计算机模拟地质化验室分样及取样常数Ks的估算

提出了计算机模拟地质化验室取样过程,考察取样误差与取样量、样品粒度之间关系,并估算取样常数。实验所得的误差与取样量之间的关系与Ingamells的取样方程一致,取样常数及取样常数和样品粒度关系式也与Ingamells推导的相符。由于计算机模拟是一颗颗取样,不用预设分布模式,不存在分析方法误差和分样操作误差的叠加,误差完全是因样品本身不均匀产生的。而且计算机模拟运算速度快,参数变换方便,使模拟更接近样品实际,能满足地质化验室的应用。     

The analytical and economic importance of correctness in sampling

Sampling is part of quality evaluation as well as of the analysis. Probabilistic and non-probabilistic sampling methods are discussed, with examples of the severe financial consequences of incorrect sampling procedures. Only probabilistic methods (cross-stream and splitting) can be correct but their correctness depends on sample increment delimitation, increment extraction and integrity of increments and final sample. Recommendations are given for designing sampling procedures and designing sampling equipment. Common sources of error are described. The need for analytical specialists to be responsible for both sampling and sample processing is emphasized.     

Sampling and metrology

The result of a measurement refers in principle only to the amount of substance actually contributing to the analytical signal. However, an appropriate definition of the measurand must include a specification of the system for which the result of the measurement should apply. All systems being inherently heterogeneous, representativity assumes importance for the metrological quality of a measurement, and the process needed to ascertain representativity is sampling. The contribution from this characteristic must be included when expressing the uncertainty of the reported value of the measurand. Representative sampling of systems that are infinite or non-uniform was developed by Pierre Gy in his Theory of Sampling. Finite systems can achieve uniformity by mechanical treatment and mixing; the heterogeneity of these systems can be characterized by a sampling constant, expressed in units of weight, for each particular species being determined. Examples of the contribution of sampling to the uncertainty of analytical results are discussed for some biological materials. Presented at the 2nd International Conference on Metrology – Trends and Applications in Calibration and Testing Laboratories, November 4–6, 2003, Eilat, Israel.     

Gy sampling theory in environmental studies: 2. Subsampling error estimates

Sampling can be a significant source of error in the measurement process. The characterization and cleanup of hazardous waste sites require data that meet site-specific levels of acceptable quality if scientifically supportable decisions are to be made. In support of this effort, the US Environmental Protection Agency (EPA) is investigating methods that relate sample characteristics to analytical performance. Predicted uncertainty levels allow appropriate study design decisions to be made, facilitating more timely and less expensive evaluations. Gy sampling theory can predict a significant fraction of sampling error when certain conditions are met. We report on several controlled studies of subsampling procedures to evaluate the utility of Gy sampling theory applied to laboratory subsampling practices. Several sample types were studied and both analyte and non-analyte containing particles were shown to play important roles affecting the measured uncertainty.

Gy sampling theory was useful in predicting minimum uncertainty levels provided the theoretical assumptions were met. Predicted fundamental errors ranged from 46 to 68% of the total measurement variability. The study results also showed sectorial splitting outperformed incremental sampling for simple model systems and suggested that sectorial splitters divide each size fraction independently. Under the limited conditions tested in this study, incremental sampling with a spatula produced biased results when sampling particulate matrices with grain sizes about 1 mm.     

Method for fractional solid-waste sampling and chemical analysis

Chemical characterization of solid waste is a demanding task due to the heterogeneity of the waste. This article describes how 45 material fractions hand-sorted from Danish household waste were subsampled and prepared for chemical analysis of 61 substances. All material fractions were subject to repeated particle-size reduction, mixing, and mass reduction until a sufficiently small but representative sample was obtained for digestion prior to chemical analysis. The waste-fraction samples were digested according to their properties for maximum recognition of all the studied substances. By combining four subsampling methods and five digestion methods, paying attention to the heterogeneity and the material characteristics of the waste fractions, it was possible to determine 61 substances with low detection limits, reasonable variance, and high accuracy. For most of the substances of environmental concern, the waste-sample concentrations were above the detection limit (e.g. Cd?>?0.001?mg?kg^?1, Cr?>?0.01?mg?kg^?1, Hg?>?0.002?mg?kg^?1, Pb?>?0.005?mg?kg^?1). The variance was in the range of 5–100%, depending on material fraction and substance as documented by repeated sampling of two highly different material fractions (‘Vegetable food’ and ‘Shoes, leather, etc.’). Statistical analysis showed for the ‘Vegetable food’ that the variance could not be attributed to a single step in the procedure, whereas in the case of ‘Shoes, leather, etc.’, the first coarse shredding was the main source of variance (20–85% of the overall variation). Only by increasing the sample size significantly can this variance be reduced. The accuracy and short-term reproducibility of the chemical characterization were good, as determined by the analysis of several relevant certified reference materials. Typically, six to eight different certified reference materials representing a range of concentrations levels and matrix characteristics were included. Based on the documentation provided, the methods introduced were considered satisfactory for characterization of the chemical composition of waste-material fractions.     

