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

文献类型： 外文期刊

作者： Shokr, Mohamed S. 1 ; Abdellatif, Mostafa A. 2 ; El Behairy, Radwa A. 1 ; Abdelhameed, Hend H. 3 ; El Baroudy, Ahmed A. 1 ; Mohamed, Elsayed Said 2 ; Rebouh, Nazih Y. 4 ; Ding, Zheli 5 ; Abuzaid, Ahmed S. 6 ;

作者机构： 1.Tanta Univ, Fac Agr, Soil & Water Dept, Tanta 31527, Egypt

2.Natl Author Remote Sensing & Space Sci, Cairo, Egypt

3.Arish Univ, Fac Environm Agr Sci, Soil & Water Dept, Arish, Egypt

4.RUDN Univ, Peoples Friendship Univ Russia, Dept Environm Management, 6 Miklukho Maklaya St, Moscow 117198, Russia

5.Chinese Acad Trop Agr Sci, Haikou Expt Stn, Haikou 570000, Peoples R China

6.Benha Univ, Fac Agr, Soils & Water Dept, Banha 13518, Egypt

关键词： arid lands; contamination indices; Nile Delta; statistical analysis; geostatistical analysis

期刊名称：AGRONOMY-BASEL （ 影响因子：3.949； 五年影响因子：4.117 ）

ISSN：

年卷期： 2022 年 12 卷 12 期

页码：

收录情况： SCI

摘要： 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 (I-n). 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.

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