Quantitation, quantification

In some cases, a limit of quantitation (quantification) may need to be considered where it is necessary not only to detect the presence of an analyte but also to determine the amount present with a reasonable statistical certainty. The limit of quantitation of an individual analytical procedure is the smallest amount of an analyte in a sample, which can be quantitatively determined with acceptable uncertainty. More detail can be found in Section 4.6.4. 

Over the past few decades there have been tremendous advances in methods to characterise the microstructure of cementitious materials, especially in making these techniques more quantitative. Quantification is essential as most commercial cements have broadly similar compositions. Unfortunately, today it is still not possible to characterise the microstructure of a cementitious material with the same precision which can be obtained in a test of mechanical performance. More precise quantification depends on good experimental methods and understanding of the workings of the different methods. 

Analytical Approaches. Different analytical techniques have been appHed to each fraction to determine its molecular composition. As the molecular weight increases, complexity increasingly shifts the level of analytical detail from quantification of most individual species in the naphtha to average molecular descriptions in the vacuum residuum. For the naphtha, classical techniques allow the isolation and identification of individual compounds by physical properties. Gas chromatographic (gc) resolution allows almost every compound having less than eight carbon atoms to be measured separately. The combination of gc with mass spectrometry (gc/ms) can be used for quantitation purposes when compounds are not well-resolved by gc. 

To quantitate proteins from staining, a densitometer aided by computer software is used to evaluate band areas of samples compared to band areas of a standard curve. Amido black, Coomassie Brilliant Blue, and silver stains are all appHcable for use in quantification of proteins. 

The detection and quantification of cyanobacterial toxins quoted in the above examples required methods which have been undergoing rapid development in recent years, and as the need for greater understanding of the properties and occurrence of the toxins continues to grow, these are continuing to be developed. This has resulted in methods of cyanobacterial toxin detection which are more sensitive, quantitative, reliable, specific and humane. Many of these methods are presented and discussed in the proceedings of a recent conference. 

As mentioned above, the interpretation of CL cannot be unified under a simple law, and one of the fundamental difficulties involved in luminescence analysis is the lack of information on the competing nonradiative processes present in the material. In addition, the influence of defects, the surface, and various external perturbations (such as temperature, electric field, and stress) have to be taken into account in quantitative CL analysis. All these make the quantification of CL intensities difficult. Correlations between dopant concentrations and such band-shape parameters as the peak energy and the half-width of the CL emission currently are more reliable as means for the quantitative analysis of the carrier concentration. 

NAA is a quantitative method. Quantification can be performed by comparison to standards or by computation from basic principles (parametric analysis). A certified reference material specifically for trace impurities in silicon is not currently available. Since neutron and y rays are penetrating radiations (free from absorption problems, such as those found in X-ray fluorescence), matrix matching between the sample and the comparator standard is not critical. Biological trace impurities standards (e.g., the National Institute of Standards and Technology Standard Rference Material, SRM 1572 Citrus Leaves) can be used as reference materials. For the parametric analysis many instrumental fiictors, such as the neutron flux density and the efficiency of the detector, must be well known. The activation equation can be used to determine concentrations ... 

In contrast with the dc source, more variables are needed to describe the rf source, and most of these cannot be measured as accurately as necessary for analytical application. It has, however, been demonstrated that the concept of matrix-independent emission yields can continue to be used for quantitative depth-profile analysis with rf GD-OES, if the measurements are performed at constant discharge current and voltage and proper correction for variation of these two conditions are included in the quantification algorithm [4.186]. 

The. statement goes on to acknowledge the contribution of the Reactor Safety Study (WASH-1400) to risk quantification but points out that safety goals were not the study objectives and that the uncertainties make it unsuitable for such a purpose. After pointing out that the death I f any individual is not "acceptable," it states two quantitative objectives ... 

For application in chemical process quantitative risk analysis (CPQRA), the hierarchical format of HTA enables the analyst to choose the level of event breakdown for which data are likely to be available. This is useful for human reliability quantification (see the discussion in Chapter 5). 

In addition, the chapter will provide an overview of htunan reliability quantification techniques, and the relationship between these techniques and qualitative modeling. The chapter will also describe how human reliability is integrated into chemical process quantitative risk assessment (CPQRA). Both qualitative and quantitative techniques will be integrated within a framework called SPEAR (System for Predictive Error Analysis and Reduction). 

The purpose of this chapter is to show that improvements in safety, quality, and productivity are possible by applying some of the ideas and techniques described in this book. The fact that error reduction approaches have not yet been widely adopted in the CPI, together with questions of confidentiality, has meant that it has not been possible to provide examples of all the techniques described in the book. However, the examples provided in this chapter illustrate some of the most generally useful qualitative techniques. Case studies of quantitative techniques are provided separately in the quantification section (Chapter 5). The first two case studies illustrate the use of incident analysis techniques (Chapter 6). 

