Geochemistry and mineralogy of shallow alluvial aquifers in Daudkandi upazila in the Meghna flood plain, Bangladesh

The shallow alluvial aquifers of the delta plains and flood plains of Bangladesh, comprises about 70% of total land area are mostly affected by elevated concentrations of arsenic (As) in groundwater exposing a population of more than 35 million to As toxicity. Geochemical studies of shallow alluvial aquifer in the Meghna flood plain show that the uppermost yellowish grey sediment is low in As (1.03 mg/kg) compared to the lower dark grey to black sediment (5.24 mg/kg) rich in mica and organic matter. Sequential extraction data show that solid phase As bound to poorly crystalline and amorphous metal (Fe, Mn, Al)-oxyhydroxides is dominant in the grey to dark grey sediment and reaches its maximum level (3.05 mg/kg) in the mica rich layers. Amount of As bound to sulphides and organic matter also peaks in the dark grey to black sediment. Vertical distributions of major elements determined by X-ray fluorescence (XRF) show that iron (Fe₂O₃), aluminum (Al₂O₃) and manganese (MnO) follow the general trend of distribution of As in the sediments. Concentrations of As, Mn, Fe, HCO₃ ⁻, SO₄ ²⁻ and NO₃ ⁻ in groundwater reflect the redox status of the aquifer and are consistent with solid phase geochemistry. Mineralogical analysis by X-ray diffraction (XRD) and scanning electron microscopy (SEM) fitted with energy dispersive X-ray spectrometer (EDS) revealed dominance of crystalline iron oxides and hydroxides like magnetite, hematite and goethite in the oxidised yellowish grey sediment. Amorphous Fe-oxyhydroxides identified as grain coating in the mica and organic matter rich sediment suggests weathering of biotite is playing a critical role as the source of Fe(III)-oxyhydroxides which in turn act as sink for As. Presence of authigenic pyrite in the dark grey sediment indicates active reduction in the aquifer.     

赤道西太平洋晚第四纪古生产力变化:来自元素比值的证据

通过对热带碳循环"973"项目于2008年暖池区专题航次采集的KX08-97321-2柱状样(01°25.01'S,157°58.91'E;水深1897m)进行X射线荧光光谱(XRF)扫描以及浮游有孔虫氧同位素测定.结果发现,In(Ba/Ti)和In(ca/Ti)指示的赤道西太平洋古生产力在过去的370ka以来具有明显...     

基于多源时空大数据的区际迁徙人群多层次空间分布估算模型——以COVID-19疫情期间自武汉迁出人群为例

已有研究很少关注区际迁徙人群在不同尺度上空间分布的动态估算问题。COVID-19疫情爆发以来,坚决防止疫情扩散成为社会最紧迫的事情。在2020年1月23日武汉“封城”前夕,已有500多 万人离开了武汉,快速准确地推算这部分人群的去向,可以为防止疫情扩散和制定防疫决策提供科学依据。本文以此为例,基于开源腾讯位置请求大数据、百度迁徙大数据、土地覆盖数据等多源地理时空大数据,提出一种区际迁徙人群多层次空间分布动态估算模型,用于推算2020年除夕 （2020年1月24日）之前从武汉流入湖北省内各地的人群数量及其分布特征。结果显示：① 春节时段湖北省各地级市农村地 区人群增加数量占人群变化总量的比例平均达124.7%,从武汉市迁入各地级市的人群中至少51.3%流入农村地区;② 区县尺 度人群变化总量的空间分布呈现3个圈层结构：第一圈层为疫情核心区,包括武汉及其周边地区,以人群流出为主;第二圈层为 重点关注区,包括黄冈、黄石、仙桃、天门、潜江、随州、襄阳,以及孝感、荆门、荆州和咸宁的部分地区,以人群总量和农村地区人 群数量大幅增加为主;第三圈层为次级关注区,包括湖北西部宜昌、恩施、神农架和荆门部分地区,以人群小幅流入为主。最后,建议湖北省内,尤其是位于第二圈层内的区县,应高度关注农村地区人群的疫情防控。此研究成果在2~3天完成,显示大数据是可以快速地响应重大公共安全事件,为决策的制定提供一定支持的。     

