基于监测及Kriging方法的京津冀地区大气污染物暴露分布研究

为了实现充分利用已有环境监测站点数据进行人群精细化暴露评估的目的,同时解决某些待测人群社区周边无监测站点时数据的选择问题,以保定市作为大气高污染研究城市,基于现场监测和Kriging（克里金插值）空间分析方法,明确了在研究大气污染物人群暴露时,某一个固定监测站污染物数据的代表性问题.研究表明:对于大气中φ（SO₂）、φ（NO₂）、颗粒物及其组分,空气质量监测点位的代表性一般为5~6 km;对于φ（CO）、φ（O₃）和φ（VOCs）,它们在城市不同地区的空间分布更为均匀,空气质量监测点位的代表性范围更大.通过使用Radial Basis Functions（径向基函数,RBF）、Local Polynomial Interpolation（局部多项式插值,LPI）、Inverse Distance Weighting（反距离权重插值,IDW）、Kriging、Kernel Smoothing（内核平滑插值,KS）和Diffusion Kernel（内核扩散插值,DK）等6种空间分析方法对大气污染物浓度进行预测发现,Kriging方法对大气污染物浓度预测时可使预测值和实测值间的偏差小于10%,准确度最高.因此,在进行某城市某点位的污染物人群暴露浓度预测时,若该点位周边5 km以内有空气质量监测点位,则可用该点位的监测值代替;若5 km以内没有空气质量监测点位,则可基于最近监测点位的污染物浓度进行Kriging空间插值,从而获得该点位的污染物暴露水平.      

基于重要抽样法的耐压球壳可靠性计算方法研究

目的 解决耐压球壳极小失效概率的可靠性计算问题。方法 在自适应Kriging的基础上,结合重要抽样法提出耐压球壳可靠性计算方法。该方法在较大失效概率下构建的Kriging模型基础上获得重要方向,在重要方向上计算得到较低失效概率下的设计点,以设计点为中心,构建小失效概率的Kriging模型,并通过此模型采用重要抽样法开展可靠性计算。结果 分别使用提出的重要抽样法和蒙特卡洛法计算了2个算例的失效概率,计算结果表明,该方法具有较高的精度和效率。使用该方法对某耐压球壳工作载荷下的失效概率进行了计算,计算得到该球壳失效概率为4.094×10^–96。结论 研究结果可为无失效方程下极低失效概率的可靠性计算问题提供参考。     

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.     

GIS环境下大区域工程场地地震液化势的二维概率评价方法

用具有概率意义的饱和砂土抗液化强度经验公式来对大区域场地进行地震液化势二维概率评价;在GIS软件ArcGIS的支持下,将取样钻孔处的液化势评价结果等价于数字高程模型(Digital Elevation Model,DEM)中的高程,利用ArcGIS空间分析模块中的Kriging插值法估计大区域场地的地震液化范围。研究表明:将Kriging法应用于岩土工程地质特征的统计推断,有助于揭示勘探孔以外的地层信息,对于大区域场地地震液化范围的判别是一个较好的手段;利用ArcGIS空间分析模块中的Kriging法,通过已勘察点的信息(液化势)来估计未勘测点的土层液化势,能够较好地区划出场地地震液化势的空间分布特征。     

融合自然-人为因子改进回归克里格对土壤镉空间分布预测

掌握土壤重金属的空间分布对于科学制定土壤污染风险管控策略具有重要支撑作用.针对目前重金属空间模拟较少考虑影响因素且平行变量间存在多重共线性,导致预测精度较低问题,选取自然-人为的23个影响因素,采用OK(普通克里格法)、NRK(仅基于自然因子的回归克里格法)和NARK(基于自然-人为因子的回归克里格法)对土壤镉空间分布...     

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。