Geochemical signatures of Mesoproterozoic siliciclastic rocks of the Kaimur Group of the Vindhyan Supergroup,Central India

The Upper Kaimur Group of the Vindhyan Supergroup in Central India, primarily consists of three rock types-DhandraulSandstone, Scarp Sandstone and Bijaigarh Shale. Mineralogically and geochemically, they are quartz arenite, sublitharenite to litharenite and litharenite to shale in composition, respectively. The A-CN-K ternary plot and CIA and ICV values suggest that the similar source rocks suffered severe chemical weathering, under a hot-humid climate in an acidic environment with higher P _{CO 2}, which facilitated high sediment influx in the absence of land plants. Various geochemical discriminants, elemental ratios like K₂O/Na₂O, Al₂O₃/TiO₂, SiO₂/MgO, La/Sc, Th/Sc, Th/Cr, Gd_N/Yb_N and pronounced negative Eu anomalies indicate the rocks to be of post-Archean Proterozoic granitic source, with a minor contribution of granodioritic input, in a passive margin setting. The sediments of the Upper Kaimur Group were probably deposited in the interglacial period in between the Paleoproterozoic and Neoproterozoic glacial epochs.     

欧洲二氧化碳地质封存能力评价——欧盟地质封存潜力项目

欧盟地质封存潜力项目的工作重点是欧洲二氧化碳点源、基础设施以及地质封存的GIS编图。该项目的主要目标是评价欧洲深部咸水含水层、油气构造与煤层中二氧化碳的地质封存能力。其他优先考虑的事项是进一步开发地质封存能力评价、经济模拟与场地选择的方法,以及开展国际合作,尤其是与中国合作。欧盟地质封存潜力项目成果包括适于二氧化碳地质封存的25个国家和欧洲大多数沉积盆地。     

环球

英国政府因空气污染遭欧盟起诉3月20日,欧盟委员会宣布,因为治理空气污染不力。决定对英国政府提起诉讼。英国政府由此面临每年超过3亿欧元巨额罚款的风险。欧盟委员会表示,因为英国空气中的二氧化碳含量未能达到欧盟的标准,他们正在对英国提起诉讼。英国因此成为第一个因为空气质量未达标而被欧盟起诉的国家。     

海水酸化会削弱鲨鱼的感官功能

<正>一般说来,海洋肉食动物鲨鱼在很大程度上靠嗅觉寻找分散于广阔环境中的猎物。然而,研究人员不久前在Global Change Bilolgy杂志在线版上报道说:根据预测,随着全球海洋的变化,鲨鱼这种久经历练的捕猎能力可能会受到损害。由于人类活动释放到大气中的二氧化碳被海水吸收,海水的酸度变得越来越大。以前的研究表明,富含二氧化碳的酸性海水可能会削弱珊瑚礁鱼类嗅     

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation （NPP） to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model （CanESM2） of the Canadian Centre for Climate Modelling and Analysis （CCCma）, which are part of the phase 5 of the Coupled Model Intercomparison Project （CMIP5）. The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m^-2 yr^-1 and-0.14 gC m^- 2 yr^-2, respec- tively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at -1.79 gC m^-2 yr^-2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m^-2 yr^-1 and 0.84 gC m^-2 yr^-2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m^2 yr^-1 and 0.83 gC m^2 yr^-2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of-0.39 kg m^-2 yr^-1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration （experiment M2）, and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-     

Verifying Fossil-Fuel Carbon Dioxide Emissions Forecasted by an Artificial Neural Network with the GEOS-Chem Model

In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions （ff） in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data （1979-2008） from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System （GEOS）-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.     

Distributions and air-sea fluxes of CO2 in the summer Bering Sea

The 3rd Chinese National Arctic Research Expedition(CHINARE–Arctic III) was carried out from July to September in 2008. The partial pressure of CO2(pCO2) in the atmosphere and in surface seawater were determined in the Bering Sea during July 11–27, 2008, and a large number of seawater samples were taken for total alkalinity(TA) and total dissolved inorganic carbon(DIC) analysis. The distributions of CO2 parameters in the Bering Sea and their controlling factors were discussed. The pCO2 values in surface seawater presented a drastic variation from 148 to 563 μatm(1 μatm = 1.013 25×10-1 Pa). The lowest pCO2 values were observed near the Bering Sea shelf break while the highest pCO2 existed at the western Bering Strait. The Bering Sea generally acts as a net sink for atmospheric CO2 in summer. The air-sea CO2 fluxes in the Bering Sea shelf, slope, and basin were estimated at-9.4,-16.3, and-5.1 mmol/(m2·d), respectively. The annual uptake of CO2 was about 34 Tg C in the Bering Sea.     

原生矿物组分对CO_2地质储存地球化学过程的影响

CO2的地质储存是迅速减少温室气体向大气排放最直接、最有效的方法之一,其封存量受很多因素影响,储层原生矿物组分是其中之一。本文以松辽盆地、美国墨西哥湾、日本Nagaoka场地资料为基础,对CO2矿物封存过程进行数值摸拟。结果表明:原生矿物组成及含量相差不大时,地球化学反应过程相似,原生矿物组成较为复杂时,地球化学反应过程也更复杂;在以石英、长石为主的砂岩储层中,长石和绿泥石是重要的溶解矿物,铁白云石和片钠铝石是主要的固碳矿物;CO2矿物封存量随着原生矿物中奥长石和绿泥石含量增加而增大,其中奥长石的影响更大。以上研究对CO2地质储存储层的选取有指导意义。     

高温地热生产井碳酸钙结垢定量评价：两相流动——以西藏羊八井为例

高温地热生产井碳酸钙结垢定量评价涉及到复杂的物理和化学过程,其中井筒中的两相流研究是评价的基础.本文首先基于质量守恒、能量守恒和动量守恒方程,建立了CO₂-H₂O体系井筒两相相变稳定流动模型,提出了稳健的求解方法,并验证了其计算结果的可靠性.然后,在西藏羊八井地热田典型井开展了静止和放喷状态下的井筒中的温度和压力测试,并结合放喷试验,采用开发的模型成功评价了高温地热生产井筒两相流动过程.结果显示：气相和液相之间的速度差对井筒中温度和压力的分布有决定性的影响,不考虑气相和液体之间的速度差,会使模型计算结果远远偏离测量值.在开采速率19.10 kg/s的条件下,计算的井口温度和压力分别约为128℃和2.6 bar;井口的气相质量分数在6%～7%之间,对应的井口气相饱和度约为0.84;从闪蒸点往上大概20～30 m气相和液相中CO₂质量分数变化较为剧烈,也是碳酸钙结垢严重井段.