Comparison of mineralization pattern of geochemical data in spatial and position-scale domain using new DWT- PCA approach

In the current research to determine the mineralization pattern and discuss the mineralization components, the information of position - scale domain of geochemical data has been analyzed. A new method is proposed based on coupling discrete wavelet transforms (DWT) and principal component analysis (PCA) for mineralization elements forecasting applications. The results of this study indicate the potential of DWT–PCA method for geochemical data processing. Wavelet transform (WT), as a multi-spectral analysis method, can decompose the spatial and temporal signals into different frequencies. The features of mineralization can be identified using the position - scale domain of geochemical data that may not be achievable in spatial domain. The geochemical data from the Dalli region have been processed in the spatial domain using PCA. The surface geochemical data of 30 elements have been transformed to position–scale domain using two-dimensional discrete wavelet transform (2DDWT). Wavelet functions (WFs) of Haar, Coiflet2, Biorthogonal3.3 and Symlet7 have been applied separately to decompose the geochemical data to high and low frequencies in one level. To obtain more accurate and complete information of mineralization, a new index has been presented based on wavelet coefficients. Based on this new index, significant results have been obtained by using PCA of the index. The coefficients distribution map (CDM) as a new exploratory criterion has been generated based on 2DDWT to show the geochemical distribution map (GDM). Finally, the results of WT have been compared with the results of spatial domain and the best method of wavelet for interpretation of geochemical data has been introduced. The results of geochemical data analysis by DWT–PCA approach have been confirmed by the exploratory drillings in the study area.     

Sequential Factor Analysis as a new approach to multivariate analysis of heterogeneous geochemical datasets: An application to a bulk chemical characterization of fluvial deposits (Rhine–Meuse delta, The Netherlands)

Sequential Factor Analysis (seqFA) is presented here as an enhanced alternative to multivariate factorial techniques including robust and classical Factor Analysis (FA) or Principal Component Analysis (PCA). A geochemical data set of 145 sediment samples from very heterogeneous, mainly riverine, deposits of the Rhine-Meuse delta (The Netherlands) analyzed for 27 bulk parameters was used as a test case. The innovative approach explicitly addresses the priority issues when performing PCA or FA: heterogeneity and overall integrity of the data, the number of factors to be extracted, and which optimum minimal set of key variables to be included in the model. The stepwise decision process is based on quantitative and objectively derived statistical criteria, yet also permitting arguments based on geochemical expertize. The results show that seqFA, preferably in combination with robust methods, yields a highly consistent factor model, and is favorable over classical methods when dealing with heterogeneous data sets. It optimizes rotation of the factors, and allows the extraction of less distinct factors supported by only a few variables, thus uncovering additional geochemical processes and properties that would easily be missed with other approaches. The identification of key variables simplifies the geochemical interpretation of the factors, and greatly facilitates the construction of a geochemical conceptual model. For the case of the fluvial deposits, the conceptual model effectively describes their bulk chemical variation in terms of a limited number of governing processes.     

Cupriferous bogs of the Coed y Brenin area,north Wales and their significance in mineral exploration

A number of bog areas with richly cupriferous peats have been outlined during a geochemical soil survey investigating the distribution of Cu, Mo, Pb and Zn in the vicinity of the Coed y Brenin porphyry copper deposit. During the first half of the last century considerable amounts of peat were extracted from the bog known as “Turf Copper” and ash derived from burning this peat was smelted as a source of Cu. “Turf Copper” bog is situated immediately to the west of the main outcrop of porphyry-style mineralization in this area. In addition, three small Cu bogs were delineated in the area of Bryn Coch to the south of the main mineralized zone, where disseminated Cu mineralization outcrops.Waters draining into the bog areas are enriched in Cu up to 0.97 mg/l. Analysis of profile samples from the bogs has indicated extreme enrichment in Cu and variable enrichments in Mo, Pb, Zn, Mn, Co, Ag and Au. Mineralized intrusive rocks in this area are significantly enriched in Cu and Au. The enrichment of Cu, up to 5.72%, and Au, up to 0.13 ppm in ashed peat samples, reflects the mobilization of these elements from adjacent mineralization by ground and surface waters and their fixation by interaction with organic matter accumulated in the bogs.The recognition of cupriferous bogs and the sampling and analysis of peats, including analysis for Au, may provide useful indicators of Cu and Au mineralization, especially in glaciated areas where mineralization may be masked by transported overburden and geochemical anomalies displaced by hydromorphic agencies.     

