Influence of site-classification approach on geochemical background values

Abstract

This study of peri-urban minerogenic topsoil on glacigenic or post-glacial deposits shows the influence of the site-classification approach on the differentiated median background (DMB) values of major elements and the potentially harmful elements (PHEs) Ba, Cr, Cu, Mn, Ni, Pb and Zn. Composite samples from forests and meadows were taken in 25 sites, each of which had five sub-sites. A fraction of <2 mm was used to determine the organic matter by loss on ignition (LOI), grain size by laser diffraction and the elemental contents by X-ray fluorescence. The following five site-classification approaches are compared: geochemical (G), using relative median contents of Al, K, Ti; textural (T), according to mean percentages of clay-sized fraction (CLF) and silt fraction (SIF); lithological (L), based on soil parent material texture from the soil database; soil type (S), presented in the soil database; and parent material (P), generalising the underlying Quaternary deposits. Sites were classified into four level groups in which the DMB values were estimated after eliminating anomalies. The average ranks of three scores according to SIF, CLF, LOI, Al, K, Ti, Fe, Mg, Ca and S in the respective groups revealed the highest value for the G approach. It better eliminates the CLF and SIF influences on the median assessment indices of PHEs in sites.

Search for the Substantiation of Reasonable Native Elemental Background Values and Reference Variables in Topsoil on Glaciogenic and Postglacial Deposits in a Vilnius Peri-Urban Area

“…However, our present study shows that the 550 variable has an insignificant correlation with the clay fraction (rS = 0.12) but a significant correlation with silt (rS = 0.70). Similar results were obtained in our earlier investigations of minerogenic topsoil around Vilnius [40], as well as by researchers studying topsoil in Spitsbergen [83].…”

“…However, in the topsoil of Spitsbergen, the correlation of P with organic matter has been assessed as insignificant [83], most probably due to the absence of a significant correlation between organic matter and the clay fraction, in contrast to that with the silt fraction. An earlier study of Vilnius peri-urban topsoil showed a significant correlation of 550 with S but not with P [40]. A possible explanation is that the total P in the soil consists not only of 30%-65% of organic forms but also 35%-70% inorganic forms, namely phosphates, and also sorbed or dissolved forms [88].…”

“…Methods that yield constant native BVs were tested in both rural areas [11,40] and urban [41][42][43]. Most of these methods are based on eliminating element anomalies and providing a background range.…”

Geochemistry of the Dust Collected by Passive Samplers as a Tool for Search of Pollution Sources: The Case of Klaipėda Port, Lithuania

“…Still, we cannot deny native source of Fe mentioned in all previously cited publications [81,82,92,93] where positive correlation of Fe with other crustal elements has been shown. We can presume partial pedogenic origin of Fe in dust of Klaip ėda basing on: (i) conclusions of these researchers, (ii) the fact that L4 cluster in the left branch of the dendrogram is the closest to the right branch and only two connections separate it from clusters R2 and R3 which include crustal elements, (iii) undeniable association of Fe with other crustal elements which is observed in topsoil (see Fe loadings on FT BT and dendrograms in our previous research of topsoil background composition [25,87]) which serves as a source of re-suspension. But presently, Fe ore stevedoring seems to be not essential source of Cr, since the highest loading of Cr is on F5 TSP , i.e., it belongs to the group of elements leaded by Pb and As and accompanied by Cr, Mn, Fe, and Ni.…”

“…However, this assignment is related to subjective factor, i.e., when different values are taken in the denominator (Equations ( 1)-( 4)) during calculation of gI, so manipulations are possible. Even small difference in selected Cv values (the study of Rudnick and Gao [32] contains data of all eleven compilers of Clarke values) or Bn values the problems of selection of which have been described by us [25,87], can determine attribution of sample to different SCC. However, whichever unique Cv or Bn value is chosen, the level of analyte content in ambient air is the same.…”