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Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery

The continuous combustion of fossil fuels and industrial wastewater pollution undermines global environmental and socio-economic sustainability. Addressing this necessitates a techno-scientific revolution to recover the renewable energy potential of wastewater towards a circular economy. Herein, a d...

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Autores principales: Tetteh, Emmanuel Kweinor, Rathilal, Sudesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8945768/
https://www.ncbi.nlm.nih.gov/pubmed/35324784
http://dx.doi.org/10.3390/bioengineering9030095
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author Tetteh, Emmanuel Kweinor
Rathilal, Sudesh
author_facet Tetteh, Emmanuel Kweinor
Rathilal, Sudesh
author_sort Tetteh, Emmanuel Kweinor
collection PubMed
description The continuous combustion of fossil fuels and industrial wastewater pollution undermines global environmental and socio-economic sustainability. Addressing this necessitates a techno-scientific revolution to recover the renewable energy potential of wastewater towards a circular economy. Herein, a developed biophotocatalytic (BP) system was examined with an engineered Fe-TiO(2) to ascertain its degradability efficiency and biogas production from industrial wastewater. The response surface methodology (RSM) based on a modified Box-Behnken designed experiment was used to optimize and maximize the BP system’s desirability. The parameters investigated included catalyst dosage of 2–6 g and hydraulic retention time (HRT) of 1–31 d at a constant temperature of 37.5 °C and organic loading rate of 2.38 kgCOD/Ld. The modified RSM-BBD predicted 100% desirability at an optimal catalyst load of 4 g and HRT of 21 d. This represented 267 mL/d of biogas and >98% COD, color, and turbidity removal. The experimental validity was in good agreement with the model predicted results at a high regression (R(2) > 0.98) and 95% confidence level. This finding provides an insight into RSM modeling and optimization with the potential of integrating the BP system into wastewater settings for the treatment of industrial wastewater and biogas production.
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spelling pubmed-89457682022-03-25 Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery Tetteh, Emmanuel Kweinor Rathilal, Sudesh Bioengineering (Basel) Article The continuous combustion of fossil fuels and industrial wastewater pollution undermines global environmental and socio-economic sustainability. Addressing this necessitates a techno-scientific revolution to recover the renewable energy potential of wastewater towards a circular economy. Herein, a developed biophotocatalytic (BP) system was examined with an engineered Fe-TiO(2) to ascertain its degradability efficiency and biogas production from industrial wastewater. The response surface methodology (RSM) based on a modified Box-Behnken designed experiment was used to optimize and maximize the BP system’s desirability. The parameters investigated included catalyst dosage of 2–6 g and hydraulic retention time (HRT) of 1–31 d at a constant temperature of 37.5 °C and organic loading rate of 2.38 kgCOD/Ld. The modified RSM-BBD predicted 100% desirability at an optimal catalyst load of 4 g and HRT of 21 d. This represented 267 mL/d of biogas and >98% COD, color, and turbidity removal. The experimental validity was in good agreement with the model predicted results at a high regression (R(2) > 0.98) and 95% confidence level. This finding provides an insight into RSM modeling and optimization with the potential of integrating the BP system into wastewater settings for the treatment of industrial wastewater and biogas production. MDPI 2022-02-26 /pmc/articles/PMC8945768/ /pubmed/35324784 http://dx.doi.org/10.3390/bioengineering9030095 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tetteh, Emmanuel Kweinor
Rathilal, Sudesh
Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery
title Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery
title_full Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery
title_fullStr Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery
title_full_unstemmed Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery
title_short Response Surface Optimization of Biophotocatalytic Degradation of Industrial Wastewater for Bioenergy Recovery
title_sort response surface optimization of biophotocatalytic degradation of industrial wastewater for bioenergy recovery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8945768/
https://www.ncbi.nlm.nih.gov/pubmed/35324784
http://dx.doi.org/10.3390/bioengineering9030095
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