Sr. Salman et Yh. Abu Ruka'H, Multivariate and principal component statistical analysis of contaminationin urban and agricultural soils from north Jordan, ENVIR GEOL, 38(3), 1999, pp. 265-270
A Multivariate analysis and principal component analysis was performed on 3
7 samples gathered from different regions in north Jordan. Twenty-eight des
criptors (variables) for each sample were used in these calculations, among
them were metal ion concentration, such as Pb, Cr, Co, Zn, Ca, Mg, Fe, Na,
K, Al, Cu, Ni, Ti, Si and Mn. Other descriptors were pH, electrical conduc
tivity others (EC), and grain sizes. It was found that the samples form thr
ee clusters, namely, agriculture, industrial and waste treatment plane regi
ons. Statistical analysis showed that the samples are classified into seven
classes, with the majority of the samples classified into three clusters.
The first three principal correlation be components explained 99.2% of the
variance. This method offers a method to classify geographical regions on a
pollution bases and to determine the possible sources of pollution for suc
h regions. This study showed that some of the agricultural farms were remot
e from the pollution sources clusters with polluted regions such as industr
ial or waste plants, petrol treatment complexes.