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1.
In order to test different hypotheses concerning the Paleozoic evolution of the Ural–Mongol belt (UMB) and the amalgamation of Eurasia, we studied Middle Devonian basalts from two localities (11 sites) and Lower Silurian volcanics, redbeds, and intra-formational conglomerates from three localities (20 sites) in the Chingiz Range of East Kazakhstan. The Devonian rocks prove to be heavily overprinted in the late Paleozoic, and a high-temperature, presumably primary, southerly, and down component is isolated at only four sites from a homoclinal section. Most Silurian redbeds are found to be remagnetized in the late Paleozoic; in contrast, a bipolar near-horizontal remanence, isolated from Silurian volcanics, is most probably primary as indicated by positive tilt and conglomerate tests. Analysis of paleomagnetic data from the Chingiz Range shows that southward-pointing directions in Ordovician, Silurian, and Devonian rocks are of normal polarity and hence indicate large-scale rotations after the Middle Devonian. The Chingiz paleomagnetic directions can be compared with Paleozoic data from the North Tien Shan and with the horseshoe-shaped distribution of subduction-related volcanic complexes in Kazakhstan. Both paleomagnetic and geological data support the idea that today's strongly curved volcanic belts of Kazakhstan are an orocline, deformed mostly before mid-Permian time. Despite the determination of nearly a dozen new Paleozoic paleopoles in this study and other recent publications by our team, significant temporal and spatial gaps remain in our knowledge of the paleomagnetic directions during the middle and late Paleozoic. However, the paleomagnetic results from the Chingiz Range and the North Tien Shan indicate that these areas show generally coherent motions with Siberia and Baltica, respectively.  相似文献   
2.
对哈萨克斯坦几次M≥6强震前动物行为异常的有关资料进行了研究,发现动物(20种)是通过其行为反应的变化对地震作出响应的。另外,在阿拉木图的山前地带(地震活动值大于9),对动物血液学和生物学指数上的动态变化进行了观察。  相似文献   
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4.
宋天锐 《中国地质》2007,34(2):315-323
笔者是在“五国编图项目”(中国、俄罗斯、哈萨斯坦、蒙古国、韩国)的中国北方磷矿床资料研究基础之上完成本论文的。中国北方磷矿床分为“沉积型”、“沉积变质型”和“岩浆型”三大类型。沉积型磷矿床主要产生于晚震旦纪陡山沱期和早古生代寒武纪早期,磷质来源以海洋生物磷为主;沉积变质型磷矿床主要产生于中元古代,磷质来源以火山磷质为主,也可能有生物磷质参与;沉积型和沉积变质型磷矿都包含陆地风化迁入盆地中的磷成分;岩浆磷矿床主要产生于海西期和加里东期的超镁铁岩浆岩,多与铁、钒、钛成为成矿系列。沉积型磷矿在华北地台南缘和塔里木地块北缘应重视,而沉积变质型在华北地台北缘有远景;岩浆型则主要勘查超镁铁岩系列。  相似文献   
5.
巴尔喀什成矿带是世界著名的中亚成矿域斑岩型铜钼成矿带,产出许多斑岩型铜钼矿床和一些石英脉-云英岩型钨钼矿床。中亚成矿域可能是一个多核成矿系统,具有以走滑断裂为边界构成的断裂构造体系并受之控制。本文对巴尔喀什成矿带巴尔喀什—阿克沙套地区11件辉钼矿样品进行了Re-Os同位素分析,得到博尔雷大型斑岩型铜(钼)矿床和东科翁腊德、扎涅特、阿克沙套石英脉-云英岩型钨钼矿床的辉钼矿模式年龄(平均值)分别为315.9Ma、298.0Ma、295.0Ma和289.3Ma;其中,东科温腊德、阿克沙套和扎涅特等3个矿床的Re-Os等时线年龄为297.9-+30..949Ma,MSWD值为0.97。辉钼矿Re-Os年龄说明巴尔喀什成矿带Cu-Mo-W成矿作用发生在315.9~289.3Ma期间,Cu-Mo-W矿床的形成可分为两期:一期为斑岩型铜钼矿床,约形成于315.9Ma;另一期为石英脉-云英岩型钨钼矿床,约形成于297.9Ma。根据辉钼矿模式年龄和等时线年龄,推测该地区花岗斑岩和伟晶岩的形成时代与相应的矿床基本同时,均为晚石炭世,属海西期构造岩浆活动的产物。通过与我国境内西、东准噶尔和东天山斑岩铜矿带的对比表明,巴尔喀什成矿带铜钼成矿作用的年龄介于东天山土屋—延东斑岩铜矿与西准噶尔包古图斑岩铜矿之间。分析表明,中亚成矿域大规模斑岩型铜钼成矿作用集中在晚石炭世,属海西晚期构造-岩浆活动的产物。  相似文献   
6.
