Assessment of Soil Pollution Levels in North Nile Delta, by Integrating Contamination Indices, GIS, and Multivariate Modeling

被引:21
作者
Abowaly, Mohamed E. [1 ]
Belal, Abdel-Aziz A. [2 ]
Abd Elkhalek, Enas E. [1 ]
Elsayed, Salah [3 ]
Abou Samra, Rasha M. [4 ]
Alshammari, Abdullah S. [5 ]
Moghanm, Farahat S. [1 ]
Shaltout, Kamal H. [6 ]
Alamri, Saad A. M. [7 ]
Eid, Ebrahem M. [7 ,8 ]
机构
[1] Kafrelsheikh Univ, Fac Agr, Soil & Water Dept, Kafr Al Sheikh 33516, Egypt
[2] Natl Author Remote Sensing & Space Sci, Agr Applicat Soil & Marine Sci Div, Cairo 1564, Egypt
[3] Univ Sadat City, Environm Studies & Res Inst, Agr Engn Evaluat Nat Resources Dept, Menoufia 32897, Egypt
[4] Damietta Univ, Fac Sci, Environm Sci Dept, New Damietta 34517, Egypt
[5] Hail Univ, Coll Sci, Biol Dept, Hail 55476, Saudi Arabia
[6] Tanta Univ, Fac Sci, Biol Dept, Tanta 31527, Egypt
[7] King Khalid Univ, Coll Sci, Biol Dept, Abha 61321, Saudi Arabia
[8] Kafrelsheikh Univ, Fac Sci, Biol Dept, Kafr Al Sheikh 33516, Egypt
关键词
trace elements; GIS; geoaccumulation index; PLI; PLSR; north Nile Delta of Egypt; HEAVY-METAL CONTAMINATION; TRACE-ELEMENT INPUTS; AGRICULTURAL SOILS; WATER; REFLECTANCE; INVENTORY; PRADESH; STRESS; AREAS; WHEAT;
D O I
10.3390/su13148027
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The proper assessment of trace element concentrations in the north Nile Delta of Egypt is needed in order to reduce the high levels of toxic elements in contaminated soils. The objectives of this study were to assess the risks of contamination for four trace elements (nickel (Ni), cobalt (Co), chromium (Cr), and boron (B)) in three different layers of the soil using the geoaccumulation index (I-geo) and pollution load index (PLI) supported by GIS, as well as to evaluate the performance of partial least-square regression (PLSR) and multiple linear regression (MLR) in estimating the PLI based on data for the four trace elements in the three different soil layers. The results show a widespread contamination of I-geo Ni, Co, Cr, and B in the three different layers of the soil. The I-geo values varied from 0 to 4.74 for Ni, 0 to 6.56 for Co, 0 to 4.11 for Cr, and 0 to 4.57 for B. According to I-geo classification, the status of Ni, Cr, and B ranged from uncontaminated/moderately contaminated to strongly/extremely contaminated. Co ranged from uncontaminated/moderately contaminated to extremely contaminated. There were no significant differences in the values of I-geo for Ni, Co, Cr, and B in the three different layers of the soil. According to the PLI classification, the majority of the samples were very highly polluted. For example, 4.76% and 95.24% of the samples were unpolluted and very highly polluted, respectively, in the surface layer of the soil profiles. Additionally, 14.29% and 85.71% of the samples were unpolluted and very highly polluted, respectively, in the subsurface layer of the soil profiles. Both calibration (Cal.) and validation (Val.) models of the PLSR and MLR showed the highest performance in predicting the PLI based on data for the four studied trace elements, as an alternative method. The validation (Val.) models performed the best in predicting the PLI, with R-2 = 0.89-0.93 in the surface layer, 0.91-0.96 in the subsurface layer, 0.89-0.94 in the lowest layers, and 0.92-0.94 across the three different layers. In conclusion, the integration of the I-geo, PLI, GIS technique, and multivariate models is a valuable and applicable approach for the assessment of the risk of contamination for trace elements, and the PLSR and MLR models could be used through applying chemometric techniques to evaluate the PLI in different layers of the soil.
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页数:20
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