Estimation of uncertainty in routine pH measurement

A procedure for estimation of measurement uncertainty of routine pH measurement (pH meter with two-point calibration, with or without automatic temperature compensation, combination glass electrode) based on the ISO method is presented. It is based on a mathematical model of pH measurement that involves nine input parameters. Altogether 14 components of uncertainty are identified and quantified. No single uncertainty estimate can be ascribed to a pH measurement procedure: the uncertainty of pH strongly depends on changes in experimental details and on the pH value itself. The uncertainty is the lowest near the isopotential point and in the center of the calibration line and can increase by a factor of 2 (depending on the details of the measurement procedure) when moving from around pH 7 to around pH 2 or 11. Therefore it is necessary to estimate the uncertainty separately for each measurement. For routine pH measurement the uncertainty cannot be significantly reduced by using more accurate standard solutions than ±0.02 pH units – the uncertainty improvement is small. A major problem in estimating the uncertainty of pH is the residual junction potential, which is almost impossible to take rigorously into account in the framework of a routine pH measurement.¹ Received: 11 August 2001 Accepted: 22 February 2002     

Alternative calculation of measurement uncertainty with global approach in food microbiology

Calculation of measurement uncertainty is a requirement for all laboratories accredited to ISO/IEC 17025 including those carrying out microbiological analyses. Today, calculation of measurement uncertainty in microbiological analyses using precision data according to global approach principles is widely recognized by the microbiologists due to difficulties in quantification of individual uncertainty sources. In food microbiology, precision data obtained from different samples usually show over-dispersion, and the use of over-dispersed data may result in large variance. The current ISO standard on measurement uncertainty in food microbiology proposes the use of log-transformed precision data to overcome this problem. This paper proposes an alternative procedure to calculate the measurement uncertainty in food microbiology using non-logarithmic precision data. The calculations used in this procedure based on relative range of duplicate analyses can be applied to intra-laboratory reproducibility data obtained from microbiological analyses of which duplicate results show relatively low variation.     

Estimation of uncertainty in electrochemical amperometric measurement of dissolved oxygen concentration

A procedure for the estimation of measurement uncertainty of dissolved oxygen (DO) concentration measurement based on the ISO approach is presented. It is based on a mathematical model that involves 14 input parameters. The uncertainty of DO concentration strongly depends on changes in experimental details (temperature difference between calibration and measurement, the time interval between calibration and measurement, etc.). The relative measurement uncertainty is, however, practically independent of the DO concentration itself. The uncertainty is the lowest if the calibration and the measurement are done at the same temperature and on the same day. A calculation tool is provided (in the form of a GUM Workbench file) for practitioners that can be used for uncertainty calculation of DO concentrations at very different experimental conditions.Electronic Supplementary Material The uncertainty calculation example is available as a GUM Workbench calculation file C_O2_meas.smu (GUM Workbench ver. 1.3.3, Metrodata GmbH) together with its data file Input_values.xls (MS Excel 97). For those users who do not have GUM Workbench, the full report of the GUM Workbench calculation is available as a PDF file C_O2_meas.pdf. This material is available via the Internet at .     

Estimation of measurement uncertainty by the budget approach for heavy metal content in soils under different land use

A reference database was used for the estimation of the standard uncertainties resulting from sampling, sample preparation, and analysis of soil samples from a target area in Switzerland. This evaluation was based on an extended reference sampling of the Comparative Evaluation of European Methods for Sampling and Sample Preparation of Soils Project. Samples were taken according to the national sampling protocols of 15 European countries and were analyzed for zinc, cadmium, copper, and lead. The combined uncertainty for all laboratories was estimated according to the ISO Guide to the Expression of Uncertainty in Measurement. It was found that the sampling uncertainty was not larger than the analytical uncertainty if more than ten sample increments were taken. The uncertainty due to variation in sampling depth and sample size reduction was only significant under unfavorable conditions. On the basis of an uncertainty budget the sampling protocols can be optimized and a ranking is possible, aimed at conditions that are fit for the specific purpose.Electronic Supplementary Material Supplementary Material is available in the online version of this article at     

Estimating measurement uncertainty: reconciliation using a cause and effect approach

 A strategy is presented for applying existing data and planning necessary additional experiments for uncertainty estimation. The strategy has two stages: identifying and structuring the input effects, followed by an explicit reconciliation stage to assess the degree to which information available meets the requirement and thus identify factors requiring further study. A graphical approach to identifying and structuring the input effects on a measurement result is presented. The methodology promotes consistent identification of important effects, and permits effective application of prior data with minimal risk of duplication or omission. The results of applying the methodology are discussed, with particular reference to the use of planned recovery and precision studies. Received: 28 October 1997 · Accepted: 17 November 1997     