Mining online footprints to predict user’s next location

Social media applications are widely deployed in mobile platforms equipped with built-in GPS tracking devices, and these devices have led to an unprecedented collection of geolocated data (geo-tags). Geo-tags, along with place names, offer new opportunities to explore the trajectory and mobility patterns of social media users. However, trajectory data captured by social media are sparsely and irregularly spaced and therefore have varying degrees of resolution in both space and time. Previous studies on next location prediction are mostly applicable for detecting the upcoming location of a moving object using dense GPS trajectories where locations are recorded at regular time intervals (e.g., 1 minute). Additionally, point features are commonly used to represent the locations of visits, but using point features cannot capture the variability of human mobility. This article introduces a new methodology to predict an individual’s next location based on sparse footprints accumulated over a long time period using social networks, and uses polygons to represent the location corresponding to the physical activity area of individuals. First, the density-based spatial clustering algorithm is employed to discover the most representative activity zones that an individual frequently visits on a daily basis, and a polygon-based region is then derived for each representative activity zone. A sparse mobility Markov chain model considering both the movements and online behaviors of the social media user is trained and used to predict the user’s next location. Initial experiments with a group of Washington DC Twitter users demonstrate that the proposed methodology successfully discovers the activity regions and predicts the user’s next location with accuracy approaching 78.94%.     

A collective human mobility analysis method based on data usage detail records

Human mobility patterns have been widely investigated due to their application in a wide variety of fields, for example urban planning and epidemiology. Many studies have introduced spatial networks into human mobility analyses at the collective level. However, these studies merely analyzed spatial network structure, and the underlying collective mobility patterns were not further discussed. In this paper, we propose a collective mobility discovery method based on community differences (CMDCD). We constructed spatial networks where nodes represent geographical entities and edge weights denote collective mobility intensity between geographical entities. The differences between communities detected from the networks constructed in different periods were then identified. Since collective spatial movement has a large influence on network structure, we can discover groups with different mobility patterns based on community differences. By applying the method to data usage detail records collected from the cellular networks in a city of China, we analyzed different collective mobility patterns between the Spring Festival vacation and workdays. The experimental results show that our method can solve these two problems of identifying community differences and discovering users with different mobility patterns simultaneously. Moreover, the CMDCD method is an integrated approach to discover groups whose mobility patterns have changed in different periods at the large spatial scale and the small spatial scale. The discovered collective mobility patterns can be used to guide urban planning, traffic forecasting, urban resource allocation, providing new insights into human mobility patterns and spatial interaction analyses.     

Residential mobility in the Seoul metropolitan region, Korea

The spatial pattern of residential mobility in Korea is found to be one of intraregional rather than interregional movement. Net inmigration has taken place only in the Seoul metropolitan region (SMR) since 1970. People from the Cholla region have formed the main stream of net inmigration into the SMR. The decentralization of population from Seoul to Kyonggi and Inchon has generated a transformation of the Seoul urban fringe since 1970. This metropolitanization process is accompanied by residential and employment suburbanization to 45kms from the center of Seoul. Residential mobility in the SMR is the result of metropolitan job opportunities, availability of housing, and the effects of the various regional policies. Availability of transportation between Seoul and its urban fringe encouraged the wide expansion of the urban areas and population redistribution within the SMR.     

Mobility of rare-earth elements and copper during shear-zone-related retrograde metamorphism

In Mid Proterozoic crystalline rocks of the Mount Isa Inlier, around Cloncurry, Australia, 2000 km² of alteration and brecciation are the product of high-temperature (> 450 °C) concentrated saline solution activity. During retrogression, this fluid was locally responsible for mobility of V, Y, Nb and light rare-earth elements (15 × enrichment). Copper and S were leached during alteration and this may have been a significant source of components in nearby Cu-Au deposits. Similar rare-earth-element behaviour has been observed in the hematite breccias which host Cu-sulfides at the giant Olympic Dam Cu-Au deposit.     

