JOURNAL ARTICLE

IMPACTS OF INDUSTRIAL WASTEWATER ON THE WATER QUALITY OF THE NILE RIVER IN EGYPT: REVIEW.

  • Published In: International Journal of Energy, Environment & Economics, 2025, v. 32, n. 4. P. 433 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Ahmed, Abdelkader T.; Tawfeek, Ahmed A.; Askri, Brahim 3 of 3

Abstract

Industrial growth has a direct impact on the water quality of the Nile River in Egypt. About 360 industries are discharging their wastewater into the Nile River. The main objective of this study is to review and evaluate the effects of these wastewater effluents on the quality of drinking water supply from the Nile through the available previous studies. Many case studies were reviewed and mapped along the Nile journey in Egypt. Review results showed that the quality of water in the drains deteriorates as it moves downstream to the Delta region. 125 major industrial plants are in the Nile valley, which represents about 18% of the existing industries and discharging 15% of the heavy metal loads. 250 industrial plants are in Greater Cairo, which represents 35% and contributing about 40% of the total metal discharges. More practical treatment methods should be selected to treat industrial effluents before discharging into natural streams such as in site filtration. In addition, a more restricted regulations need to be applied on wastewater discharging into the Nile River. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Energy, Environment & Economics. 2025/10, Vol. 32, Issue 4, p433
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2025
  • ISSN:1054-853X
  • Accession Number:189374218
  • Copyright Statement:Copyright of International Journal of Energy, Environment & Economics is the property of Nova Science Publishers, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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