Evaluation of the fundamental sampling error in the sampling of particulate solids

Chemical analysis is a multi-stage process, which starts with primary sampling and ends with evaluation of the resuts. Especially in trace analysis and microanalysis of solid materials, sampling can far outweigh all other sources of error. For estimating the reliability of complete analytical procedures, a method is needed which can be used to estimate the errors made in the primary and the secondary sampling and sample preparation steps. Based on Gy's theory of sampling, a computer program (SAMPEX) was written for the solution of practical sampling problems. The method involves the estimation of the sampling constant, C. For well-characterized materials, C can be estimated from the material properties. If the necessary material properties are difficult to estimate, C can be evaluated experimentally. The program can be used to solve the following problems: minimum sample size for a tolerated relative standard deviation of the fundamental sampling error; relative size for a tolerated for a given sample size; maximum particle size of the material for a specified standard deviation and sample size; balanced design of a multi-stage sampling and sample-reduction process; and sampling for particle size determination.     

Collaborative sampling trial in the context of quality assurance in the German marine monitoring programme for the North Sea and the Baltic Sea

This paper presents the assessment of a collaborative trial in sampling in the Baltic Sea in the framework of quality assurance in the German marine monitoring programme for the North Sea and the Baltic Sea. The objective of investigations was to determine the influence of sampling on analytical results for selected monitoring parameters and to harmonize the procedure for sampling of sea water to a large extent. In these studies the staff of three vessels took replicate sea water samples, 1 m below the surface and below the halocline, at two monitoring stations. Mass concentration mean values for different nutrient parameters were obtained from each sample, all in one laboratory. Data produced from the hierarchical design were treated with robust analysis of variance (ANOVA) to generate uncertainty estimates, as standard uncertainties (“u” expressed as standard deviation), for geochemical variation (s _geochem), primary sampling (s _sampling), and chemical analysis (s _analysis). Geochemical variation dominated the total variance in all cases. Sampling and analytical uncertainties contributed together up to 15% of the total variance and had a relative measurement uncertainty (u%) of less than 2% for all the parameters investigated. Thus for this study the sampling protocol and the analytical method could be regarded as fit-for-purpose. M. Gluschke was formerly affiliated to the Federal Environmental Agency, P.O. Box 33 00 22, 14191 Berlin, Germany.     

Uncertainty of sampling in chemical analysis

 Uncertainty of sampling is the contribution from sampling errors to the combined uncertainty associated with an analytical measurement when the measurand is the concentration of the analyte in the 'target', the total bulk of material that the sample is meant to represent. Of the errors considered to contribute to uncertainty, random errors of sampling, characterised by precision, are much more accessible to investigation than those due to bias. Where an approximation to random sampling can be achieved, realistic precisions can normally be estimated. In some instances reproducibility precision is significantly greater than repeatability precision, and the contribution of between-sampler variations to sampling uncertainty must be acknowledged. However, the collaborative trial of a sampling method is an expensive and difficult exercise to execute. A system of internal quality control for routine sampling can be introduced. Fitness for purpose has been defined in terms of the required combined uncertainty of sampling and analysis. Received: 4 November 1997 · Accepted: 26 November 1997     

Metrological estimation of sampling and sample preparation procedures as applied to analytical testing of technogenic origin raw material containing recoverable precious metal

 Different schemes of analytical testing including the sampling, sample preparation and sample analysis operations are considered as applied to a lot of raw material containing recoverable precious metal. The errors resulting from the step-by-step operations of the analytical testing are estimated. Sampling and sample preparation operations are found to be significant contributors to the total error of determination of the percentage and /or weight of a precious metal of interest in a lot. Some ways to diminish both the sampling error and the total error of the analytical testing procedure are recommended. Received: 28 December 1998 · Accepted: 22 February 1999     

Chemical and environmental sampling: quality through accreditation, certification and industrial standards