岩石地球化学数据挖掘及弱异常识别--以新疆阿舍勒铜矿为例

勘查地球化学找矿工作的重点在于正确解译地球化学数据,以便从冗杂的地质信息中精准提取与成矿有关的异常信息,指导找矿研究。然而,地球化学数据属于成分数据,具有闭合效应,只有对数据进行正确的预处理才能应用多元统计分析方法,还原元素真实的空间分布。本文在阿舍勒铜锌矿区外围南侧区域共收集1009件地表原生晕样品,对样品中的13种微量元素进行测试,并对原始数据、对数及ilr变换后的数据进行EDA分析,对比数据空间分布及内部结构特征。运用(稳健)主成分分析,结合成分数据双标图及第一主成分点位图,解译三类数据指示的元素组合与成矿信息之间的关联。随后运用多重分形滤波技术,对以ilr变换为基础的稳健主成分得分数据分解元素组合异常和背景分布特征。结果表明:①经过对数及ilr变换后的数据相比原始数据空间尺度更均匀,数据近似正态分布;②三类数据双标图表明,仅ilr变换后的数据消除了“闭合效应”,且其第一主成分元素分组揭示了研究区铜矿化与铅锌多金属矿化组合;以对数变换与ilr变换为基础的第一主成分点位图表明,后者主成分得分异常能够较好指示研究区地质找矿信息;③结合研究区地质找矿信息、元素组合异常及背景空间分布特征,最终圈定3个有利找矿靶区。     

Application of classical statistics,logratio transformation and multifractal approaches to delineate geochemical anomalies in the Zarshuran gold district,NW Iran

The aim of this study is to discriminate the geochemical anomalies in the Zarshuran district, NW Iran, using different geochemical methods and present a more useful method where anomalous areas better coincide with the geological features. For this methods of delineation, geochemical anomalies were compared using geological features, occupied area of anomalies respect to the total study area, and field observations. Frequency based analysis such as mean + 2SDEV and median + 2MAD and concentration–area (C–A) multifractal methods were adopted for estimating thresholds and separating geochemical anomalies in uni-element data, as well as multi-element ones. Threshold values obtained from mean + 2SDEV and median + 2MAD, from original point geochemical data, are smaller than those of the pixel values; this may be due to the stronger variance of pixel values. In addition, the C–A multifractal method, as a useful tool to identify weak geochemical anomalies, was applied for defining the threshold values. Robust principal component analysis (RPCA) methods coupled with isometric log-ratio (ilr) transformations were utilized to open the geochemical data in order to reduce the effects of the data closure problem. The 20-quantile intervals decomposed anomaly maps from PC1 were obtained from the classical PCA, robust PCA showed that the upper quintile (>80 quintile) of classical PCA covers a larger area (32.54%) than the robust PCA (18.16%), and as a result, the robust PCA displayed smaller areas and has good spatial associations with outcrops of hydrothermal Au–As mineralization in this area; coincident with the known Zarshuran former mining area (ore field), Zarshuran unit, Ghaldagh silicified limestone occurrence and newly explored works confirmed by field observation. Although the C–A model shows a smaller area (8.06%), this anomaly location is limited to the Zarshuran old mining area with no new exploration targets. Comparison of the models indicates that the RPCA model is not only beneficial to further Au exploration in the study area, but also provides a meaningful geological study to the community of the compositional data analysis.     

