Fundamentals of sampling

The term sampling Is vague [2] as It Is used to describe a variety of operations such as (a) collection of the sample from its source (e.g. a pa-clent, lake, waggon or the environment of an industrial area), (b) preserva- 

The principal aim of this preliminary operation is to obtain a sample aliquot representative of the material to be analysed. 

It is immediately apparent that the complete automation of this sub-stage is a difficult task. Only in a few instances (e.g. the automatic in vivo determinations described In Chapter 14 and performed with the on-line process analysers dealt with in Chapter 17) is this ideal objective affordable. Much more often, some of the above-mentioned operations involve human participation, although It is still termed automated [1]. Therefore, although many clinical analysers are classed as automatic, the blood and urine samples that they handle are collected and even treated manually before they are placed on the sampler. Such is also the case with automatic off-line water pollutant analysers, also calling for manual collection and preservation of samples. Consequently, the automated sampling concept as used here refers to the Introduction Into the analyser or instrument concerned of a definite portion of sample collected from its source and even treated manually, with the few exceptions stated above. 

Automatic sampling systems can be classified according to different criteria (see Table 3.1), namely  

With weight/voiume measurement Without quantitation 

---

For determination of the aerodynamic diameters of particles, the most commonly apphcable methods for particle-size analysis are those based on inertia aerosol centrifuges, cyclones, and inertial impactors (Lundgren et al.. Aerosol Measurement, University of Florida, Gainesville, 1979 and Liu, Fine Paiiicles—Aerosol Generation, Measurement, Sampling, and Analysis, Academic, New York, 1976). Impactors are the most commonly used. Nevertheless, impactor measurements are subject to numerous errors [Rao and Whitby, Am. Ind. Hyg. A.s.soc.]., 38, 174 (1977) Marple and WiUeke, "Inertial Impactors, in Lundgren et al.. Aerosol Measurement and Fuchs, "Aerosol Impactors, in Shaw, Fundamentals of Aerosol Sci-... 

Sampling of slurries and solids, differs fundamentally from sampling a completely mixed liquid or gas, A hulk quantity of sohds incorporates characteristic heterogenity—that is, a sample Sj differs inherently from a sample S2 when both are taken from a thoroughly mixed load of solids as a result of property variances embodied in solids. In contrast, all individual samples from a completely mixed liquid or gas container are statistically identical. 

Variations in measurable properties existing in the bulk material being sampled are the underlying basis for samphng theory. For samples that correctly lead to valid analysis results (of chemical composition, ash, or moisture as examples), a fundamental theoiy of sampling is applied. The fundamental theoiy as developed by Gy (see references) employs descriptive terms reflecting material properties to calculate a minimum quantity to achieve specified sampling error. Estimates of minimum quantity assumes completely mixed material. Each quantity of equal mass withdrawn provides equivalent representation of the bulk. 

Example 4 Calculation of Sample Weight for Surface Moisture Content An example is given with reference to material with minimal internal or pore-retained moisture such as mineral concentrates wherein physically adhering moisture is the sole consideration. With this simphfication, a moisture coefficient K is employed as miiltipher of nominal top-size particle size d taken to the third power to account for surface area. Adapting fundamental sampling theory to moisture sampling, variance is of a minimum sample quantity is expressed as... 

Part A, dealing with the Fundamentals of Quantitative Chemical Analysis, has been extended to incorporate sections of basic theory which were originally spread around the body of the text. This has enabled a more logical development of theoretical concepts to be possible. Part B, concerned with errors, statistics, and sampling, has been extensively rewritten to cover modern approaches to sampling as well as the attendant difficulties in obtaining representative samples from bulk materials. The statistics has been restructured to provide a logical, stepwise approach to a subject which many people find difficult. 

The simplicity mentioned above exists for various kinds of samples that meet the fundamental requirements laid down in Chapters 6 and 7. Examples are a thin film on a suitable substrate, a sample dissolved at low concentration in a solvent transparent to x-rays, or a sample uniformly dispersed in a similarly transparent medium. In all cases, scattered x-rays should be at a minimum to keep the background low. From the point of view taken here, a trace is thus regarded as a major constituent in a sample if sensible absorption and enhancement effects are absent—if, that is, Equation 7-3 is valid. 

Figure 1. Histogram of measurements of molar U/Ca ratio in a number of samples of reef-building corals and one giant clam sample (after Edwards 1988). Also indicated is the U/Ca ratio of seawater. This illustrates the point that corals do not fractionate U from Ca by large amounts when they make their skeletons. U/Ca ratios of corals are similar to values from inorganically precipitated marine aragonite. Mollusks along with most other biogenic minerals exclude uranium. Note that the horizontal axis is on a log scale and that the U/Ca ratio of the clam is almost 5 orders of magnitude lower than that of the corals. This difference is the fundamental reason why there are difficulties with uranium-series dating of mollusks.

Fluorescence measurements are fundamentally different to absorption measurements [20,173,180]. The fluorescence intensity depends only on the population of sample molecules and can be calculated in several ways. Independent of "the method chosen at low sample concentrations the fluorescence signal, F, is adequately described by equation (7.26)... 

---