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Factorial Design and Optimization of Date Stone as A Natural Coagulant for Organic and Heavy Metals Removal from Industrial Wastewater

Paper Topic: 
Water and Wastewater Treatment
 
Volume: 
 
Issue: 
 

Pages :
99 - 107

Corresponing Author: 
Mohammed Shadi S. Abujazar
 
Authors: 
Abu Amr Salem S. Abujazar MohammedShadi S. Karaağaç Sakine Ugurlu Karrar kareem Mehdi Motasem Y.D. Alazaiza Bashir Mohammed JK Fatihah Suja vakili Amir Hossein
Paper ID: 
gnest_04486
Paper Status: 
Published
Date Paper Accepted: 
06-11-2022
Paper online: 
16/11/2022
Visual abstract: 
Abstract: 

Several chemical coagulants previously utilize for wastewater treatment with significant performance in removing heavy metals and other parameters. However, their cost effective and the residual of toxic chemical precipitates that pose problems to human health and the environment. Therefore, using plant-based natural coagulants is considered as an alternative technique which is non-toxic, biodegradable and environmentally friendly. This research aims to explore the performance of date stones as a natural coagulant in iron and steel plant wastewater treatment and to optimize the operating parameters to assess the feasibility of using date stones in the wastewater treatment sector. Response Surface Methodology (RSM), a statistical experimental design, was used to improve the COD, TSS, NH3-N, and heavy metals removal efficiency using 1.4 g/200 mL date stones as control parameters, as well as pH and settling time. At pH 8, the most significant removal efficiency for COD, NH3-N, Fe, Mn, Al, Cu, and Ni was 61, 63, 93, 93, 96.5, 51, and 86 %, respectively. The quadratic models for the parameters chosen were found to be significant with low probability (<0.001), except for NH3-N (0.004), Fe (0.0042), and Ni (0.0025). The study's results revealed the potential of utilizing date stones as a natural coagulant for the treatment of iron and steel industrial wastewater

Keywords: 
Industrial Wastewater, Natural coagulant, Date Stone, Treatment, Removal Efficiency, Heavy Metals, Factorial Design and Optimization