Soil, lead sampling variability

There are a variety of field and laboratory analytical methods for soil lead measurement, depending on the type of analysis and its purposes in a given evaluation. Bulk soil lead measurement refers to measurement of the total lead content of the soil sample. Chemical speciation and micromineralogical studies in the context of human lead exposure variability refer to amounts of specific chemical forms of lead and their geochemical states. These studies are sometimes done in tandem with relative bioavailability testings, i.e., amounts of lead being absorbed under in vivo or in vitro simulation of in vivo conditions (Casteel et al., 2006) with respect to Pb source attribution. Stable isotopic analysis studies deal with the quantitative stratification of lead s stable isotopic composition into the four main stable isotopes lead-204, lead-206, lead-207, and lead-208 (Gulson et al., 1995, 1997). 

The very wide variation of the lead content of the investigated soil samples is, moreover, conspicuous. RLS regression yields qualitatively comparable results, but with lower correlation coefficients (see Tab. 9-6). This is primarily because many outliers were eliminated from the data obtained (Tab. 9-7). Since the measuring points weighted with vv, = 0 are not outliers in the classical sense, but environment-related variability, preference should be given to LMS regression when environmental data have to be analyzed. The RLS regression should primarily be reserved for cases with real outliers. 

In the early stages following the amendment of the soil, individual sludge pellets were still visible in the sample and some passed through the sieve intact. This would obviously lead to homogeneity problems. The physical break up of pellets during the growing season would be consistent with the reduced variability over time. 

A useful method of recording numerical data is in the form of a table. All tables should have a title that adequately describes the data presented (they may need to be numbered so that they can be quoted in the text). It is important to display the components of the table such that it allows direct comparison of data and to allow the reader to easily understand the significance of the results. It is normal to tabulate data in the form of columns and rows, with columns running vertically and rows horizontally. Columns contain, for example, details of concentration and units, sampling sites or properties measured, while rows contain numerical or written descriptions for the columns. The first column often contains the independent variable data, e.g. concentration or site location, while subsequent columns may contain numerical values of concentrations for different metals or organics. A typical tabulated set of data obtained from an experiment to determine the level of lead in soil by using atomic absorption spectroscopy is shown in Table 1.4. 

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