Executive summary In the CEN/STAR Trends Analysis workshop on Sampling, initiated by request of the Nordic Innovation Centre, specially invited experts provided presentations on demands about regulation concerning sampling quality, sampling standard developments, quality assurance systems and practical experience from different sampling situations and cases. The workshop arrived at recommendations on the importance of proper sampling for environmental and product control purposes, especially to support European regulations, trade agreements and monitoring of environment. Sampling is an integrated part of the whole measurement process and should therefore be especially considered from the viewpoint of the end-user of the results. There is a need for raising quality control issues in sampling and for the establishment of a more uniformly co-ordinated European quality system for sampling. With the standard methods available, there are in principle two different ways of achieving third party assessment of the sampling protocols and procedures: accreditation of sampling organisations based upon international, national, or in-house standards and methods, and certification of individual samplers’ competences for sampling. Several activities or efforts as well as research and standardisation needs for raising the quality issues in sampling were identified and presented in a paper by the workshop.All the presentations and Workshop Proceedings are electronically available on the Nordic Innovation Centre's web site at and more specifically at     

Design of experiment for evaluation of uncertainty from sampling in the framework of the fitness for purpose concept: a case study

The design of an experiment for the evaluation of sampling uncertainty in the framework of the fitness for purpose concept is described in terms of probabilities (risks of the user) of type 1 and type 2 errors in decisions concerning the significance of effects influencing the sampling uncertainty and the measurement results. As a case study, an experiment based on the duplicate method for quantification of the sampling uncertainty and inhomogeneity (heterogeneity) of a melt of tin-free bronze produced in a 10-ton reflective oven is analyzed. The melt is defined as the sampling target. It is shown that the number of such targets (melts), the number of samples under analysis and the number of replicate analyses can be minimized, i.e., the size and cost of the experiment can be reduced, if the user knows which risks are acceptable. When inhomogeneity of the sampling target has a systematic character, like the decrease of the mass fraction of aluminum from the beginning to the end of the melt pouring in the case study, the inhomogeneity effect can be separated from the sampling uncertainty and evaluated according to the user’s needs.     

Influence of sampling to the homogeneity of Cu-Ti-Zn alloy samples for the analyses with glow discharge optical emission spectroscopy

 Using Plackett-Burman experimental design the parameters of different ways of sampling (design and materials of the sampling mold, conditions of solidification of samples) that influence on the homogeneity of copper-titanium-zinc alloy samples in the production of titanium zinc were determined. Based on these results, the homogeneity of samples taken with two different sampling molds was investigated with GD-OES technique regarding alloyed elements (Cu and Ti) and impurities (Fe, Pb, Cd, Sn, Al) and was evaluated with analysis of variance (ANOVA). For Cu, Ti and Fe an overall (combined) uncertainty for different sampling approaches were estimated and compared to the expanded uncertainty evaluated without including the uncertainty due to sampling. Received: 28 October 2002 Accepted: 2 January 2003 Presented at CERMM-3, Central European Reference Materials and Measurements Conference: The function of reference materials in the measurement process, May 30–June 1, 2002, Rogaška Slatina, Slovenia Correspondence to B. Kokliˇc     

Sampling of water, soil and sediment to trace organic pollutants at a river-basin scale

Sampling is considered a crucial step in the analysis of organic compounds in the environment. This review describes field sampling techniques and provides detailed step-by-step procedures for collection and preservation of all major environmental matrices (water, sediment and soil) integrated as part of the river-basin water cycle. Attention is given to the prerequisites for obtaining reliable samples, and the practical issues of sample collection (planning, field sampling, sampling strategies and equipment and data quality assessment) are considered. Considering the heterogeneity of environmental matrices, special considerations for each matrix are given to solve typical problems and to find the most appropriate solutions to ensure the quality of the sample. The procedures described in the next sections are commonly used protocols that reflect true field conditions and current state-of-the-art techniques used in the sampling of organic compounds. The aim is to signify the importance of sampling to the overall analytical procedure. Finally, quality control issues to be considered in environmental sampling are given.     

增量取样量接近分析试样量时的取样——理论修正与结果

化学分析取样几乎总是一个多步骤过程,所有的步骤都会导致分析结果的总体不确定性。样品采取之后,不论后续采样过程如何精细,前期采样阶段的误差都无法在后续采样过程中更正。第一次取样是最重要的,通常其方差远远超过实验室测量的方差。但这不意味着在最终实验室分析试样制备阶段可以忽略采样理论的原理。现代分析仪器旨在处理小样本(从毫克到几克)。在这种情况下,如果样品是包含少量分析物的混合颗粒,则物料的不均匀性可能会很大以至于破坏整个分析过程。不均匀性计算和样品制备过程中基本采样误差方差的估计对于开发适用的分析程序至关重要。在样本制备的最后步骤中,新的增量本是父增量本的重要组成部分,在估算样本方差时必须考虑到这种影响。TOS提供了用于处理这些情况的工具。通过两个案例阐明了不均匀性计算的应用。在第一个例子中,评估了鸡饲料中低含量添加剂的成分不均匀性,在第二个例子中,对样品制备进行了优化,以校正用于分析硅灰石精矿中矿物杂质含量的红外仪器。在处理颗粒混合物和评估混样效率时,不均匀性评估也很重要。     

