Calcium Hydroxide-Based Degradation of Hydrocarbons in Petroleum Refinery Wastewater
Authors
Khedidja Benouis1, *, Yasmina Khane2, 3, Yassine Khalfi1, Soufiane Guella1, Amine Chalabi4
1Laboratory of Process Engineering, Materials and Environment, faculty of Technology, University of Djillali Liabes, PO Box 89, Sidi Bel Abbes 22000 –Algeria.
2Université de Ghardaia, B.P 455, Ghardaïa, Algerie
3Laboratory of Applied Chemistry, ACTR Univ Ain Temouchent, PO Box 284, Ain Temouchent 46000 –Algeria.
4Department of mechanical engineering, faculty of Technology, University of Djillali Liabes, PO Box 89, Sidi Bel Abbes 22000 –Algeria.
*Corresponding author. Email: benouis_khadidja@yahoo.fr
Corresponding Author
Khedidja Benouis
Available Online 2 February 2022.
- DOI
- 10.2991/aisr.k.220201.018How to use a DOI?
- Keywords
- Petroleum Refinery; Effluent; Hydrocarbons; Process; Coagulation
- Abstract
Hydrocarbons, aldehydes, sulfides, heavy metals, and other contaminants from petroleum treatment processes have been discovered in the oil and gas industry liquid discharge. Hydrocarbons primarily cause the pollution shared by all units. The purpose of this study is to assess the performance of the coagulation-flocculation process in the primary treatment stage for the removal of hydrocarbons and turbidity from the effluent of the Algerian oil refinery RA1/Z. Using 1 g/L of calcium hydroxide coagulant and operating at a stirring speed of 100 rpm for 3 minutes, an excellent elimination of 95.1 % and 90.4 %, respectively, of turbidity and hydrocarbons, was achieved.
- Copyright
- © 2022 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Khedidja Benouis AU - Yasmina Khane AU - Yassine Khalfi AU - Soufiane Guella AU - Amine Chalabi PY - 2022 DA - 2022/02/02 TI - Calcium Hydroxide-Based Degradation of Hydrocarbons in Petroleum Refinery Wastewater BT - Proceedings of the 2nd International Conference on Industry 4.0 and Artificial Intelligence (ICIAI 2021) PB - Atlantis Press SP - 94 EP - 98 SN - 1951-6851 UR - https://doi.org/10.2991/aisr.k.220201.018 DO - 10.2991/aisr.k.220201.018 ID - Benouis2022 ER -