非传统化探方法研究的新进展

在20世纪的找矿实践中,水系沉积物、土壤和岩石地球化学测量等传统化探方法发挥了令矿产资源勘查界瞩目的重要作用。随着深部找矿,特别是覆盖区找矿工作的日益增多,传统化探方法已不完全适应这种找矿条件,急需有新的方法技术予以补充。20世纪诞生的一套非传统化探方法,如选择性提取法、生物地球化学测量、地下水地球化学测量、地下气体测量等,重又受到青睐。在现代化学分析技术的支撑下,选择性提取技术成为当前化探界研究的热点,试点性研究显示了其找寻隐伏矿的有效性;生物地球化学找矿方法在植物积累元素的控制条件、分析测试方面均取得了较大进展,已经从幼年期进入成熟的早期阶段;地下水地球化学测量方法在地下水中矿物饱和度与物质计算、高质量的物理化学数据的获取和不同矿床类型的元素化合物指示标志的研究与评价方面做了大量的工作。同时,数据处理技术、重矿物地球化学找矿标志和同位素地球化学示踪技术的研究近年来也受到了极大关注。实验性研究表明,尽管这些非传统技术在找寻隐伏矿方面显示了良好的应用前景,但仍有许多问题需要深入研究。     

Mass fluxes of xenobiotics below cities: challenges in urban hydrogeology

Urban areas are the focus of major ecological, social and economical activity. They are thus also prime locations of increasing conflict with regard to water use and water protection. As a direct and/or indirect consequence of urban land use and human activity, urban water systems are frequently polluted with organic contaminants including waste water-born xenobiotics such as pharmaceuticals, personal care products (collectively known as PPCPs) and endocrine-active substances. This study reviews new integrated methodologies including flux calculations as well as chemical investigations for determining the impact of human activities on urban water systems and on processes within the urban watershed. The use of indicator substances, representing different contaminant sources and pathways, integral pumping tests and mass balance approaches are suitable alternatives within these environments. The issues are explored using contaminant mass balance examples from Halle/Saale and Leipzig, Germany.     

Capability of vis-NIR spectroscopy and Landsat 8 spectral data to predict soil heavy metals in polluted agricultural land (Iran)

Heavy metals are toxic elements that have hazardous effect on the environment. They cause soil pollution as a result of their toxicity, potential reactivity, and mobility in soils. There are so many methods for the measurement of heavy metal concentrations in soils and aquatic systems. The traditional methods used for detecting heavy metal distribution in soil involve laboratory analysis and raster sampling. Both of them are expensive and time-consuming for large areas. Remote sensing techniques are used for obtaining the earth’s surface information, and these techniques have been used in the investigations of heavy metal distributions in preliminary analysis of soils as a rapid method. Today, near-infrared reflectance spectroscopy (NIRS) of soil characteristics has been of interest as a significant object. The present investigation is focused on the detection of heavy metals in contaminated soils by the application of reflectance spectroscopy in the spectral range of 350 to 2500 nm. This study also discusses the circumstances of the applied current methods for the detection and estimation of arsenic (As), cadmium (Cd), nickel (Ni), and lead (Pb) in contaminated agricultural soils. In the first part of laboratory spectroscopy, estimations were done using heavy metal reflectance spectroscopy and partial least square regression (PLSR) approaches, while in the second part, the heavy metal estimations were done using soil organic carbon reflectance spectroscopy through the PLSR approaches. Similar to the tasks above, estimations of As, Cd, Ni, and Pb by using Landsat 8 images were done in the forms of direct and indirect methods and the distribution of heavy metals in the study area was determined. Finally, the results obtained using direct and indirect methods were compared with the wet chemical measurements of heavy metals and organic carbon. It was found that although the direct detection of heavy metals using the images of Landsat 8 produced more accurate results than the indirect detections, the results obtained from laboratory spectroscopy corresponded more with the results from atomic adsorption spectroscopy. On the other hand, based on the fact that the soil has a complex content, the use of nonlinear methods, such as artificial neural networks in predicting soil heavy metal contents, could be regarded as a trusted method.     

