APPLICATION OF PATTERN RECOGNITION TO SPECIATION DATA OF HEAVY METALS IN SUSPENDED PARTICULATES OF URBAN AIR

In order to get a better knowledge of the air pollution levels of the urban air of Barcelona,twelvesamples from three stations of the air-monitoring control network were analysed.Each control station isrepresentative of a different environmental situation.Thus the station at Plaa Molina responds to asimple domestic and urban traffic situation;the station at Poble Nou to the influence of medium andsmall industries,mainly metallurgical;and the station at Montcada to a zone in which there existimportant industries,a cement factory,two highways and railroads.The total content of unsedimentable particles,three inorganic anions(chlorides,sulphates andnitrates)and six heavy metals(Fe,Pb,Cu,Mn,Cr and Cd)were determined on all the samples obtainedduring the same period of time.The use of an analytical scheme of sequential extraction has alsopermitted the subdivision of the total content of each metal into the following four fractions:(1)solubleor exchangeable;(2)associated with carbonates and/or with iron and manganese oxides;(3)bound toorganic matter;and(4)residual.The use of principal component analysis applied to the data as a whole showed the associations andcorrelations between the various parameters as well as between the different above mentioned fractions.The predominant presence of Cd in the‘soluble or exchangeable’fraction is confirmed,while the othermetals are mainly associated with the‘carbonates and/or Fe and Mn oxides’and‘bound to organicmatter’fractions.Hierarchical cluster analysis applied to the twelve samples showed clearly the presence of threedifferent classes closely related to the origin(station)of the samples.Thus it becomes feasible to proposefor each station a possible profile of the content in terms of the different parameters considered.     

THREE-WAY METHODS FOR THE CALIBRATION OF CHROMATOGRAPHIC SYSTEMS:COMPARING PARAFAC AND THREE-WAY PLS

For the calibration of chromatographic systems,different methods can be used.One class of methodsutilizes three-way approaches.The calibration problem is stated in such a way that the decompositionof a three-way array can serve for the prediction of retention on new stationary phases.Two three-way approaches are presented:the Unfold-PCA and PARAFAC models.The theory ofboth methods is presented and the differences are highlighted,the main difference being that PARAFACis a trilinear decomposition whereas Unfold-PCA is not.Both three-way methods are evaluated on asmall data set consisting of retention measurements of eight solutes at six mobile phase compositions onsix stationary phases.The differences in performance of the two models are minor,For calibration purposes,two variants of the methods are discussed:three-way PLS and an extensionof PARAFAC.Again the theory and differences between the two methods are explained.The predictiveperformance of the two methods is compared using the same data set as earlier.The differences inpredictive performance,however,are minor.Both methods are capable of predicting 98% of thevariation in the test sets.Yet,there are other considerations when comparing methods than predictiveperformance,e.g.the quality of the predictions.     

基于地物特征提取的车载激光点云数据分类方法

车载激光扫描测量方法较传统摄影测量方法具有更多优点,它能快速采集大面积、高精度的三维空间数据,具有广阔的应用前景。针对车载激光扫描数据的分类问题,提出了一种基于地物特征提取的点云数据分类方法,即采用主成分分析(PCA)方法,在提取多种街区地物点云数据几何特征和总结地物对象特征知识规则的基础上,根据选取的主特征设计一套阶层式的分类方法,并利用该方法对一套车载激光点云数据进行了分类试验。结果表明,该方法的分类效果良好,具有一定的实用性。     

ASTER数据在北方铝土矿预普查中的应用——以豫西渑池地区为例

ASTER数据的光谱和空间分辨率均具有一定优势,适合于中等比例尺的矿产预普查。为了探讨ASTER数据应用于铝土矿预普查的效果,通过对ASTER图像彩色合成、地质解译及异常信息提取,对豫西渑池地区的铝土矿进行了预普查试验。结果表明,在北方基岩裸露地区,应用ASTER数据圈定"赋矿影像单元"和提取铝土矿遥感找矿信息能获得较好的效果。     

耦合PCA-SVM算法的金矿矿床规模预测分析研究

判断矿床(点)的类型是矿床勘探中的重要内容,传统预测金矿成矿规模的方法不仅耗时耗力,而且所需的经济成本较大。为提高矿床规模的勘探效率和准确度,揭示元素与金矿成矿规模的潜在联系,文中提出了耦合主成分分析(principal component analysis,PCA)和支持向量机(support vector machine,SVM)算法的预测分析PCA-SVM(principal component analysis-support vector machine)方法。该方法先通过主成分分析提取数据中的主要特征,再将主要特征带入支持向量机算法,从而训练出最优分类器以预测金矿成矿规模。文中共使用了3 812个金矿样本数据用于学习训练和预测分析,训练准确率为92.3%,测试准确率为88.7%,分别比直接使用支持向量机算法高出14.3%和17.1%。基于PCA-SVM的预测模型,不仅消除了人为主观因素的影响,而且有效提高了勘探过程中矿床预测的准确率和矿床勘探的效率,为地质勘查工作提供依据。     

Identification of the anomaly component using BEMD combined with PCA from element concentrations in the Tengchong tin belt,SW China

