Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models

The potential of an algae-based system as an environmentally friendly and low-cost wa�ter treatment method to eliminate contaminants from water bodies has been considered. The purpose of this research was to see how effective Scenedesmus sp is in eliminating nutrients from meat processing wastewat...

Full description

Saved in:
Bibliographic Details
Main Authors: Ahmad Latiffi, Nur Atikah, Radin Mohamed, Radin Maya Saphira, Al-Gheethi, Adel, Tajuddin, R. M., Al-Shaibani, Muhanna M., N. Vo, Dai-Viet, Rupani, Parveen Fatemeh
Format: Article
Language:English
Published: Elsevier 2022
Subjects:
Online Access:http://eprints.uthm.edu.my/7233/1/J14263_12e90daa24d15e91e3f6418f336fb4b1.pdf
http://eprints.uthm.edu.my/7233/
https://doi.org/10.1016/j.eti.2022.102535
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uthm.eprints.7233
record_format eprints
spelling my.uthm.eprints.72332022-07-05T01:42:49Z http://eprints.uthm.edu.my/7233/ Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models Ahmad Latiffi, Nur Atikah Radin Mohamed, Radin Maya Saphira Al-Gheethi, Adel Tajuddin, R. M. Al-Shaibani, Muhanna M. N. Vo, Dai-Viet Rupani, Parveen Fatemeh TP248.13-248.65 Biotechnology The potential of an algae-based system as an environmentally friendly and low-cost wa�ter treatment method to eliminate contaminants from water bodies has been considered. The purpose of this research was to see how effective Scenedesmus sp is in eliminating nutrients from meat processing wastewater (MPWW) throughout the phycoremediation process. Response surface methodology (RSM) and an artificial neural network (ANN) model were applied to improve the inactivation process as a function of cell concentra�tions (3–7 log10 CFU/mL) and time (1–13 days). At 103 to 107 cell/mL of Scenedesmus sp., phycoremediation was carried out at atmospheric temperature (28 ± 2 ◦C, ±2500lux for 12:12 h of light/dark and pH 8). The findings documented 73.76% as the highest removal efficacy of total nitrogen (TN) and 77.85% of total phosphorus (TP), 75.40% of ammonia nitrogen (NH4-H), 77.88% of orthophosphate (PO3− 4 ), and 64.97% of chemical oxygen demand (COD). The ANN revealed that both factors contribute significantly to the nutrient removal process. The batch kinetic coefficients of NH4-H removal were Km = 40.10 mg/L and k = 1.43 mg mg −1Chl a d −1 . Meanwhile, for PO3− 4 , 1.07 mg mg −1Chl a d−1 , as well as 42.80 mg/L, were obtained. The NH4-N yield coefficient of NH4-N was Yn = 0.0192 mg Chl a mg −1 while PO3− 4 was equal to Yp = 0.0409 mg Chl a mg −1 . These findings indicated successful use of Scenedesmus sp. for efficient pollutant removal from meat processing wastewater plants. Elsevier 2022 Article PeerReviewed text en http://eprints.uthm.edu.my/7233/1/J14263_12e90daa24d15e91e3f6418f336fb4b1.pdf Ahmad Latiffi, Nur Atikah and Radin Mohamed, Radin Maya Saphira and Al-Gheethi, Adel and Tajuddin, R. M. and Al-Shaibani, Muhanna M. and N. Vo, Dai-Viet and Rupani, Parveen Fatemeh (2022) Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models. Environmental Technology & Innovation, 26. pp. 1-11. ISSN 2352-1864 https://doi.org/10.1016/j.eti.2022.102535
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TP248.13-248.65 Biotechnology
spellingShingle TP248.13-248.65 Biotechnology
Ahmad Latiffi, Nur Atikah
Radin Mohamed, Radin Maya Saphira
Al-Gheethi, Adel
Tajuddin, R. M.
Al-Shaibani, Muhanna M.
N. Vo, Dai-Viet
Rupani, Parveen Fatemeh
Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models
description The potential of an algae-based system as an environmentally friendly and low-cost wa�ter treatment method to eliminate contaminants from water bodies has been considered. The purpose of this research was to see how effective Scenedesmus sp is in eliminating nutrients from meat processing wastewater (MPWW) throughout the phycoremediation process. Response surface methodology (RSM) and an artificial neural network (ANN) model were applied to improve the inactivation process as a function of cell concentra�tions (3–7 log10 CFU/mL) and time (1–13 days). At 103 to 107 cell/mL of Scenedesmus sp., phycoremediation was carried out at atmospheric temperature (28 ± 2 ◦C, ±2500lux for 12:12 h of light/dark and pH 8). The findings documented 73.76% as the highest removal efficacy of total nitrogen (TN) and 77.85% of total phosphorus (TP), 75.40% of ammonia nitrogen (NH4-H), 77.88% of orthophosphate (PO3− 4 ), and 64.97% of chemical oxygen demand (COD). The ANN revealed that both factors contribute significantly to the nutrient removal process. The batch kinetic coefficients of NH4-H removal were Km = 40.10 mg/L and k = 1.43 mg mg −1Chl a d −1 . Meanwhile, for PO3− 4 , 1.07 mg mg −1Chl a d−1 , as well as 42.80 mg/L, were obtained. The NH4-N yield coefficient of NH4-N was Yn = 0.0192 mg Chl a mg −1 while PO3− 4 was equal to Yp = 0.0409 mg Chl a mg −1 . These findings indicated successful use of Scenedesmus sp. for efficient pollutant removal from meat processing wastewater plants.
format Article
author Ahmad Latiffi, Nur Atikah
Radin Mohamed, Radin Maya Saphira
Al-Gheethi, Adel
Tajuddin, R. M.
Al-Shaibani, Muhanna M.
N. Vo, Dai-Viet
Rupani, Parveen Fatemeh
author_facet Ahmad Latiffi, Nur Atikah
Radin Mohamed, Radin Maya Saphira
Al-Gheethi, Adel
Tajuddin, R. M.
Al-Shaibani, Muhanna M.
N. Vo, Dai-Viet
Rupani, Parveen Fatemeh
author_sort Ahmad Latiffi, Nur Atikah
title Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models
title_short Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models
title_full Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models
title_fullStr Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models
title_full_unstemmed Nutrients elimination from meat processing wastewater using Scenedesmus sp.; optimizations; artificial neural network and kinetics models
title_sort nutrients elimination from meat processing wastewater using scenedesmus sp.; optimizations; artificial neural network and kinetics models
publisher Elsevier
publishDate 2022
url http://eprints.uthm.edu.my/7233/1/J14263_12e90daa24d15e91e3f6418f336fb4b1.pdf
http://eprints.uthm.edu.my/7233/
https://doi.org/10.1016/j.eti.2022.102535
_version_ 1738581593652461568
score 13.160551