Geochemical interaction between the freshwater and marine hydrospheres

The results of more than 40 years long authors’ investigations in the field of the freshwater (river input) and marine (ocean waters) hydrospheres are summarized. The latest estimations of the global average concentrations of many chemical elements in river water and suspended matter and in ocean water and suspended matter are presented. It is shown that particulate suspended forms of many elements are predominant in river waters (“rivers are the kingdom of suspended forms of elements”), while their dissolved forms prevail in ocean waters (“ocean is the kingdom of dissolved forms of elements”). Sedimentary and biogeochemical processes of the river material transformation in the river-sea mixing zone (the so-called “marginal filter of the ocean”) were studied thoroughly. It was shown that radical quantitative and qualitative changes of dissolved and particulate suspended substances take place in this zone, resulting in the governed transformation of dissolved forms into suspended particulate forms and their following deposition on the bottom. The first data on the losses of 35 chemical elements in the river-sea mixing zone are presented. These data prove that the concentrations of dissolved elements in river and ocean waters are in regular and close relationship with their losses in the river-sea mixing zone and with the types of element distribution in ocean water column (conservative, biogenic, and lithogenic). This indicates the existence of a geochemical system in the entire (freshwater and marine) hydrosphere, which calls for deep and detailed investigations.     

The use of principle component analyses in characterising trace and major elemental distribution in a 55 kyr peat deposit in tropical Australia: Implications to paleoclimate

The Lynch’s Crater peat deposit in NE-Australia is a sensitive environmental archive located in the tropical Southern Hemisphere. This unique deposit illustrates that local and regional changes had a profound effect on the local Australian ecosystem over the past 55 kyr. To obtain a proxy of past climate changes, trace and major element geochemistry analyses were applied to a 13 m peat core from the crater. Principle component analysis (PCA) was used to identify the main factors that control elemental distribution in the peat and to add interpretative strength to the geochemical behavior of selected major and trace elements. For example, Sc, Al, Cu, and Pb were found to be related to increased erosion of the basin soils, and from this, several periods of significant flux from atmospheric input and/or terrigenous run-off were identified. Geochemically mobile elements during rock weathering and pedogenesis, such as Mg, Ca, and Sr helped to identify the peat ombrotrophic-minerotrophic boundary at ∼1.5 m depth and offered important information about fluxes of these nutrients to the mire and their dynamics within the deposit. Arsenic and V comparisons between the peat record (high concentrations in some peat sections) and in local basin rocks (very low concentrations), suggested the presence of a long range, atmospheric dust source early in the formation of the mire. The Lynch’s Crater peat record presents a continuous record of environmental change in tropical Australia and contributes new understanding to geochemical processes in peatlands.     

Using robust staged R-mode factor analysis and logistic function to identify probable Cu-mineralization zones in Khusf 1:100,000 sheets,east of Iran

Factor analysis method is a multivariate analysis technique that is widely used for the interpretation of stream sediment geochemical data. The purpose of factor analysis is describing the changes in a set of multi-element geochemical data by reducing the dimension of the data and variables to a number of factors that can present the hidden association between elements. Differences in mobility, physical, and chemical properties of the elements and the nature of the factor analysis method in which the matrix of all data is used cause paragenes elements not to be found on the output of factor analysis. In this research, to improve the output of factor analysis for deriving the best reagent multi-element mineralization, robust staged factor analysis method was used according to the close nature of geochemical data in order to identify the Cu-mineralization potential in Khusf 1:100,000 sheets located at the east of Iran. The robust staged factor analysis enhances the recognition of anomalous geochemical signatures and increases geochemical anomaly intensity and the percentage of the total explained variability of data. As indicated by the results of the study, few anomalous zones have been found in the study area. The observation of chalcopyrite and malachite mineralization in andesite and dacite–andesite rocks in a region during the field study confirms the effectiveness of the robust SFA technique. Such studies can be used by mine engineers and geologists for designing an optimum grid exploration on the next exploration steps.     