Concentration of elements or element groups in a geological body is the result of multiple stages of rockforming and ore-forming geological processes.An ore-forming element group can be identified by PCA(principal component analysis)and be separated into two components using BEMD(bi-dimensional empirical mode decomposition):(1)a high background component which represents the ore-forming background developed in rocks through various geological processes favorable for mineralization(i.e.magmatism,sedimentation and/or metamorphism);(2)the anomaly component which reflects the oreforming anomaly that is overprinted on the high background component developed during mineralization.Anomaly components are used to identify ore-finding targets more effectively than ore-forming element groups.Three steps of data analytical procedures are described in this paper; firstly,the application of PCA to establish the ore-forming element group;secondly,using BEMD on the o re-forming element group to identify the anomaly components created by different types of mineralization processes; and finally,identifying ore-finding targets based on the anomaly components.This method is applied to the Tengchong tin-polymetallic belt to delineate ore-finding targets,where four targets for Sn(W)and three targets for Pb-Zn-Ag-Fe polymetallic mineralization are identified and defined as new areas for further prospecting.It is shown that BEMD combined with PCA can be applied not only in extracting the anomaly component for delineating the ore-finding target,but also in extracting the residual component for identifying its high background zone favorable for mineralization from its oreforming element group.     

苏州市大气PM_(2.5)中水溶性无机离子的源解析及其气象因子分析

为了探明PM_(2.5)中水溶性无机离子的来源和气象因子对其浓度变化的影响,利用2012年2、5、8和11月苏州市PM_(2.5)中水溶性无机离子浓度和本站气象观测数据,分析了苏州市水溶性无机离子的时间变化特征,解析了当地PM_(2.5)中水溶性无机离子的主要来源,探讨了气象因素对离子组分的影响。结果表明:(1)苏州市PM_(2.5)中水溶性无机离子年均浓度大小依次为:SO_4~(2-)NO_3~-NH_4~+Na~+Cl~-K~+Ca~(2+)Mg~(2+)F~-;SO_4~(2-)、NH_4~+和NO_3~-为PM_(2.5)中最重要的3种水溶性无机离子物种,其总和占PM_(2.5)总质量浓度的50.9%。各离子的季节浓度特征均为冬季最高、夏季最低。(2)通过运用主成分分析法对苏州市PM_(2.5)中水溶性无机离子进行来源分类解析,发现第一类为二次污染源和生物质燃烧,其贡献率为32.84;第二类为道路扬尘及工业排放,其贡献率为19.99%;第三类为海盐污染,其贡献率为18.43%。(3)通过水溶性无机离子与气象条件的相关性分析发现,风向、风速和温度与水溶性无机离子浓度的相关性较显著,这三者是颗粒物浓度变化的主要影响因子。(4)利用HYSPLIT后向轨迹模式对外来污染物进入苏州市的轨迹进行聚类分析后发现:因受季风气候影响,苏州市外来污染物的输入路径存在明显的季节性变化特征,其中夏半年输送主径源自海上,冬半年主径源自内陆。     

基于PCA算法的星载GNSS-R海面目标反演

提出使用主成分分析(principal components analysis,PCA)抑制时延多普勒图(delay Doppler map, DDM)中的海杂波,提高海面目标反演精度。以挪威Snøhvit采气平台作为海面目标,采用2016-11-13的DDM数据进行目标反演。结果显示,未使用PCA抑制海杂波前,反演位置平均误差为17.65 km;抑制海杂波后,反演位置平均误差为11.42 km,位置精度提升35.30%。     

ETM+(TM)蚀变遥感异常提取方法研究与应用——方法选择和技术流程

从原理、模型试验及实际数据处理等方面分析对比了比值法、光谱角法及主分量分析法的优劣;选择了以主分量分析为主、光谱角法为辅进行蚀变遥感异常的提取;引用了误差理论某些基本概念,以标准离差σ作为遥感异常切割的尺度;建立了"去干扰异常主分量门限化技术流程"。以西藏驱龙—甲马蚀变遥感异常群为例,展示了此技术的效果,并与高光谱研究结果进行了比较。     

Effect of seasonal flushing on nutrient export characteristics of an urbanizing,remote, ungauged coastal catchment

Urbanization is a primary driver of nutrient export in coastal catchments; however, estimating the rate of export from urbanizing, remote and ungauged communities with episodic rainfall characteristics has rarely been reported in tropical and subtropical areas. In this study, the coastal catchment of Roebuck Bay near Broome, northwestern Australia, was instrumented to elucidate the effect of seasonal flushing on nutrient export. A cost-effective framework involving temporary gauging and community participation led to a quantitative estimate of surface hydrology and nutrient dynamics from this urbanizing, remote and ungauged catchment. The contribution of nutrient export was larger from the older Broome town site sub-catchments compared to sub-catchments that have been progressively urbanized since 2000. A distinctive seasonal first flush phenomenon, with an initial 30% of runoff volume containing 40–70% of the nutrient load was a key feature. This indicates there are opportunities for storm-water management to minimize impacts through adopting water-sensitive urban design principles.