NDLI: The Extent and Prediction of Heavy Metal Pollution in Soils of Shahrood and Damghan, Iran

Content Provider	Springer Nature Link
Author	Sakizadeh, Mohamad Mirzaei, Rouhollah Ghorbani, Hadi
Copyright Year	2015
Abstract	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 represented more than 98 % of the overall variance. The correlation 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 components was 0.984 confirming the predictive ability of this method.
Starting Page	770
Ending Page	776
Page Count	7
File Format	PDF
ISSN	00074861
Journal	Bulletin of Environmental Contamination and Toxicology
Volume Number	95
Issue Number	6
e-ISSN	14320800
Language	English
Publisher	Springer US
Publisher Date	2015-08-25
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Heavy metals Soil pollution Factor analysis Partial least squares regression Pollution Environmental Health Ecotoxicology Soil Science & Conservation Environmental Chemistry Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
Content Type	Text
Resource Type	Article
Subject	Health, Toxicology and Mutagenesis Pollution Medicine Toxicology

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