| نویسندگان | محمد ساکی زاده-روح اله میرزایی محمد آبادی-هادی قربانی |
| نشریه | B ENVIRON CONTAM TOX |
| تاریخ انتشار | 0-0-01 |
| نمایه نشریه | ISI |
چکیده مقاله
The levels of 12 heavy metals (Ag, Ba, Be, Cd,
Co, Cr, Cu, Ni, Pb, Tl, V, Zn) were considered in 229 soil
samples in Semnan Province, Iran. To discriminate
between natural and anthropogenic inputs of heavy metals,
factor analysis was used. Seven factors accounting for
90.5 % of the total variance were extracted. The mining
and agricultural activities along with geogenic sources
have been attributed as the main causes of the levels of
heavy metals in the study area. The partial least squares
regression was utilized to predict the level of soil pollution
index (SPI) considering the concentrations of 12 heavy
metals. The eigenvectors from the first three PLS repre-
sented more than 98 % of the overall variance. The cor-
relation coefficient between the observed and predicted SPI
was 0.99 indicating the high efficiency of this method. The
resultant coefficient of determination for three PLS com-
ponents was 0.984 confirming the predictive ability of this
method.