The Chemical Process Industry (CPI) uses various quantitative and qualitative techniques to assess the reliability and risk of process equipment, process systems, and chemical manufacturing operations. These techniques identify the interactions of equipment, systems, and persons that have potentially undesirable consequences. In the case of reliability analyses, the undesirable consequences (e.g., plant shutdown, excessive downtime, or production of off-specification product) are those incidents which reduce system profitability through loss of production and increased maintenance costs. In the case of risk analyses, the primary concerns are human injuries, environmental impacts, and system damage caused by occurrence of fires, explosions, toxic material releases, and related hazards. Quantification of risk in terms of the severity of the consequences and the likelihood of occurrence provides the manager of the system with an important decisionmaking tool. By using the results of a quantitative risk analysis, we are better able to answer such questions as, Which of several candidate systems poses the least risk Are risk reduction modifications necessary and What modifications would be most effective in reducing risk ... 

Sotolon (4,5-dimethyl-3-hydroxy-2(5H)-furanone) and solerone (4-acetyl- y-butirrolactone) were claimed to be responsible for some aroma characteristic of flor sherries wines. These compounds are present only as traces, and are chemically unstable. A system of two gas chromatographs coupled with a four-port switching valve was used to quantitate these components without previous fractionation. The first chromatograph was equipped with an on-column injector, in order to avoid thermal degradation of sotolon in the heated injector, a DB-5 column and an FID. The second chromatograph was equipped with an on-column injector, a DB-1701 column and an FID. The method allowed quantification of solerone and sotolon at concentrations as low as a few ppb (29). 

The amorphous orientation is considered a very important parameter of the microstructure of the fiber. It has a quantitative and qualitative effect on the fiber de-formability when mechanical forces are involved. It significantly influences the fatigue strength and sorptive properties (water, dyes), as well as transport phenomena inside the fiber (migration of electric charge carriers, diffusion of liquid). The importance of the amorphous phase makes its quantification essential. Indirect and direct methods currently are used for the quantitative assessment of the amorphous phase. 

QA/QC Control Metrics QT Prolongation Quantification of Diug Effect Quantitative PCR Quinolinic Acid Quinolones... 

The procedure for the determination of total secondary alkanesulfonates with TLC and of total monosulfonates specified as homologs and isomers by derivatization GC-MS is shown in Fig. 18. The specific clean-up for sewage sludges prior to total secondary alkanesulfonate determination is outlined in Fig. 19. TLC conditions are given in Table 9. The limits of the quantification of secondary alkanesulfonates are summarized in Table 10. For eight samples and one operator the TLC time schedule is 4 days sample pretreatment and sublation, clean-up, TLC performance, and quantitative evaluation of TLC [24]. 

Factors may be classified as quantitative when they take particular values, e.g. concentration or temperature, or qualitative when their presence or absence is of interest. As mentioned previously, for an LC-MS experiment the factors could include the composition of the mobile phase employed, its pH and flow rate [3], the nature and concentration of any mobile-phase additive, e.g. buffer or ion-pair reagent, the make-up of the solution in which the sample is injected [4], the ionization technique, spray voltage for electrospray, nebulizer temperature for APCI, nebulizing gas pressure, mass spectrometer source temperature, cone voltage in the mass spectrometer source, and the nature and pressure of gas in the collision cell if MS-MS is employed. For quantification, the assessment of results is likely to be on the basis of the selectivity and sensitivity of the analysis, i.e. the chromatographic separation and the maximum production of molecular species or product ions if MS-MS is employed. 

The use of volatile chemicals as systematic markers has the obvious advantage of lending itself to quantification through GLC. In many, if not most, of the cases discussed below, qualitative differences in monoterpene profiles would not have been sufficient to allow distinctions to be made between taxa, or even between individuals within a population. This is true because most conifers synthesize many of the same monoterpenes, although often in vastly different relative concentrations. It is these quantitative differences that have been constructively used in the following examples. Structures of the terpenes commonly studied are presented in Fig. 3.7. 

The advantages of SIMS are its high sensitivity (detection limit of ppms for certain elements), its ability to detect hydrogen and the emission of molecular fragments that often bear tractable relationships with the parent structure on the surface. Disadvantages are that secondary ion formation is a poorly understood phenomenon and that quantification is often difficult. A major drawback is the matrix effect secondary ion yields of one element can vary tremendously with chemical environment. This matrix effect and the elemental sensitivity variation of five orders of magmtude across the periodic table make quantitative interpretation of SIMS spectra oftechmcal catalysts extremely difficult. 

Alkaline hydrolysis (saponification) has been used to remove contaminating lipids from fat-rich samples (e.g., pahn oil) and hydrolyze chlorophyll (e.g., green vegetables) and carotenoid esters (e.g., fruits). Xanthophylls, both free and with different degrees of esterification with a mixture of different fatty acids, are typically found in fruits, and saponification allows easier chromatographic separation, identification, and quantification. For this reason, most methods for quantitative carotenoid analysis include a saponification step. 

The accuracy and precision of carotenoid quantification by HPLC depend on the standard purity and measurement of the peak areas thus quantification of overlapping peaks can cause high variation of peak areas. In addition, preparation and dilution of standard and sample solutions are among the main causes of error in quantitative analysis. For example, the absorbance levels at of lutein in concentrations up to 10 mM have a linear relationship between concentration and absorbance in hexane and MeOH on the other hand, the absorbance of P-carotene in hexane increased linearly with increasing concentration, whereas in MeOH, its absorbance increased linearly up to 5 mM but non-linearly at increasingly higher concentrations. In other words, when a stock solution of carotenoids is prepared, care should be taken to ensure that the compounds are fuUy soluble at the desired concentrations in a particular solvent. 

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