<正>The Central Asian metallogenic domain(CAMD) is a multi-core metallogenic system controlled by boundary strike-slip fault systems.The Balkhash metallogenic belt in Kazakhstan,in which occur many large and super-large porphyritic Cu—Mo deposits and some quartz vein- and greisen-type W—Mo deposits,is a well-known porphyritic Cu—Mo metallogenic belt in the CAMD.In this paper 11 molybdenite samples from the western segment of the Balkhash metallogenic belt are selected for Re—Os compositional analyses and Re—Os isotopic dating.Molybdenites from the Borly porphyry Cu deposit and the three quartz vein-greisen W—Mo deposits—East Kounrad.Akshatau and Zhanet—all have relatively high Re contents(2712—2772μg/g for Borly and 2.267—31.50μg/g for the other three W—Mo deposits),and lower common Os contents(0.670—2.696 ng/g for Borly and 0.0051—0.056 ng/g for the other three).The molybdenites from the Borly porphyry Cu—Mo deposit and the East Kounrad,Zhanet,and Akshatau quartz vein- and greisen-type W—Mo deposits give average model Re—Os ages of 315.9 Ma,298.0 Ma,295.0 Ma,and 289.3 Ma respectively.Meanwhile,molybdenites from the East Kounrad,Zhanet,and Akshatau W—Mo deposits give a Re—Os isochron age of 297.9 Ma,with an MSWD value of 0.97.Re-Os dating of the molybdenites indicates that Cu—W—Mo metallogenesis in the western Balkhash metallogenic belt occurred during Late Carboniferous to Early Permian(315.9—289.3 Ma),while the porphyry Cu—Mo deposits formed at—316 Ma,and the quartz vein-greisen W—Mo deposits formed at ~298 Ma.The Re—Os model and isochron ages thus suggest that Late Carboniferous porphyry granitoid and pegmatite magmatism took place during the late Hercynian movement.Compared to the Junggar-East Tianshan porphyry Cu metallogenic belt in northwestern China,the formation of the Cu—Mo metallogenesis in the Balkhash metallogenic belt occurred between that of the Tuwu-Yandong in East Tianshan and the Baogutu porphyry Cu deposits in West Junggar. Collectively,the large-scale Late Carboniferous porphyry Cu—Mo metallogenesis in the Central Asian metallogenic domain is related to Hercynian tectono-magmatic activities.  相似文献   
7.
哈萨克斯坦萨亚克铜矿田产于晚石炭世闪长玢岩、石英闪长玢岩或花岗闪长玢岩与中石炭统灰岩的接触带上,铜矿体呈透镜状、脉状产于矽卡岩中。其成矿期可以划分为4个阶段:石榴子石矽卡岩阶段(Ⅰ)、绿帘石-石榴子石矽卡岩阶段(Ⅱ)、磁铁矿阶段(Ⅲ)和石英-硫化物阶段(Ⅳ)。铜矿化主要发生在石英-硫化物阶段,形成石英、黄铁矿、黄铜矿、磁黄铁矿,呈浸染状或脉状产于不同类型的矽卡岩或块状磁铁矿中。矽卡岩中的石榴子石有3种类型:石榴子石矽卡岩中的钙铁榴石(Grt-a)、交代钙铁榴石的含Al钙铁榴石(Grt-b)和绿帘石-石榴子石矽卡岩中具有环带结构的石榴子石(Grt-c)。从第一类到第三类石榴子石,平均w(Al2O3)从<1%逐渐升高至~5%;分子式中平均Fe3+原子数从2.15逐渐降低至1.57,显示成矿体系中Al的摩尔浓度逐渐升高、氧逸度逐渐降低。绿帘石-石榴子石矽卡岩中发育少量辉石,属于钙铁辉石-透辉石系列,在辉石分类图中落于普通辉石范围内。矽卡岩的地质特征、矿物组合和矿物化学特征表明,萨亚克矽卡岩是与花岗岩类侵入岩有关的岩浆热液与灰岩通过接触交代反应形成的钙质矽卡岩,随着矽卡岩化和成矿作用的进行,成矿体系的温度和氧逸度逐渐降低、pH值升高,导致磁铁矿和黄铁矿-磁黄铁矿-黄铜矿矿物组合依次发生沉淀。  相似文献   
8.
