Environmental impacts from mining at Taojiang Mn ore deposit, central Hunan, China

The Taojiang Mn ore deposit was exploited in the early 1960s, and waste rocks were developed since then. Because the Mn ores were hosted within the metal-enriched black shales （Peng et al., 2004）, the continuous mining has led to the exposure of an immense quality of black shales, which might cause serious impacts on environments. The present study deals with this environmental issue with samples from the waste rocks, and from the surrounding soils and surface water. The mineralogy of the waste rock was studied using EMPA, then a large number of elements in all waste rock, soil, and water samples were analyzed at a wide range of concentrations with high accuracy using an Elan6000 ICP-MS machine at Guangzhou Institute of Geochemistry, Chinese Academy of Sciences. The waste rock is composed mostly of black shales, with minor Mn carbonates. Both black shales and Mn carbonates of the waste rock contain many sulfide minerals, mainly pyrite, with minor galena, sphalerite, chalcopyrite, and others. The waste rocks are enriched in many metals including Sc, V, Cr, Co, Ni, Fe, Mn, Cu, Zn, Pb, Th, U, Mo, Sb, Sn, Tl, and others, and the metals are mostly hosted within the sulfides. Weathering of waste rocks might cause emission of the following metals： V, Cd, Ni, Th, U, Mo, Sb, Tl, Sc, Cr, Cu, Zn, Sn, and minor Co, and Pb. The surrounding soils are highly enriched in Cr, Co, Cu, Zn, Mn, Mo, Cd, Tl, and Pb, with the enrichment factors of 2.67.3.8, 7.26, 7.27, 8.2, 5.7, 13, and 5.4, respectively. The element ratios （Rb/Cs, Fe/Mn, Nb/Zr, Hf/Zr, and Ba/Sr） and REE distribution patterns of the soils are similar to those of the waste rocks and bedrocks.     

Testing earthquake prediction methods: «The West Pacific short-term forecast of earthquakes with magnitude MwHRV ≥ 5.8»

Analyzing the tables and probability maps posted by Yan Y. Kagan and David D. Jackson in April 2002–September 2004 at http://scec.ess.ucla.edu/~ykagan/predictions_index.html and the catalog of earthquakes for the same period, the conclusion is drawn that the underlying method could be used for prediction of aftershocks, while it does not outscore random guessing when main shocks are considered.     

A way to synchronize models with seismic faults for earthquake forecasting: Insights from a simple stochastic model

Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobservable: important parameters cannot (or can rarely) be measured in Nature. Earthquakes, though, provide indirect but measurable clues of the stress and strain status in the lithosphere, which should be helpful for the synchronization of the models.The rupture area is one of the measurable parameters of earthquakes. Here we explore how it can be used to at least synchronize fault models between themselves and forecast synthetic earthquakes. Our purpose here is to forecast synthetic earthquakes in a simple but stochastic (random) fault model. By imposing the rupture area of the synthetic earthquakes of this model on other models, the latter become partially synchronized with the first one. We use these partially synchronized models to successfully forecast most of the largest earthquakes generated by the first model. This forecasting strategy outperforms others that only take into account the earthquake series. Our results suggest that probably a good way to synchronize more detailed models with real faults is to force them to reproduce the sequence of previous earthquake ruptures on the faults. This hypothesis could be tested in the future with more detailed models and actual seismic data.     

云南中强震的水氡前兆异常特征

2001年云南澜沧5.0、施甸5.2,5.9,5.3、宁蒗5.8、楚雄5.3和江川5.1级地震前，云南49项水氡前兆中的一些台站出现突出的异常。研究发现，根据这些异常项的异常特征和空间分布特征及历史震例，可对这几次地震预报的三要素，尤其是地点和时间做出较好的判断。     

川滇地区地震(Ms≥5.0)破裂类型与前兆异常分布的关系

对川滇地区 31次 (组 ) 5 .0级以上地震与余震次数的关系进行了统计 ,结合“强地震分为走滑型地震和断错型地震”的理论 ,确定了各次 (组 )地震的破裂类型。从物理机制上对地震破裂类型与震前前兆异常分布关系进行了讨论 ,由此进一步探讨了 5 .0级以上地震震后趋势预测     

试述福建顺昌南舟萤石矿地质特征

顺昌南舟萤石矿位于顺昌县埔上镇南舟村境内，1996年福建省区域地质调查队开展1：5万埔上幅区调时发现矿体，后开展普查工作表明该矿床规模大、交通方便，易于开采，现已投入开发利用。南舟萤石矿成矿地质特征在闽北丰富的萤石资源中具有一定代表性。     

b值在地震预测中的三类应用及其物理基础与须注意的问题

将b值在地震预测中的直接应用归为三类：1）根据b值的动态变化预测地震。2）根据G－R律求出各级地震平均复发周期或年均发生率，推测未来一定时段如50年或100年内发生各级地震的危险性。3）根据G－R直线在横轴的截距，预测强余震的震级。讨论了这三种用法的物理基础及现有工作中容易出现的问题。     

江苏高邮地震台地磁变化与地震关系的初探

分析了江苏高邮地磁台1980年至2002年地磁垂直分量日变幅逐日比值的高值异常与江苏及邻区ML5．0以上地震之间的关系，发现它们之间有良好的对应关系，通过分析地磁垂直分量谐波幅度的逐日比，提出了适用于高邮地磁台的地震分析预报参数，并对其内检预报效能进行了评价。     

岳阳及周边地区地震构造与地震活动性研究

陈述了岳阳市及周边地区的主要断裂带及其地震活动，归纳了发震部位。认为利用小震条带预报本区地震具有积极意义，并运用数理统计法预测了本区今后50及100年内的地震活动水平。     

淇、卫河流域“96·8”致洪暴雨过程的数值模拟

应用LASGREMM模式 ,对淇、卫河流域“96·8”致洪暴雨过程进行了模拟预报分析。结果表明 ,LAS GREM模式不仅能较准确地预报淇、卫河流域暴雨落区 ,而且可以进一步分析天气过程的特点及演变情况