纳滤分离铝锂过程研究

本文探讨了纳滤分离Al~(3+)和Li~+的可行性,研究了含盐量和铝锂比对分离效率的影响,提出了从锂云母浸出液中分离回收锂的新方法。实验结果表明,纳滤膜对Al~(3+)和Li~+的截留率随含盐量的升高而降低,其中Li~+始终呈现负浓度梯度扩散的趋势,而Al~(3+)的截留率始终稳定在99%以上。当含盐量为45 g/L时,铝锂分离因子最高可达248.33,膜面相应Zeta电位的绝对值达到最大。随着溶液中铝锂比的变化,Al~(3+)和Li~+的截留率分别在不同铝锂比的条件下出现拐点,溶液的pH呈现先下降后上升最后下降的复杂趋势。本实验研究发现,DK膜能够在酸性环境下实现高效的铝锂分离和锂的浓缩,从而为锂云母浸出液中锂的提取提供新的思路。     

全球粮食安全格局的时空演化

Food security is the primary prerequisite for achieving other Millennium Development Goals(MDGs).Given that the MDG of“halving the proportion of hungers by 2015”was not realized as scheduled,it will be more pressing and challenging to reach the goal of zero hunger by 2030.So there is high urgency to find the pattern and mechanism of global food security from the perspective of spatio-temporal evolution.In this paper,based on the analysis of database by using a multi-index evaluation method and radar map area model,the global food security level for 172 countries from 2000 to 2014 were assessed;and then spatial autocorrelation analysis was conducted to depict the spatial patterns and changing characteristics of global food security;then,multi-nonlinear regression methods were employed to identify the factors affecting the food security patterns.The results show:1)The global food security pattern can be summarized as“high-high aggregation,low-low aggregation”.The most secure countries are mainly distributed in Western Europe,North America,Oceania and parts of East Asia.The least secure countries are mainly distributed in sub-Saharan Africa,South Asia and West Asia,and parts of Southeast Asia.2)Europe and sub-Saharan Africa are hot and cold spots of the global food security pattern respectively,while in non-aggregation areas,Haiti,North Korea,Tajikistan and Afghanistan have long-historical food insecurity problems.3)The pattern of global food security is generally stable,but the internal fluctuations in the extremely insecure groups were significant.The countries with the highest food insecurity are also the countries with the most fluctuated levels of food security.4)The annual average temperature,per capita GDP,proportion of people accessible to clean water,political stability and non-violence levels are the main factors influencing the global food security pattern.Research shows that the status of global food security has improved since the year 2000,yet there are still many challenges such as unstable global food security and acute regional food security issues.It will be difficult to understand these differences from a single factor,especially the annual average temperature and annual precipitation.The abnormal performance of the above factors indicates that appropriate natural conditions alone do not absolutely guarantee food security,while the levels of agricultural development,the purchasing power of residents,regional accessibility,as well as political and economic stability have more direct influence.     

Mineral Potential Mapping Using a Conjugate Gradient Logistic Regression Model

Mineral potential prediction is a process of establishing a statistical model that describes the relationship between evidence variables and mineral occurrences. In this study, evidence variables were constructed from geological, remote sensing, and geochemical data collected from the Lalingzaohuo district, Qinghai Province, China. Based on these evidence variables, a conjugate gradient logistic regression (CG-LR) model was established to predict exploration targets in the study area. The receiver operating characteristic (ROC) and prediction–area (P-A) curves were used to evaluate the effectiveness of the CG-LR model in mineral potential mapping. The difference between the vertical and horizontal coordinates of each point on the ROC curve was used to determine the optimal threshold for classifying the exploration targets. The optimal threshold corresponds to the point on the ROC curve where the difference between the vertical coordinate and the horizontal coordinate is the largest. In exploration target prediction in the study area, the CG algorithm was used to optimize iteratively the LR coefficients, and the prediction effectiveness was tested for different epochs. With increasing iterations, the prediction performance of the model becomes increasingly better. After 60 iterations, the LR model becomes stable and has the best performance in exploration target prediction. At this point, the exploration targets predicted by the CG-LR model occupy 14.39% of the study area and contain 93% of the known mineral deposits. The exploration targets predicted by the model are consistent with the metallogenic geological characteristics of the study area. Therefore, the CG-LR model can effectively integrate geological, remote sensing, and geochemical data for the study area to predict targets for mineral exploration.

