Measurement uncertainty factors

When setting the goals of a measurement project, it has to be asked, What exactly has to be determined. What are the final quantities required and what is the inaccuracy that can be tolerated in these quantities Only when these factors are known can an analysis be made, where the quantities to be measured and the measurement accuracy of each quantity are defined. This analysis is based on the mea surement method selected, and on the computation of measurement uncertainties. Usually the analysis of measurement uncertainties is made after monitoring however, making it beforehand is part of good planning practice. This approach ensures that the correct information with the desired accuracy is achieved. 

The measurement uncertainty is transformed into a corresponding uncertainty of the final result due to algebraic distortions and weighting factors, even if the calculator s accuracy is irrelevant. 

For any given measurement process, more than one instance of each type of error can apply. Therefore, errors are insufficient to describe the quality of a measurement result. Measurement uncertainty, on the other hand, combines into a single range the effect of all of the different factors that can influence a measurement result. 

Canada [8]. In this document all three approaches have been performed after an extensive literature study of effects documented and environmental concentrations measured in the Canadian aquatic environment. Thus, based on the most sensitive endpoint found in the literature (LC50 of nonylphenol (NP) for winter flounder 17 pig L-1 [9]), and applying an uncertainty factor of 100, for NP a PNEC of 0.17 p.g L-1 was derived. Analogously, NEC were derived for nonylphenol ethoxylates (NPEO) and nonylphenol ethoxy carboxylates (NPEC) these are listed in Table 7.4.1. 

Although the measurement uncertainties limit the conclusions which can be drawn from these results, the data set proved useful for the determination of general Influences on rainwater composition In the Seattle area and for the demonstration of the application of these exploratory data analysis techniques. Current efforts to collect and analyze aerosol and rainwater samples over meteorologically appropriate time scales with precise analytical techniques are expected to provide better resolution of the factors controlling the composition of rainwater. 

In 1988, the US-EPA adopted the ADI approach in its regulatory measures against environmental pollution with a number of modifications (US-EPA 1988, 1993). Instead of the terms ADI and safety factor, the terms Reference Dose (RfD) and uncertainty factor (UF), respectively, were selected. The RfD is derived from the NOAEL by dividing by the overall UF. The overall UF originally suggested and reconfirmed in 2002 (US-EPA 2002) generally consists of a 10-fold factor for each of the following ... 

As is the case for LIF, calibration to obtain absolute concentrations is a challenge. In the instrument shown in Fig. 11.45, a calibration source based on the photolysis of water at 185 nm is installed in the inlet. From the absorption cross section of HzO gas at 185 nm, its concentration, the light intensity, and the sample flow rate, the concentration of OH generated by the photolysis can be calculated. However, not only is there significant uncertainty in the absorption cross section for HzO at 185 nm (e.g., see Lazendorf et al., 1997 Hofzumahaus et al., 1997, 1998 and Tanner et al., 1997), but the measured calibration factor was highly variable from day to day, by as much as a factor of two (Tanner et al., 1997). 

CX/MAS 02/13 (2002), Codex Alimentarius Commission, Codex Committee on Methods of Analysis and Sampling (FAO/WHO),The use of analytical results Sampling, relationship between the analytical results, the measurement uncertainty, recovery factors and the provisions in Codex standards, agenda item 9 of the 24th session, Budapest, Hungary, Nov. 18-22, 2002. 

Of importance to the traceability of the results is a proper estimate of the measurement uncertainty of each participant. The error bars in figure 5.7 are the expanded uncertainties reported by the laboratories, in some cases with a coverage factor relating to more appropriate degrees of freedom. Table... 

There are several terms used in measurement uncertainty that must be defined. An uncertainty arising from a particular source, expressed as a standard deviation, is known as the standard measurement uncertainty (u). When several of these are combined to give an overall uncertainty for a particular measurement result, the uncertainty is known as the combined standard measurement uncertainty (uc), and when this figure is multiplied by a coverage factor ( ) to give an interval containing a specified fraction of the distribution attributable to the measurand (e.g., 95%) it is called an expanded measurement uncertainty [U). I discuss these types of uncertainties later in the chapter. 

When assessing measurement uncertainty as part of a method validation, enough experiments are done to have degrees of freedom that do not adversely affect the coverage factor, and usually is taken as 2. As long as subsequent field measurements followed the validated method, a measurement uncertainty can be then quoted with = 2. For the most part, therefore, the expanded uncertainty should be calculated from the combined standard uncertainty by... 

As reproducibility standard deviation from interlaboratory method validation studies has been suggested as a basis for the estimation of measurement uncertainty if it is known sR can be compared with a GUM estimate. It may be that with good bias correction, the estimate may be less than the reproducibility, which tends to average out all systematic effects including ones not relevant to the present measurement. Another touchstone is the Horwitz relation discussed in section 6.5.4. A rule of thumb is that the reproducibility of a method (and therefore the estimated measurement uncertainty) should fall well within a factor of two of the Horwitz value. 

For a measurement result to be metrologically traceable, the measurement uncertainty at each level of the calibration hierarchy must be known. Therefore, a calibration standard must have a known uncertainty concerning the quantity value. For a CRM this is included in the certificate. The uncertainty is usually in the form of a confidence interval (expanded uncertainty see chapter 6), which is a range about the certified value that contains the value of the measurand witha particular degree of confidence (usually 95%). There should be sufficient information to convert this confidence interval to a standard uncertainty. Usually the coverage factor ( see chapter 6) is 2, corresponding to infinite degrees of freedom in the calculation of measurement uncertainty, and so the confidence interval can be divided by 2 to obtain uc, the combined standard uncertainty. Suppose this CRM is used to calibrate... 

Consideration of factors that could contribute to measurement uncertainty from the use in the analysts laboratory revision of the uncertainty budget accordingly... 

Measurement uncertainty is a critical parameter for nearly every kind of analytical system. Parameters in the second column of table 8.3 are not unimportant and must be established, but they are not likely to become limiting factors in the development of the method. In table 8.3, where selectivity is in parentheses, this is not to say that the method should not be demonstrably capable of analyzing the target analyte, but that it should be clear very quickly whether or not the method is doing its job. 

The major components of uncertainty are combined according to the rules of propagation of uncertainty, often with the assumption of independence of effects, to give the combined uncertainty. If the measurement uncertainty is to be quoted as a confidence interval, for example, a 95% confidence interval, an appropriate coverage factor is chosen by which to multiply the combined uncertainty and thus yield the expanded uncertainty. The coverage factor should be justified, and any assumptions about degrees of freedom stated. 

The standard recognizes the factors that determine the correctness and reliability of test results human factors, accommodation and environment, methods, equipment, sampling, and the handling of test items. In this list, measurement traceability is mentioned, but in fact metrological traceability, with measurement uncertainty and method validation, are really subsumed in methods. (subsection 5.4). The effect of each of these factors on measurement uncertainty will differ considerably among kinds of tests. 

The first protocols developed for evaluation of the performance of diffusive samplers were based on workplace applications. The European standard EN838 1995 (EN (1995)) is an example. This approach has been adapted to provide a protocol for the evaluation of the performance of diffusive samplers for ambient air monitoring (EN, 2004a). It describes a series of tests that enable a calculation of the measurement uncertainty. The key sampler related factors assessed are ... 

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