Jw. Einax et U. Soldt, Geostatistical and multivariate statistical methods for the assessment of polluted soils - merits and limitations, CHEM INTELL, 46(1), 1999, pp. 79-91
The complexity and the large variance of environmental data sets limit the
use of common statistical methods for the assessment of the state of pollut
ion. Therefore, the application of geostatistical and multivariate statisti
cal methods is recommended. In principle, both types of statistics are able
to detect spatial or temporal structures in data sets. The merits and limi
tations of these statistical methods shall be demonstrated for the investig
ation of three very different examples of soil pollution. The first case st
udy is characterized by a distinct spatial structure and a relatively large
number of samples. Both geostatistical and multivariate statistical method
s are well suited for the characterization of the state of pollution. The s
econd example is typical for a case study under practical and economic limi
tations. In this case it is possible to describe the polluted area semiquan
titatively by means of multivariate statistical methods. The third data set
is characterized by a relatively diffuse distribution of the contaminants
in an old uranium mining waste dump. Methods of homogeneity testing can be
used as an alternative to geostatistical and multivariate statistical metho
ds. (C) 1999 Elsevier Science B.V. All rights reserved.