     

Characteristics of Permeability Changes in Bituminous Coal Under Conditions of Stress Variation Due to Repeated Mining Activities

The factors affecting permeability change under repeated mining of coal seams are important study aspects that need to be explored. This study combined various stress variation characteristics of protective seam mining and simplified the stress path of repeated mining in protective seam mines. Based on the results from the bespoke gas flow and displacement testing apparatus, seepage tests for simulated repetitive mining were carried out. The results simulated the actual behavior very well. With any drastic increase in the mining influence, the axial deviation stress in the stress path increased, and the greater the difference in coal permeability during the unloading and stress recovery stage, the more substantial the increase in permeability. The change in coal permeability was significantly influenced by the severity of simulated repeated mining cycles. When the mining stress exceeded a critical value, the permeability of the coal sample increased with the increase in the number of loading and unloading cycles, but the reverse was true when the mining stress was lower than the critical value. The effective sensitivity of seepage to the applied stress decreased with an increase in the number of stress cycles. With a decrease in the deviation stress, that is, with lower severity of mining influence, the effective sensitivity of coal seepage to stress gradually decreased.

     

Exploring Spatially Non-stationary Relationships in the Determinants of Mineralization in 3D Geological Space

Exploring the spatial relationships between various geological features and mineralization is not only conducive to understanding the genesis of ore deposits but can also help to guide mineral exploration by providing predictive mineral maps. However, most current methods assume spatially constant determinants of mineralization and therefore have limited applicability to detecting possible spatially non-stationary relationships between the geological features and the mineralization. In this paper, the spatial variation between the distribution of mineralization and its determining factors is described for a case study in the Dingjiashan Pb–Zn deposit, China. A local regression modeling technique, geological weighted regression (GWR), was leveraged to study the spatial non-stationarity in the 3D geological space. First, ordinary least-squares (OLS) regression was applied, the redundancy and significance of the controlling factors were tested, and the spatial dependency in Zn and Pb ore grade measurements was confirmed. Second, GWR models with different kernel functions in 3D space were applied, and their results were compared to the OLS model. The results show a superior performance of GWR compared with OLS and a significant spatial non-stationarity in the determinants of ore grade. Third, a non-stationarity test was performed. The stationarity index and the Monte Carlo stationarity test demonstrate the non-stationarity of all the variables throughout the area. Finally, the influences of the degree of non-stationary of all controlling factors on mineralization are discussed. The existence of significant non-stationarity of mineral ore determinants in 3D space opens up an exciting avenue for research into the prediction of underground ore bodies.

     

北斗卫星类型间偏差快速改正分析

针对北斗卫星类型间偏差（ISTB）导致载波相位差分高精度定位（RTK）的整周模糊度无法固定问题,本文提出了改进ISTB快速改正方法,在观测量层面仅利用1组不同卫星类型的载波相位差分观测量即可实现ISTB估计与改正,实际应用中较传统方法更具普适性与简易性。该方法的测试结果表明,ISTB值由NH码调制不同引起,不同频点的ISTB值具有不一致性;此外,有无改正ISTB的北斗RTK性能对比反映了ISTB会严重降低整周模糊度固定与RTK定位性能。由此可知,本文方法能够保障现阶段北斗接收机更新换代过程中北斗RTK的高精度与高可靠性能。     

