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Patterns in the soil and in the vadose zone                           291

                   compounds) are very soluble in water and are primarily found in dissolved form in the
                   pore water solution of the vadose zone .  These substances are particularly susceptible to
                   leaching  to groundwater. The field variability of soil and pore water composition and related
                   biogeochemical processes is known to be quite high and to occur across very short spatial
                   (e.g. several metres)) and temporal scales (e.g. days) (e.g. Parkin, 1993; Daniels et al., 2001;
                   Eghball et al., 2003; Cox et al., 2003). There are many reasons for this; they include the
                   complex, interrelated processes associated with nutrient cycles, short-range spatial variability
                   of the soil properties such as soil texture , organic matter content , and pore size distribution,
                   and spatial and temporal variability  of soil management practices (e.g. ploughing, fertiliser
                   application, sowing, and harvest), and climatic factors such as temperature, precipitation,
                   and evapotranspiration . Short-range spatial variability and short-term temporal variability
                   may interfere with the ability to detect regional patterns of variation: for example, differences
                   in nitrate concentrations in pore water between fields.  To reveal regional patterns of
                   concentrations that are subject to high variability, the sample support  (see section 1.5) can be
                   increased by bulking samples or averaging the results of sample analysis.
                      Field-based studies on patterns of organic pollutants in soil at the landscape or regional
                   scale  as a consequence of agricultural  activities are very rare, probably because such studies
                   require a large number of field samples and the costs of laboratory analysis are high. Studies
                   on spatial variability  of inorganic pollutants in soil are more common (e.g. Sauer and Meek,
                   2003; Spijker, 2005).
                      Spijker (2005) presented an analysis of the natural and man-induced geochemical
                   patterns in soils of the rural part of the province of Zeeland , the Netherlands. Samples of
                   young Holocene marine clayey sediments were collected at two depths (the plough zone at
                   5–30 cm and the C-horizon  at about 40–80 cm) at 270 locations on agricultural  land and
                   analysed for the elemental composition. This study revealed that for the major elements (Al,
                   Si, Ca, Mg, S) the largest significant source of small-scale  variation occurred at the field scale
                   (about 300 m). The major source of variation for heavy metals  generally appeared to be at
                   a smaller scale than for the major elements, probably because of local human interference.
                   Before the regional patterns of soil contamination could be analysed, the natural variation
                   due to differences in soil properties, notably clay matter content, had to be removed first.
                   To do so, a linear regression between the different elements and the aluminium  (Al O )
                                                                                        2  3
                   content was performed for the deeper samples from the C-horizon. This regression is similar
                   to the regression described in the previous section (see Equation 16.3), but in this case the
                   Al O  content was used as a proxy for clay content . Organic matter was omitted from the
                     2  3
                   regression, because the organic matter content s in the samples were quite low (about 3
                   percent maximum) and did not contribute much to the variation in element concentrations.
                   The enrichment in the topsoil for each location was determined by calculating the difference
                   between the actual measured concentration and the regression prediction based on the Al O
                                                                                        2  3
                   content of the topsoil. In this way, it was shown that the topsoil was enriched in Cd , Sb, As,
                   Cu , Pb , Zn , and P O . The strong correlation between Cd and phosphorus  (see Figure 16.4)
                                  2  5
                   suggests that the Cd enrichment was primarily the consequence of input as impurities of
                   phosphate fertilisers . Figure 16.5 shows the regional variation in Cd enrichment: compared
                   with the rest of the province, the western part of the central peninsula (Walcheren and
                   Noord-Beveland) is more enriched in Cd whereas the south (Zeeuws-Vlaanderen) is less
                   enriched in Cd. These regional differences might reflect differences in fertilisation rates, or
                   fertilisers containing different amounts of Cd.
                   16.4.3  Effects of atmospheric deposition

                   Deposition of atmospheric pollutants (e.g. acidifying component, POPs, heavy metals)
                   is often a major source of diffuse soil contamination, especially in non-agricultural areas,










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