2019
DOI: 10.1080/15320383.2019.1637818
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Profile Distribution and Source Identification of Potentially Toxic Elements in North Nile Delta, Egypt

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Cited by 15 publications
(11 citation statements)
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“…The soil-specific factors played substantial roles in controlling metal behaviors in soils. The predominance of Pb (total and available) solely in the same PC affirms the unique behavior of Pb in the studied soils [53]. Results of the HCA agreed well with those of correlation and PCA.…”
Section: Multivariate Statistical Analysissupporting
confidence: 80%
“…The soil-specific factors played substantial roles in controlling metal behaviors in soils. The predominance of Pb (total and available) solely in the same PC affirms the unique behavior of Pb in the studied soils [53]. Results of the HCA agreed well with those of correlation and PCA.…”
Section: Multivariate Statistical Analysissupporting
confidence: 80%
“…In contrast to Ni concentration in irrigation waters, total Ni showed a significant 1.40-fold decrease and a slight 1.16-fold decrease in the ADW-and the SEW-irrigated soils compared with the control soils, respectively. These findings clarify that the accumulations of Cr, Co, and Ni in the studied soils were mainly governed by lithological factors rather than human intervention Jahin, 2019 and. The Cu content in the ADW-irrigated soils showed a slight 1.45-fold decrease compared with the control soils that interfered with the contents in irrigation water.…”
Section: Environmental Indicatorssupporting
confidence: 56%
“…Similarly, the total Co contents in all soils exceeded the ANC in the earth's crust; however, the metal was not detected in irrigation water sources. Cr, Co, and Ni are common in ultramafic rocks (serpentine), which dominate the Nile Delta alluvial sediments (Abuzaid and Jahin, 2019). Total Co showed significant decreases of 1.47 and 1.50-folds in the ADW-and the SEW-irrigated soils compared with the control soils, respectively.…”
Section: Environmental Indicatorsmentioning
confidence: 98%
“…Statistical-based methods, including principal component analysis/factor analysis (PCA/FA) have been widely used to estimate the weights of parameters or indicators when developing an index [22,23]. The PCA/FA assumes linear relationships among the selected parameters [24]. However, non-linear relationships also occur among them [25].…”
Section: Introductionmentioning
confidence: 99%