Sampling and sampling strategies for environmental analysis

Sampling errors are generally believed to dominate the errors of analytical measurement during the entire environmental data acquisition process. Unfortunately, environmental sampling errors are hardly quantified and documented even though analytical errors are frequently yet improperly reported to the third decimal point in environmental analysis. There is a significant discrepancy in directly applying traditional sampling theories (such as those developed for the binary particle systems) to trace levels of contaminants in complex environmental matrices with various spatial and temporal heterogeneities. The purpose of this critical review is to address several key issues in the development of an optimal sampling strategy with a primary goal of sample representativeness while minimizing the total number of samples and sampling frequencies, hence the cost for sampling and analysis. Several biased and statistically based sampling approaches commonly employed in environmental sampling (e.g. judgmental sampling and haphazard sampling vs. statistically based approaches such as simple random, systematic random, and stratified random sampling) are examined with respect to their pros and cons for the acquisition of scientifically reliable and legally defensible data. The effects of sample size, sample frequency and the use of compositing are addressed to illustrate the strategies for a cost reduction as well as an improved representativeness of sampling from spatially and temporally varied environmental systems. The discussions are accompanied with some recent advances and examples in the formulation of sampling strategies for the chemical or biological analysis of air, surface water, drinking water, groundwater, soil, and hazardous waste sites.     

Optimization of sampling frequency for routine river water quality monitoring

Sampling frequency is an important factor to be considered during the design of a water monitoring network,and the cost-effective selection of possible ways and means for the optimization of sampling frequency is still needed.This paper introduces water pollution index deviation ratio comparison(WPI DRC),a procedure for the optimization of sampling frequency for a routine river water quality monitoring system.Sampling frequency optimized using WPI DRC at monitoring station X5 in the mainstream of Xiangjiang River is compared with that established using the traditional Statistical Algorithm method.The result of comparison indicates that WPI DRC is more feasible than the traditional one.And then,the sampling frequencies for other 16 monitoring stations also have been optimized,and the results show the sampling frequencies of all the stations except that X4 are reduced,and there is no unacceptable difference between water quality evaluation results at 17 stations before and after the optimization.Therefore,it is concluded that WPI DRC is an effective optimization process with operable results,which can be used to fulfill the requirement of practical monitoring work.     

装运铁矿石取样的最佳实践

商业交易的装运铁矿石取样应当按照ISO 3082进行。尽管近年来合规性已有所改善,但在一些方面仍存在明显问题,包括:1)大流量样品截取器的设计和操作;2)在二级取样阶段对一级增量样品的划分;3)缩分之前用于减小样品粒度的破碎机的破碎性能;4)在每个取样阶段保留的样品质量;5)样品缩分。取样是测量过程开始的地方,因此如果样品不具有代表性,整个过程在开始时就被破坏了。正确取样的“金规则”是“被取样物料的所有部分都必须有相等的概率被收集到并成为最终分析样品的一部分”。如果不遵守这一规则,那么就很容易引入偏差。例如,在实践中不可能从库存料堆或船舶现场采集到具有代表性的样品。必须在构建堆料或分解堆料时,或在船舶的装载或卸载时取样。在满足“正确取样的金规则”后,取样站设计还应符合以下要求:1)采集的样品质量必须足够大,以考虑粒度大小的影响,将基本误差、分组误差和离析误差降低到可接受的水平;2)需要采取足够数量的增量样品,以将长期质量波动误差降低到可接受的水平;3)应正确地选择取样位置,以避免由于诸如斗轮取料机和离心泵等设备存在的质量周期性变化所造成的影响;4)附加错误诸如样品污染、样品溢出、颗粒降解和操作员失误等,需要从一开始就加以消除。因此为了消除不良的取样做法,确保取样能够兑现应有的承诺,需要通过改进工作人员的培训和提高认识来确保所取样品没有重大偏差,确保样品的总体精度满足所需的任务要求。     

Accreditation of sampling activities

Since the introduction of ISO/IEC 17025 it is a requirement for all accredited laboratories to include sampling in their quality statements. It is well understood that sampling and handling of the sample are key factors in the validity of a result. The fact that many laboratories worldwide are not involved in sampling poses a challenge to accreditors liability. This article describes the Israel Laboratory Accreditation Authoritys (ISRAC) and other accreditors approaches to sampling.Presented at the Second International Conference on Metrology—Trends and Applications in Calibration and Testing Laboratories, 4–6 November 2003, Eilat, Israel.