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

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Listed:
  • Mohamed E. Abowaly

    (Soil and Water Department, Faculty of Agriculture, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt)

  • Abdel-Aziz A. Belal

    (Agricultural Applications, Soil and Marine Science Division, National Authority for Remote Sensing and Space Sciences, Alf Maskan, Cairo 1564, Egypt)

  • Enas E. Abd Elkhalek

    (Soil and Water Department, Faculty of Agriculture, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt)

  • Salah Elsayed

    (Agricultural Engineering, Evaluation of Natural Resources Department, Environmental Studies and Research Institute, University of Sadat City, Minufiya 32897, Egypt)

  • Rasha M. Abou Samra

    (Environmental Sciences Department, Faculty of Science, Damietta University, New Damietta 34517, Egypt)

  • Abdullah S. Alshammari

    (Biology Department, College of Science, Ha’il University, Ha’il 55476, Saudi Arabia)

  • Farahat S. Moghanm

    (Soil and Water Department, Faculty of Agriculture, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt)

  • Kamal H. Shaltout

    (Botany Department, Faculty of Science, Tanta University, Tanta 31527, Egypt)

  • Saad A. M. Alamri

    (Biology Department, College of Science, King Khalid University, Abha 61321, Saudi Arabia)

  • Ebrahem M. Eid

    (Biology Department, College of Science, King Khalid University, Abha 61321, Saudi Arabia
    Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt)

Abstract

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.

Suggested Citation

  • Mohamed E. Abowaly & Abdel-Aziz A. Belal & Enas E. Abd Elkhalek & Salah Elsayed & Rasha M. Abou Samra & Abdullah S. Alshammari & Farahat S. Moghanm & Kamal H. Shaltout & Saad A. M. Alamri & Ebrahem M., 2021. "Assessment of Soil Pollution Levels in North Nile Delta, by Integrating Contamination Indices, GIS, and Multivariate Modeling," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:8027-:d:596737
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    References listed on IDEAS

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    1. Elsayed, Salah & Elhoweity, Mohamed & Ibrahim, Hazem H. & Dewir, Yaser Hassan & Migdadi, Hussein M. & Schmidhalter, Urs, 2017. "Thermal imaging and passive reflectance sensing to estimate the water status and grain yield of wheat under different irrigation regimes," Agricultural Water Management, Elsevier, vol. 189(C), pages 98-110.
    2. Panos Panagos & Cristiano Ballabio & Emanuele Lugato & Arwyn Jones & Pasquale Borrelli & Simone Scarpa & Alberto Orgiazzi & Luca Montanarella, 2018. "Potential Sources of Anthropogenic Copper Inputs to European Agricultural Soils," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
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    1. Mohamed E. Abowaly & Raafat A. Ali & Farahat S. Moghanm & Mohamed S. Gharib & Moustapha Eid Moustapha & Mohssen Elbagory & Alaa El-Dein Omara & Shimaa M. Elmahdy, 2022. "Assessment of Soil Degradation and Hazards of Some Heavy Metals, Using Remote Sensing and GIS Techniques in the Northern Part of the Nile Delta, Egypt," Agriculture, MDPI, vol. 13(1), pages 1-17, December.

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