中蒙跨境阿尔泰构造带稀有元素锂区域地球化学分布

锂被称为21世纪改变世界的“绿色能源金属”和“白色石油”,战略意义显著。阿尔泰构造带是重要的稀有金属成矿带,开展阿尔泰地区锂资源远景优选至关重要。在中蒙跨境阿尔泰地区,按相同的工作方法(采样方法、采样介质、实验室分析测试、数据统计、图件制作)开展了约300 000 km2的1∶100万国家尺度地球化学填图,分析了包括稀有元素锂在内的69种元素,填补了中蒙边界地区稀有、稀土元素地球化学分布的空白。研究结果表明：中国境内锂元素背景值(235×10-6)低于蒙古境内锂元素背景值(259×10-6);对于划分的构造单元而言,阿尔泰构造带、阿尔泰南缘弧盆系和准噶尔地块锂背景值和平均值均高于总体含量值,尤其是阿尔泰构造带锂含量背景值(316×10-6)和平均值(329×10-6)特征明显,说明该构造单元是锂元素的富集区;根据85%累积频率圈定出24个锂地球化学异常区并优选出3个锂地球化学省,结合地质条件讨论异常性质,为该区寻找稀有金属矿床提供了重要选区。     

Assessment of groundwater water quality in central and southern Gulf Coast aquifer,TX using principal component analysis

Principal component analysis has been applied for source identification and to assess factors affecting concentration variations. In particular, this study utilizes principal component analysis (PCA) to understand groundwater geochemical characteristics in the central and southern portions of the Gulf Coast aquifer in Texas. PCA, along with exploratory data analysis and correlation analysis is applied to a spatially extensive multivariate dataset in an exploratory mode to conceptualize the geochemical evolution of groundwater. A general trend was observed in all formations of the target aquifers with over 75 % of the observed variance explained by the first four factors identified by the PCA. The first factor consisted of older water subjected to weathering reactions and was named the ionic strength index. The second factor, named the alkalinity index explained greater variance in the younger formations rather than in the older formations. The third group represented younger waters entering the aquifers from the land surface and was labeled the recharge index. The fourth group which varied between aquifers was either the hardness index or the acidity index depending on whether it represented the influences of carbonate minerals or parameters affecting the dissolution of fluoride minerals, respectively. The PCA approach was also extended to the well scale to determine and identify the geographic influences on geochemical evolution. It was found that wells located in outcrop areas and near rivers and streams had a larger influence on the factors suggesting the importance of surface water–groundwater interactions.     

结构方程模型在地球化学数据分析中的应用

为了实现通过确定地球化学组合元素来反映成矿异常, 本文在主成分分析模型的基础上, 引入了新的结构方程模型(SEM).与主成分所不同的是, 结构模型综合了经典统计方法中的因子分析和路径分析方法, 以与研究对象具有较好的拟合度为标准来确定最优解, 并通过模型最优解来确定新的成分组合, 因此结构模型所确定的成分变量不一定是具有最大变化性, 而是与研究对象最接近的因子变量, 该因子能够更好地反映研究对象.介绍了结构方程模型方法的原理, 并利用加拿大Nova Scotia省西南部湖泊沉积物地球化学数据建立了与热液型金矿有关的地球化学元素结构方程模型, 研究了结构方程模型所给出的组合变量空间分布规律以及与金矿床的关系.与主成分分析方法所给出的计算结果进行对比发现, 结构模型所计算的与金矿相关的组合变量与矿床的空间相关性较高, 并且对金矿床(矿点)也具有较好的预测性.      