An application of Bayesian spatial statistical methods to the study of racial and poverty segregation and infant mortality rates in the US

The infant mortality rate is a fundamental measure of population health used internationally. In the United States, the infant mortality rate is higher than what would be expected for a country of its affluence. We present an analysis of US county infant mortality rates using modern Bayesian spatial statistical methodologies. Our key predictors in our statistical analysis are residential racial and poverty segregation, measured by the dissimilarity, interaction and spatial proximity indexes. We use both Exploratory Spatial Data Analysis methods and Hierarchical Bayesian spatial regression models to examine the influences of these segregation measures on the infant mortality rate for each county, net of income inequality, degree of rurality and relative socioeconomic deprivation. The spatial measures of racial segregation suggest that when blacks live in close proximity to each other, this tends to increase the infant mortality rate. The results for poverty segregation suggest the same pattern, when poor populations live in close proximity to one another this is generally detrimental to the county infant mortality rate. However, interaction between blacks and whites and poor and non-poor residents of an area is protective for infant mortality.     

Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.     

二维圆弧型井眼轨道设计问题的通解

二维圆弧型井眼轨道是常规定向井、水平井轨道设计优先考虑的剖面类型,应用比较广泛。但是由于井段组合形式很多,并且对于同一种井段组合还有很多种未知数求解组合,推导每种井段组合和求解组合情况下的解的计算公式的工作非常繁重和复杂。研究了任意井段组合和任意求解组合的通解问题,发现井眼轨道设计问题的约束方程组可以化归成线性代数方程组或者4种典型方程组之一;得到了4种典型方程组的实数解的计算公式,并给出了有实数解的判别条件。对于二维圆弧型井眼轨道设计问题的基础理论研究和计算机软件开发都有重要的意义。     

液压式解卡工艺管柱的研究及应用

近年来，葡萄花油田平均每年拔不动待大修的油水井约有40口，采取常规地面解卡机或者应用大修架子处理解卡存在安仝隐患和作业费用高的实际问题，为此开展了液压井卜解卡技术研究，该技术主要由泄油器、液压式井下解卡器、安全接头和打捞工具等组成，通过地面泵车打压来控制井下液压解卡器实施解卡，既可消除安全隐患，又可节约作业成本，在油田开发的中后期具有广阔的应用前景。     

水稻、小麦与土壤中重金属Cd含量的关系模拟研究

土壤污染防治工作已成为提升耕地质量、保护国土生态安全的重要任务之一.为了科学预测我国大宗农作物(如水稻、小麦)与土壤重金属含量的关系,减少安全利用类农用地的大量农产品与土壤的协同监测,实现重金属污染农用地的安全利用,本研究以重金属Cd为例,选取对水稻、小麦Cd含量影响较大的土壤Cd含量、土壤pH值、土壤阳离子交换量(C...     

System boundary setting in life cycle assessment of biorefineries: a review

A growing interest for biorefineries has resulted in a subsequent increase in publication of lifecycle assessments (LCA) of such systems in later years. This study explores choices made in system boundary setting in LCAs of biorefinery systems. Based on a review of 38 case studies published in the scientific literature, the study aims to identify and discuss methodological differences and effects of these on overall results. The review shows that the definition of feedstock is of key importance for chosen system boundary settings. Direct inputs and agriculture activities are included in 80 % of the systems where feedstock is regarded as dedicated biomass, while omitted when defined as residue. Land conversion for provision of dedicated biomass, as well as use of agriculture/forest residues, results in impacts with direct connection to the investigated biorefinery system, motivating inclusion of these processes in the assessment. However, these aspects are considered in less than 40 and 30 % of systems using dedicated biomass and residues as feedstock, respectively. Indirect land use changes and ‘lost opportunities’ can be relevant to assess—independent of the type of feedstock used, particularly when using consequential modeling. Such indirect aspects are, however, not always addressed in a coherent manner. Finally, it is observed that the end-of-life stage of bio-materials/chemicals commonly is not captured within set system boundaries, generating comparative disadvantage for bio-based systems, when compared to fossil reference systems. In summary, it can be concluded that omitting key issues from the investigated system can reduce the relevance of gained results, as well as the possibilities for cross-study comparisons. This calls for further development and use of already existing guidelines in this field.     

