Characterizing spatial distribution and sources of heavy metals in the soils from mining-smelting activities in Shuikoushan, Hunan Province, China

The spatial variation of heavy metals in the soils in Shuikoushan mining-smelting area, Hunan Province, China, was investigated using multivariate and geo-statistic analysis. A total of 106 composite soil samples were collected in an area of about 100 km2. Concentrations of total As, Cd, Pb, Zn, Cu and Cr were measured using inductively coupled plasma mass spectrometry (ICP-MS). Arsenic and Pb were found to have a common source, indicating the same sources and spreading processes, such as aerosols and airborne particulates from smelting chimneys. Airborne sources from smelting chimneys contributed greatly to Cd in the area, which demonstrated the same dispersion pattern as As and Pb. However, two hot spots of Cd around smelters were possibly enlarged by wastewaters, demonstrating another important source of Cd in Shuikouhsan. Geo-statistic interpolated mapping demonstrated that hotspots of Zn were only found proximal to the large smelters, suggesting that Zn primarily came from the chimneys of larger smelters. The major Cu hot-spots appeared closely to the tailing dam, indicating that weathering and leaching of tailings were the major sources of Cu contamination in Shuikoushan. Our findings indicated that airborne volatile particles and aerosols contributed the most to As, Cd, Pb, Zn and Cu contamination, while Cd and Cu may also derive from the discharge of wastewater from smelters and the leaching of tailings, respectively.     

基于观测数据空间化的北京市PM_(2.5)时空分异

PM2.5在地球表面上的变化是连续的,但由于地面海拔起伏和站点分布的相对稀疏,直接内插法很难顾及这种情况。文章运用反距离权重(IDW)、Kriging、经验贝叶斯克里金法(EBK)、多元回归+残差内插的综合空间化手段,对北京市2015年1月的PM2.5数据进行分析。结果表明:利用多元回归+残差内插方法空间化更优,且PM2.5存在显著的正局部空间自相关,中度以上污染主要分布在北京市东南部和房山区。时间上,PM2.5质量浓度逐时均值呈"W"型。3 h尺度上,PM2.5质量浓度与相对湿度和露点温度正相关,与能见度、大气压和风速负相关,与温度不相关。     

绿色食品产地生态环境质量分析与评价--以庆安县国家级生态农业示范区为例

采用1993年、2000年和2003年庆安县生态环境质量监测数据,通过指数评价和加权综合评价法,分析评价庆安县绿色食品产地的生态环境质量,并利用GIS地理统计等功能,用变异估计法及克里格插值法,以可视化的方式展现绿色食品产地环境质量的空间分布.结果表明,庆安县中部和西南部的环境质量最好,最适宜发展AA级绿色食品基地; 西北部和东南部的绿色食品产地环境质量虽然是清洁、安全的,但有逐渐恶化趋势,需引起进一步关注.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

燃气爆炸作用下房屋裂缝开展的分形模拟

烯气爆炸灾害下房屋裂纹开展有的模式与受均布压力破坏时的相同,在参照实验所得混凝土裂缝的分形维数资源的基础上编制了相应的软件,利用分形插值的方法实现裂缝开展的模拟,模拟结果较好地反映了裂缝发展的真实情况,且较以往的模拟方法节约了大量存储空间。     

Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

Comparison of Point Estimation Techniques in the Spatial Analysis of Radium-226, Radium-228 and Potassium-40 in Soil

Many environmental surveys require the implementation of estimation techniques to determine the spatial distribution of the variable being investigated. Traditional methods of interpolation and estimation, for example, inverse distance squared and triangulation often ignore features of the data set such as anisotropy which may have a significant impact on the quality of the estimates produced. Geostatistical techniques may offer an improved method of estimation by modelling the spatial continuity of the variable using semi-variogram analysis. The theoretical model fitted to the semi-variogram is then used in the assignation of weighting factors to the samples surrounding the location to be estimated. This paper outlines the results of a comparison between three common estimation methods, polygonal, triangulation and inverse distance squared and a geostatistical method, in the estimation of soil radionuclide activities. The geostatistical estimation method known as kriging performed best over a range of parameters used to test the performance of the methods. Kriging exhibited the best correlation between actual and estimated values, the narrowest error distribution and the lowest overall estimation error. Polygonal estimation was best at reproducing the data set distribution. Conditional bias was evident in all the methods, low values being over-estimated and high values being under-estimated.     

基于GIS空间插值方法的长湖水质评价

通过对各插值方法选择后取反距离加权法与克立格法对长湖的污染现状进行分析,结果表明大部分水域水质处于Ⅴ类和劣Ⅴ类,只有主要出水口习家口和刘岺闸附近的部分水域的水质可以达到Ⅳ类水质标准.同时发现反距离加权法与克立格法均具有较高的精度,但克立格法优于反距离加权法,这两种方法评价湖泊水质都能取得比较好的效果.     

土壤连续属性空间插值方法及其精度的研究进展

作为土壤变化的时空定量监测方法,土壤属性空间插值方法及其精度是计量土壤学和"数字土壤"领域的重要研究内容。文章首先介绍了土壤属性空间插值的常用方法,包括克立格插值法(Kriging)、反距离权重法(IDW)、样条插值法(Spline)、贝叶斯最大熵(BME)、地理加权回归(GWR)以及高精度曲面建模方法(HASM);其次阐述了土壤属性空间插值精度验证的方法和指标;再次总结了能够提高土壤属性插值精度的6种途径,包括合理选择插值方法、准确设定插值方法参数、合理设计采样数目和密度、注意空间自相关程度和范围的影响、科学安排实验分析顺序以及结合辅助信息进行插值;最后从插值方法的选择、验证指标的选取以及辅助信息的结合三个方面指出了土壤属性空间插值方法及其精度的未来研究方向。     

城市表层土壤重金属污染分析研究

根据某城市土壤表层中的8种重金属Cu、Pb、Cd、Hg、As、Cr、Ni、Zn的浓度数据,利用地统计学原理方法,研究了不同功能区土壤重金属的污染特征。结果表明Cd、Cu、Hg、Pb和Zn在工业区和主干道路区浓度超标,并且这几种元素的富集系数偏高,说明污染来源主要是工业生产、汽车尾气排放及汽车轮胎磨损等。此研究对城市土壤重金属污染治理及修复、重金属污染重点行业污染控制等提供参考。