Geochemical anomalies in the mantle of the Pamirs and Tien Shan with applications to the deep-seated sources of ore material

The mantle metasomatites (fluidized magmatic rocks) of the Pamir-Tien Shan region show extremely high contents of lithophile and chalcophile trace elements, which often exceeds the regional average abundances of the Earth’s crust. Geochemical relations were established between mantle and crustal rocks, and it was shown that the compositions of magmatic rocks of different age and formation depth and polychronous mineralization are relatively stable. These data and some other facts indicate the possible influence of mantle fluids (melts) on the crustal rocks and processes. An alternative model implies the geochemical influence of crustal rocks on the geochemical characteristics of the regional mantle. The ore material of alkali basic rocks and some hydrothermal and rare metal deposits shows a geochemical affinity to the supposed mantle (mantle-crustal) sources. The ore-bearing fluids (melts) were presumably related to the evolution of ultradeep “hot” material of mantle plumes and “daughter” diapirs carrying alkaline, trace, and ore elements.     

Environmental Monitoring and Peat Assessment Using Multivariate Analysis of Regional-Scale Geochemical Data

A compositional multivariate approach was used to analyse regional-scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey of Northern Ireland. The multi-element total concentration data presented comprise X-ray fluorescence (XRF) analyses of 6862 rural soil samples collected at 20-cm depth on a non-aligned grid at one site per \(2\,\hbox {km}^{2}\). Censored data were imputed using published detection limits. Each soil sample site was assigned to the regional geology map, resulting in spatial data for one categorical variable and 35 continuous variables comprised of individual and amalgamated elements. This paper examines the extent to which soil geochemistry reflects the underlying geology or superficial deposits. Since the soil geochemistry is compositional, log-ratios were computed to adequately evaluate the data using multivariate statistical methods. Principal component analysis (PCA) and minimum/maximum autocorrelation factors (MAF) were used to carry out linear discriminant analysis (LDA) as a means to discover and validate processes related to the geologic assemblages coded as age bracket. Peat cover was introduced as an additional category to measure the ability to predict and monitor fragile ecosystems. Overall prediction accuracies for the age bracket categories were 68.4 % using PCA and 74.7 % using MAF. With inclusion of peat, the accuracy for LDA classification decreased to 65.0 and 69.9 %, respectively. The increase in misclassification due to the presence of peat may reflect degradation of peat-covered areas since the creation of superficial deposit classification.     

Introducing a new approach of geochemical anomaly intensity index (GAII) for increasing the probability of exploration of shear zone gold mineralization

Increasing the prediction rate in the identification of mineralization zones using the stream sediment geochemical data is an essential issue in the regional exploration stage. The various univariate (such as fractal and probability plot (PP) methods) and multivariate methods (such as principal component analysis (PCA)) have been performed for interpreting the geochemical data and detecting the mineralization areas. In this study, a new geochemical criterion named geochemical anomaly intensity index (GAII) was proposed for geochemical anomaly mapping. This approach was developed based on the PCA method and the catchment basin coefficient (CBC). The GAII as a weighted geochemical index is calculated using the mineralization principal component (MPC) scores and CBC. GAII can be mapped and utilized for geochemical anomaly mapping and detecting the mineralization areas. Besides, GAII can identify paragenesis elements better than the current methods. In this research, GAII was successfully used to generate geochemical anomaly maps on shear zone gold mineralization in the southwest of Saqqez, NW Iran. The geochemical data have been divided into three groups based on catchment basins and the host rock type. Then the MPCs and paragenesis elements of Au mineralization have been obtained individually using PCA. Three mineralization paragenesis groups consisting of (Au, Sn), (Au, W), and (Au, As, Sb and Ba) have been recognized for different catchment basins of the southwest of Saqqez district using PCA. GAII was calculated and mapped based on the CBC_{(Au, Sn)}, CBC_{(Au, W)}, CBC_{(Au, As, Sb, Ba)}, and their MPC scores. GAII accurately detected the Au mineralization zones and improved the geochemical anomaly map in this area compared to the PP method, concentration-area fractal model, and U-spatial statistics method. The results demonstrated that GAII was successfully used for (a) identifying the mineralization paragenesis elements, (b) intensifying the geochemical anomaly, and (c) increasing the prediction rate of mineralization zones. The shear zone gold mineralization areas in the southwest of Saqqez district were effectively detected using this new data analysis approach. GAII has provided better results than the current PP method, concentration-area fractal model, and U-spatial statistics method.     