高分六号宽幅相机在轨几何定标及精度验证

高分六号宽幅相机能够实现单相机成像幅宽优于800 km,对大尺度地表观测和环境监测具有独特优势。在轨几何定标是光学遥感卫星几何处理的关键环节,直接影响影像的几何质量。本文充分考虑高分六号宽幅相机超大视场的畸变特性以及多谱段的成像特点,提出宽幅相机在轨几何定标方法,采用基于探元指向角的几何定标模型补偿宽幅相机系统误差,通过绝对定标和相对定标方法联合估计各波段的内外定标参数。利用Landsat 8影像、资源三号DSM为参考数据,对宽幅相机进行绝对定标处理,再利用ASTER GDEM为参考数据进行相对定标处理,其几何定标结果表明,高分六号宽幅影像绝对定位精度在3像素左右,内部几何精度能稳定在1像素,且波段间配准精度在0.3像素以内,表明在轨几何定标后高分六号宽幅影像几何质量得到了明显的提升。     

GNSS多频融合精密单点定位频率间卫星钟偏差研究

全球导航卫星系统(GNSS)提供多频信号,多频融合已经成为一种趋势。在精密钟差估计(PCE)的过程中,卫星钟差参数会吸收卫星端稳定的伪距偏差和时变的相位偏差,这些偏差均与频率相关。因而使用不同的观测值进行PCE时,得到的卫星钟差估值是不同的,它们之间的差值被定义为频率间卫星钟偏差(IFCB)。按组成成分,IFCB可以分成伪距相关的IFCB(CIFCB)和相位相关的IFCB(PIFCB)两部分。国际GNSS服务(IGS)提供的精密卫星钟差产品是基于双频消电离层(IF)组合观测值生成的。由于IFCB的存在,导致IGS卫星钟差产品不能直接应用于多频精密单点定位(PPP)。IFCB的精确考虑已经成为多频PPP的一个关键问题。本研究旨在对IFCB特性和估计方法开展系统深入的研究,并评估其对多频PPP解的影响。     

机载光学全谱段遥感林火监测

森林火灾是一种危害极大的自然灾害,是森林扰动的主要类型之一,直接影响森林生态系统结构、碳循环甚至全球气候的变化。近年来,航空平台和传感器的技术进步有效地提升了机载遥感系统探测和监测森林火灾的能力,推动了机载遥感在森林可燃物调查及载量评估、火险测报预测、火场态势及火情监测、灾害损失评估以及火烧迹地生态修复治理等方面的应用。本文首先介绍了中国林业科学研究院机载光学全谱段遥感系统CAF-LiTCHy（Chinese Academy of Forestry’s LiDAR,Thermal,CCD and Hyperspectral airborne observation system）,描述了激光雷达扫描仪、热红外相机、CCD相机和高光谱传感器等传感器的参数;然后,阐明了集成方案和观测数据的处理方法;最后,以四川省西昌市“3.30森林火灾”作为该系统火后灾情遥感调查和灾情评估应用示例,综合多传感器数据特征,进行森林火烧程度评价,分析该系统采集的正射影像、冠层高度模型、高光谱影像、热红外影像在森林火灾监测评价中的潜力。研究结果表明CAF-LiTCHy机载遥感观测系统能有效获取森林火灾的灾情信息、火场及火环境参数,可为预防、预报预警、扑救指挥、灾害评估和生态修复提供支持。     

代表性人口空间分布数据集的精度评价——以2010年广东省为例

以人口密度差异显著的广东省为研究区,比较Worldpop、GPW v4和2种中国公里网格人口分布数据集的空间分布一致性,并以第六次全国人口普查数据为真值,按人口密度分为高、中、低3组,从误差的数值分布和空间分布两方面定量评价4种数据集的精度,最后讨论估算误差的可能来源及数据适用性。结果表明,4种网格人口数据集中Worldpop整体精度最高,且在人口密集区的精度也是最高;GPW v4在低人口密度和中人口密度区域精度略高于Worldpop,但对镇街内人口分布细节刻画不够详细;2种中国公里网格人口分布数据集精度较前两者低,主要受空间化方法和模型变量的选择所限制。Worldpop适合用于人口密度中等及人口密度高区域的精细化研究,GPW v4适合用于长时序、最小研究单元大于镇街的研究,第一种中国公里网格人口分布数据集适合用于需要考虑镇街内人口分布和空间异质性的研究,第二种中国公里网格人口分布数据集适用于需要考虑人口分布细节和空间格局变化的长时序研究。