浙江中部典型黑色岩系分布区土壤-作物富硒特征与重金属风险评价

富硒土地是生产富硒农产品的宝贵资源,黑色岩系形成的土壤通常富含硒和重金属元素。为了指导这类富硒土地资源的安全开发利用,选择浙江中部典型黑色岩系分布区,通过调查土壤-作物中硒和重金属的浓度及生物有效性,评价农产品富硒率,识别作物重金属超标风险。结果显示:研究区富硒土壤占38%,足硒土壤占62%,水稻和莲子富硒率分别为85.71%和100%;受黑色岩系风化成土影响,研究区土壤镉含量介于污染筛选值和风险管控值之间的样品比例为26%,且Cd活动态和潜在活动态所占比例分别为57%和40%,水稻籽实中Cd超标率为31%,莲子Cd含量均不超标。基于土壤重金属总量和形态的风险评价表明,富硒土壤开发利用的风险区主要位于西皮山岗和腰塘边一带,建议禁止种植农产品,其他黑色岩系发育的富硒丘陵地区,虽然土壤镉含量较高,但因土壤Cd的生物有效性和水稻中Cd的超标率较低,应加以保护和合理开发利用。     

Application of heavy stable isotopes in forensic isotope geochemistry: A review

Light stable isotopes have been used for many years to characterize the source and transport of materials. More recently heavy isotope systems such as Sr, Nd and Pb have been added to this list in order to aid source identification. With the advent of multiple collector ICP-MS, the range of isotopic tools now available has increased considerably, however, until the isotope systematics of these new non-traditional isotope systems have become better understood, they will not be as useful in characterizing material source and transportation. Applications using heavy metal stable isotopes (mostly traditional heavy isotopes) have reached most avenues in science, including earth sciences, archaeology, anthropology, animal physiology, ecology and toxicology. This field will continue to grow as new applications are developed and techniques become simpler and quicker. This paper provides a review of how this field has grown and presents two new applications using Pb and Sr isotopes in glazes to determine the source of ore used in glazes, and using Sr isotopes to determine the origin of undocumented deceased Mexican border crossers.     

Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.     

Experiences and perspective in compiling long-term remote sensing data sets on landscapes and biospheric processes

Remote sensing has been employed to study the Earth's landscapes for more than a century. Over the last thirty years major changes in all aspects of the technology, as well as scientific understanding of the measurements, have revolutionized use of these data for terrestrial research. The emergence of biophysical interpretations of land remotely sensed data has created great interest in the potential of these data to study the dynamics of landscapes and biospheric processes as contributors to global change. However, the evolutionary history of land remote sensing, particularly in the Landsat era, has in many ways worked against this use of the data. Until recently, there was little appreciation of the need to compile long-term historical records of these observations. There are currently no formal scientific institutional systems dedicated to preserving and distributing the long-term record of Earth observations acquired by Landsat, AVHRR or other land observing systems. As the International Geosphere-Biosphere Program begins, this issue should be one of the first priorities of the participants.     

Multi-model ensemble schemes for predicting northeast monsoon rainfall over peninsular India

The northeast (NE) monsoon season (October, November and December) is the major period of rainfall activity over south peninsular India. This study is mainly focused on the prediction of northeast monsoon rainfall using lead-1 products (forecasts for the season issued in beginning of September) of seven general circulation models (GCMs). An examination of the performances of these GCMs during hindcast runs (1982–2008) indicates that these models are not able to simulate the observed interannual variability of rainfall. Inaccurate response of the models to sea surface temperatures may be one of the probable reasons for the poor performance of these models to predict seasonal mean rainfall anomalies over the study domain. An attempt has been made to improve the accuracy of predicted rainfall using three different multi-model ensemble (MME) schemes, viz., simple arithmetic mean of models (EM), principal component regression (PCR) and singular value decomposition based multiple linear regressions (SVD). It is found out that among these three schemes, SVD based MME has more skill than other MME schemes as well as member models.     

The impact of the parking situation in shopping centres on store choice behaviour

The article discusses the effects of changing the parking situation in the surrounding of shopping centres on consumers store choice behaviour. To get insight into these effects a hierarchical logit model of parking lot and store choice behaviour is estimated and validated. The research is based on before-and-after data of supermarket visitors collected in a major regional shopping centre in a suburban area in The Netherlands. The model is estimated using the before data. At the level of the supermarkets the estimated hierarchical logit model performs very well. The model is less accurate at the level of parking lots but still performs satisfactory. Significant attributes are a constant representing the characteristics of the supermarket, the distance between supermarket and parking lot, the number of parking spaces per parking lot, the location of the parking lot vis-à-vis the origin of the consumer, and the availability of supermarket trolley facilities at the parking lot. Validating the model by reproducing the after data yields less satisfactory results. Especially the model does not perform very well on predicting parking lot choice. This revised version was published online in July 2006 with corrections to the Cover Date.     