Unmasking multivariate anomalous observations in exploration geochemical data from sheeted-vein tin mineralization near Emmaville, N.S.W., Australia

Previous interpretations of surface-rock geochemical data from the sheeted-vein tin mineralization in the Emmaville district have been carried out using classical statistics. These investigations revealed low-contrast geochemical patterns of 3 to 5 ppm Sn, supported by 80 to 160 ppm F, block-average contours defining four of the six known mineral occurrences. Principal component scores for the association dominated by F-Li-Rb have defined the same four mineral occurrences. For the prospecting of similar deposits it is highly desirable to improve the data processing techniques to achieve more acceptable geochemical contrasts between anomalous and background levels. Minimum volume ellipsoid (MVE) estimation, a high-breakdown method (capable of accommodating up to 50% outliers) recently developed in robust statistics is applied to a subset of the data from the northeastern part of the Emmaville district. The anomalies related to mineralization in this part of the district are not as well developed compared to those in the west. The data set used in this study consists of 133 observations with 6 elements, namely Cu, Li, Rb, F, As and Sn.The detection of multivariate outliers (anomalous observations) by Mahalanobis distance calculation was carried out on the surface rock geochemical data. The robust Mahalanobis distances computed from MVE estimates of location and scatter shows little variation over background areas but are sharply enhanced over mineralization. In contrast, the usual Mahalanobis distances either fail to indicate the presence of mineralization altogether, or, at best, respond with feebly enhanced values that do not satisfactorily indicate the presence of mineralization.Graphical display of results from classical RQ-PCA performs poorly, revealing only 6 weakly anomalous observations related to mineral occurrences. Several additional observations from these occurrences have also gone undetected. On the other hand, results from MVE-robust RQ-mode principal component analysis show that the background observations cluster tightly within the 95% tolerance ellipse while the anomalous observations (related to mineral occurrences) are greatly enhanced and the variables that characterize them are clearly indicated. Results are consistent with those of robust Mahalanobis distance procedure; both techniques indicate essentially the same observations as being anomalous.     

Stream sediment geochemical exploration for gold in Central Eastern Desert,Egypt: Application of the concentration-number fractal model,factor analysis,and geochemical mineralization probability index

Geochemical exploration by stream sediment sampling using bulk leach extractable gold (BLEG) technique and applying concentration-number (C-N) fractal model, factor analysis (FA), and geochemical mineralization probability index (GMPI) resulted in the recognition of new Au occurrences around the Sukari gold mine in the central Eastern Desert of Egypt. The geochemical data of 128 stream sediment samples collected from the study area was used for delineating the geochemical anomalies and characterizing the dispersion trains of ore and associated elements (Au, Ag, As, Sb, Cu, Pb, Zn, Mo). Statistical analysis of the geochemical data applying the C-N fractal modeling enabled us to identify significant anomaly and background populations of the investigated elements and to construct reliable geochemical anomaly maps. Factor analysis using centered log-ratios (CLR), to address the problem of closed compositional data, revealed significant element associations for mineralization (Au, As, Mo, Zn, Ba), country rock compositions (Rb, Li, Be, Sn, Bi for granite, and Co, Cr, Ni for mafic rocks), and element mobility (e.g. Sb, Zr, and Ag). Weak and moderate Au anomalies that cannot be detected by factor score maps can be delineated clearly by using the C-N fractal method and GMPI distribution map. Our study revealed that Ag, As, and Sb are the main pathfinder elements for gold mineralization in arid to semiarid regions exemplified by the Sukari gold district. Silver can be used as a “direct” pathfinder, whereas As and Sb are “indirect” pathfinders for Au in such regions. The spatial distribution of Au and Ag anomalies indicate that gold mineralization in the Sukari district is structurally controlled. However, the spatial distribution of Cu, Pb, Zn, and Mo is controlled by mineralogical and lithological factors and is not related to any significant base metal deposits.     

