Assessment of Potential Heavy Metal Contamination Hazards Based on GIS and Multivariate Analysis in Some Mediterranean Zones

Assessment of Potential Heavy Metal Contamination Hazards Based on GIS and Multivariate Analysis in Some Mediterranean Zones

One of the most significant challenges that global decision-makers are concerned about is soil contamination. It is also related to food security and soil fertility. The quality of the soil and crops in Egypt are being severely impacted by the increased heavy metal content of the soils in the middle...

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Bibliographic Details
Published in:Agronomy (Basel) Vol. 12; no. 12; p. 3220
Main Authors: Shokr, Mohamed S, Abdellatif, Mostafa A., El Behairy, Radwa A., Abdelhameed, Hend H., El Baroudy, Ahmed A., Mohamed, Elsayed Said, Rebouh, Nazih Y., Ding, Zheli, Abuzaid, Ahmed S.
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-12-2022
Subjects:
Analysis
arid lands
Cadmium
Climate change
Cluster analysis
contamination indices
Decision making
Ecosystems
Fertilizers
Food contamination
Food contamination & poisoning
Food security
Geographic information systems
Geospatial data
geostatistical analysis
Hazard assessment
Heavy metals
Irrigation
Lead
Manganese
Metal concentrations
Metals
Multivariate analysis
Nile Delta
Pesticides
Pollution
Pollution index
Principal components analysis
Soil contamination
Soil fertility
Soil pollution
Spatial data
Statistical analysis
Zinc
Egypt
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Summary:One of the most significant challenges that global decision-makers are concerned about is soil contamination. It is also related to food security and soil fertility. The quality of the soil and crops in Egypt are being severely impacted by the increased heavy metal content of the soils in the middle Nile Delta. In Egypt’s middle Nile Delta, fifty random soil samples were chosen. Inverse distance weighting (IDW) was used to create the spatial pattern maps for four heavy metals: Cd, Mn, Pb, and Zn. The soil contamination levels in the research area were assessed using principal component analysis (PCA), contamination factors (CF), the geoaccumulation index (I-Geo), and the improved Nemerow pollution index (In). The findings demonstrated that using PCA, the soil heavy metal concentrations were divided into two clusters. Moreover, the majority of the study region (44.47%) was assessed to be heavily to extremely polluted by heavy metals. In conclusion, integrating the contamination indices CF, I-Geo, and In with the GIS technique and multivariate model, analysis establishes a practical and helpful strategy for assessing the hazard of heavy metal contamination. The findings could serve as a basis for decision-makers to create effective heavy metal mitigation efforts.
ISSN:2073-4395
2073-4395
DOI:10.3390/agronomy12123220