不同模式道路网交通便捷性比较

道路网在城市发展中起着关键作用。交通便捷的城市,往往与其他城市经济贸易等交流频繁,在区域中能够获得更好的发展机会,并能有效节约社会资源。城市道路网呈多种模式,不同模式道路网独有的几何和结构特征导致其交通便捷性差异明显,但对这种差异缺乏定量分析和比较。本文基于目视观察大量城市数字地图,认为真实道路网基本呈格网、环形放射、自由3种典型模式。针对以上典型模式,定义用于描述交叉口之间移动难易程度的无效移动系数和通达度指标,结合现有的连接度指标采用网络分析方法分别从几何和结构的角度比较不同模式道路网的交通便捷性差异。结果表明,格网和环形放射模式无效移动系数低,邻近交叉口之间距离多为有效移动,道路网连接度较高,交通便捷性良好。自由模式道路走向任意,难以有效连线构网,相邻交叉口之间无效移动系数较大,连接度相对低,便捷性相对较差。受规模因素的影响,格网模式交叉口之间平均最短路径较大,消除规模因素影响整体道路网具有良好的通达性。     

Precise and Accurate Doping of Nanoporous Silica Gel for the Synthesis of Trace Element Microanalytical Reference Materials

This study presents an experimental procedure to fabricate high‐purity silica glass containing a selected element at a specified mass fraction. The procedure was used to prepare glasses doped with trace‐level mass fractions of Ti with the goal of improving analytical confidence when measuring trace elements in quartz. Systematic tests were performed to determine the ideal conditions and procedures for doping nanoporous silica gel with the highest efficiency of dopant recovery. Silica gel was cleaned in concentrated HCl, immersed in a non‐polar doping medium at a controlled pH and doped with precise quantities of ICP‐MS standard solution. Using liquids composed of longer chain molecules as the doping medium diminishes recovery, suggesting that large molecules could obstruct nanopores to inhibit capillary uptake of the dopant. A control experiment using crystalline quartz reinforced the effectiveness of nanoporous silica gel for doping with trace‐level precision. Layered aggregates of silica gel doped with different Ti mass fractions were hot‐pressed to create multi‐layered reference materials that were analysed with multiple techniques at a variety of spatial scales. Analyses at the intra‐grain scale (cathodoluminescence scanning electron microscopy, electron probe microanalysis), at the single grain scale (SIMS), at the sample layer scale (EPMA, laser ablation‐ICP‐MS) and at the bulk scale (ICP‐OES) demonstrated acceptable homogeneity at sample volumes characteristic of most microanalysis techniques and show that nanoporous silica gel holds promise as a highly retentive doping substrate for preparing reference materials for laser‐, electron‐ and ion‐beam microanalysis.     

Understanding the bias of call detail records in human mobility research

ABSTRACT

In recent years, call detail records (CDRs) have been widely used in human mobility research. Although CDRs are originally collected for billing purposes, the vast amount of digital footprints generated by calling and texting activities provide useful insights into population movement. However, can we fully trust CDRs given the uneven distribution of people’s phone communication activities in space and time? In this article, we investigate this issue using a mobile phone location dataset collected from over one million subscribers in Shanghai, China. It includes CDRs (~27%) plus other cellphone-related logs (e.g., tower pings, cellular handovers) generated in a workday. We extract all CDRs into a separate dataset in order to compare human mobility patterns derived from CDRs vs. from the complete dataset. From an individual perspective, the effectiveness of CDRs in estimating three frequently used mobility indicators is evaluated. We find that CDRs tend to underestimate the total travel distance and the movement entropy, while they can provide a good estimate to the radius of gyration. In addition, we observe that the level of deviation is related to the ratio of CDRs in an individual’s trajectory. From a collective perspective, we compare the outcomes of these two datasets in terms of the distance decay effect and urban community detection. The major differences are closely related to the habit of mobile phone usage in space and time. We believe that the event-triggered nature of CDRs does introduce a certain degree of bias in human mobility research and we suggest that researchers use caution to interpret results derived from CDR data.