Soil-5, A New IAEA CErtifiEd Reference Material for Trace Element Determinations*

60 geochemical laboratories from the world over, contributing in all 3687 bits of chemical data on 60 elements, haue willingly participated in the study of SOIL-5 as a reference material. The preparation of SOIL-5 in 45 kg and homogeneity teats are described; in addition, all the data compiled are presented. In evaluating the compiled data, the use of four concurrent tests for outlier-rejection at the same level of significance, has been applied. After proper statistical treatment, “recommended values” could be established for 31 elements, most of them trace elements and “information values” for 29 elements. 23 of the recommended values could be given with a “relatively high” degree confidence whereas the other 18 recommended Values with a “reasonable” degree of confidence. An attempt is made to compare the analytical methods employed; the existence of possible sy3tematic differences is pointed ont.     

Some scientific and applied problems of supergene geochemistry in the U.S.S.R.

Demands of modern human society require a wide application of the principles of hypergene geochemistry in order to explore for deeply buried minerals, protect the environment, assist in some medical and biological problems, etc.; such is impossible without a sound theoretical basis for this science. It is necessary that the processes associated with deep weathering be investigated, as well as the mechanisms of element transport (electrochemical transfer, vapor transport, migration of elements in pore water, etc.) and the formation of geochemical halos in various secondary environments. More effective techniques (based on chemical extractions, artificial sorbents, biological methods, etc.) must be developed in order to make further advances in all aspects of applied supergene geochemistry. Toward this end, the successful application of artificial sorbents to exploration and environmental problems is illustrated, and “geochemistry of technogenesis”, one of the main branches of hypergenesis, is discussed and shown to be presently at the stage of “geochemical inventory”. Technogenic geochemistry consists of detailed data collection for all elements and, primarily, geochemical mapping of affected environments. One of the objectives of technogenic geochemistry is the development of the theory and implementation of practical measures necessary to utilize the most efficient geochemical systems in the various natural situations affected by man. Lack, or excess, of certain chemical elements in the environment are important geochemical factors to be considered in the study of endemic disease (i.e. “medical geochemistry”). Studies are illustrated which show a general tendency for areas with higher percentages of cancer to have higher average contents of Mn, Pb and Co, but lower amounts of Cu, compared with regions with moderate oncological disease rates. The importance of studying the modes of occurrence of chemical elements in the secondary environments is stressed. By the end of this century the role of environmental geochemistry is expected to be substantially more important and will require scientists specifically trained in this subject.     

Changes in vegetation condition in areas with different gradients (1980–2010) on the Loess Plateau, China

This study characterized and compared changes in vegetation condition in areas with different gradients during the past three decades across the entire Loess Plateau. For this purpose, changes in vegetation type and vegetation coverage at sites with 0 – 15° and >15° slope gradients were determined by analyzing land use data and Normalized Difference Vegetation Index (NDVI) data, respectively. The software Arc/Info 9.3, land use transformation matrix, linear regression analysis, and Mann–Kendall test were used for the data processing and analysis. Policy influences, human impacts, and climate variability were also taken into account to find the reasons for vegetation condition change. The results indicated that the “Grain-For-Green” project achieved initial success. Areas of farmland and grassland changed most extensively, and far greater areas of farmland were transformed into forest and grassland than vice versa. Moreover, the conversion of farmland to forest and grassland mainly occurred in areas where slopes exceeded 15°, while grassland was mainly changed to farmland in areas with gentle slopes. Vegetation coverage on the Loess Plateau exhibited overall increases after the implementation of “Grain-For-Green” project. Regions with sparse vegetation have declined sharply, mostly in steeply sloped areas. Vegetation coverage has increased significantly in most regions, particularly in the parts traversed by the principal sediment source of the Yellow River, which could help to control the severe soil and water losses. However, regions with sparse vegetation on the Loess Plateau still covered 71.1 % of the total area in 2010. Therefore, it is important to further increase vegetation coverage in the future.