Measurement uncertainty in microbiological cultivation methods

Microbiological analyses are carried out on clinical, food, feed and environmental samples. The aims of the analyses are diagnostic or estimation of the safety or the quality of the sample. Important decisions are made on the basis of microbiological analyses. Little attention, however, is paid to the uncertainty of measurement of microbiological analyses. In microbiological cultivation techniques the result is obtained by counting individual objects. The normally low number of counted objects strongly affects the result of the analysis and its uncertainty. Because of the importance of the particle statistical variation to the uncertainty, the approaches developed for chemical analyses are not directly applicable to microbiology. This paper discusses microbial analyses and describes a novel guidance document for the estimation of measurement uncertainty in culturing methods [1]. Received: 7 October 2000 Accepted: 8 March 2001     

ISO uncertainty and collaborative trial data

 The possibility of using interlaboratory study repeatability and reproducibility estimates as the basis for measurement uncertainty estimates is discussed. It is argued that collaborative trial reproducibility is an appropriate basis for estimating uncertainty in routine testing provided certain conditions are met by the laboratory. The primary shortcomings relate to establishment of traceability and consequent estimation of bias associated with the method, and quantitatively establishing the relevance to the single laboratory. Approaches to resolving both difficulties are proposed, the former via full implementation of trueness determination suggested in ISO 5725 : 1994 or by independent checks on individual accuracy and precision, the latter via a reconciliation procedure. The paper also discusses other factors including sampling and sample pre-treatment, change in sample matrix, and the influence of level of analyte. Received: 28 October 1997 · Accepted: 17 November 1997     

Estimating the measurement uncertainty in forensic breath-alcohol analysis

The evidentiary weight attributed to forensic breath alcohol results in drunk-driving prosecutions requires that measurement uncertainty be established and shown to be fit-for-purpose. The principal components contributing to breath alcohol measurement uncertainty include: (1) biological/sampling, (2) instrumental, (3) traceability and (4) the water/air partition coefficient for control standards. Employing duplicate breath results from over 92,000 subjects to estimate the biological/sampling component and assuming reasonable forensic values for the other components, the combined and expanded uncertainty is determined for a practical example. The combined uncertainty for an unbiased single determination breath alcohol measurement was: . Employing the expanded uncertainty (k = 2.58), the 99% confidence interval for a mean breath alcohol concentration of 0.0935 g/210 L was 0.0866 to 0.1004 g/210 L. The proportion of combined uncertainty associated with each component was determined to be: biological/sampling 73%, analytical 10%, traceability 13% and water/air partition coefficient 4%. These are forensically acceptable estimates and demonstrate fitness-for-purpose of breath alcohol measurement when employing appropriate elements of quality control.     

Development of a standard for the organization of the interlaboratory comparisons in microbiology of food

The ILAC G13 Guide and the ISO IEC Guide 43-1 are the common, general and horizontal bases for accreditation of providers of proficiency testing and interlaboratory comparisons used by several accreditation bodies. Despite their widespread use, these guides omit specific technical requirements, and sometimes even elements of quality management, clearly defined for the organization of proficiency-testing schemes for microbiology of food. The Sub-Committee 9 “Microbiology of food” of ISO TC34 has created a working group (WG4) to establish a standard detailing such specific requirements for microbiology of food. This technical standard will describe those specific requirements of proficiency testing which organizers of proficiency-testing schemes and any subcontractors must satisfy in addition to the requirements of the ILAC G13 Guide and the ISO IEC Guide 43-1 to achieve accreditation or other recognition.     

Repeatability: some aspects concerning the evaluation of the measurement uncertainty

Various publications stress the importance of the repeatability (i.e. precision) of the calculation of the measurement of uncertainty. We reveal by detailing an example from production control in the pharmaceutical industry that the effect of other influence quantities should not be neglected, because their magnitude is even larger than the contribution of repeatability. We review the role of repeatability within the calculation of measurement uncertainty for several common validation and day-to-day measurement scenarios. They show that measurement models need to consider the measurement sequences of the various scenarios. Otherwise the size and effect of the repeatability might be overestimated. At the end Monte Carlo simulations were used to investigate the determination of the repeatability under certain restrictions. The simulation uncovered a significant bias toward the common formula for calculating the standard deviation when it is based on a duplicated measurement of a sample. Papers published in this section do not necessarily reflect the opinion of the Editors, the Editorial Board and the Publisher     

塑料中镉的测定不确定度评定

建立了用实验室内精密度和偏差的数据来评定塑料中镉的测定不确定度的方法. 通过研究不同基体和不同含量水平的样品, 考察了方法的精密度和回收率, 分别计算并合并了两者的测量不确定度. 结果表明精密度和回收率的相对不确定度分量分别为0.026和0.068, 合成不确定度为0.072, 扩展不确定度为0.14. 此评定过程为实验室评定测量不确定度提供了一种新的方法, 简单、合理, 计算结果可靠.     

石墨炉原子吸收光谱法测定土壤中铅量的测量不确定度评定

通过石墨炉原子吸收光谱法对土壤中的铅量进行了测定,对影响测量结果的不确定度分量进行了量化的计算.从而得出影响铅量测量不确定度的主要因素是测量样品消解液中的铅的质量浓度引起的不确定度.     