萨亚克大型铜矿田位于哈萨克斯坦北巴尔喀什斑岩成矿带中部,以矽卡岩型矿床为主。通过对矿区石英闪长岩的矿物化学和地球化学研究,发现石英闪长岩呈斑状结构,斑晶为斜长石和角闪石,其中的斜长石斑晶主要为中长石,角闪石斑晶为镁质普通角闪石;岩石属于高钾钙碱性系列,富集Rb、Sr、Ba等大离子亲石元素和轻稀土元素,亏损Nb、Ta和重稀土元素,高Sr/Y、La/Yb比值,与埃达克岩相似。地球化学特征指示萨亚克矿区侵入岩形成于岛弧环境,为矽卡岩-斑岩型成矿提供了有利的构造背景,岩石可能是岛弧玄武质岩浆在高压下经结晶分异而成。根据角闪石温压计及其成分与氧逸度和岩浆中水含量之间的关系,确定萨亚克石英闪长玢岩中角闪石斑晶结晶时岩浆的温度为799~843℃、处于3.6~9.6km深度范围内(P=1.2~3.2kbar)、氧逸度logfO2=-11.5~-12.0(ΔFMQ=2.0~2.8)、平均水含量为1.2%,相对较高的氧逸度和水含量有利于形成富含挥发分和Cu、Au等成矿物质的岩浆,是最终演化形成大型岩浆-热液型铜矿田(斑岩型、矽卡岩型)的有利条件。  相似文献   
9.
Affected by climate change and policy factors, Kazakhstan is the country with the most severe ecological degradation and grassland conflicts in Central Asia. Therefore, studying the state of grassland carrying resources in Kazakhstan is particularly important for understanding the responses of grassland ecosystems to climate change and human activities. Based on Kazakhstan's remote sensing data and animal husbandry statistics, this study analyzes the patterns of changes in grassland ecosystems in Kazakhstan based on the supply and consumption of these ecosystems. The results show that: 1) From 2003 to 2017, the number of livestock raised in Kazakhstan showed a trend of sustained and steady growth. Due to freezing damage, the scale of livestock farming decreased in 2011, but a spatial difference in the livestock farming structure was not obvious. 2) The fluctuation of grassland supply in Kazakhstan has increased, while the consumption due to animal husbandry has also continued to increase, resulting in an increasing pressure on the grassland carrying capacity. 3) Between 2003 and 2017, the overall grassland carrying status of Kazakhstan have been abundant, but the grassland carrying pressure index has shown a steadily increasing trend, the grassland carrying pressure is growing, and it is mainly determined by grassland productivity. The greater pressure in lower Kyzylorda state, the southern Kazakhstan state of the cultivated land and the northern Kazakhstan state has gradually expanded to include the agro-pastoral zone and the semi-desert zone.  相似文献   
10.
Quantitative analysis of the impact factors in energy-related CO2 emissions serves as an important guide for reducing carbon emissions and building an environmentally-friendly society. This paper aims to use LMDI method and a modified STIRPAT model to research the conventional energy-related CO2 emissions in Kazakhstan after the collapse of the Soviet Union. The results show that the trajectory of CO2 emissions displayed U-shaped curve from 1992 to 2013. Based on the extended Kaya identity and additive LMDI method, we decomposed total CO2 emissions into four influencing factors. Of those, the economic active effect is the most influential factor driving CO2 emissions, which produced 110.86 Mt CO2 emissions, with a contribution rate of 43.92%. The second driving factor is the population effect, which led to 11.87 Mt CO2 emissions with a contribution rate of 4.7%. On the contrary, the energy intensity effect is the most inhibiting factor, which caused–110.90 Mt CO2 emissions with a contribution rate of–43.94%, followed by the energy carbon structure effect resulting in–18.76 Mt CO2 emissions with a contribution rate of–7.43%. In order to provide an in-depth examination of the change response between energy-related CO2 emissions and each impact factor, we construct a modified STIRPAT model based on ridge regression estimation. The results indicate that for every 1% increase in population size, economic activity, energy intensity and energy carbon structure, there is a subsequent increase in CO2 emissions of 3.13%, 0.41%, 0.30% and 0.63%, respectively.  相似文献   
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