Heavy metal distribution and assessment in stream sediments of River Orle,Southwestern Nigeria

Ten heavy metals, namely, Ag, As, Cd, Co, Cr, Cu, Hg, Ni, Pb and Zn were partially extracted using aqua regia digestion method and analysed by ICP-AES from 56 stream sediment samples collected from River Orle, Igarra area, southwestern Nigeria. The analytical results were used to produce geochemical distribution maps for the elements and were subjected to univariate statistical analysis in order to evaluate the distribution and abundance of the heavy metals in the study area. The degree of pollution of these stream sediments by these heavy metals was evaluated by calculating such parameters as enrichment factors (EF), as well as pollution load and geo-accumulation indices (PLI and Igeo). Co, Cr, Cu, Ni, Pb and Zn are widely distributed in the drainage system while the distribution of Ag, Cd, As and Hg is restricted to only parts of the drainage system with Ag and Cd being localized to one sample site each near Epkeshi in the southern part of the study area. Cr and Pb display anomalously high concentrations, each from a site, also in the same locality where Ag and Cd were detected, indicating the likelihood that the four elements, Cr, Pb, Ag and Cd, are genetically related. Calculation of the enrichment factor (EF), pollution load index (PLI) and geo-accumulation index (Igeo) yielded results that indicate that all the 56 stream sediment sites, except one located about 4 km southeast of Epkeshi in the southern part of the Orle drainage system, are practically unpolluted by heavy metals. The relatively high metal concentration of this anomalous site having Pb EF of 62.5, PLI of 1.14 and Pb Igeo of 2.44 signifies Pb pollution. Both natural and anthropogenic sources of the Pb contamination around Epkeshi locality are possible. In conclusion, the levels of concentrations of heavy metals in the study area, in general, do not constitute any serious environmental risk except for Pb which needs to be monitored at only one site in the study area. Therefore the concentration ranges for the different heavy metals in the study area can serve as baseline environmental data against which the degree of pollution of these heavy metals can be evaluated in future.     

A New Differentiable Parameterization Based on Principal Component Analysis for the Low-Dimensional Representation of Complex Geological Models

A new approach based on principal component analysis (PCA) for the representation of complex geological models in terms of a small number of parameters is presented. The basis matrix required by the method is constructed from a set of prior geological realizations generated using a geostatistical algorithm. Unlike standard PCA-based methods, in which the high-dimensional model is constructed from a (small) set of parameters by simply performing a multiplication using the basis matrix, in this method the mapping is formulated as an optimization problem. This enables the inclusion of bound constraints and regularization, which are shown to be useful for capturing highly connected geological features and binary/bimodal (rather than Gaussian) property distributions. The approach, referred to as optimization-based PCA (O-PCA), is applied here mainly for binary-facies systems, in which case the requisite optimization problem is separable and convex. The analytical solution of the optimization problem, as well as the derivative of the model with respect to the parameters, is obtained analytically. It is shown that the O-PCA mapping can also be viewed as a post-processing of the standard PCA model. The O-PCA procedure is applied both to generate new (random) realizations and for gradient-based history matching. For the latter, two- and three-dimensional systems, involving channelized and deltaic-fan geological models, are considered. The O-PCA method is shown to perform very well for these history matching problems, and to provide models that capture the key sand–sand and sand–shale connectivities evident in the true model. Finally, the approach is extended to generate bimodal systems in which the properties of both facies are characterized by Gaussian distributions. MATLAB code with the O-PCA implementation, and examples demonstrating its use are provided online as Supplementary Materials.     

Pre-Set Delay Electronic Detonators: Merits Opposite Programmable Systems

The South African mining industry first experienced en-masse use of electronic detonators in the Narrow Reef environment using AEL's Electrodet™ pre-set delay system. In recent years, programmable systems such as AEL's Smartdet™ have also established their position, and within both AEL and the mines there has been important learning around the strengths and weaknesses of these systems. In general, the fixed delay systems tend to be more easily appreciated by less-skilled work teams, and are very well suited to simple layouts, especially long, narrow blasts. However, development of programmable row controllers and series delay inserts has greatly expanded the field of usefulness of these systems while retaining most of the simplicity of use. The programmable systems are immensely flexible and therefore able to function under any condition, but require a higher level of discipline and knowledge. Much has been done to address this issue and make the systems user friendly, so the systems have converged to some extent. These systems are both valuable tools for achieving control over blasting in underground and surface applications. The choice of system is very dependent on the prevailing conditions. Accurate timing with electronic enhancements continues to show an increasing range of benefits to mining operations. There is a strong parallel with non-electronic initiation systems which helps to understand the appropriate use of the systems.