Information on measurement uncertainty in test and product standards

According to ISO/IEC 17025, accreditation bodies generally accept that test procedures in normative documents have been validated. This contribution investigates, with respect to measurement uncertainty, the methodical basis of this practice in general and examines specifically two very different groups of products: asphalt, with its major components mineral aggregates and bitumen, and metal wire cloth. The author concludes that both the general and the specific situations are incoherent. The practice of accepting standardised test procedures a priori as validated does not have a sound basis in all cases. Both the concept, and the practical application, of validation or fitness for purpose vary in different product groups. The impact of this situation on the practice of accreditation should be taken into account in order to reduce market distortions in single-product groups. Laboratories face fundamental consequences from this practice.Presented at the Metro Trade Workshop on Traceability and Measurement Uncertainty in Testing, 30–31 January 2003, Berlin, Germany     

The evaluation of measurement uncertainty from method validation studies

 A protocol has been developed illustrating the link between validation experiments, such as precision, trueness and ruggedness testing, and measurement uncertainty evaluation. By planning validation experiments with uncertainty estimation in mind, uncertainty budgets can be obtained from validation data with little additional effort. The main stages in the uncertainty estimation process are described, and the use of trueness and ruggedness studies is discussed in detail. The practical application of the protocol will be illustrated in Part 2, with reference to a method for the determination of three markers (CI solvent red 24, quinizarin and CI solvent yellow 124) in fuel oil samples. Received: 10 April 1999 / Accepted: 24 September 1999     

The application of the measurement uncertainty concept to in-process control in pharmaceutical development

 Any analytical data is used to provide information about a sample. The "possible error" of the measurement can be of extreme importance in order to have complete information. The measurement uncertainty concept is a way to achieve quantitative information about this "possible error" using an estimation procedure. On the basis of the analytical result, the chemist makes a decision on the next step of the development process. If the uncertainty is unknown, the information is not complete; therefore this decision might be impossible. The major problem for the in-process control (IPC) procedure is that not only the repeatability but also the intermediate precision (which expresses the variations within laboratories related to different days, different analysts, different equipment, etc.) has to be good enough to make a decision. Unfortunately, the statistical information achieved from one single analytical run only gives information about the repeatability. This paper shows that the estimation of the measurement uncertainty for IPC is a way to solve the problem and gives the necessary information about the quality of the procedure. An example demonstrates that an estimate of uncertainty based on the standard deviations of an analytical method gives a value similar to one based on the standard deviations obtained from a control chart. Therefore, the estimation is both a very useful and also a very cost-effective tool. Though measurement uncertainty cannot replace validation in general, it is a viable alternative to validation for all methods that will never be used routinely. Received: 24 May 1996 Accepted: 10 August 1996     

A software package comparison for uncertainty measurement estimation according to GUM

Six commercial programs devoted to the estimation of measurement uncertainty were compared for feasibility in order to be applied in routine chemical analysis. The main features of each program were discussed. They were applied to two well-documented case studies. Several screen captures were considered for illustration.     

Evaluation of measurement uncertainty in analytical assays by means of Monte-Carlo simulation

The main limitations of the Guide to the expression of Uncertainty Measurement (GUM) approach for evaluating the measurement uncertainty of analytical assays are presented and explained. The advantages of using Monte-Carlo simulation against the GUM approach are outlined and discussed and the principle of propagation of distributions is explained. The procedure of Monte-Carlo analysis is illustrated by two case studies. A first simple example quoted from the EURACHEM Guide and dealing with the preparation of a calibration standard is used to present the technique with detail in a step-by-step way. In this case the results obtained by both approaches are very similar. A second example deals with the calibration of mass according to a strong non-linear model. In this case, the Monte-Carlo analysis leads to better results.     

The evaluation of measurement uncertainty from method validation studies

 A protocol has been developed illustrating the link between validation experiments and measurement uncertainty evaluation. The application of the protocol is illustrated with reference to a method for the determination of three markers (CI solvent red 24, quinizarin and CI solvent yellow 124) in fuel oil samples. The method requires the extraction of the markers from the sample matrix by solid phase extraction followed by quantification by high performance liquid chromatography (HPLC) with diode array detection. The uncertainties for the determination of the markers were evaluated using data from precision and trueness studies using representative sample matrices spiked at a range of concentrations, and from ruggedness studies of the extraction and HPLC stages. Received: 10 April 1999 · Accepted: 24 September 1999     

A case study in the practical estimation of measurement uncertainty

This case study is written for analytical laboratories, in order to give support to the implementation of the concept of measurement uncertainty for routine measurements. The aim is to provide a practical, understandable and common way of performing measurement uncertainty calculations, based mainly on pre-existing quality control and validation data. Practical examples taken directly from environmental laboratory monitoring are presented and explained. However, the approach is very general and should be applicable to most testing laboratories in the chemical field. Following the protocol of evaluation illustrated in the case study, it is possible to ensure that most relevant uncertainty components associated with the method are covered. Contributions associated with sampling, homogenisation, sub-sampling, and so on, are, however, excluded.