and solution/precipitation microtextures. Fluvially transported grains exhibit abrasion and solution/precipitation microtextures.     

Smart Interpretation – automatic geological interpretations based on supervised statistical models

A method that infers a statistical model, which describes a relation between the knowledge of a geologist (quantified by geological interpretations) and the available information (such as geophysical data, well log data, etc.) that a geologist uses when he/she interprets is proposed and tested. The statistical model is then used to perform automatic geological interpretations wherever the same kinds of information, as used for the initial interpretations, are available. This methodology is named Smart Interpretation (SI). In this study, we look at two different approaches to infer such a model, and we demonstrate the applicability of the model to predict the depth to a low resistivity subsurface layer, based on interpretations from a geological expert, using a 19-layered resistivity model obtained from inversion of airborne electromagnetic (AEM) data. This study shows that SI is capable of making predictions with great accuracy. The method is fast and is able to handle large amounts of data of different origin, which suggest that the method may become a very useful approach to assist in geological modeling based on increasingly large amounts of data of different nature.